title: Dropout, nonusage attrition, and pretreatment predictors of nonusage attrition in a commercial Web-based weight loss program.
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.
authors.affiliation: School of Health Sciences, Faculty of Health, The University of Newcastle, Callaghan, Australia. melinda.neve@newcastle.edu.au
authors.forename: Melinda J
authors.initials: MJ
authors.lastname: Neve
authors.forename: Clare E
authors.initials: CE
authors.lastname: Collins
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Morgan
mesh_terms: D000328:Adult; D001315:Australia / Q000453:epidemiology; D015331:Cohort Studies; D003194:Computer-Assisted Instruction / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D020407:Internet / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000517:prevention & control / Q000628:therapy*; D016017:Odds Ratio; D010043:Outcome and Process Assessment, Health Care; D010349:Patient Compliance / Q000706:statistics & numerical data*; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D010353:Patient Education as Topic / Q000379:methods*; D015995:Prevalence; D015397:Program Evaluation; D012648:Self Care / Q000379:methods; D016896:Treatment Outcome; D015431:Weight Loss; D055815:Young Adult