PERCEPTIONS OF A DIETARY SELF-MONITORING MOBILE APP RESEMBLING THE CANADA'S FOOD GUIDE: A QUALITATIVE STUDY PDF Free Download
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PERCEPTIONS OF A DIETARY SELF-MONITORING MOBILE APP RESEMBLING
THE CANADA’S FOOD GUIDE: A QUALITATIVE STUDY
by
Maryam Kheirmandparizi
B.Sc., Shahid Beheshti University of Medical Sciences- Tehran, Iran, 2014
M.Sc., Shiraz University- Shiraz, Iran, 2021
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
in
THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES
(Human Nutrition)
THE UNIVERSITY OF BRITISH COLUMBIA
(Vancouver)
August 2023
©Maryam Kheirmandparizi, 2023
ii
The following individuals certify that they have read, and recommend to the Faculty of Graduate
and Postdoctoral Studies for acceptance, a thesis entitled:
Perceptions of a dietary self-monitoring mobile app resembling the Canada’s Food Guide: a
qualitative study
submitted by
Maryam Kheirmandparizi
in partial fulfillment of the requirements for
the degree of
Master of Science
in
Human Nutrition
Examining Committee:
Dr. Tamara Cohen, Assistant Professor, Faculty of Land and Food Systems, UBC
Supervisor
Dr. Annalijn Conklin, Assistant Professor, Faculty of Pharmaceutical Sciences, UBC
Supervisory Committee Member
Dr. Sarah Purcell, Assistant Professor, Department of Medicine, UBC
Additional Examiner
Additional Supervisory Committee Members:
Dr. Ryan Rhodes, Professor, School of Exercise Science, Physical & Health Education,
University of Victoria
Supervisory Committee Member
Dr. Scott Lear, Professor, Faculty of Health Sciences, Simon Fraser University
Supervisory Committee Member
iii
Abstract
Background and Purpose: Dietary self-monitoring is a behavioural technique that helps
to elicit and sustain dietary changes over time. Current dietary self-monitoring tools focus on
itemizing foods and serving sizes (portions), making them complex, time-consuming, and hard to
use for people with limited or low health literacy. Furthermore, there are no plate-based dietary
self-monitoring tools that conform to the 2019 Canada Food Guide (CFG). This thesis explored
the perceptions of potential end-users (i.e., members from the general public) and Registered
Dietitians (RDs) on a dietary self-monitoring mobile application (app) resembling the CFG,
called iCANPlateTM.
Methods: Qualitative data were collected through virtual focus groups. Questions in the
focus group guide were based on the Capability, Opportunity, Motivation- Behaviour (COM-B)
model to explore perceptions of using the CFG and available dietary self-monitoring tools. A
prototype of iCANPlateTM (version 0.1) was presented to gain feedback on perceived barriers
and facilitators to using the app, and suggestions on future versions. Trained researchers used
transcripts of audio-recorded focus groups to conduct thematic analysis.
Results: Seven focus groups with RDs (n=44) and nine focus groups with members from
the general public (n=52) were conducted. During the focus groups, participants discussed
potential facilitators and barriers to using the current iteration of iCANPlate. They were
interested in the simplicity of iCANPlate and its capacity to foster self-awareness of dietary
behaviours rather than weight or calorie counting. However, concerns were raised regarding
iCANPlate’s potential to improve adherence to dietary self-monitoring, primarily caused by a
iv
lack of food classifications, conceptualizing proportions, and lack of inclusivity. In addition,
participants suggested necessary and optional components for iCANPlate’s future versions.
Conclusions: Overall, participants liked the simplicity of iCANPlate and its ability to
promote self-awareness of dietary intakes, primarily through visual representation of foods on a
plate as opposed to reliance on numerical values or serving sizes. Findings from this study will
be used to further develop the app with the goal of increasing adherence to plate-based dietary
approaches.
v
Lay Summary
Maintaining a healthy diet is important for overall well-being, but it can be challenging. Current
diet tracking methods can be difficult and time-consuming, making it hard for people to stick to
them. This thesis looks at ways to help people eat healthier by exploring a new way of tracking
food intake. A new app called iCANPlate, which resembles the plate-based approach to eating, is
proposed here. Virtual focus groups with members of the public and Registered Dietitians were
conducted to gain feedback on the app. Overall, participants liked the app’s simplicity but were
concerned about its usefulness for different health conditions and cultures. Participants also
suggested adding more features to the app. Findings from this study will be used to improve the
app to help people make healthier food choices.
vi
Preface
This thesis is an original and unpublished work of the author, the thesis supervisory committee,
grant investigators, and the iCANPlate research team. Dr. Tamara Cohen (Primary Investigator,
TRC), Dr. Jean-Philippe Gouin, Dr. Maryam Kebbe, Dr. Ryan Rhodes, Dr. Biagina-Carla
Farnesi, and Dr. Nizar Bouguila wrote the grant proposal and secured funding for the study.
Celeste C. Bouchaud (CCB) and the author moderated the focus groups. The author analyzed the
qualitative data with two trained researchers, Rana Madani Civi (RM) and Coralie Bergeron
(CB). The thesis writing was completed with editorial and supervisory feedback, input, and
support from the supervisor (Cohen, TRC). The supervisory committee, Dr. Tamara Cohen, Dr.
Annalijn Conklin, Dr. Ryan Rhodes and Dr. Scott Lear supported this thesis by providing
feedback on a submitted manuscript written by the author based on this thesis. Ethics approval
for the original research was obtained from the University of British Columbia (Behavioural
Research Ethics Board Number: H21-01353) and Concordia University (Montreal, QC, Canada,
Ethics Number: 30012869).
vii
Table of Contents
Abstract ......................................................................................................................................... iii
Lay Summary .................................................................................................................................v
Preface ........................................................................................................................................... vi
Table of Contents ........................................................................................................................ vii
List of Tables ................................................................................................................................ xi
List of Figures .............................................................................................................................. xii
List of Abbreviations ................................................................................................................. xiii
Acknowledgements .................................................................................................................... xiv
Dedication ................................................................................................................................... xvi
Chapter 1: Introduction ................................................................................................................1
1.1 Background ..................................................................................................................... 1
1.2 Prior Work ...................................................................................................................... 3
1.3 iCANPlateTM: The Dietary Self-Monitoring App ........................................................... 5
Chapter 2: Literature Review .......................................................................................................9
2.1 Introduction ..................................................................................................................... 9
2.2 Theoretical Background of Self-Monitoring ................................................................ 10
2.2.1 Self-monitoring in Behaviour Change Technique Taxonomy .............................. 12
2.3 Dietary Self-Monitoring................................................................................................ 13
2.3.1 Beneficial Health Outcomes Related to Dietary Self-Monitoring ........................ 14
2.3.2 Special Considerations for inclusive dietary self-monitoring tools ...................... 18
2.3.2.1 Ethnocultural Diversity ..................................................................................... 18
viii
2.3.2.2 Gender ............................................................................................................... 20
2.3.2.3 Health Literacy Level ....................................................................................... 21
2.4 Adherence to Dietary Self-Monitoring ......................................................................... 23
2.4.1 Definition of Adherence to Dietary Self-Monitoring ........................................... 23
2.4.2 Adherence to Different Dietary Self-Monitoring Tools ....................................... 25
2.4.2.1 Paper-Based Tools ............................................................................................ 26
2.4.2.2 Technology-Based Tools .................................................................................. 29
2.4.3 Improving Adherence to Dietary Self-Monitoring ............................................... 33
2.4.3.1 Plate-Based Tool ............................................................................................... 36
2.5 Canada’s Food Guide .................................................................................................... 40
Chapter 3: Methodology..............................................................................................................42
3.1 Study Design ................................................................................................................. 42
3.2 Participants and recruitment ......................................................................................... 42
3.3 Focus Group Guide Development ................................................................................ 44
3.4 Study Procedure ............................................................................................................ 47
3.5 Data Analysis ................................................................................................................ 48
3.6 Ethical Considerations .................................................................................................. 49
Chapter 4: Results........................................................................................................................51
4.1 Participants .................................................................................................................... 51
4.2 Perceptions of the Current Iteration of iCANPlate ....................................................... 57
4.2.1 Facilitators to the Use of a Plate-Based Dietary Self-Monitoring App ................ 57
4.2.1.1 Self-Awareness of Dietary Behaviours ............................................................. 57
4.2.1.2 Simplicity .......................................................................................................... 58
ix
4.2.2 Barriers to Using the Plate-Based Dietary Self-Monitoring App ......................... 59
4.2.2.1 Lack of Food Classifications ............................................................................ 59
4.2.2.2 Conceptualizing Proportions ............................................................................. 61
4.2.2.3 Lack of Inclusivity ............................................................................................ 62
4.3 Components to Include in Future Iterations of iCANPlate ........................................... 64
4.3.1 Essential Component to Add to iCANPlate .......................................................... 64
4.3.1.1 Educational Content and Tutorials.................................................................... 64
4.3.1.2 Report Dashboard ............................................................................................. 65
4.3.1.3 Accessibility ...................................................................................................... 65
4.3.2 Optional Components to Add to iCANPlate ......................................................... 66
4.3.2.1 Personalization .................................................................................................. 66
4.3.2.2 Automatic Food Logging .................................................................................. 67
4.3.2.3 Recording Other Eating Behaviours ................................................................. 68
4.3.2.4 Social Interaction .............................................................................................. 68
4.3.2.5 Professional Support ......................................................................................... 69
4.3.2.6 Interactivity ....................................................................................................... 70
4.3.2.7 Incentivization................................................................................................... 70
Chapter 5: Discussion and Conclusion ......................................................................................72
5.1 Primary Findings ........................................................................................................... 72
5.1.1 Facilitators of Using the iCANPlate App ............................................................. 73
5.1.2 Barriers to Use the iCANPlate App ...................................................................... 75
5.1.3 Essential Components Suggested to Add ............................................................. 77
5.1.4 Optional Components Suggested to Add .............................................................. 78
x
5.2 Strengths and Limitation ............................................................................................... 80
5.3 Implications for Research and Practice......................................................................... 82
5.4 Conclusion .................................................................................................................... 83
Bibliography .................................................................................................................................84
Appendices ..................................................................................................................................100
Appendix A Consolidated criteria for reporting qualitative studies ....................................... 100
Appendix B Focus Group Guide............................................................................................. 103
B.1 Section 1: Perceptions of the 2019 CFG ................................................................. 103
B.2 Section 2: History of using dietary self-monitoring tools ....................................... 103
B.3 Section 3: Content and features of the proposed app .............................................. 103
xi
List of Tables
Table 1- Comparison of paper-based and technology-based dietary self-monitoring tools ......... 33
Table 2- Mapping of the focus group guide to the COM-B constructs ........................................ 46
Table 3- Socio-demographic characteristics of the study sample ................................................. 53
Table 4- Major categories, themes and subthemes reported by the general public participants... 55
Table 5- Major categories, themes and subthemes reported by Registered Dietitians ................. 56
xii
List of Figures
Figure 1- An example of the paper version of the plate-based tool resembling the 2019 CFG ..... 5
Figure 2- An example of food recording within the iCANPlate prototype .................................... 7
Figure 3- Action loop described in the self-regulation process .................................................... 12
Figure 4- First plate-based tool developed in Sweden .................................................................. 37
Figure 5- The COM-B model with examples of the related questions. ........................................ 44
Figure 6- Recruitment flow chart .................................................................................................. 70
xiii
List of Abbreviations
App: Application
BCT: Behavior Change Technique
BCW: Behaviour Change Wheel
BMI: Body Mass Index
CFG: Canada’s Food Guide
CI: Confidence Interval
COM-B: Capabilities, Opportunities, and Behavior
CVD: Cardiovascular Disease
RCT: Randomized Controlled Trial
RD: Registered Dietitian
xiv
Acknowledgements
This research has been made possible through the invaluable support of numerous
individuals who not only stood by me but also embraced the significance of this study.
First and foremost, my deepest gratitude to my supervisor, Dr. Tamara Cohen, who
accepted me as part of the iCANPlate team. I will forever be thankful for your support and
extraordinary patience throughout the ups and downs of this journey. I have learned and grown
greatly under your exceptional expertise and invaluable guidance. I am incredibly fortunate to
have been mentored by someone as dedicated and inspiring as you. I would also like to extend
my heartfelt appreciation to the co-applicants of the iCANPlate study: Dr. Jean-Philippe Gouin
and Dr. Maryam Kebbe; thank you for your constructive feedback and suggestions which have
greatly enriched this study. I also want to acknowledge the members of my master’s thesis
committee, Dr. Ryan Rhodes, Dr. Annalijn Conklin, and Dr. Scott Lear, for your time, expertise,
and valuable input throughout this journey.
My appreciation to the funding agencies Social Sciences and Humanities Research
Council and the Howard Webster Foundation for their grant support, which made this research
possible.
I express my sincere gratitude to all Registered Dietitians and general public participants
who generously dedicated their time and shared their insights. Your contributions were essential
in shaping the outcomes of this study, and I am humbled by your willingness to engage in the
research process.
I want to acknowledge the support and encouragement of the previous and present
members of the Nutrition and Eating Behaviour (NEB) lab, and especially the iCANPlate team
xv
whose belief in my abilities has been a constant source of motivation. Your friendship and
support have made this journey more enjoyable and memorable.
To my friends: Hadis, Kate, Sara, Goli, Mahya, Maede, Roqi, Mohadese, Hengame, and
Samane, I appreciate our genuine friendship.
Finally, I owe a profound gratitude to my family: my partner, Hossein, your love and
encouragement have been my rock. You have consistently provided a receptive ear and offered
invaluable perspectives and suggestions that have made this journey achievable, and I am
eternally grateful to you. I would also like to acknowledge my exceptionally supportive siblings,
my brother, Amir, and my sisters, Monir and Marjan. Your constant support and insightful
conversations have been invaluable to this journey. Last but not least, I express my deepest
gratitude to my parents for their unconditional love and lifelong encouragement. Your sacrifices,
guidance, and belief in me have been the driving force behind my achievements. I am forever
grateful for the values you instilled in me that helped me in fulfilling this degree.
xvi
Dedication
This thesis is dedicated to all women around the world who courageously strive for
freedom, with special recognition for women in Iran.
1
Chapter 1: Introduction
1.1 Background
Dietary self-monitoring (e.g., diet tracking), as a behaviour change technique (BCT),
plays a key role in both the adoption and maintenance of new dietary behaviours.1 Self-
monitoring functions by increasing self-awareness of one’s actions and the conditions under
which they occur.2,3 The Control Theory1 recognizes that despite intending to change behaviours
or to maintain healthy behaviours, an intention does not always translate into the desired
behaviour.4 This “intention-behaviour gap” can be attributed to difficulties individuals
experience with self-regulation.5,6 Self-monitoring is central in the self-regulation process as it
involves a conscious focus on one’s behaviour through systematic monitoring of one’s goal-
oriented behaviours.2 Studies on behaviour change indicate that consistent self-monitoring,
regardless of the content or comprehensiveness of what is being monitored, is crucial for
maintaining dietary changes over time and achieving dietary goals.7–10
While self-monitoring is important in bridging the “intention-behaviour gap”, adherence
to dietary self-monitoring over time is compounded by the complexity and time-consuming
nature of current tools.11–13 Scholarly works show decreases in adherence to dietary self-
monitoring during weeks 3-5 of interventions intended to last 4 and 6 months when participants
are asked to self-monitor diet using paper-based tools.12 Technology-based tools present
advantages over paper-based dietary self-monitoring tools such as providing date and time
stamps, instant feedback of food comparisons, and reminder signals to lessen the burden of self-
monitoring.14–16 Among technology-based tools, mobile applications (apps), in particular, have
been increasingly used in randomized controlled trials to encourage adherence to dietary self-
2
monitoring.17,18 Systematic reviews of diet improvement interventions have also revealed that
mobile apps are more effective in assisting individuals with weight management19 and changing
eating behaviours compared to paper-based tools and websites.19,20
Inherent challenges, however, are present with available technology-based tools, such as
an over-emphasis on calorie counting and portion measurement, which was associated with
higher levels of dietary restraint and eating concerns.21 These challenges ultimately lead to
declines in adherence to dietary self-monitoring.14,17 In fact, a decline in adherence to dietary
self-monitoring using technology-based tools has been shown to occur as early as week nine.13
Moreover, available apps are often health and numeracy literacy dependent,22 meaning that using
these apps to self-monitor dietary intake requires information literacy (i.e., the knowledge to
itemize food items), numeracy skills, and digital literacy.23–25
Shifting towards less complex and more user-friendly approaches, such as the plate-based
approach to eating over itemizing foods, could enhance adherence to dietary self-monitoring.26
Using this approach for dietary self-monitoring includes filling in the proportions of each section
to reflect the amount of each food type consumed. The lack of food itemization, texts, or
numbers in the plate-based approach makes dietary self-monitoring less complex and more
accessible especially to individuals with varying levels of health literacy.22,23,27 In addition, the
visual depiction of a plate in this approach facilitates the understanding of healthy eating
information for the general public.28 Using the plate-based approach to meal planning has been
shown to improve health outcomes, showing comparable efficacy to more demanding
interventions including carbohydrate counting22 or calorie-counting.29 Additionally, this
approach has been associated with the promotion of healthy eating behaviours by reducing the
consumption of refined carbohydrates, sugar, and total fat.29,30
3
In 2019, Canada joined a growing number of countries and associations31–33 in adopting
the plate-based approach to healthy eating as a new national nutrition guideline.34 This approach
is embodied in the updated Canada’s Food Guide (CFG) and involves visual representation of
three main food groups on a “plate” (i.e., half the plate being vegetables and fruits, a quarter of
the plate being protein, and a quarter of the plate being whole-grain foods). The general message
of CFG is to focus on the proportions of different food groups in one’s diet rather than on serving
sizes.34 With no quantitative dietary recommendations, this simplified plate-based approach was
suggested to be easier to comprehend and use for dietary planning on a daily basis.35
While this new food guide takes a more holistic approach as opposed to a prescriptive
approach (specifically sex-and-age-based food group recommendations), unique issues related to
the 2019 CFG as a dietary recommendation have been identified, including the likelihood of
calcium and vitamin D inadequacy36 associated with the removal of milk and milk products as a
separate food group,37 and lack of cultural representation on the foods present on the plate.38 The
plate-based approach to nutrition education has also been criticized in the literature, whereby it is
regarded to being perceived as too simplistic by some users;39 it can be challenging to follow the
recommended amounts without clear portion sizes denoted;39 and finally it can be difficult when
conceptualizing mixed dishes (i.e., various ingredients in a single dish).40
1.2 Prior Work
The presented study represents the continuation of a previous cross-over, mixed methods
study41 that was carried out at Concordia University (Montreal, QC) from May to June 2020 as
part of a master’s thesis (by CCB) to fulfill degree requirements at McGill University. This study
4
evaluated perceptions of the usability of a traditional paper-based food journal (3-day food diary)
compared to a paper-based version of the plate-based approach resembling the 2019 CFG.42
Forty-five healthy older adults (40% men, 63.0±5.6 years) were randomly assigned to
self-monitor their dietary intake using paper tools: either a standard food diary or a plate-based
tool (Figure 1). Participants were asked to use one tool for one week (three non-consecutive
days), then the other tool for another three non-consecutive days the following week. Thematic
analysis identified easy, visual, and quick as the main themes for the plate-based tool, and detail,
quantification, and familiarity for the traditional food journal. In addition, 62% of participants
preferred the plate-based approach for making dietary changes over time.
5
Figure 1- An example of paper version of the plate-based tool resembling the 2019
CFG. Participants were asked to drew lines on circles to describe the proportion of foods
from the three food groups as shown on the CFG. When the foods did not “fit” in the
plate, space was provided for them to jot them down. Beverages were notes in the form of
a list. Participants were instructed to not include portion or serving sizes, not the same of
the foods or meals.
1.3 iCANPlateTM: The Dietary Self-Monitoring App
The premise behind the concept of iCANPlateTM is to create a dietary self-monitoring
tool that is inclusive and accessible to all Canadians to assist them in self-monitoring their
dietary intake in accordance with the 2019 CFG. The app was developed with funding from
6
Social Sciences and Humanities Research Council and the R. Howard Webster Foundation
through Concordia University; Raphaël Titsworth-Morin, from Éphémère Creative Ltd was hired
to develop the prototype iCANPlateTM version 0.1 (Figure 2).
The iCANPlate app resembles a plate in the form of a pie chart whereby the user records
meals and snacks by adjusting the proportions of each food group to match the proportions of the
foods on their plate. As depicted in Figure 2, the three food categories on the app match those
recommended in the CFG: vegetables and fruits (green), grain foods (orange), and protein foods
(pink). The main goal of the app is to allow users to self-monitor foods consumed as they would
appear on a plate, categorizing the food into the appropriate CFG category and indicating the
proportion of the plate occupied by the food. Importantly, iCANPlate is not intended to be used
as a dietary assessment tool, as it does not ask users to record details or count serving sizes and
calories.
7
Figure 2- An example of food recording within the iCANPlate prototype (version 0.1)- The colours
correspond to the different food categories that match the CFG: protein foods (pink), vegetables and fruits
(green) and grain products (orange). Users adjust the proportions of the food categories based on their meals
by sliding buttons up or down. The input proportions on the app correspond to the food image, which
includes pasta, chicken breast, and salad.
1.4 Project’s Rational and Objective
Dietary self-monitoring is a key component for helping individuals attain and maintain
healthy dietary behaviours.1 However, current dietary self-monitoring tools mostly focus on food
itemizing and are not aligned with the new CFG. Furthermore, users find them too complex and
time-consuming to be completed on a regular basis,11–13, especially among individuals with low
levels of health literacy.22 All of these may lead to declines in adherence to dietary self-
monitoring. Using a simplified plate-based approach, as embodied in CFG, for dietary self-
monitoring might be more accessible and inclusive for individuals with low levels of health
literacy compared to the current tools. By providing a less complex and more user-friendly
8
approach, the plate-based approach has the potential to enhance adherence to dietary self-
monitoring among the general public.
The aim of this study was to explore potential end-users’ (i.e., general public) and
Registered Dietitians’ (RDs’) perceptions of iCANPlate, a mobile plate-based app that mirrors
the CFG. RDs in this project are considered the “knowledge-user” since they are the allied health
professionals who would integrate the app into their practice.43 Including input by both “end-
users” and “knowledge-users” at this stage of app development is critical and an important
necessary first step; findings of this study will contribute to the successful adoption,
implementation, and continued use of the app.44,45
Results from this qualitative study will be used to further develop iCANPlate. The
overarching goal of the iCANPlate project is to create an accessible and inclusive app that
promotes healthy eating patterns to be used by all Canadians.
9
Chapter 2: Literature Review
2.1 Introduction
Healthy eating is a central factor in one’s overall well-being and healthy human
development from the early stages of life to later adulthood.46 The World Health Organization
suggests that healthy eating can reduce the risk of non-communicable chronic diseases (e.g.,
obesity, diabetes, cardiovascular disease (CVD), and cancer).47 Additionally, healthy eating has
been linked to a lower risk of all-cause mortality worldwide and in Canada.48,49 However, many
Canadians have unhealthy eating patterns and do not adhere to dietary guidelines.50,51 Given the
importance of the preventive role of healthy eating in chronic diseases, along with the low
adherence rates to the recommended dietary guidelines in high-income countries, including
Canada, there is a clear need for effective strategies to promote and sustain healthy dietary
behaviours. Self-monitoring is a critical component of behaviour change and goal attainment and
is the primary focus of this thesis.
In this chapter, a review of the existing literature on dietary self-monitoring and its
efficacy in promoting healthy eating behaviours will be presented. This chapter will define self-
monitoring, discuss its theoretical background, and highlight its significance in behaviour
modification. It will then focus on dietary self-monitoring and its role in the promotion of health
outcomes. Adherence to dietary self-monitoring, its effectiveness, and a comparison of
adherence to different dietary self-monitoring tools will also be discussed. Additionally,
suggestions for improving adherence to dietary self-monitoring, including the plate-based
approach, will be presented. Lastly, the chapter will provide an overview of the 2019 CFG and
the plate-based approach recommended by the food guide.
10
2.2 Theoretical Background of Self-Monitoring
Self-monitoring is a BCT referring to the act of keeping a record of one’s behaviour
related to a specific domain of behaviour change or a desired outcome of the behaviour.52 Within
the health behaviour domain, including diet and physical activity, self-monitoring is found to
decrease undesirable behaviours and increase desired behaviours.53–57 The process of self-
monitoring is highly selective in nature and typically depends on individuals’ existing cognitive
structures and beliefs.58
It is suggested that this technique is essential for adopting new behaviours.59 Several
explanations have been offered as to how and why self-monitoring facilitates behaviour change.
Self-monitoring provides individuals with an opportunity to evaluate progress toward goals,
comply with recommendations, acquire a better understanding of key behaviours, identify areas
of concern, and feel accomplished through the process.59 Additionally, self-monitoring may
function by bringing habitual behaviours that are normally automatic and partially unconscious60
into conscious awareness.61
Historically, health and social psychology theories have been devoted to understanding
what predicts and affects human behaviour.62 Certain psychological theories provide a
framework for understanding the complex processes involved in behaviour change. Self-
monitoring is grounded in the broader behaviour change construct of self-regulation, which has a
long history in the field of psychology and is required to make changes in behaviours.59 Theories
such as Self-Regulation Theory, Social Cognitive Theory, and Control Theory provide insights
into the concept of self-monitoring by demonstrating its potential to promote positive behaviour
change in multiple areas, including weight loss, physical activity, and dietary behaviours.
11
Social Cognitive Theory,58 proposed by Albert Bandura, explains human behaviour and
asserts that self-regulation is achieved through self-monitoring.58 The theory emphasizes the role
of observational learning, self-regulation, and self-efficacy in human behaviour. Self-regulation
is defined and encompasses regulating internal drives in response to external triggers to manage
human behaviour.63–65 Typically, this takes the form of replacing an existing behaviour or
response with a less common yet more desirable one. The self-regulatory mechanism operates
through three fundamental sub-functions, comprising self-monitoring, its determinants and
consequences; judgment of one’s behaviour; and affective self-reaction.58 Self-regulation’s
success partly depends on the accuracy, consistency, and proximity time of the self-monitoring
activities.58 This theory endorses self-monitoring dietary intake, making individuals more aware
of their internal and external drives to regulate their eating patterns.
Self-Regulation Theory,59 developed by Frederick Kanfer, proposes self-observation, as
a broader concept of self-monitoring, is a first step towards self-directed behaviour modification.
In fact, self-observation should be considered for conceptualizing self-regulatory processes,
characterized by integrating three components, self-reaction, self-evaluation, and self-
reinforcement, to achieve self- or externally prescribed behaviour standards.66,67,68 Hence, the
practice of dietary self-monitoring is based on self-regulation theory, suggesting that the three
components are required to achieve healthy eating behaviours.
Control Theory,69 developed by Carver and Scheier, focuses on how individuals
regulate their behaviour to achieve and maintain their goals in their environment. It posits that as
part of regulating behaviour, it is necessary to set goals, monitor the behaviour, receive feedback,
and adjust goals based on the feedback received.69 In the context of healthy eating, this theory
12
highlights the importance of setting healthy eating goals, regularly self-monitoring dietary
intake, and adjusting the behaviour in order to achieve healthy eating behaviours.
In all these theories self-monitoring, as an integral part of self-regulation, enables
individuals to identify the gaps between their current behaviour and their goals to alter their
behaviour accordingly. As shown in Figure 3, self-regulation is a dynamic process that involves
setting goals, monitoring progress, and adjusting behaviour in order to achieve those goals.
Through this action loop, self-monitoring can help individuals to be more motivated and better
equipped to regulate their future behaviours.70
2.2.1 Self-monitoring in Behaviour Change Technique Taxonomy
A BCT refers to an observable, irreducible, and replicable methodology employed by
practitioners to modify behaviours.71 It represents a specific and essential component of an
intervention aimed at behaviour change and serves as a potentially “active ingredient” in the
intervention.72 BCTs can be utilized independently or in conjunction with other BCTs. Adopting
Figure 3- Action loop described in the self-regulation process - adapted from Burnette et
al.69- Path represents the direct link between goal setting and goal operation, whereas Path a
represents the link between goal setting and goal monitoring once the input function is available
(i.e., once individuals can determine how far their current situation differs from their standard).
d
c
a
b
Goal Operating
Goal Setting
Input Function
Goal Monitoring
13
a common language and delineating BCTs enables researchers and practitioners to enhance
communication and identify active ingredients in complex behaviour change interventions.
In 2013, Michie et al. developed a hierarchically structured taxonomy of techniques (v1)
for behaviour change interventions.72 The BCT taxonomy includes a standardized terminology
for describing the constituent behaviour change techniques.56 The taxonomy (v1) encompasses
93 hierarchical BCTs organized into 16 clusters. Self-monitoring of behaviour (2.3) and self-
monitoring of outcomes(s) of the behaviours (2.4) are examples of the techniques classified
under the feedback and monitoring cluster. Multiple systematic reviews have identified effective
BCTs within lifestyle interventions aimed at improving diet73 and weight74,75 outcomes. Based
on their findings, interventions incorporating BCTs, such as self-monitoring, social support, and
goal setting, have been found to be more effective.73–75 This thesis focuses on the first definition
of the self-monitoring technique (2.3), which involves establishing a strategy to monitor and
record behaviour(s) in the context of the behaviour change process.
2.3 Dietary Self-Monitoring
Dietary self-monitoring refers to the application of self-monitoring specific to nutritional
situations. It is essential to distinguish dietary self-monitoring and dietary assessment in the
context of nutrition, as these are two distinct methods of obtaining information about an
individual’s dietary intake. Dietary assessment involves collecting information on an individual’s
dietary intake through a variety of methods, such as food frequency questionnaires, 24-hour
recalls, or food diaries. This information is typically then analyzed to determine the individual’s
nutrient intake and identify any potential dietary deficiencies or excesses.76
14
Dietary self-monitoring is the process of collecting and recording information about
one’s food intake to promote awareness of dietary behaviours.77 Unlike dietary assessment,
which focuses on a quantitative analysis of the nutrient intake,8 dietary self-monitoring allows
individuals to increase their perceived behavioural control by gaining more insight into their
dietary patterns and thereby making informed decisions about their potential dietary deficiencies
or excesses.8 Dietary self-monitoring enhances self-awareness, an initial first step to making
behavioural changes.78 Indeed, the interaction between awareness, self-observation, recording,
and self-evaluation has the potential to enhance self-management by improving individuals’
capacity to self-monitor and attend to their health.79
2.3.1 Beneficial Health Outcomes Related to Dietary Self-Monitoring
The use of self-monitoring has been linked with several positive health outcomes. It is
widely acknowledged that self-monitoring is a critical component of behavioural interventions
frequently recommended and used for interventions involving weight loss,80–82 and when
individuals try to lose weight without professional help.83 Most studies on dietary self-
monitoring targeted weight management as the primary health outcome.
A systematic review84 of the literature included n=48 studies to identify successful
strategies for weight loss and its long-term maintenance. A successful intervention was defined
as achieving ≥5% weight loss from baseline and maintaining this weight loss for at least 12
months from the baseline during a maintenance phase (the minimum amount of time for all
interventions was three months). Findings of the review revealed that 92% of successful
interventions included some element of behaviour training, and dietary self-monitoring (n=21)
was the most frequently used technique.84 The study provides valuable insights into effective
15
weight loss and weight maintenance strategies, including dietary self-monitoring. However, the
primary objective of this study was not to specifically examine the effects of dietary self-
monitoring on health outcomes. Therefore, an in-depth exploration of different types of dietary
self-monitoring and their comparative effects on outcomes such as weight was not within the
scope of this research.
Furthermore, several systematic reviews have presented evidence supporting the benefits
of dietary self-monitoring among populations with or at risk of chronic diseases. A meta-
analysis85 comprising n=18 studies was conducted to summarize and synthesize the clinical
evidence regarding the efficacy of mobile apps for lifestyle modification across different
subtypes of diabetes. Thirteen studies emphasized dietary self-monitoring as a key component,
encompassing both short-term interventions spanning 3-6 months (n=10) and long-term
interventions spanning 9-12 months (n=3). Eleven studies were specifically focused on Type 2
diabetes, with six studies incorporating dietary self-monitoring. Findings of the review provide
compelling evidence for the efficacy of mobile apps in facilitating lifestyle modification in Type
2 diabetes.85 However, further research is required for the other subtypes of diabetes.
Another systematic review86 of n=5 studies (ranging from 6 to 16 weeks) revealed the
clinical benefits of dietary self-monitoring using mobile apps in chronic kidney disease.
Specifically, the review suggested beneficial effects on intradialytic weight gain, fluid,
potassium, and sodium intake in dialysis patients. However, statistical significance was not
achieved because of the small sample sizes in all included studies and the lack of emphasis on
dietary self-monitoring in four studies.86 One of the included studies, conducted by Welch et
al.,87 observed that sodium intake significantly decreased after a 6-week intervention (P=0.05).
This particular study accounted for adherence to dietary self-monitoring and
16
only examined active users (those who used the app more than 50% of the time). Despite the
limited number of included studies, the review presents valuable insights into the clinical
benefits of dietary self-monitoring in chronic kidney disease. Given that the review was
conducted more than eight years ago and considering the rapid advancement of technology in
chronic disease management, it is important to note that this review may not include several
significant studies conducted in recent years.
To further explore the relationship between dietary self-monitoring and other health
outcomes such as hypertension, a meta-analysis88 (n=15) was conducted to investigate
whether self-monitoring via mobile apps impacts health behaviours in patients with
hypertension. Findings showed that behavioural app-based self-monitoring interventions have a
small but significant effect on reducing systolic blood pressure by an average of 1.64 mmHg
(95% Confidence Interval (CI) 2.73-0.55). The meta-analysis88 identified four studies
investigating the relationship between behavioural self-monitoring (all of which included the
dietary self-monitoring component) and dietary outcomes. According to the authors, behavioural
self-monitoring is moderately effective in modifying dietary behaviours by reducing
consumption of high-sodium foods (standardized mean difference between 0.44 and 0.79).88 In
the review, there is no distinction between behavioural self-monitoring and dietary self-
monitoring, which limits the ability to evaluate the specific effects of each.
Among individuals at risk of developing Type 2 diabetes, a systematic review89 of n=37
studies was conducted to identify the BCTs and digital features most frequently used in effective
technology-based diabetes prevention interventions. Interventions considered effective resulted
in clinically significant weight loss and improved additional outcomes related to diabetes
onset. Both short-term interventions (characterized by achieving >3% weight loss at < 6 months)
17
and long-term interventions (characterized by achieving >5% weight loss at <12 months) were
investigated in the review. In 75% of short- and long-term interventions, self-monitoring of
behaviour (such as self-monitoring of diet) emerged as a beneficial behaviour change
technique.89 Despite the fact that the review provides insights into the associations between
specific BCTs, digital features, and effectiveness in interventions, causality cannot be inferred
from these findings. Further research is needed to determine which intervention components are
most effective, particularly for specific subgroups of the population, according to factors such as
age, gender, ethnicity, location, and socioeconomic status.
Another systematic review90 (n=24) was conducted to determine if adherence to self-
monitoring using mobile apps for preventing and managing CVD is associated with improved
health behaviour changes and CVD risk factor outcomes. The review included n=18 studies
comprising a dietary self-monitoring feature. User engagement was categorized by frequency
and pattern of self-monitoring activities using various measures, including tracking the number
of log-ins per week or month, number of days using the app, total time spent using the app, and
frequency of using different app features. Surprisingly, while some studies have shown a
potential link between dietary self-monitoring and greater weight loss, the review does not
provide a comprehensive picture of how user engagement with mobile apps is associated with
other CVD health-related outcomes. Authors of the review proposed two possible explanations:
(1) potential underpowered studies within the review that may have hindered the detection of a
significant relationship between user engagement and cardiovascular disease (CVD) outcomes,
and (2) the lack of a medication adherence component in the majority of interventions,
potentially impacting the overall effectiveness of the interventions.90 The review did not
differentiate participant demographics (e.g., race and sex), which may pose limitations to the
18
generalizability of the results. By not accounting for these demographic factors, the review may
overlook potential variations in the effectiveness of self-monitoring using mobile apps for
different population groups. A more comprehensive analysis that considers diverse
demographics would enhance the applicability and relevance of the findings.
Overall, the incorporation of self-monitoring into health promotion programs is highly
recommended to improve health outcomes in populations with chronic diseases and obesity.
Nevertheless, significant gaps in the existing literature highlight the need for targeted studies that
evaluate the effectiveness of interventions within diverse populations. Such studies are essential
to provide a deeper understanding of how different factors interact and influence health
outcomes. These considerations can optimize the benefits of self-monitoring in health promotion
programs and effectively empower individuals to make informed dietary choices and attend to
their health care.
2.3.2 Special Considerations for inclusive dietary self-monitoring tools
There are several demographic factors to consider to ensure that dietary self-monitoring
tools are inclusive to all Canadians. Various factors may influence individuals' willingness to
uptake and engage with dietary self-monitoring tools, including ethnocultural background, age,
gender, education level, etc.80,91–93 However, the existing literature on all contributing factors is
limited, making it challenging to discuss each comprehensively.
2.3.2.1 Ethnocultural Diversity
In the Canadian context, it is projected that by 2036, individuals belonging to minority
ethnocultural groups will represent up to 40% of the population and nearly half of the population
19
will consist of immigrants or second-generation immigrants.94 This demographic shift highlights
the importance of considering ethnocultural diversity in eating patterns when developing dietary
self-monitoring tools.
To evaluate the baseline variations in demographic characteristics on the usage of diet-
related self-monitoring behaviour, a study91 was conducted among postmenopausal women
(n=123, mean age 57.9 ± 5.0) with overweight or obesity (defined as BMI ≥25 kg/m2, or
≥23 kg/m2 for Asian-American women) participating in a year-long dietary weight management
intervention. Participants were instructed to maintain a daily food record for a minimum of 6
months or until they achieved their individual weight loss goal, which was set at 10% of their
baseline body weight. The findings of the study showed a statically significant association
between race/ethnicity status and dietary self-monitoring (P < 0.05), with a trend towards a
higher amount of dietary self-monitoring (P = 0.07) among non-Hispanic white women.91 After
adjusting for the intervention arm and baseline BMI, it was observed that non-whites were less
likely to monitor energy intake on most days of the week compared to non-Hispanic whites
(adjusted odds ratio, 0.36; 95% CI, 0.13-0.97; P <0.05). No significant association was observed
between education level (college graduate or more compared to some colleges or less) and the
adoption of dietary self-monitoring. The study concluded the ability to better recognize groups
who are less likely to self-monitor might be beneficial in promoting these behaviours in future
interventions.91 Most participants in this study were non-Hispanic whites (n=103, 84%), limiting
the generalizability of the findings compared to other races/ethnicities. Therefore, caution should
be exercised when extrapolating these results to more diverse populations.
In contrast to the trends observed in developed countries where technology-based tools
for health interventions are increasingly prevalent,95 there is a low prevalence of such methods
20
being applied to minority ethnic groups. This discrepancy may be attributed to various factors,
including language barriers, limited access to education, and financial constraints.96 These
barriers can impede the adoption and utilization of technology-based tools among minority
ethnic groups, hindering their ability to benefit from the advancements in health technologies.
Addressing these barriers is crucial to ensure equitable access to effective health interventions
for all population groups, regardless of their ethnic backgrounds.
2.3.2.2 Gender
Unlike biological sex, the role of gender is a social construct based on cultural
stereotypes of what attitudes, behaviours, and characteristics are considered conventionally
masculine or feminine.97 Gender norms play a significant role in shaping perceptions of
appropriate food choices for men and women.98 In terms of their eating behaviour, women
generally adhere more closely to dietary guidelines than men99 and have a higher self-determined
motivation for eating-related behaviours (P = 0.002).100 More specifically, women have
exhibited a higher likelihood compared to men in reporting the conscious consumption of high-
fat foods, eating fruit and fibre, and practising salt limitation.101 Women also demonstrated a
higher propensity for engaging in dieting practices and placed a greater emphasis on the
importance of healthy eating.101 These gender variations can probably impact an individual’s
intention and capacity to categorize food types within different meals, emphasizing the
significance of integrating gender considerations in the design of the dietary self-monitoring
intervention. However, limited literature explores the nuances within gender related to dietary
self-monitoring. Therefore, future studies are warranted to further investigate and understand
these gender-specific dynamics and their implications in the context of dietary self-monitoring.
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2.3.2.3 Health Literacy Level
A high level of health literacy is necessary to correctly self-monitor one’s diet using
current dietary self-monitoring tools.7,27,22 Health literacy refers to the ability of individuals to
obtain, process, and understand basic health information and services required to make informed
health decisions.102 As outlined by the National Network of Libraries of Medicine,103 health
literacy includes (a) personal literacy (i.e., ability to find, understand, and use health information
and services), (b) organizational health literacy (i.e., the degree to which organizations equitably
enable individuals to find, understand, and use health information and services), (c) digital health
literacy (the ability to seek, find, understand, and appraise health information from electronic
sources), and (d) numeracy skills (i.e., the ability to perform a set of mathematical skills essential
in a data-driven society).
Current dietary self-monitoring tools typically necessitate a relatively high level of health
literacy since they usually require reading and writing abilities (personal literacy) to itemize food
items, numeracy skills, particularly for portion counting, and digital literacy to use a dietary self-
monitoring app.23–25,27 An association has been shown between the level of health literacy with
self-efficacy, social support, and knowledge, all of which contribute positively to an individual’s
ability to engage in effective self-monitoring practices.104
A study105 was conducted with n=53 (mean BMI= 35.6 ± 6.4 kg/m2) to assess factors
associated with poor weight loss results that required intensified interventions.105 A six-month
stepped-care treatment approach was employed, consisting of three steps. Step-1 involved a self-
administered Diabetes Prevention Program using a calorie-counting technology-based self-
monitoring tool (Fitbit® website, US) to enhance weight loss and participant engagement,
22
including instructions to maintain a daily calorie deficit of 500-1000 calories. Those who did not
meet weight loss goals (defined as 2.5% of their baseline body weight at two months, 5.0% at
four months, and 7.5% at six months) progressed to Step-2, which incorporated meal
replacement, and finally to Step-3, which introduced individual counselling alongside meal
replacement. The findings from the study105 revealed that participants who did not undergo any
additional steps or only stepped up once achieved a clinically significant weight loss (i.e.,
>5%).105 However, participants who stepped up twice experienced insignificant weight loss.
Findings revealed that participants in Step-3 had significantly lower health literacy levels and a
lower frequency of self-monitoring (P=0.03).105 Compared to other variables, a trend was shown
between lower health literacy and greater attrition (P=0.09). The study105 concluded that regular
self-monitoring and high health literacy are significant predictors of successful weight loss. The
authors mentioned although health literacy research among weight loss participants is still in its
early stages, further investigation into tailored weight loss interventions for individuals with low
health literacy is crucial for future advancements in this field.105
From an organizational health literacy perspective, the National Academies of Sciences,
Engineering, and Medicine stated that it is crucial to consider health literacy in the delivery of
care to decrease the cost of care and poor outcomes.106 Linking self-monitoring with health
literacy has shown potential benefits, including improved adherence to healthy behaviours,
enhanced problem-solving abilities, and increased knowledge about healthy behaviours.107–111
Moreover, poorer literacy and numeracy levels have been related to lower dietary intakes of
vegetables and fruits and high consumption of sugar-sweetened beverages,27 which necessitates
considering health literacy in nutritional interventions. Hence, streamlining the requirements of
23
health literacy and numeracy skills may increase the proportion of people who feel confident
about self-monitoring their health.112
2.4 Adherence to Dietary Self-Monitoring
Adherence refers to the extent to which an individual implements a behaviour, such as
eating a healthy diet, taking prescription medications, or making lifestyle changes, that is aligned
with a recommendation and/or instructions made by healthcare providers.15,113 In studies that
used comprehensive lifestyle intervention strategies, there was a substantial association between
health outcomes and adherence to dietary self-monitoring.84,114,115
It has been postulated that possessing self-regulation and self-monitoring skills, including
specific indicators such as frequency, consistency, and accuracy in the self-monitoring process,
is a prerequisite for effective changes in health behaviour.2,80 These indicators can be used to
reflect the level of adherence.116 A precise comprehension of the indicators above, which have
undergone changes in meaning due to the incorporation of technology, is essential in evaluating
the effectiveness of dietary self-monitoring.
2.4.1 Definition of Adherence to Dietary Self-Monitoring
Adherence to dietary self-monitoring can vary widely among individuals, and there is no
consensus as to what constitutes adherence to self-monitoring of dietary intake.84,117 Measuring
frequency in the context of dietary self-monitoring has evolved. A systematic review of n=24
studies was conducted to report the effects of self-monitoring on three components of diet,
physical activity, and weight in weight loss behavioural interventions. Only five studies included
a technology-based tool and fifteen studies specifically focused on dietary self-monitoring.
24
Assessment of adherence to dietary self-monitoring in the included studies involved various
measures, including the frequency of submitted diaries (n=3), researchers’ and clinicians’ ratings
of diary completeness (n=3) and based on a self-reported survey on both frequency and
consistency (n=3). Findings of the review commented on studies that used researchers’ or
clinicians’ judgment scores to evaluate the accuracy and completeness of a record (n=4),
showing that individuals with more complete self-monitoring records experienced greater weight
loss compared to those with less complete records (P< 0.05).80 Findings related to the effect of
adherence to dietary self-monitoring when measuring by frequency or consistency were mixed.
Authors noted that this variability in the measurement method makes it impossible to compare
adherence across studies. Moreover, one of the included studies observed the occurrence of
backfilling, wherein individuals submitted diaries that were completed for days when the diaries
were not initially opened, making the adherence measurement more complicated.118 The review
found various gaps in the literature, such as insufficient knowledge regarding the optimal
frequency and duration of self-monitoring for diet and exercise, as well as limited evidence on
the effectiveness of self-monitoring among under-represented subpopulations in weight loss
studies.118 This review was conducted in 2011 and included only five studies using a technology-
based tool which means that particularly many currently popular dietary self-monitoring tools
(e.g., apps) were not included in the review.
Later, in 2018 a narrative review119 of studies (n=29) focused on defining adherence to
dietary self-monitoring using mobile apps. Two main themes were extracted in relation to the
definition of adherence from the included studies: 1) Recorded amount of calorie intake, and 2)
Frequency of dietary self-monitoring. The first theme of adherence pertains to the level of detail,
accuracy, and completeness in dietary self-monitoring. It involved n=11 studies that defined
25
adherence as the completion of recording a minimum amount of calorie intake or a calorie
amount within a specific range of calories. For example, individuals were adherent when the
recorded dietary intake in a given day exceeded 50% of their calorie goal. The importance of the
level of detail remains unclear, as it is the process of dietary self-monitoring that has been linked
to improved health outcomes, not its comprehensiveness.26 The majority of the included studies
(n=20) defined adherence under the second theme that relates to the consistency and/ or
frequency of dietary self-monitoring. It includes the frequency of dietary intake recording
(n=15), the frequency of interaction with the app (number of log-ins into the app or the app
usage) (n=8), and the timing of recording (2). The study discussed that many apps offer a “stay
logged in” feature, making it possible for a user to remain logged into the app for an extended
duration, while their actual usage or frequency of accessing the app can vary significantly
(P<0.05). Therefore, the importance of understanding the number of log-ins and the app content
that users access is unclear. The study concluded that until a consensus is established, it is
advisable to investigate multiple indicators of adherence to dietary self-monitoring through apps
and examine their associations with weight loss. Further research is required to explore the
various types and levels of adherence to dietary self-monitoring using apps and their impact on
weight loss within diverse populations.119
2.4.2 Adherence to Different Dietary Self-Monitoring Tools
The type of dietary self-monitoring tool used can impact adherence to dietary self-
monitoring and, subsequently, eating behaviours and health outcomes. A variety of tools and
methods are available to assist individuals in monitoring their food intake. Traditionally, these
tools are paper-based diaries.12 With the advent of technology, more tech-based tools such as
26
websites and mobile apps are becoming increasingly available.120 By using a dietary self-
monitoring tool, the individual is directed to document all their food consumption. This
documentation can be extended to include the location of the individual when eating (e.g., at
home or away), the time of day, the quantity consumed, and the target nutrient values (e.g.,
sodium, potassium, and fat grams).
In an ideal situation, the individual should record their food intake as it occurs. According
to the Social Cognitive theory, focusing on the distal effects of actions is ineffective in rectifying
past events and may offer limited direction for the future. Intermittent self-monitoring is only
partially informative, making self-regulation less effective than paying attention to one’s
performance on a regular basis.58 Real-time recording allows individuals to make adjustments to
their food intake so that they do not exceed their daily target values (e.g., calories, fat,
carbohydrates, sodium, cholesterol, or potassium).8
2.4.2.1 Paper-Based Tools
Paper-based tools include traditional methods such as food diaries and journals. These
tools typically involve writing down the food and drink items consumed in a 24-hour period.
They can also include other information such as time and place of consumption as well as the
individual’s hunger level and mood. Self-monitoring tools in a paper-based format have been
repeatedly linked to significant weight loss outcomes.12
Paper-based tools are characterized by their ease of use with minimal training, wide
availability in various formats, and cost-effectiveness.8 However, they have several limitations.
Firstly, the use of paper diaries requires literacy (defined as reading, writing, and calculation
abilities to record the food intake),8 which may be challenging for those with limited reading and
27
writing and numeracy skills or poor handwriting. Secondly, manually completing daily diaries is
a time-consuming and tedious process requiring the calculation and recording of food intake.
Thirdly, the use of paper diaries in public situations may lead to social unease.8 Moreover, using
a paper-based tool for dietary self-monitoring lacks instant feedback and may lead to misplaced
diary entries.78,84
A qualitative study conducted by Burke et al. explored participants’ experiences of
dietary self-monitoring. Participants had most recently completed an 18-month cognitive
behavioural weight management intervention. As part of the intervention, participants were
instructed to use a paper-based diary to record their daily food intake (i.e., calorie and fat grams).
Adherence to self-monitoring was defined as the number of days on which a participant recorded
a full day’s intake. The findings revealed challenges associated with reduced adherence to self-
monitoring, including difficulty managing the time, computational, and organizational demands
of the process.78 Hence, the development of a tool that effectively addresses these demands and
alleviates the challenges associated with dietary self-monitoring is crucial to enhance adherence.
In a 24-month clinical trial called the SAMRT trial conducted by Burke et al.,121,114 three
different approaches to self-monitoring diet and exercise were compared, including (1) a
personal digital assistant with feedback message (n=70), (2) a personal digital assistant without
feedback message (n=68), and (3) a paper-based diary (n=72). At six months, the percent mean
± SD weight loss in all groups was significant (personal digital assistant with feedback message
7.3± 6.6%; personal digital assistant without feedback message 5.5± 7.0%; paper-based diary
5.3± 5.9%) without any significant differences among the groups (P>0.05). Nevertheless, at six
months, the groups that utilized a personal digital assistant had significantly higher (P<0.01)
adherence (60%, 53% adherent) compared to the paper-based diary (31% adherent), which was
28
measured based on consistency. Declines in adherence to self-monitoring began by the 3rd week
in all three groups. The research concluded that consistency moderated the relationship between
using a paper-based tool for dietary self-monitoring and weight loss.114 The study was carried out
over a long period, enabling a better understanding of the longitudinal trends in dietary self-
monitoring. However, it lacked a control group that received standard care without any self-
monitoring component to account for the placebo effect of participation in a weight loss study.
Findings from this study thus suggest using technology-based tools may increase adherence to
dietary self-monitoring compared to paper-based tools while achieving similar results.
Peterson et al. conducted a study with 220 women (mean ± SD, age = 59.3 ± 6.1 years)
with obesity (mean body mass index (BMI) = 36.8 ± 4.9 kg/m2) who were asked to self-monitor
their dietary intake using a paper-based tool. During a 12-month care program, participants were
instructed to complete records at least three days each week, including the type, amount, caloric
content, and time of consumption for all foods and drinks consumed. After analyzing the
collected recordings, they concluded that there is a significant interaction between consistency
and frequency and not with comprehensiveness (P = 0.004). Further, the combination of high
consistency and frequency in dietary self-monitoring was linked to weight loss (total
effect = −0.0014, P < 0.001), and the adherence to daily calorie goals was the mediator of this
association (z = −4.3475, P < 0.0001).10 Collectively, these studies suggest that in order to make
dietary changes, content accuracy or comprehensiveness of what is monitored is less important
than the regular act of self-monitoring followed by self-regulation.10
29
2.4.2.2 Technology-Based Tools
Self-monitoring has recently gained popularity due to the availability of technology that
supports the monitoring and logging of personal information.122 Unlike conventional paper-based
approaches, dietary self-monitoring through technology-based tools is a convenient alternative.
These programs eliminate the burden of maintaining handwritten records, searching for nutrient
information in pocket manuals, and manually calculating their nutritional intake (Table 1).8
Mobile apps, in particular, provide several advantages, such as being free or low cost, instant
access to comprehensive nutrition information databases, simplified data entry through barcode
scanning, and providing immediate feedback in terms of nutrients and calories.10,15,123
Despite the limited evidence for the use of dietary self-monitoring apps,115 these tools are
widely used by the general public.124 Literature has shown that in comparison to traditional
approaches, such as paper diaries, dietary self-monitoring using mobile apps is associated with
promoting greater adherence to tracking protocols.125–129 However, it was determined that there
were no significant differences in weight loss among the groups who self-monitored their diet
with either a paper-based or a tech-based tool.128
A pilot study conducted in the United Kingdom (n= 128 adults with BMI ≥27 kg/m2)
aimed to assess the acceptability and feasibility of a self-monitoring weight management mobile
app (My Meal Mate) compared to a website and paper diary. The app involved an extensive food
and drinks database and required self-monitoring daily calorie intake toward achieving the set
goals. Participants were randomized to receive the intervention by one of the three modes of
delivery over six months. Adherence (frequency of use) to dietary self-monitoring was
significantly higher in the mobile app group (P<0.001). The mobile group showed the highest
adherence to dietary self-monitoring at six months, with a mean of 92±67 days completed
30
compared with 35±44 days in the website group and 29 ±39 days in the diary group. Since the
trial was not statistically powered to detect a difference in weight change among the groups, no
significant differences were reported in terms of weight loss among the three groups (mean
weight loss of -5.0 kg (95% CI -6.7 to -3.3)). This study provides useful information on the
efficacy of mobile apps on adherence to dietary self-monitoring compared to traditional tools.
However, there was a 38% attrition rate in the study overall, with more non-completers at
follow-up in the diary and the website groups compared to the mobile group (P<0.001). There
was a high rate of retention in the mobile group, with 93% returning for follow-up at six months
(compared with 53% in the diary group and 55% in the website group).18
In an uncontrolled prospective study,130 a single-arm design was used to examine the
effectiveness of using a calorie-counting app (Calorie Counter by FatSecret app, Melbourne,
Australia) for self-monitoring dietary intake. Ninety adults (mean age 42 ±10.1 years; mean BMI
35.1± 6.2 kg/m2) with obesity or overweight (overweight was defined as a BMI of 25.0 to
29.9 kg/m2, n = 21; and obesity was defined as a BMI ≥ 30 kg/m2, n = 69) who expressed interest
in weight loss participated in an 8-week trial. Authors found that similar to paper-based tools in
Peterson et al.’s study,10 consistency (≥3 days/week), frequency (≥50% of days), and not
comprehensiveness (≥50% of weekly calorie goals) of the tool were the indicators associated
with weight loss.130 This study reinforces the value of the regular act of dietary self-monitoring
over the accuracy and comprehensiveness of the recorded dietary intake for promoting healthy
dietary behaviours and achieving successful health outcomes.
Another study131 (n=47) compared the effectiveness of (1) a calorie-counting weight
management app called Lose It! (Boston, US), (mean age 43.7 ± 3.5), (2) a paper-based tool
(mean age 40.8 ± 3.8), and (3) a memo function on mobiles without a specific dietary self-
31
monitoring app (mean age 41.5 ± 4.0) over eight weeks. Attrition rates were significantly higher
in the memo function and paper-based tool groups compared to the app group, which had no
attrition (P=0.05). The app group recorded significantly more complete days than the paper-
based tool group (43.0 ± 2.5 and 30.7 ± 4.6 days, respectively; P= 0.024; effect size = 0.153), but
no differences were noted between the memo function (34.8 ± 3.5 days) and paper-based tool
groups, or between the app and the memo function groups. Both the memo function and paper-
based tool groups reported twice the number of missing days as the app group (21.0 ± 4.9, 21.3 ±
3.4, and 10.3 ± 2.1 days, respectively; P = 0.04; effect size = 0.136). There was a significant
reduction in body weight and BMI values across all groups (P < 0.001; effect size = 0.542), but
no group differences were noted between groups (P = 0.19; effect size = 0.073). Diet quality was
assessed through three-day food records at baseline and week eight using Healthy Eating Index
scores, which did not show significant changes across the groups (P = 0.25; effect size = 0.097).
However, total scores decreased slightly (−6%) in the app group and increased slightly in the
other groups (+3% and +9% for memo function and paper-based tool groups, respectively)
(P = 0.29; effect size = 0.089). The study suggests that using a mobile app for dietary self-
monitoring may lead to more consistent data entry and higher adherence compared to paper-
based methods. However, it did not result in improved diet quality or greater weight loss
compared to other methods. While this study provides evidence that using a mobile app may lead
to more consistent dietary self-monitoring, its findings should be interpreted with caution due to
the study’s limitations, such as its small sample size, limited evaluation of only one calorie-
counting app, and the study’s short duration. Longer-term studies are required to observe
sustained changes in behaviours, such as changes in diet quality.
32
In spite of the advantages of technology-based methods over paper-based records,
adherence to current dietary self-monitoring tools is challenging.13 A secondary data analysis
was conducted on data collected from two 6-month randomized trials: Dietary Intervention to
Enhance Tracking with Mobile Devices (n=81; mean age 48.1±11.9; mean BMI 34.7±5.6) and
Self-Monitoring Assessment in Real Time (n=43; mean age 42.4±12.4; mean BMI 34.5±5.7).
Intervention groups in both trials used a calorie-counting dietary self-monitoring app (FatSecret,
Melbourne, Australia) to record their dietary intake. The app involves an extensive database to
search for foods and beverages and allows barcode scanning for data entry. Seven methods of
tracking adherence to self-monitoring, measuring frequency, consistency, and completeness,
were examined. To identify the timing of declines in self-monitoring, the last week in which the
percentage of participants meeting adherence criteria for self-monitoring was still at least 50%
(meaning at least half of the participants were still meeting that particular adherence criterion)
was examined. This study demonstrated that the final week that at least half of the participants
were tracking was at week 9 (out of 24), and for tracking at least two eating occasions per day, it
was Week 10.13
Declines in adherence can be attributed to the fact that the process of self-monitoring
using available technology-based tools can be complex and time-consuming and require a lot of
steps: 1) enter food products by typing them in or scanning barcodes on labels, 2) identify the
food item (either manually or from a tab), and 3) record the portion/ serving size consumed. This
procedure makes dietary self-monitoring complicated, time-consuming, and demanding a high
amount of effort, which can result in difficulties in maintaining the behaviour.14 Based on an
estimation from a structured behavioural weight control program (24 weeks), dietary self-
monitoring using a web-based journal takes about 23 minutes per day during the first month,
33
with slight reductions in burden noted in subsequent months (e.g., 14.6 minutes in month 6).132
The tool was based on US Department of Agriculture dietary analysis data and provided
participants with a calorie and a dietary fat goal. Participants were required to look for the foods
in a big database and measure their portions and count calories to adhere to their calorie and fat
goals.
Table 1- Comparison of paper-based and technology-based dietary self-monitoring tools
Positive Aspects
Negative Aspects
Paper-based
tools
• Ease of use8
• Minimal training8
• Wide availability in various formats8
• Cost-effectiveness8
• Literacy dependency8
• Tedious8,78
• Manual writing and calculating8
• Searching for nutrient
information in pocket manuals8
• Illegible handwriting8
• Socially uneasy8
• Lack of instant feedback78,84
• Recall biased (because of
delayed recording)8
Technology-
based tools
• Free or low cost8
• Instant access to comprehensive
nutrition information databases
• Simplified data entry through barcode
scanning13
• Providing immediate feedback in
terms of nutrients and calories8
• Providing summaries8
• Automatic calculations8
• Detecting adherence to self-
monitoring8
• Equipped with password-protection8
• Literacy dependency8
• Training and practice
dependent14
• Over complicated14
• Time-consuming14
• Requiring a high amount of
effort14
• Health literacy dependency23–25
2.4.3 Improving Adherence to Dietary Self-Monitoring by Simplifying Tools
To reduce the burden of current dietary self-monitoring, several approaches have been
suggested, such as recording using technology, decreasing the monitoring scope, and
34
simplification of recording. It has been shown that the level of quantification needed to complete
the self-monitoring tasks may be a factor contributing to the reduction of the retention rate.133 A
systematic review (n=59 studies) to identify dietary self-monitoring implementation strategies in
behavioural weight loss interventions divided the included studies into two groups based on the
intensity level of monitoring, including (1) interventions requiring self-monitoring of all dietary
intake (n=45, 75%), and (2) interventions requiring self-monitoring of fewer than all dietary
intake commonly referred to as “abbreviated intake” (e.g., vegetable intake only, snack intake)
(n=12, 25%). Platforms used for dietary self-monitoring differed among the studies and included
mobile phone apps (n=19), paper food diaries (n=22), wearables (n=2), websites (n=27), and
personal digital assistants (n=2). Most of the studies showed a significant reduction in weight
when adhering to dietary self-monitoring (61% in all dietary intake studies and 67% in
abbreviated intake studies).133 However, based on their findings, using abbreviated self-
monitoring approaches motivates adherence to dietary self-monitoring as it is thought to be less
burdensome.133 The authors noted that the adherence data lacked sufficient consistency to enable
formal testing of monitoring adherence by different types of self-monitoring. Hence, the
potential relationship between the intensity level (recording all intake or only certain aspects of
diet) of dietary self-monitoring and weight loss outcomes is unclear. The authors suggested that
carefully designed interventions are needed to test the efficacy of abbreviated monitoring
protocols.133
In a 16-week Randomized Controlled Trial (RCT), 42 adults with overweight and obesity
(BMI ≥25.0 kg/m2) were self-monitoring their physical activity and dietary intake on a paper
diary using a traditional detailed approach (n=21; 38.0±5.9 years; BMI 32.0±1.6 kg/m2) or an
abbreviated approach of self-monitoring (n=21; 35.0±6.6 years; BMI 32.5±1.5 kg/m2). This
35
study focused on itemizing foods and estimating the calories and serving sizes in both groups.
Adherence to self-monitoring, defined as frequency (total number of food records submitted by
an individual), significantly increased in the group that followed the abbreviated method
(15.2±1.4) compared to the detailed approach (14.0±2.0, P=0.04). However, there was no
significant weight loss between the groups (−7.5±5.3 kg and −7.6±5.5 kg in the detailed self-
monitoring group and abbreviated self-monitoring group, respectively; P=0.91) despite a
significant decrease in weight observed in all participants who completed the diaries (P <
0.001).26 Authors suggest that the increased adherence to dietary self-monitoring when using the
abbreviated version might be attributed to participants being subjected to less of a burden. Thus,
simplified tools were suggested to reduce this barrier and enhance adherence to self-monitoring
and potentially result in improved weight-loss outcomes.
Both of the above studies still included some level of quantifications for calorie counting
and portion measurements, which can be burdensome for many individuals. A study134 using a
randomized controlled design in postmenopausal women (n=19,542; mean age 62.3±6.8 years)
over 8.5 years described paper-based original and additional self-monitoring tools, as well as
trends in their use over time. Participants were initially provided with original tools, which
included counting portions using a traditional food diary and Fat Scan, a list of 1,100 foods to
look up fat content in foods. A clear decline of 6-7% in dietary self-monitoring was observed in
the first three years and of 3-4% in the following years. Additional tools were then developed,
including a mini version of the diary, which was more portable and contained more ethnic foods;
simpler check-off forms to check mark foods and portions they had eaten in a day and answer
yes/no questions to monitor their behaviour. The use of these additional tools increased over
time, with 52% of the sample utilizing them. Results of a multiple linear regression analysis
36
investigating the relationship between self-monitoring duration and tool use, while adjusting for
age, ethnicity, education, and region, revealed significant variations in the number of monitored
days associated with tool use and clinic control minus intervention percent energy from fat
quartiles. Women who used the additional tools monitored their dietary intake for 2.2 days more
than those who used the original tools (P<0.001). The study highlights the importance of
introducing simpler self-monitoring tools to enhance engagement and sustain adherence. While
the study provides valuable insights, its limitations include the specific participant population,
limiting the generalizability of the findings, and the fact that it was conducted more than 20 years
ago, potentially affecting its relevance in today’s technological context. Further research is
needed in the context of new technologies to determine the optimal self-monitoring technique
and its long-term effects.
2.4.3.1 Plate-Based Tool
Shifting towards less complex and more user-friendly approaches could enhance
adherence to dietary self-monitoring26 and promote healthy eating behaviours. One such
approach is the plate-based approach, which was originally developed in Sweden (Figure 4)33 to
teach meal planning to patients with diabetes. This approach has gained considerable attention in
recent years by several countries and associations, including the United States’ MyPlate,31 Half-
Plate Rule,135 Food and Agriculture Organization of the United Nations,136 Sweden,32, United
Kingdom,137 and Brazil.138
37
Figure 4- First plate-based tool developed in Sweden (adapted from Karlstorm et al.,139
1988)- Drawings illustrate the three different sections in the model and form an inverted “Y”.
The smallest portion, about one-quarter of the surface, represents the dietary contribution from
meat, cheese, fish, and eggs. The two remaining sections are equal in size and represent the
dietary contribution from vegetables and fruits, as well as rice, pasta, potatoes, and bread.
The plate-based approach has been shown to be less complex by not requiring food
itemization, text, or numbers, making it more accessible to individuals with varying levels of
health literacy.22,23,27 The visual depiction of a plate in this approach facilitates the understanding
of healthy eating information for the general public, making it easier to comprehend and
follow.28 Studies have shown that using the plate-based approach for meal planning has been
associated with the promotion of healthy eating behaviours by reducing the consumption of
refined carbohydrates, sugar, and total fat.29,30 This approach was found to be as effective as
more demanding interventions such as carbohydrate counting22 or calorie-counting29 in
improving health outcomes.
Rice
Pasta
Bread
Potatoes
Vegetables
Fruits
Fish
Meat
Eggs
Cheese
38
The simplicity of the plate-based approach could potentially improve adherence and
mitigate barriers to nutrition education and self-monitoring. By simplifying the approach and
providing clear visual cues, individuals may find it easier to understand and follow healthy
eating guidelines, leading to better health outcomes. This could be particularly beneficial for
individuals with lower health literacy, who may struggle with more complex approaches.
A study conducted by Nydahl et al. (1993) aimed to investigate attitudes and use of the
plate-based approach by health professionals (n=87, mean age 43.9 years) who provide dietary
advice to patients with diabetes. After attending a diabetic training course over two periods,
participants completed a questionnaire comprising open-ended and fixed-alternative questions to
assess their attitude towards the plate-based approach, including its advantages and
disadvantages in providing dietary advice. The majority of participants highlighted the
advantages of this approach (130 over 25 comments). The plate-based approach was praised for
its simplicity, ease of use, understanding, and memorization. Nevertheless, there were concerns
that it was too simple, and there was difficulty following the recommended amounts. The authors
discussed it is evident that dividing a meal (e.g., mixed dishes) into three sections is difficult and
suggested the whole meal should be considered from the plate-based approach standpoint.39 This
study provides valuable information from the health professionals’ point of view on the plate-
based approach as a meal planning tool. However, further research is required to examine the
perspectives of the general public or patients on the plate-based approach, especially beyond the
context of diabetic education. Additionally, the utilization of the plate-based approach for self-
monitoring purposes remains unclear and warrants investigation in future studies.
A 3-armed RCT was recently conducted among 104 young adults to analyze whether
visual plate-related dietary guidance systems (E.g., MyPlate guideline or the Half-Plate Rule)
39
help individuals eat healthier when eating at home or in restaurants. Participants were asked to
follow either of the guidance systems or to eat as they normally would (control condition).
Results indicated that individuals who followed either of the two plate-based dietary guidance
systems did not report that they ate any healthier (P>0.20) than those who followed no system.
Debriefing interviews revealed that the limited availability of many foods, including fruits and
vegetables, hindered participants from adhering to the guidelines. The study concluded that both
visual plate-based guides were easy to understand and following them helped reduce eating-
related questions compared to when there was no system. Authors highlighted the importance of
the simplicity and flexibility of the plate-based tools and suggested that these dietary guidance
systems can be adapted for use in apps, monitoring devices, or as simple reminder icons.
A 6-month RCT aimed to compare the effectiveness of different approaches to nutrition
education in diabetes self-management education and support in improving glycemic control.
The study randomized 150 adults with type 2 diabetes (mean age 55 (47, 62) years) into the
control group to receive general health education or one of the intervention groups to receive
education and support to self-manage their diabetes for three months: carbohydrate gram
counting or modified plate method. The results at six months showed that the glycated
hemoglobin (HbA1C) improved within the plate method (−0.83% (−1.29, −0.33), P < 0.001) and
carbohydrate counting (−0.63% (−1.03, −0.18), P = 0.04) groups but not the control group
(P = 0.34). However, participants with a low level of health literacy (stratified by numeracy
status) achieved poorer improvement in HbA1c levels at six months when using carbohydrate
counting (−0.33%, (−0.83, 0.18), P = 0.18) compared to the plate-method self-monitoring
approach (−0.76%, (−1.37, −0.15), P = 0.02).22 This study is of value since it assessed the
effectiveness of the plate-based approach in diabetes self-management education and also
40
considered the potential confounding effect of participants’ numeracy skills when using standard
diabetes education methods such as carbohydrate counting. However, the study population was
limited to adults with type 2 diabetes, which may limit the generalizability of the findings to
other populations. Additionally, the study did not involve a dietary self-monitoring approach, so
further research is needed to determine the efficacy of the plate-based approach in improving
adherence to dietary self-monitoring in larger sample sizes.
2.5 Canada’s Food Guide
Food guides are nutrition educational tools intended to assist individuals follow a healthy
diet.140 Throughout the evolution of science, new insights have been generated regarding
nutrition’s role in health promotion and chronic disease prevention. Changing the number of
representative food groups was included in the updated versions of the food guides. For instance,
vegetables and fruits were merged into one group in 1977, and four food groups were included in
the guide until 2019.
In January 2019, Canada joined a growing number of countries and associations31–33 in
adopting the plate-based approach to healthy eating as a new national nutrition guideline.34 The
new CFG provides a visual representation of a plate to simplify guidelines for healthy eating and
facilitate understanding of the information for the general public.28 By focusing on the
proportions of the plate rather than the numbers of portions and serving sizes, the new guide
emphasizes the importance of eating three food groups: vegetables and fruits (half of the plate),
protein foods (a quarter of the plate), and whole grains (a quarter of the plate). Moreover, the
guide recommends considering water as the preferred beverage.34
41
The three food groups that Health Canada emphasizes that should be regularly consumed
are normally found in dietary patterns that are linked with positive health effects.141–145 A
prominent theme in the new food guide is the frequent intake of plant-based foods such as
vegetables, fruit, whole grains, and plant-based proteins for their potential health benefits. Plant-
based foods are typically associated with reducing the risk of type 2 diabetes, CVD, and colon
cancer.142 The new guide diverges from the previous formats that served as both an educational
resource and a policy tool, and it is now easier to comprehend and use on a daily basis.35 With no
quantitative dietary recommendations, the simplified plate method is arguably flexible and
adaptable.
In a cross-sectional Canadian qualitative study, parents with diverse levels of education
and income participated to explore their perceptions and interpretations of the 2019 CFG.38
“Visually appealing” and “focused on eating behaviours” were some of the emerging themes
from the semi-structured interviews. However, the lack of cultural representation in the food
guide was one of the negative themes that arose in the study.38 This major drawback of lacking
all foods in the plate method is because of the fact that it focuses on broader eating patterns.
42
Chapter 3: Methodology
3.1 Study Design
This qualitative study used online focus groups on Zoom with members of the general
public and RDs and was carried out through the University of British Columbia (Vancouver, BC,
Canada). This study followed the Consolidated Criteria for Reporting Qualitative Research146
checklist (Appendix A). Multiple focus groups were conducted with an expected number of 45
participants per target audience.147,148 Our goal was to recruit sufficient participants to meet
thematic saturation, defined as the point where no new themes or relevant information emerged
through the thematic analysis.149 Ethics approval was obtained from the University of British
Columbia (Behavioural Research Ethics Board Number: H21-01353) and Concordia University
(Montreal, QC, Canada, Ethics Number: 30012869).
3.2 Participants and recruitment
Prior to recruitment, approximately 45 participants per set of focus groups (6-8
participants per group; 6-7 focus groups total per set) were planned.147,148 Our goal was to recruit
sufficient participants to meet thematic saturation, defined as the point where no new themes or
relevant information emerged through the thematic analysis.149
General Public: Convenience sampling strategy was used to recruit members of the
general public. Our goal was to consider a balanced representation of gender (e.g., man and
woman) and diversity in age and cultural background. Recruitment methods included online ads
on a research centre listserv at PERFORM Centre (Concordia University, Montreal, QC).
Members of this listserv have consented to receive email from researchers for recruitment
43
purposes. Additionally, recruitment was carried out through the graduate student community
listserv of the University of British Columbia and social media platforms such as Facebook and
Twitter. Eligibility criteria for the general public included: English-speaking adults over 18 years
familiar with operating a mobile device and had access to the technology required for video and
audio connectivity (i.e., Zoom). We excluded individuals with cognitive impairment, a disability
related to blindness or deafness, or those who did not know how to use a mobile app.
RDs: Based on convenience sampling, RDs were recruited via social media, primarily on
Facebook in various closed groups of RDs across Canada. Eligible RDs were English-speaking
(>18 years), familiar with using a mobile phone, and capable of participating in a focus group
discussion over Zoom.
Interested participants from both groups contacted the research team via email.
Researchers called participants to complete screening and determine eligibility. Following the
screening process, eligible participants were informed about the study’s purpose and procedure
via a consent form on Qualtrics® (Provo, UT). Upon consenting electronically, the same
platform directed them to complete a sociodemographic questionnaire (age, gender, ethnicity).
Members from the general public reported their highest level of education and previous
experience with using dietary self-monitoring tools. RDs were asked to report their years of
practice and experience in recommending self-monitoring tools during their clinical practice.
After completing the survey, participants were scheduled to participate in one focus group at a
convenient time.
44
3.3 Focus Group Guide Development
The COM-B model, as part of the Behaviour Change Wheel,150 was used to develop the
focus group guide.151 Since this model offers a comprehensive insight into the factors that
influence behaviour change,152 was chosen rather than traditional theoretical models or theories
that focus on overarching constructs (Figure 5).
Figure 5- The COM-B model150 with examples of the related questions.
The COM-B model suggests that three sets of factors influence health behaviour change:
(1) Capability, comprising psychological capability (i.e., knowledge of health-related behaviours,
elements of self-regulation, memory, comprehension, and thought processes) and physical
capability (i.e., physical skills needed to use iCANPlate); (2) Opportunity, including physical
opportunity (i.e., resources affecting adherence to dietary self-monitoring) and social opportunity
45
(i.e., social support); and (3) Motivation that constitutes of reflective motivation (i.e., beliefs
about capabilities and consequences of engaging in dietary self-monitoring using the app) and
automatic motivation (i.e., reinforcement and incentives affecting adherence).150 The complete
mapping of the focus group guide to the COM-B constructs is outlined in Table 2.
46
Table 2- Mapping of the focus group guide to the COM-B constructs150- Italicized words pertain to the RD
focus groups only.
CAPABILITY
Psychological
Capability
• What do you/ your clients know about CFG?
• Which diet-tracking methods or apps have you ever used/ suggested to
your clients (if any)?
• How do you suggest dairy products be tracked on the app?
• What other eating behaviours or elements of the CFG should be
included in this app?
Physical Skills
• What features are required to ensure accessibility for all users?
OPPORTUNITY
Physical
Opportunity
• What makes it easy/ hard for you/your clients to eat in accordance with
the plate method that mirrors the CFG?
• Many “other foods” are not shown on the CFG. Which foods can you
think of that you/ your clients would find difficult to represent on the
plate? How do you suggest they be tracked on the app? How could
they be classified within the app?
• How do you suggest beverages be tracked within the app?
• Which instructions should be provided to users to support their use of
the app?
• What would be considered a successful day?
Social
Opportunity
• What features can facilitate social support and enhance user adherence
to the app?
MOTIVATION
Reflective
Motivation
• How do you view the app working on recording all meals throughout
the day?
• Which features in the app could improve users’ confidence when
tracking their food intake?
• What makes it easy or hard for you/ your clients to use the tools you
have experience with?
• What would be considered a successful day?
Automatic
Motivation
• What did/didn’t you like about the plate-based dietary self-monitoring
app?
• Which features would incentivize users to adhere to using the app?
N/A
• Which other features can you think of that we did not discuss?
47
The focus group guide was structured using open-ended questions. Discussions were
prompted by three sections: Section 1- Perceptions of the 2019 CFG; Section 2- History of using
dietary self-monitoring tools; Section 3- Content and features of the proposed dietary self-
monitoring app (Appendix B). The same guide was used for both RDs and the general public
focus groups. A pilot virtual focus group with six participants (non-dietitian students from the
Nutrition and Eating Behaviour Lab at the UBC) was conducted to test and refine the guide to
ensure its comprehensiveness.153 Data from the pilot focus group was not analyzed or included in
the results.
3.4 Study Procedure
Following extensive training in qualitative research methodology two trained female
interviewers including a qualified RD (CCB) and a graduate student (MKh the author)
moderated each set of focus groups. A trained note-taker was available on each call to take notes
and help with technical challenges. CCB had prior professional relationships with some RD
participants. CCB was not involved in data coding to maintain impartiality in data analysis.
Throughout the study, efforts were made to establish a good rapport with the participants.
Each focus group started with an overview of the project, which included a brief
description of the CFG for the general public focus groups and a general description of dietary
self-monitoring for all focus groups. Participants then participated in a discussion based on
Sections 1 and 2 of the focus group guide. Afterwards, a brief demonstration of the prototype
iCANPlateTM (version 0.1) was presented, following which participants engaged in a discussion
to explore their perceptions of the prototype. Participants did not have access to the app, nor
were they required to download it. They simply viewed the prototype and how it functions
48
through the Zoom screen-sharing feature. The interviewer and note taker conducted a debriefing
session following each focus group to determine the saturation point.
The focus group sessions were audio-recorded. Upon the completion of focus groups, RDs were
compensated by a $100 (CAD) gift card which was regarded as an equitable remuneration for
their professional time (the average hourly rate for an RD consult in Canada is ~ $120 (CAD)/
hour) and general public participants received a $25 (CAD) gift card.
3.5 Data Analysis
After verbatim transcribing the audio recordings, any identifiable information associated
with participants was removed. Transcripts were analyzed using qualitative analysis software
NVivo12 Pro (QSR International). To ensure methodological integrity, we employed a
combination strategy of inductive and deductive qualitative analysis. Following the thematic
analysis outlined by Braun and Clarke,154 two independent female researchers analyzed the
transcripts from the RD group (MKh the author, RM) and general public group (MKh the author,
CB) to generate themes and subthemes. Data analysis involved an iterative process following
coding techniques to identify themes and subthemes that emerged from the data. The language
used for labelling the themes and subthemes was quoted directly from the participants’
descriptive responses or the focus group guide.
Both coders of each set read the transcripts to become familiar with the data. The first
author (MKh the author) read and re- read the data multiple times to develop initial codebook.
The codebook contained the list of data- driven categories and their definitions (examples from
the data). A reflective report during the coding process (memoing) was conducted to demonstrate
self-awareness in the analytical process and enhance their qualitative skills. Both coders used the
49
codebook for the analytic coding. They reorganized it iteratively until the research team reached
a consensus, ensuring a cohesive and agreed-upon approach to the analysis.
While the identified themes were often linked to the specific questions in the guide, the
participant-driven nature of focus group discussions along with the open-ended questions
allowed us to explore concepts that were not necessarily included in the focus group guide.
Therefore, relevant themes were considered present even if they were not directly related to a
particular question.
Two researchers (MKh the author and CB) then used deductive thematic analysis,
whereby the COM-B model151 was followed as a framework to organize the extracted
subthemes. According to the available literature, the coders identified specific constructs that
each subtheme pertained to. They regularly convened until they reached a unanimous consensus.
While the interview guide was based on the COM-B model, the researchers analyzed the data in
its literal form, meaning that some of the participants’ perceptions were coded into a different
construct than initially intended. Throughout the qualitative analysis, discrepancies between
coders were resolved via mutual discussions or consultation with a third independent reviewer
(TRC). The latter was particularly beneficial when consensus could not be achieved through
discussion alone.
3.6 Ethical Considerations
Ethics approval was obtained from the University of British Columbia (Behavioural
Research Ethics Board number: H21-01353) and Concordia University (Montreal, QC, Canada,
Ethics Number: 30012869). For the recruitment purposes, a Facebook social media page was
created. We clearly stated in the description section of the study profile, if people choose to post
50
to the page, “like” the page, or “follow” it, they will become publicly identified with the study.
We ensured all participants voluntarily participated in the focus groups without feelings of
coercion by providing transparent information and guidance that enabled participants to make
knowledgeable decisions. Additionally, we reiterated the importance of voluntary participation
(freedom to withdraw at any time) in the study. A standard consent form was obtained from each
participant, and their right to refuse to participate in the study was respected. Only the research
team involved in the data analysis had access to the data. The study ensured confidentiality and
anonymity of participants. Each participant was assigned a unique code to safeguard their
identity, and a separate encrypted master list linked the codes to participant names. This
password-protected file was securely stored and was accessible only by first author (MKh) and
the corresponding author (TRC). During the focus group sessions, participants were encouraged
to use nicknames for further identity protection. However, maintaining complete anonymity was
challenging in the RD focus groups due to the potential recognition of participants from their
work or school settings.
51
Chapter 4: Results
4.1 Participants
Focus groups were conducted from July 2021 to August 2021. The sessions ranged from
64 to 115 minutes (mean of 83 minutes). In total, 82 individuals from the general public
consented to the study, with 67 participating in their scheduled focus group (18% attrition);
similarly, 56 RDs consented, with 50 participating in scheduled focus groups (Detailed
recruitment flow chart available in Figure 6). The final sample size for summary statistics
(Table 3) was smaller as some focus group participants did not complete the initial demographic
questions after consent. Therefore, information was available for 52 members from the general
public (24 women, mean age ± SD of 40.2 ± 18.4; 28 men, mean age of 42.6 ± 16.5) from nine
focus groups, and 44 RDs (39 women, mean age of 33.6 ± 7.0; 5 men, mean age of 31.4 ± 3.5)
from seven focus groups.
52
Figure 6- Recruitment flow chart
53
Table 3- Socio-demographic characteristics of the study sample
a RDs were asked for a history of recommending dietary self-monitoring tools to their clients
b Responses to this question (n=30) were for those who had a history of using/recommending self-monitoring
tools
c Checklists, portion counting, plate-based tool
N/A, Not applicable
General Public
RD
Total number, n
52
44
Age (years), mean (SD)
41.4 (17.2)
33.4 (6.7)
Gender, n (%)
Man
28 (54%)
5 (11%)
Woman
24 (46%)
39 (89%)
Ethnicity, n (%)
White
25 (48%)
30 (68%)
Indigenous
2 (4%)
0
South Asian
2 (4%)
1 (2%)
Chinese
1 (2%)
11 (25%)
Black
1 (2%)
0
Filipino
2 (4%)
0
Arab
2 (4%)
1 (2%)
West Asian
9 (17%)
0
Others-mixed
8 (15%)
1 (2%)
Highest education levels, n (%)
Postsecondary certificate, diploma or degree
46 (88%)
44 (100%)
Some postsecondary education
0
0
Secondary (high) school diploma or equivalent
6 (12%)
0
Less than secondary (high) school graduation
0
0
Years of practice, n (%)
≤2 years
N/A
14 (32%)
3-5 years
N/A
14 (32%)
6-10 years
N/A
11 (25%)
>10 years
N/A
5 (11%)
History of using dietary self-monitoring tools, n (%)
Yes
30 (58%)
35 (79%) a
No
22 (42%)
9 (21%) a
Types of dietary self-monitoring tools used,b n (%)
Paper and pen food journals
9 (17%)
40 (32%) a
Itemizing mobile apps
15 (29%)
31 (25%) a
Web-based tools
4 (7%)
14 (11%) a
Simplified self-monitoring toolsc
7 (13%)
24 (19%) a
Others
3 (6%)
3 (2%) a
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Thematic analyses revealed four main themes with 15 subthemes derived from
participants. The main themes were clustered into two major categories (Table 4): the current
iteration of iCANPlate described in the main text, and components to include in future iterations
of iCANPlate. Table 4 displays the mapping of each subtheme for both categories of main
themes to a corresponding COM-B construct.
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Table 4- Major categories, themes and subthemes reported by the general public participants
Categories
Themes
Sub-themes
Related COM-B construct
The current iteration of
iCANPlate
A. Facilitators to use a plate-
based dietary self-
monitoring app
1. Self-awareness of dietary
behaviours
• Psychological Capability/
Reflective Motivation
2. Simplicity
• Psychological Capability
B. Barriers to using a plate-
based dietary self-
monitoring app
3. Lack of food classifications
• Psychological Capability/ Physical
Opportunity/ Reflective Motivation
4. Conceptualizing proportions
• Physical Opportunity
5. Lack of inclusivity
• Social Opportunity
Components to include in
future iterations of
iCANPlate a
C. Essential components to
add to iCANPlate
6. Educational content and
tutorials
• Psychological Capability/
Reflective Motivation
7. Report dashboard
• Psychological Capability
8. Accessibility
• Physical Opportunity/ Capability
D. Optional components to
add to iCANPlate
9. Personalization
• Reflective Motivation
10. Automatic food logging
• Physical Capability
11. Recording other eating
behaviours
• Psychological Capability
12. Social interaction
• Social Opportunity
13. Professional support
• Physical Opportunity
14. Interactivity
• Motivation/ Physical Opportunity
15. Incentivization
• Reflective Motivation
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Table 5- Major categories, themes and subthemes reported by Registered Dietitian participants
Categories
Themes
Sub-themes
Related COM-B construct
The current iteration of
iCANPlate
A. Facilitators to use a
plate-based dietary self-
monitoring app
1. Self-awareness of dietary
behaviours
• Psychological Capability/
Reflective Motivation
2. Simplicity
• Psychological Capability
B. Barriers to using a plate-
based dietary self-
monitoring app
3. Lack of food classifications
• Psychological Capability/ Physical
Opportunity/ Reflective Motivation
4. Conceptualizing
proportions
• Physical Opportunity
5. Lack of inclusivity
• Social Opportunity
Components to include in
future iterations of
iCANPlate a
C. Essential components to
add to iCANPlate
6. Educational content and
tutorials
• Psychological Capability/
Reflective Motivation
7. Report dashboard
• Psychological Capability
8. Accessibility
• Physical Opportunity/ Capability
D. Optional components to
add to iCANPlate
9. Personalization
• Reflective Motivation
10. Automatic food logging
• Physical Capability
11. Recording other eating
behaviours
• Psychological Capability
12. Social interaction
• Social Opportunity
13. Professional support
• Physical Opportunity
14. Interactivity
• Motivation/ Physical Opportunity
15. Incentivization
• Reflective Motivation
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4.2 Perceptions of the Current Iteration of iCANPlate
During the study, participants provided valuable feedback on the current iteration of
iCANPlate. Specifically, they shared their facilitators to use iCANPlate, as well as potential
barriers to use the current iteration of the app. The following sections provides an in-depth
description of these findings.
4.2.1 Facilitators to the Use of a Plate-Based Dietary Self-Monitoring App
Positive perceptions toward iCANPlate were discussed during the focus groups. This
theme was further broken down into two sub-themes: Self-awareness of dietary behaviours and
simplicity.
4.2.1.1 Self-Awareness of Dietary Behaviours
The general public and RD participants stated that the app would foster self-awareness of
overall dietary patterns rather than promoting calorie-counting or itemizing specific foods. This
aspect was perceived as an attractive feature of the plate-based approach, potentially increasing
users’ willingness to use the app. General public members explained that general self-awareness
of eating patterns, rather than needing to enter specific details, could facilitate achieving dietary
goals.
“I think generally the concept is nice because it’s more about patterns over the long
term, and just to know what’s on your plate, those proportions, versus not having to be
super-exact with it every single time you log in. I think that’s nice because it’s easy to get
sucked into numbers.” [General Public- Focus group 2- Participant 2]
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RDs stated that this app would allow users to focus on improving their dietary
behaviours, especially food quality, rather than promoting caloric restriction. RDs acknowledged
that the plate-based dietary self-monitoring was a weight-neutral approach focusing on diet
quality rather than weight loss. They noted that this approach differs from most publicly
available dietary self-monitoring tools that focus exclusively on body weight and calorie-
counting, which could promote the development of eating disorders.
“It could be easier to have a better understanding of the amount of food you’re eating
throughout the week. I’m thinking about that because of like workout things [...] maybe
with foods you can do something similar for people to be more aware of what they’re
eating” [RD- focus group 2- Participant 6]
4.2.1.2 Simplicity
Focus group participants stated that the simplicity of the app’s usability would facilitate
its use. They found the pie-like division of the plate to be familiar and straightforward.
Participants noted that the app’s simplified interface did not require high literacy levels. Most
members of the general public asserted that the visual (i.e., using the plate) was natural. A
consensus emerged in all focus groups that data entry in the app was simple and would alleviate
the annoyance of tedious logging, which is common in many dietary self-monitoring apps.
Hence, they suggested that the plate-based approach is more user-friendly and accessible to
varying literacy and comprehension levels. One general public participant voiced that:
“First seeing the app, I did like the simplicity of it and maybe just like – it’s not too
simplistic but simple that everyone with different levels of literacy can use.” [General
Public- Focus group 6- Participant 2]
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RDs highlighted the advantage of the lack of quantification in iCANPlate for portions or
calories, and how it would simplify the process of dietary self-monitoring for their clients or
patients. According to RDs, avoiding a number-focused approach can help their clients increase
self-awareness of their dietary behaviours, especially those who struggle with understanding
portions. RDs discussed that by providing a simple method without the need to focus on
numerical data, this plate-based approach could improve adherence to diet self-monitoring over
time.
“Yeah, I think it’s easy, just because the proportions [in the plate-based method] are kind
of easy to remember.” [RD- focus group 3- Participant 5]
4.2.2 Barriers to Using the Plate-Based Dietary Self-Monitoring App
Participants expressed various barriers to using the current iteration of iCANPlate to self-
monitor their dietary behaviours. Three subthemes emerged under this theme: 1) lack of food
classifications 2) Conceptualizing proportions 3) lack of inclusivity.
4.2.2.1 Lack of Food Classifications
RD and general public participants indicated that because several essential dietary
components are not depicted in the literal picture of the 2019 CFG, users of iCANPlate might
have difficulty using the app. Specifically, general public participants suggested including other
categories of foods that are depicted in the CFG, such as seasonings, sugary foods, cooking oil,
and processed/ultra-processed foods.
“But it’s interesting when you look at it what we eat that is not on this plate every day or
on the weekends, our glass of wine, excuse me. Or our granola bar after workout. I mean
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there’s so many foods we all have every day that wouldn’t make this plate” [General
Public- Focus group 3- Participant 2]
They also stated that the app’s inability to allow users to differentiate specific food
qualities (e.g., low-fat versus high-fat food choices) would be a barrier to its usability. RDs
voiced concern that the lack of precision in classifying food qualities could create a misleading
impression of an individual’s diet, leading to inappropriate dietary recommendations for clients.
An RD commented on the categorization of starchy vegetables in the fruits and vegetables
section, highlighting the potential issue of providing advice that may not align with individuals’
dietary goals and needs, particularly in cases such as diabetes. Another RD stressed the
importance of including all foods and said:
“I would say there’s also the fact that people try to reproduce what’s in the plate exactly.
So, they’re like, oh, but I’m eating excess food, but there’s, it’s not in the plate. So, can I
eat it or not? So, it makes it difficult for them to know if you can include the food or not
into their diet or not.” [RD -Focus group 4- Participant 4]
There was also a consensus among the general public participants that recording all
beverages in iCANPlate is important. RDs suggested creating separate beverage categories, such
as hydrating/non-hydrating drinks, sweetened/unsweetened drinks, and alcohol. Furthermore, the
absence of a separate category for dairy foods (milk and milk products) in the CFG might
confuse future app users. They proposed emphasizing the dairy foods group either as a fourth
separate group for logging or as a separate section in the app. RDs generally agreed that, in
alignment with the CFG, dairy products should be categorized under the protein category. RDs
proposed creating a distinct section dedicated to calcium or dividing the protein category into
high-calcium and low-calcium protein sources to ensure adequate calcium consumption.
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“Being a plant-based dietitian for all my career my idea is that there's so much
misguidance right now that I'm happy there's not a dairy food group, but I'm not happy
that there's not a calcium food group. Because as countries, we can’t agree on how much
calcium people need but I do think that we need to highlight calcium choices in a way
that I just don't think we don't need to just – it can just be dairy has calcium. It doesn't
have to be, “You need to include dairy and this is why” and just understanding.” [RD -
Focus group 6- Participant 2]
4.2.2.2 Conceptualizing Proportions
The participants were concerned that it would be harder to conceptualize the proportions
of foods not typically served on a standard plate. Examples included foods that are not served on
traditional dishes (e.g., sandwiches or smoothies), on dishes other than plates (e.g., bowls), or on
varying plate sizes, or meals that are served on multiple containers and plates (e.g., multi-course
meals). Participants also exemplified mixed dishes (e.g., lasagna) to be particularly challenging
to conceptualize within the app unless the user made the dish or was familiar with the exact
recipe. A member of the general public who had prior experience using the plate-based approach
on a paper tool stated:
“I did this for a week on paper, and it works well for meals where you have a bunch of
different things on the plate. But, if you’re eating a stew or a bowl of pasta, it’s harder to
figure out because it’s all in one pot.” [General public- Focus group 2- Participant 1]
Given that this challenge was particularly attributed to the absence of serving or portion
sizes, some general public participants suggested that simple and universal methods to count
portions (e.g., hand models or measuring cups) could be included as an optional feature.
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“I personally liked the portion sizes and the servings per day. I think that with the new
plate method, it is hard for people to know how many fruits and vegetables they really
should eat. I find I get that as a question a lot and I try to focus on making half the plate.
They're like, but how many should I have? So, I think a lot of people do like having that.”
[RD -Focus group 5- Participant 7]
RDs discussed that human error in estimating the proportions could have a negative
impact on the accuracy of input data in the app. Thus, it is possible that the app’s data would not
provide reliable information to assess dietary behaviours. And, as RDs further emphasized, the
iCANPlate app does not involve assessing the actual amount of each food group on the plate but
rather their proportion relative to each other.
4.2.2.3 Lack of Inclusivity
Both groups mentioned that the app might be less appropriate for individuals with
specific health conditions or certain dietary requirements. A general public member living with
diabetes stated that the app might be less helpful for individuals with a particular health
condition:
“I think the whole plate thing is geared for regular people, for people who have health
problems or whatever, like for myself, I am diabetic, I don’t know if I would enter my
intakes.” [General public -Focus group 4- Participant 2]
Conversely, some RDs suggested that the plate-based approach in iCANPlate could
benefit individuals with diabetes if certain modifications were made to the food groups outlined
by the CFG. For example, an RD highlighted the importance of considering the carbohydrate
content in fruits for individuals with diabetes and said:
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“We should kind of tailor it a little bit. So rather than having both fruits and vegetables
[together], it needs to be the veggie focus first.” [RD- Focus group 4- Participant 4]
RDs agreed that, in line with CFG recommendations, iCANPlate would not be
appropriate for patients undergoing hospitalization or individuals with specific medical
conditions, including cognitive impairments or brain or spinal injuries. In addition, RDs with
prior experience working with eating disorder populations noted that recording dietary intake
using the plate-based approach, similar to other dietary self-monitoring tools, could induce
anxiety in this population.
In addition to the app’s exclusion of people with diagnosed diseases, the lack of cultural
inclusivity was also raised as a concern by both RDs and general public participants. The general
public expressed that recording some cultural foods within the app might be harder. The general
public participants stressed that if the goal of iCANPlate is to improve the dietary behaviours of
Canadians, it should reflect the cultural diversities present in the country.
“I don’t know if it [the app] would include all types of foods like different ethnic foods –
for example, there are a lot of foods, fruits and vegetables from African or Chinese
cultures, as well as Indigenous Canadian foods, so you have to think of that as well.”
[General public -focus group 4- participant 2]
Several RDs agreed that individuals from diverse cultural backgrounds tend to consume
mixed dishes. Yet, the app’s compartmentalized nature made it difficult to conceptualize the
various components of a mixed dish. Hence, they articulated that the app may not reflect the
average diet of their ethnically diverse clients. They also emphasized the crucial role of cultural
inclusivity in dietary self-monitoring concerning acceptability and adherence to iCANPlate by
end-users.
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4.3 Components to Include in Future Iterations of iCANPlate
Two themes, consisting of essential and optional components, were suggested by
participants from both RDs and the general public groups for the future iterations of iCANPlate.
The first theme encompasses the necessary elements that participants expressed must be
integrated into the app to enable independent use, while the second theme lists desirable features
that could add value to the app.
4.3.1 Essential Component to Add to iCANPlate
This theme encompasses three sub-themes that are deemed necessary by focus group
participants who have seen the prototype the current iteration of iCANPlate. These sub-themes
include educational content and tutorials, report dashboard, and accessibility. These sub-themes
have been identified as critical components to ensure the independent use of iCANPlate as a tool
for self-monitoring the dietary intake.
4.3.1.1 Educational Content and Tutorials
General public participants highlighted that basic nutritional knowledge (i.e., categorizing
different food groups) is needed to use the plate-based approach effectively. One member of the
general public stated that:
“What about people who don’t have the education level required? There could be a
section, something like a quick introduction to nutrients: This is what grains or proteins
are, this is what they do, this is why it’s important to eat them.” [General public -focus
group 2- participant 4]
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RDs discussed the possibility that the general public could misinterpret information in the 2019
CFG. They recommended adding guidance to this plate-based dietary self-monitoring app to
enhance the end-user’s comprehension of the CFG.
4.3.1.2 Report Dashboard
Participants from both groups suggested that this dietary self-monitoring app should
automatically summarize inputted data over specific periods. They recommended the app
provide a report dashboard of users’ dietary intake to enhance their self-awareness of dietary
behaviours, identify areas for improvement, and better understand their eating patterns.
Additionally, RDs emphasized the importance of incorporating a report dashboard within
iCANPlate that can be compared to dietary recommendations provided by the CFG. An RD
mentioned the role of dietitians to review their client’s summaries within iCANPlate and observe
changes in their dietary patterns and said:
“For example, here’s what was changing their dietary pattern over these days of these
weeks. We do it in the spring, summer and fall and see how different their dietary
patterns are and how well they meet food guide recommendations.” [RD- focus group 2-
participant 1]
4.3.1.3 Accessibility
All focus groups (general public and RDs) suggested key accessibility features for visual
impairment and language to be incorporated into the dietary self-monitoring app. Haptic
feedback (e.g., vibration), voice control, text-to-speech, high contrast mode, and colour blinding
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patterns were the suggested features to improve the accessibility of iCANPlate to individuals
with visual impairments. One member of the general public said:
“I know a lot of blind people use smartphones, which sounds very counterintuitive, but
your phone can voice out whatever you press on your screen. So, it might be made
compatible with that, the app.” [General public -focus group 6- participant 1]
Considering diverse populations living in Canada, participants in all focus groups
(general public and RDs) suggested that this plate-based dietary self-monitoring app should
support multiple languages, particularly official languages of French and English.
4.3.2 Optional Components to Add to iCANPlate
RDs and the general public participants discussed many optional components to add to
iCANPlate that could be valuable, but they were not considered essential. The following sub-
themes will explore the features proposed by participants: Personalization, automatic food
logging, recording other eating behaviours, social interactivity, interactivity with professionals,
Interactivity with the app, and incentivization to use the app.
4.3.2.1 Personalization
Participants in the general public and RD groups suggested personalizing the user’s
profile and goals is necessary. They mentioned that the profile and goal-setting pages could be
customized based on age, gender, body measurements, activity level, culture, language, chronic
conditions, and dietary preferences and restrictions. One member of the general public, an app
developer themselves, stressed the importance of providing customizable options for users and
said:
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“The more you let people choose their desired features, you’re looking at a happy user.”
[General public -focus group 9- participant 2]
RDs highlighted that balance between annoyance and usefulness should be established,
ensuring that the app provides valuable information and feedback to the user without being
excessively disruptive or intrusive. They noted that individual preferences vary in providing this
balance, and a suggestion could be customizing notifications and some app features, such as
optional components.
4.3.2.2 Automatic Food Logging
Participants in both groups were particularly vocal about having alternatives to make data
input more user-friendly in this dietary self-monitoring app. Notably, using the mobile’s camera
to scan their plate or a barcode was proposed to simplify the process. Some suggested having
artificial intelligence built into the app to analyze what was on their plate. A barcode feature
could also facilitate the usage of the app by making it quicker for packaged foods. Participants
also suggested that having the option to overlay the proportions on the app over what they are
eating with the camera could assist them in determining how to fill out the app correctly.
“There’s a lot of imaging technology that could be part of this new app where all you
have to do is with your phone. You just take a picture, right? And then the picture can
analyze what’s on your plate, bowl, or whatever.” [General public -focus group 3-
participant 2]
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4.3.2.3 Recording Other Eating Behaviours
When asked what other elements of eating behaviours, such as tracking mood while
eating, should be included in this app that mirrors the CFG, general public members stressed the
need to keep the app as simple as possible, avoiding any additional features that would burden
and discourage users. By contrast, RDs emphasized the importance of incorporating other eating
behaviours into the app, considering them an integral component of the 2019 CFG. Topics raised
included adding questions about mindfulness and intuitive eating principles (e.g., internal hunger
cues). RDs suggested that adding a feature to ask questions about end-users’ feelings would
potentially increase awareness of their eating behaviours:
“So, by including questions on their sense of fullness, how hungry they were, the satiety
like the clients really get into it, and it motivates them to keep going, and then they start
to see patterns.” [RD-focus group 2- participant 3]
RDs clarified that these features should be optional according to the end-user preferences
to avoid overwhelming the app.
4.3.2.4 Social Interaction
The general public and RD groups both expressed a desire for this dietary self-monitoring
app to include social interaction features. Specifically, some members of the general public
suggested a feature to connect with friends and family, and some others preferred linking the app
to their existing social media platforms. Although a few general public participants raised
concerns about the discouraging effects of competition, many agreed that sharing progress and
dietary data could help users stay on track and could be included in the app as an optional
feature.
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“So, I think something that would help us be in a group so that we can – in a group that
all of us have this challenge- would be really helpful for us. I don’t know; it would work
for me a lot.” [General public- focus group 6- participant 4]
The integration of social interaction features into the app was also voiced by RDs, who
suggested that it would motivate individuals to engage with the app actively, compare their
dietary behaviours with others, and explore new eating styles and foods.
4.3.2.5 Professional Support
The notion of connecting with professional support, such as dietitians or health coaches,
was a recurring suggestion among the general public focus groups. They concurred that real-time
access to healthcare professionals might be more advantageous than artificial intelligence but
noted that the cost could hinder many end-users.
All RD focus groups stressed the importance of offering a professional support option,
allowing end-users to connect with RDs for more personalized advice and support. They
suggested this connection could promote healthier dietary choices, prevent disordered eating, and
improve overall health outcomes.
Furthermore, RDs suggested including a support chat feature in the app, where end-users
could ask both artificial intelligence and a real-time expert (i.e., an RD) for answers to frequently
asked questions or more in-depth queries. An RD said:
“Probably having, like, online live dietitian Q&A. I chat box just as that’s what I am
craving for when I – not about diet. But when I’m searching on other websites, there are
certain things I have no idea of, and I really hope to chat with experts on that topic in
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real time to get answers to my questions. That would be really luxurious” [RD- focus
group 4- participant 1]
4.3.2.6 Interactivity
Members of the general public and RDs recommended that the plate-based dietary self-
monitoring app should provide interactive features for users. In all focus groups, participants
raised the need for analyzing the recorded dietary intakes to generate meaningful cues to action,
reminders, and feedback on end-users eating behaviours. Specifically, participants discussed that
the app should provide suggestions for foods in each food category, food alternatives, and
recipes to help end-users make healthier choices.
Additionally, reminders were discussed to be helpful for end-users to achieve their
determined goals, such as reminders on when to use the app or to drink water. For feedback,
participants suggested analyzing eating behaviours using artificial intelligence. In this context,
participants found positive and encouraging quotes such as “Good job, you’re on track today” to
be valuable in helping them achieve their goals while not evoking guilt.
“I wonder if you could put in suggestions. Like, try and choose whole grains, or try and
have mostly water as your fluid, things like that. To get people thinking about their habits
and prompt them because I know it’s easy to forget these sorts of things.” [RD-focus
group 3- participant 2]
4.3.2.7 Incentivization
RDs and general public participants suggested features such as gamification and material
incentives or rewards (e.g., monetary values) to encourage end-users to continue using
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iCANPlate and strive to meet their dietary goals. Participants discussed that end-users could be
incentivized upon completing their goals, such as increasing the intake of specific nutrients (e.g.,
protein or vegetables). There were discussions within the general public groups that actual
monetary values and gamification would improve adherence to the app. A general public
member said that:
“I don’t know whether the app or whatever would be able to afford this but make it so
that you win little emojis or whatever, and you have to collect a certain amount to get
into a draw to win something like a $50 gift card or something. I know that usually
always works for me.” [General public- focus group 4- participant 2]
However, many RD participants specifically suggested non-specific incentives (e.g.,
virtual rewards), not material ones.
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Chapter 5: Discussion and Conclusion
5.1 Primary Findings
This qualitative study explored the general public and RDs’ perceptions of a dietary self-
monitoring mobile app that uses a plate-based approach based on the 2019 CFG. To the best of
our knowledge, this is the first study that describes a plate-based approach to self-monitoring
dietary intake through a mobile app. The main goal of iCANPlate is to increase adherence to
self-monitor dietary intake with the idea of helping individuals bridge the “intention-behaviour
gap” to implement and maintain healthy eating behaviours. Our findings revealed that the
prototype (version 1.0) of iCANPlateTM has the potential to facilitate these changes, given its
simplicity and self-awareness approach. Yet, barriers to using the app were also discussed,
particularly related to conceptualizing the proportions, lack of details on food classification, and
inclusivity for cultural foods and health conditions. This thesis also provided important
suggestions for further development of the app.
Our study used the COM-B model as our framework to understand the barriers and
facilitators to using the app from the intention-behaviour gap model. In this study, we report
mainly on the capability and opportunity components, which is not surprising. Given that self-
monitoring is a post-intentional BCT155 to increase psychological capabilities156 and provide
users with opportunities to incorporate healthy behaviours in their routines.157 As a result,
variables related to motivation are commonly regarded as the precursors to the formation of
intention.2,158 Moreover, as discussed in the COM-B model, capability and opportunity
components would eventually influence and may facilitate motivation into changing the
behaviour.150 Employing a theoretical framework serves as a guide in developing and facilitating
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the functionality of mobile health behaviour interventions.159,160 The results from this study will
be used to improve the interface and content of the app before moving to the next developmental
steps.
5.1.1 Facilitators of Using the iCANPlate App to Self-Monitor Dietary Intake
Participants in focus groups agreed with the app’s focus on fostering self-awareness of
dietary behaviours, through self-monitoring proportions of different food groups on a plate rather
than itemization. In line with our results, the notion of self-awareness of one’s lifestyle
behaviours and risk factors falls under the psychological capability category of the COM-B
model.161 Our findings align with a study conducted among breast cancer survivors living with
overweight or obesity. According to their participants, using a dietary self-monitoring app
improved their self-awareness, resulting in lower calorie intake by preventing mindless calorie
consumption.162 Consistent with our results, a recent study demonstrated that augmenting self-
awareness contributes to the attainment of sustainable behaviours when striving for a healthy
lifestyle.163 Taken together, these findings indicate that developing self-awareness through self-
monitoring of dietary behaviours may be a key component in improving adherence to dietary
self-monitoring.
Interestingly, increasing self-awareness of dietary behaviours in our study was
particularly valued compared to tracking weight or calories. This echoes conclusions drawn in
the literature among weight management app users who also preferred self-awareness of their
eating behaviours through self-monitoring rather than counting calories, to motivate themselves
to modify their eating behaviours.123,164,165 This is likely attributed to the fact that counting
calories can be excessively complicated164 and thereby may reduce adherence to dietary self-
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monitoring. Focusing on body weight and calories rather than self-awareness may increase the
risk of developing restrained eating or even eating disorders.164,166 Hence, calorie-counting
approaches may not be ideal for individuals seeking to adopt sustainable dietary behaviours.
Instead, the self-awareness approach that emphasizes monitoring food group proportions on a
plate may be effective in motivating individuals to modify their eating behaviours and maintain a
healthy lifestyle.
The simplicity of the proposed prototype iCANPlate was identified as another facilitator
for its use and a way to improve adherence to dietary self-monitoring. Participants agreed that
the simple interface and simplified method of food/drink logging would make iCANPlate a user-
friendly and visually straightforward tool accessible to varying levels of literacy and numeracy
skills. This could be explained by the reported association between the accuracy of portion-size
estimation and literacy and numeracy skills.23 Therefore, the absence of portions and serving
sizes in iCANPlate has the potential to make nutrition information more accessible for
individuals with limited literacy and numeracy skills. This finding is consistent with a systematic
review that highlighted the importance of ease of use and minimal input in promoting
engagement with health and well-being mobile apps.167 Supporting our findings, that review167
further noted that these factors are associated with low cognitive load, which is a critical element
of the psychological capability component in the COM-B model.167 User-friendliness, as part of
the app’s simplicity, was identified under the opportunity component of the COM-B model
influencing eHealth utilization.168
Our finding regarding the simplicity of the plate-based approach are consistent with
another study22 which evaluated the effectiveness of the plate-based approach for nutrition
education in a population with diabetes (n=150, median age (IQR)=55 (45, 60)). In that study,
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the plate-based approach to nutrition education improved health outcomes among participants
with low numeracy skills compared to the carbohydrate counting method of other dietary self-
monitoring tools.22 This is of particular importance given that poorer literacy and numeracy
levels have been related to lower dietary intakes of vegetables and fruit, and higher consumption
of sugar-sweetened beverages.27
5.1.2 Barriers to Use the iCANPlate App to Self-Monitor Dietary Intake
Although the simplicity of iCANPlate could improve its user-friendliness, concerns were
raised about its inadequate classifications. Specifically, participants expressed that the app’s
simplicity would render it difficult to log foods that were not explicitly depicted in the visual
representation of the CFG. Similar to these findings, a study with general public members and
health care professionals agreed that missing food items and classifications in digital health
interventions are significant barriers to selecting and engaging with a dietary app.166
Another concern related to missing food items is the inability in logging beverages other
than water that was categorized under the physical opportunity component. Given the high
prevalence of sugary drinks and sugar-sweetened beverages consumption (23% of mean energy
intake) in a nationally representative sample of Canadians,169 it is crucial to include the recording
of all beverages in dietary self-monitoring.
A lack of classification for various food qualities was also raised as another inhibiting
factor under the reflective motivation in recording all elements of dietary intakes. Consistently,
beliefs about the usefulness and utility of health and well-being mobile apps have been reported
under the reflective motivation construct of the COM-B model.167,170 Reflective motivation is
essential in the context of health apps because when people perceive a health app as useful and
76
effective, they are more likely to use it consistently and rely on its recommendations.171 These
concerns were similar to the Heles et al. study that reported a simplified method for dietary self-
monitoring can lead to similar short-term weight loss compared to detailed dietary self-
monitoring; the simple approach used check marks in boxes to estimate the fat content and
portion size (based on energy content) of meals and snacks.26 It will therefore be important to
include certain aspects of diet quality in a simplified dietary self-monitoring tool (i.e.,
iCANPlate) so as to improve health outcomes.133 Further research is required to determine how
to best represent these categories of foods within iCANPlate while also maintaining its
simplicity.
Our study findings suggest that foods from different cultures may be more challenging to
record within the current iteration of iCANPlate. As a limitation of the 2019 CFG itself, other
qualitative research on parents has also shown that the 2019 CFG does not reflect their
traditional foods.38 Embracing cultural diversity within health apps was considered an important
factor contributing to user engagement under the social opportunity construct of the COM-B
model.172,173 In the absence of cultural food representations on the CFG, incorrect assumptions
can be made regarding the health benefits and nutritional value of cultural foods.174 Our findings
are in line with the results from a multi-lingual survey-based study where the general public
members and health care professionals ( n=2,382) agreed that missing major food items (e.g.,
local foods) in digital health interventions are significant barriers to selecting and engaging with
a dietary self-monitoring tool.166 This finding was confirmed with another qualitative study
whereby Saudi women with overweight and obesity expressed the need for culturally sensitive
information in an ideal weight management app.175 Hence, cultural inclusivity is another area for
further development of the iCANPlate.
77
A barrier to physical opportunity was difficulty in conceptualizing different proportions
within the iCANPlate app. Participants attributed this challenge particularly due to the absence of
serving and portion sizes. Similarly, unconvincing portion size estimation was mentioned as a
barrier to selecting a nutrition and diet app.123
5.1.3 Essential Components Suggested for the Future Iterations of iCANPlate
The study findings suggest that incorporating essential and optional components into
future iterations of iCANPlate that align with the COM-B model can improve individuals’
capability, opportunity, and motivation to engage in dietary self-monitoring behaviour,150
ultimately leading to better adherence to the plate-based dietary approach suggested by the 2019
CFG. The recommended essential components, such as educational content and tutorials, report
dashboard, and accessibility features, were reported to be necessary to use the app independently.
In the context of essential components participants expressed the need for providing
educational content and tutorials within iCANPlate. Educational information related to health
and well-being aspects and instructions on how to effectively use the app are categorized under
the psychological capability of the COM-B model.167 There is strong evidence that providing
proper educational opportunities can improve the uptake of health information through digital
health technologies among populations with low health literacy levels.176 Besides, inadequate
food literacy to translating the 2019 CFG recommendations was highlighted in another study.177
Therefore, appropriate educational content and instructions along with the simple interface can
further lead to the potential of iCANPlate to engage individuals with lower health literacy skills.
The report dashboard was also mentioned as another essential component to be
incorporated into the future version of the app which falls under the psychological capability
78
component of the COM-B model.167 Users’ ability to access report dashboard and monitor their
progress was found to facilitate behaviour monitoring.167
Another essential component suggested by our participants was accessibility, which can
be categorized under the physical opportunity component of the COM-B model.167 Consistent
with findings from focus groups, language accessibility was shown to be an important factor that
should be taken into consideration when designing a health app.178 The importance of
considering visual impairments in iCANPlate’s design was also emphasized by participants,
which aligns with the United Nations Sustainable Development Group’s pledge to “leave no one
behind”.179
5.1.4 Optional Components Suggested for the Future Iterations of iCANPlate
Optional components were suggested as non-essential items which can be explained by
the COM-B model. Automatic food logging and recording other eating behaviour, would fall
under the capability component.167 While personalization, social interaction, and professional
support fall under the opportunity component. Interactivity with the app and incentivization fall
under the motivation component, as proposed by Szinay et al.167
In accordance with many qualitative studies12,180,181 on user experience with dietary self-
monitoring mobile apps, this study found that minimal food data input was a key factor in
adherence. As previously discussed, users often stop using apps because of the demanding nature
of data entry. In our study, participants proposed enabling a camera feature to allow them to scan
their meal and have artificial intelligence deconstruct what is on their plate for them or simply
scan the barcode of their packaged food. These features would facilitate the user’s experience as
79
well as removing the “burden” of dietary assessment. These findings align with previous studies
reporting barcode scanners as being well liked to streamline data entry.123,182
One of the optional components to include in future iterations was personalization of the
app to meet the specific needs of the user. This finding is supported by a systematic review
deeming personalization to be a facilitator of adherence to using nutrition apps.183 Including
tailoring and personalization in health apps has been shown to promote adherence to healthy
behaviours184,185 making this an interesting component to include in future iterations of the app.
Moreover, participants expressed the need to personalize the app in accordance with their diet
and have features tailored towards their needs. This finding is supported by a systematic review
conducted on 28 publications that highlighted 7 studies deeming personalization towards
individuals needs to be a facilitator of nutrition apps usage.183
Interactivity was another component to be included in the future iteration of iCANPlate at
three levels: first, interactivity with app; second, social interaction; and third, professional
support. Popularity of interactivity features such as the ability to receive daily feedback and
interact with the app is mirrored in Peng et al.’s study and has been found to enhance adherence
to health-specific mobile app usage.184
The inclusion of social interactivity was suggested as another optional feature in future
iterations of iCANPlate to enhance user adherence to the app. While social interactivity was
identified as a potential facilitator, concerns were expressed in this study that the concept of
competition could be discouraging. Others consistently have shown that adding a social feature
can be demotivating for some users and decrease adherence.180
Interactivity with professionals is another feature which is considered important since
only less than 1% of available popular technology-based weight management tools are developed
80
with identifiable professional input.95 This is problematic, as without professional guidance,
users may be misled and begin unhealthy diets or develop eating disorders.186,187 In line with the
results of this study, connecting with a health professional (e.g., RDs) through an app is
perceived as being expensive.45 Thus, more research needs to be done before considering adding
social interactivity and interactivity with professional features to iCANPlate.
Automatic motivation construct was a facilitating factor to promote user engagement.
Qualitative findings in this study showed that incentivization such as monetary value and
gamification was the underpinning factor of automatic motivation to improve adherence to use
iCANPlate. Similarly, the perceived value of the incentives was shown to be associated with
weight loss in a systematic review.188 Previously explored in another research,189 gamification
was an external factor stated by participants to motivate their usage of the app. Other motivators
such as interactivity were also stated by the participants. Consistent with research,189,190 receiving
daily feedback is one of the most liked features and can enhance adherence and improve weight
loss. Adding a social feature can however be demotivating for some user and decrease
adherence.180 More research needs to be done on this feature to assess its acceptability in
iCANPlate.
5.2 Strengths and Limitation
This study presents the first dietary self-monitoring mobile app to be developed in
accordance with the CFG. This app is intentionally developed to follow the plate-based approach
to dietary education which mirrors the dietary recommendations around the world.31–33 A
strength of this study was our ability to recruit an equal ratio of men and women from different
ethnic backgrounds to participate in the general public focus groups. This helps to represent the
81
diverse population living in Canada and can increase the reliability of the collected
information.191 Moreover, we engaged both members of the general public and RDs. This is
particularly important since involving potential end-users and RDs’ perceptions in the
development of iCANPlate will increase the chance of obtaining higher levels of appreciation
and prolonged use of the app by the general users and knowledge-users.44 Finally, another
strengths of the research was that the focus groups were held virtually, allowing for improved
diversity and inclusion in the recruitment approach.
Nevertheless, this study is not without limitations. First, RD participants were primarily
women of white ethnicity, in line with the composition of the profession in Canada. However,
the majority of RDs stated to have clients from different ethnic backgrounds whose needs were
reflected in the focus group discussions. Secondly, it should be noted that the general public
participants in this study had a comparatively high level of education. Moreover, health literacy
levels of the general public participants were not measured in this study, however, they
demonstrated self-awareness about their health and dietary behaviours during the focus group
discussions. Since there is a known association between education and health literacy,192,193 this
factor may have influenced the study’s results. Given the hypothesis that the simplicity of
iCANPlate will facilitate the process of dietary self-monitoring for the general public, it is
crucial to explore the perceptions of individuals with varying levels of health literacy regarding
the use of iCANPlate.
Another noteworthy limitation of this study pertains to the qualitative analysis, where a
comprehensive examination of gender differences was not undertaken while presenting the
findings. Given that gender may potentially influence the use of dietary self-monitoring tools,
82
considering such variations in the analysis could have added valuable insights to our study and
should be considered in future research endeavors.
5.3 Implications for Research and Practice
The findings of this study have several implications for future research and practice
regarding iCANPlate, as well as other similar digital health interventions for dietary behaviour
change. Firstly, the results suggest that user-friendliness and simplicity are important influencers
of mobile health utilization. The plate-based approach has the potential to simplify dietary self-
monitoring, increase adherence, and facilitate eliciting positive dietary changes. The high level
of education among the study participants may have influenced the study’s results. Therefore,
future research should aim to include a more diverse sample, including individuals with lower
levels of education and health literacy, to ensure that digital health interventions are accessible
and effective for a wider range of populations.
Secondly, this thesis identified several desirable and essential features that could add
value to iCANPlate. Future research should evaluate the effectiveness of these features in
improving user engagement, motivation, and behaviour change while considering a balance
between simplicity and precision.
From a practical standpoint, the study’s findings provide valuable insights for developers
and practitioners in designing and implementing digital health interventions for dietary
behaviour change. Specifically, the study highlights the importance of integrating the simplified
dietary self-monitoring tool into RDs practice, to help their clients achieve positive dietary
behaviour change.
83
5.4 Conclusion
In conclusion, this thesis explored the perceptions of the general public and RDs on
iCANPlate, a dietary plate-based self-monitoring app intended to mirror the 2019 CFG. The goal
of iCANPlate is to help Canadians adhere to healthy eating practices that are aligned with the
CFG. The study findings provided important insight into barriers and facilitating features that
should be taken into consideration when developing the app to uphold user engagement.
Exploring the perceptions of individuals from lower levels of health are needed to be able to
draw conclusions on the accessibility of iCANPlate to the greater Canadian population. The
results of this study will be used to improve the content of the app before moving to the next
development steps.
84
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Appendices
Appendix A Consolidated criteria for reporting qualitative studies (COREQ): 32-item
checklist146
No. Item
Guide questions/description
Reported on
Page #
Domain 1: Research team and reflexivity
Personal characteristics
1. Interviewer/facilitator
Which author/s conducted the interview or focus
group?
Page 47
2. Credentials
What were the researcher’s credentials? E.g., PhD,
MD
Page 100
3. Occupation
What was their occupation at the time of the study?
Page 47
4. Gender
Was the researcher male or female?
Page 47
5. Experience and
training
What experience or training did the researcher
have?
Page 47
Relationship with participants
6. Relationship
established
Was a relationship established prior to study
commencement?
Page 47
7. Participant knowledge
of the interviewer
What did the participants know about the
researcher? e.g., personal goals, reasons for doing
the research
Page 47
8. Interviewer
characteristics
What characteristics were reported about the inter
viewer/facilitator? e.g., Bias, assumptions, reasons
and interests in the research topic
Page 47
Domain 2: Study design
Theoretical framework
9. Methodological
orientation and Theory
What methodological orientation was stated to
underpin the study? e.g., grounded theory, discourse
analysis, ethnography, phenomenology, content
analysis
Page 44, 45,
46, 49
Participant selection
10. Sampling
How were participants selected? e.g., purposive,
convenience, consecutive, snowball
Page 42, 43
11. Method of approach
How were participants approached? e.g., face-to-
face, telephone, mail, email
Page 42, 43
101
12. Sample size
How many participants were in the study?
Page 42, 51,
52
13. Non-participation
How many people refused to participate or dropped
out? Reasons?
Page 51, 52
Setting
14. Setting of data
collection
Where was the data collected? e.g. home, clinic,
workplace
Page 42
15. Presence of non-
participants
Was anyone else present besides the participants
and researchers?
No
16. Description of sample
What are the important characteristics of the
sample? e.g. demographic data, date
Page 51,53
Data collection
17. Interview guide
Were questions, prompts, guides provided by the
authors? Was it pilot tested?
Page 64, 102,
103
18. Repeat interviews
Were repeat interviews carried out? If yes, how
many?
No
19. Audio/visual
recording
Did the research use audio or visual recording to
collect the data?
Page 48
20. Field notes
Were field notes made during and/or after the
interview or focus group?
Page 47,48
21. Duration
What was the duration of the interviews or focus
group?
Page 51
22. Data saturation
Was data saturation discussed?
Page 42
23. Transcripts returned
Were transcripts returned to participants for
comment and/or correction?
No
Domain 3: Analysis and findings
Data analysis
24. Number of data
coders
How many data coders coded the data?
Page 48, 49
25. Description of the
coding tree
Did authors provide a description of the coding
tree?
Page 48, 49
26. Derivation of themes
Were themes identified in advance or derived from
the data?
Page 48, 49
27. Software
What software, if applicable, was used to manage
the data?
Page 48
28. Participant checking
Did participants provide feedback on the findings?
No
Reporting
29. Quotations presented
Were participant quotations presented to illustrate
the themes/findings? Was each quotation identified?
e.g., participant number
Page 56-69
30. Data and findings
consistent
Was there consistency between the data presented
and the findings?
Page 54-69
102
31. Clarity of major
themes
Were major themes clearly presented in the
findings?
Page 54-69
32. Clarity of minor
themes
Is there a description of diverse cases or discussion
of minor themes?
Page 54-69
103
Appendix B Focus Group Guide
B.1 Section 1: Perceptions of the 2019 CFG
1. What do you/ your clients know about CFG? What makes it easy/hard for your clients
to eat in accordance with the plate-based approach that mirrors CFG?
B.2 Section 2: History of using dietary self-monitoring tools
2. Which diet-tracking methods or apps have you ever used/ suggested to your clients (if
any)? What makes it easy or hard for you/ your clients to use the tools you have
experience with?
3. Do you know of any diet tracking tools that currently resembles the CFG or the plate-
based approach? Which apps?
[Showing a video of the prototype iCANPlate app]
B.3 Section 3: Content and features of the proposed app
4. What did/didn’t you like about the plate-based dietary self-monitoring app app?
5. How do you view the app working to record all meals throughout the day? (Consider
breakfast, lunch, supper and snacks)
6. What would be considered a successful day? What proportion indicates a balanced,
healthy diet? How should improvements be defined for the purposes of the app?
104
7. Many “other foods” are not shown on the CFG. Which foods can you think of that
your clients would find difficult to represent on the plate? How do you suggest they
be tracked on the app? How could they be classified within the app?
8. How do you suggest beverages be tracked within the app? Should beverages be
included on the plate? Should beverages be included in “other foods”? Should there
be different classifications for beverages?
9. How do you suggest dairy (specifically liquid milk) products be tracked on the app?
10. What other eating behaviours or elements of the CFG should be included in this app
(E.g., tracking mood, feelings, etc.)
11. Which instructions and support should be provided to the users to support and
enhance your/ your clients use of the app?
12. What features can facilitate social support and enhance user adherence to the app?
13. Which features in the app could improve user’s confidence when tracking their food
intake?
14. What features are required to ensure accessibility for all users?
15. Which other features of a dietary self-monitoring tool could be helpful in mirroring
new CFG that we have not discussed yet?
