Cited by 137Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsInnovative Human-Technology Interaction

Dropout, Nonusage Attrition, and Pretreatment Predictors of Nonusage Attrition in a Commercial Web-Based Weight Loss Program

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Neve, Melinda J, Collins, Clare E, Morgan, Philip J·2010·Journal of Medical Internet Research

Abstract

BACKGROUND: An understanding of the factors that predict retention and website use are critical to the development of effective Web-based weight loss interventions. However, poor retention (dropout attrition) and website utilization (nonusage attrition) are major inhibitors to the effectiveness of Web-based programs. OBJECTIVE: The study aimed to (1) describe the prevalence of dropout and nonusage attrition and (2) examine pretreatment predictors of nonusage attrition in a cohort of commercial Web-based weight loss program participants. METHODS: Participants enrolled in the online program, The Biggest Loser Club, Australia, from August 15, 2007, to May 31, 2008. Only those who subscribed for 12 or 52 weeks were included in this study. All data were collected by the program proprietors, SP Health Co Pty Ltd (Sydney, Australia), and provided in "deidentified" form. Data collected included responses to a pretreatment survey (sociodemographic and behavioral characteristics), subscription history (date of enrollment and subscription end), and website use (log-ins, food and exercise diary entries, weigh-ins, and forum posts). Participants were classified as a member of the program at 12 or 52 weeks if they held an active subscription plan at that point in time. Participants were classified as nonusers at 12 or 52 weeks if they had stopped using all of the website features and had not returned. Predictors of nonusage attrition were explored using Cox proportional hazards regression analysis. RESULTS: Of the 9599 eligible participants, 6943 (72%) subscribed to the program for 12 weeks, and 2656 (28%) subscribed for 52 weeks. Of all participants, 31% (2975/9599) were classified as overweight, 61% (5866/9599) were classified as obese, 86% (8279/9599) were female, and participants' mean (SD) age was 35.7 (9.5) years. The 12 week and 52 week subscribers' retention rates were 97% and 77% respectively. Of 12 week subscribers, 35% were classified as program "users" after 12 weeks, and 30% of 52 week subscribers were classified as "users" after 52 weeks. Significant predictors of nonusage attrition among 12 week subscribers included age (hazard ratio for 45 to 55 years of age = 0.83, 95% confidence interval [CI] 0.73 - 0.93, P = .001; hazard ratio for 55 to 65 years of age = 0.80, 95% CI 0.66 - 0.99, P = .04), exercise level (hazard ratio = 0.76, 95% CI 0.72 - 0.81, P < .001), emotional eating (hazard ratio = 1.11, 95% CI 1.04 - 1.18, P = .001), eating breakfast (hazard ratio = 0.88, 95% CI 0.82 - 0.95, P = .001), and skipping meals (hazard ratio = 1.12, 95% CI 1.04 -1.19, P = .001). For 52 week subscribers, eating breakfast (hazard ratio = 0.88, 95% CI 0.79 - 0.99, P = .04) and not drinking tea or coffee with sugar (hazard ratio = 1.23, 95% CI 1.11 - 1.37, P < .001) were the pretreatment characteristics that significantly decreased risk of nonusage attrition. CONCLUSIONS: The findings demonstrate a high prevalence of nonusage attrition among a cohort of commercial Web-based weight loss program participants. Several sociodemographic and behavioral factors were shown to independently predict nonusage attrition.

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Authors
Neve, M. J., Collins, C. E., & Morgan, P. J.
Affiliations
University of Newcastle Australia (AU)
Venue
Journal of Medical Internet Research
Published
2010-12-14
Volume
12
Issue
4
Pages
e69
ISSN
1438-8871 (ISSN-L)
OpenAlex
W1981687717
Cited by
137
References
45
Citations by year
2026: 1 · 2025: 2 · 2024: 6 · 2023: 3 · 2022: 13 · 2021: 7 · 2020: 13 · 2019: 9 · 2018: 11 · 2017: 9 · 2016: 25 · 2015: 7 · 2014: 6 · 2013: 10 · 2012: 7
FWCI
14.20
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion)
  • NOVA (University of Newcastle Australia) (submittedVersion)
Funders
  • Medical Research Council
  • National Health and Medical Research Council
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
online health interventions, participant retention, predictors of attrition, internet use, obesity, overweight, commercial weight loss programs, user engagement, online forums, weight loss outcomes, sociodemographic predictors, behavioral predictors
MeSH terms
Adult, Australia, Computer-Assisted Instruction, Female, Humans, Male, Middle Aged, Obesity, Outcome and Process Assessment, Health Care, Patient Compliance, Patient Dropouts, Patient Education as Topic, Self Care, Cohort Studies, Program Evaluation, Weight Loss, Prevalence, Confidence Intervals, Odds Ratio, Treatment Outcome, Internet, Young Adult

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