Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Mar 31;8(3):e24871.
doi: 10.2196/24871.

Optimizing Engagement in an Online Dietary Intervention for Depression (My Food & Mood Version 3.0): Cohort Study

Claire Louise Young #  1 , Mohammadreza Mohebbi #  2 , Heidi M Staudacher #  1 , Frances Kay-Lambkin #  3 , Michael Berk #  4 , Felice Nellie Jacka #  1   5   6   7 , Adrienne O'Neil #  1
Affiliations

Optimizing Engagement in an Online Dietary Intervention for Depression (My Food & Mood Version 3.0): Cohort Study

Claire Louise Young et al. JMIR Ment Health. .

Abstract

Background: Online interventions can be a cost-effective and efficient way to deliver programs to large numbers of people regardless of geographic location. However, attrition in web-based interventions is often an issue. Developing ways to keep participants engaged is important for ensuring validity and limiting potential biases. We developed a web-based dietary intervention as part of The My Food & Mood study which aimed to optimize ways to engage participants with low mood or depressive symptoms to promote dietary behavior change. Different versions of the My Food & Mood program were tested during optimization. Iterations were developed based on user feedback and usage analysis.

Objective: The purpose of this study was to compare engagement and nonusage attrition across 4 program iterations-which differed by platform format, delivery mode, and activity type-to create an optimized version.

Methods: Each program version contained modular videos with key activities with respect to implementing behavior change techniques of equivalent levels of required participation and length: version 1.0, desktop program and smartphone app; version 2.1, desktop or smartphone program; version 2.2, desktop program; and version 3.0, smartphone app. Adults with PHQ-8 scores of 5 or greater were recruited online and assigned to 1 of the 4 versions. Participants were asked to use the program for 8 weeks and complete measures at weeks 4 and 8. Engagement data were collected from the web-based platform system logs and customized reports. Cox regression survival analysis examined nonusage attrition and Kruskal-Wallis tests compared engagement across each cohort.

Results: A total of 614 adults participated. Kruskal-Wallis tests showed significant differences across the 4 cohorts in all engagement measures. The smartphone app (version 3.0) had the greatest engagement as measured by weeks engaged, total usage time, total time key activities, number of active sessions, percentage of activities completed against protocol, goals completed, and percentage of videos watched. Cox regression multivariate survival analysis showed referral from a health practitioner (hazard ratio [HR] 0.344, P=.001) and greater proficiency with computers (HR 0.796, P=.049) reduced the risk of nonusage attrition. Computer confidence was associated with an increased risk of nonusage attrition.

Conclusions: My Food & Mood version 3.0, a dietary intervention delivered via smartphone app with self-monitoring tools for diet quality and mood monitoring, was the version with greatest engagement in a population with low mood or depression. The iterative design techniques employed and analysis of feedback from participants resulted in a program that achieved lower rates of nonusage attrition and higher rates of intensity of use.

Keywords: depression; dietary intervention; eHealth; engagement; low mood; mHealth; nonusage attrition; nutritional psychiatry; online intervention.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: FNJ has received industry support for research from Meat and Livestock Australia, Woolworths Limited, the A2 Milk Company, Be Fit Foods and travel support and speakers’ honoraria from Sanofi-Synthelabo, Janssen Cilag, Servier, Pfizer, Health Ed, Network Nutrition, Angelini Farmaceutica, Eli Lilly, and Metagenics. She has written two books on diet and health for commercial publication. MB has received support from Cooperative Research Centre Simons Autism Foundation Cancer Council of Victoria, MBF Rotary Health Meat and Livestock Board, Woolworths, Beyond Blue, Geelong Medical Research Foundation, Bristol Myers Squibb, Eli Lilly, Glaxo SmithKline, Organon, Novartis, Mayne Pharma, and Servier; speaker honoraria from Astra Zeneca, Bristol Myers Squibb, Eli Lilly, Glaxo SmithKline, Lundbeck, Pfizer, Sanofi, Synthelabo, Servier, Solvay, and Wyeth. He has been a consultant for AstraZeneca, Bristol Myers Squibb, Eli Lilly, Bioadvantex, Merck, GlaxoSmithKline, Lundbeck, Janssen, Cilag, and Servier. MB is a co-inventor of two provisional patents regarding the use of n-acetylcysteine and related compounds for psychiatric indications, which, while assigned to the Mental Health Research Institute, could lead to personal remuneration upon commercialization. The other authors have no conflicts to declare.

Figures

Figure 1
Figure 1
Total time key activities.
Figure 2
Figure 2
Average duration per session.
Figure 3
Figure 3
Percentage watched videos.
Figure 4
Figure 4
Per protocol percentage.
Figure 5
Figure 5
Survival curve (Cox regression) for nonusage attrition versus weeks engaged across all cohorts of the My Food & Mood Program.
See this image and copyright information in PMC

References

    1. Depression and other common mental disorders: global health estimates. World Health Organization. 2017. [2021-02-17]. https://www.who.int/mental_health/management/depression/prevalence_globa...
    1. Pedersen ER, Paves AP. Comparing perceived public stigma and personal stigma of mental health treatment seeking in a young adult sample. Psychiatry Res. 2014 Sep 30;219(1):143–50. doi: 10.1016/j.psychres.2014.05.017. http://europepmc.org/abstract/MED/24889842 - DOI - PMC - PubMed
    1. Liu JX, Goryakin Y, Maeda A, Bruckner T, Scheffler R. Global health workforce labor market projections for 2030. Hum Resour Health. 2017 Feb 03;15(1):11. doi: 10.1186/s12960-017-0187-2. https://human-resources-health.biomedcentral.com/articles/10.1186/s12960... - DOI - DOI - PMC - PubMed
    1. Andrews G, Issakidis C, Sanderson K, Corry J, Lapsley H. Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders. Br J Psychiatry. 2004 Jun;184:526–33. doi: 10.1192/bjp.184.6.526. - DOI - PubMed
    1. Ayuso-Mateos JL, Nuevo R, Verdes E, Naidoo N, Chatterji S. From depressive symptoms to depressive disorders: the relevance of thresholds. Br J Psychiatry. 2010 May;196(5):365–71. doi: 10.1192/bjp.bp.109.071191. - DOI - PubMed

LinkOut - more resources