Evidence map›Paper›PMID 21156470›Full record

ArticleJournal of medical Internet research2010

Dropout, nonusage attrition, and pretreatment predictors of nonusage attrition in a commercial Web-based weight loss program.

Melinda J Neve, Clare E Collins, Philip J Morgan

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 3 pooled it
15.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

89 citing papers in PubMed, 3 syntheses or guidelines pooled it, 143 citations in OpenAlex.

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  11. Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2018
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29 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Melinda J NeveSchool of Health Sciences, Faculty of Health, The University of Newcastle, Callaghan, Australia. melinda.neve@newcastle.edu.au
Clare E Collins
Philip J Morgan
University of Newcastle Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn 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.

objectiveThe 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.

methodsParticipants 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.

resultsOf 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.

conclusionsThe 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.

Indexed as

Weight LossAdultAustraliaCohort StudiesComputer-Assisted InstructionConfidence IntervalsFemaleHumansInternetMaleMiddle AgedObesityOdds RatioOutcome and Process Assessment, Health CarePatient CompliancePatient Dropouts

Identifiers

PMID21156470
PMCPMC3056525
OpenAlexW1981687717

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.