Fluctuations in MHealth Engagement Following Receipt of Goal-discrepant Feedback Messages

Overview

Journal Digit Health

Date 2025 Jan 13

PMID 39801582

Authors

Lex Hurley

Nisha G OShea

Brooke T Nezami

Carmina G Valle

Deborah F Tate

Affiliations

Soon will be listed here.

Abstract

Objective: Digital behavior change interventions can successfully promote change in behavioral outcomes, but often suffer from steep decreases in engagement over time, which hampers their effectiveness. Providing feedback on goal performance is an established technique to promote goal attainment; however, theory indicates that sending goal-discrepant feedback messages could cause some users to respond more negatively than others. This analysis assessed whether goal-discrepant messaging was negatively associated with participant engagement, and if this relationship was exacerbated by baseline depressive symptoms within the context of a three-month weight loss pilot mHealth intervention.

Methods: This analysis applied a generalization of log-linear regression analysis with = 52 participants (78.8% female, 61.5% white, ages 21-35) to assess the likelihood of reading consecutive program messages following receipt of messages with goal-discrepant content.

Results: Receipt of goal-discrepant messages was associated with a significantly lower likelihood (RR = 0.89) of participants reading the next program message sent, compared to receiving positive/neutral messages or no message, but these relationships were not influenced by depressive symptoms in this sample.

Conclusion: Feedback on goal performance remains an important behavior change technique; however, sending push messages that alert participants to their goal-discrepant status seems to reduce the likelihood that participants will read future program messages. Sending messages containing positive or neutral content does not seem to carry this negative risk among individuals in goal-discrepant states.

References

Luppino F, de Wit L, Bouvy P, Stijnen T, Cuijpers P, Penninx B . Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010; 67(3):220-9. DOI: 10.1001/archgenpsychiatry.2010.2. View

Bianchini F, Kaaks R, Vainio H . Overweight, obesity, and cancer risk. Lancet Oncol. 2002; 3(9):565-74. DOI: 10.1016/s1470-2045(02)00849-5. View

Neve M, Morgan P, Jones P, Collins C . Effectiveness of web-based interventions in achieving weight loss and weight loss maintenance in overweight and obese adults: a systematic review with meta-analysis. Obes Rev. 2009; 11(4):306-21. DOI: 10.1111/j.1467-789X.2009.00646.x. View

Carey R, Connell L, Johnston M, Rothman A, de Bruin M, Kelly M . Behavior Change Techniques and Their Mechanisms of Action: A Synthesis of Links Described in Published Intervention Literature. Ann Behav Med. 2018; 53(8):693-707. PMC: 6636886. DOI: 10.1093/abm/kay078. View

Bandura A, Locke E . Negative self-efficacy and goal effects revisited. J Appl Psychol. 2003; 88(1):87-99. DOI: 10.1037/0021-9010.88.1.87. View

Lustria M, Noar S, Cortese J, Van Stee S, Glueckauf R, Lee J . A meta-analysis of web-delivered tailored health behavior change interventions. J Health Commun. 2013; 18(9):1039-69. DOI: 10.1080/10810730.2013.768727. View

Yardley L, Spring B, Riper H, Morrison L, Crane D, Curtis K . Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions. Am J Prev Med. 2016; 51(5):833-842. DOI: 10.1016/j.amepre.2016.06.015. View

Bhutani S, VanDellen M, Cooper J . Longitudinal Weight Gain and Related Risk Behaviors during the COVID-19 Pandemic in Adults in the US. Nutrients. 2021; 13(2). PMC: 7922943. DOI: 10.3390/nu13020671. View

Flores Mateo G, Granado-Font E, Ferre-Grau C, Montana-Carreras X . Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis. J Med Internet Res. 2015; 17(11):e253. PMC: 4704965. DOI: 10.2196/jmir.4836. View

10.

Noar S, Benac C, Harris M . Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychol Bull. 2007; 133(4):673-93. DOI: 10.1037/0033-2909.133.4.673. View

11.

Lin P, Grambow S, Intille S, Gallis J, Lazenka T, Bosworth H . The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2018; 6(10):e10471. PMC: 6245957. DOI: 10.2196/10471. View

12.

Tolli A, Schmidt A . The role of feedback, casual attributions, and self-efficacy in goal revision. J Appl Psychol. 2008; 93(3):692-701. DOI: 10.1037/0021-9010.93.3.692. View

13.

Vandelanotte C, Muller A, Short C, Hingle M, Nathan N, Williams S . Past, Present, and Future of eHealth and mHealth Research to Improve Physical Activity and Dietary Behaviors. J Nutr Educ Behav. 2016; 48(3):219-228.e1. DOI: 10.1016/j.jneb.2015.12.006. View

14.

Klasnja P, Smith S, Seewald N, Lee A, Hall K, Luers B . Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps. Ann Behav Med. 2018; 53(6):573-582. PMC: 6401341. DOI: 10.1093/abm/kay067. View

15.

Rivera J, McPherson A, Hamilton J, Birken C, Coons M, Iyer S . Mobile Apps for Weight Management: A Scoping Review. JMIR Mhealth Uhealth. 2016; 4(3):e87. PMC: 4978862. DOI: 10.2196/mhealth.5115. View

16.

Mangieri C, Johnson R, Sweeney L, Choi Y, Wood J . Mobile health applications enhance weight loss efficacy following bariatric surgery. Obes Res Clin Pract. 2019; 13(2):176-179. DOI: 10.1016/j.orcp.2019.01.004. View

17.

Khubchandani J, Price J, Sharma S, Wiblishauser M, Webb F . COVID-19 pandemic and weight gain in American adults: A nationwide population-based study. Diabetes Metab Syndr. 2022; 16(1):102392. PMC: 8743853. DOI: 10.1016/j.dsx.2022.102392. View

18.

Valle C, Queen T, Martin B, Ribisl K, Mayer D, Tate D . Optimizing Tailored Communications for Health Risk Assessment: A Randomized Factorial Experiment of the Effects of Expectancy Priming, Autonomy Support, and Exemplification. J Med Internet Res. 2018; 20(3):e63. PMC: 5856933. DOI: 10.2196/jmir.7613. View

19.

Weissman M, Sholomskas D, Pottenger M, Prusoff B, Locke B . Assessing depressive symptoms in five psychiatric populations: a validation study. Am J Epidemiol. 1977; 106(3):203-14. DOI: 10.1093/oxfordjournals.aje.a112455. View

20.

Addis M, Mahalik J . Men, masculinity, and the contexts of help seeking. Am Psychol. 2003; 58(1):5-14. DOI: 10.1037/0003-066x.58.1.5. View