Evidence map›Paper›PMID 22201703›Full record

Trial reportJournal of medical Internet research2011

Attrition in web-based treatment for problem drinkers.

Marloes G Postel, Hein A de Haan, Elke D ter Huurne, Job van der Palen, Eni S Becker, Cor A J de Jong

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of medical Internet research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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

60 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Trial
  14. Trial
  15. Trial
  16. Trial
  17. Trial
  18. Trial
  19. Trial
  20. Trial
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

6 authors.

Marloes G PostelTactus Addiction Treatment, Enschede, Netherlands. m.postel@tactus.nl
Hein A de Haan
Elke D ter Huurne
Job van der Palen
Eni S Becker
Cor A J de Jong

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWeb-based interventions for problem drinking are effective but characterized by high rates of attrition. There is a need to better understand attrition rates in order to improve the completion rates and the success of Web-based treatment programs.

objectiveThe objectives of our study were to (1) examine attrition prevalence and pretreatment predictors of attrition in a sample of open-access users of a Web-based program for problem drinkers, and (2) to further explore attrition data from our randomized controlled trial (RCT) of the Web-based program.

methodsAttrition data from two groups of Dutch-speaking problem drinkers were collected: (1) open-access participants enrolled in the program in 2009 (n = 885), and (2) RCT participants (n = 156). Participants were classified as noncompleters if they did not complete all 12 treatment sessions (9 assignments and 3 assessments). In both samples we assessed prevalence of attrition and pretreatment predictors of treatment completion. Logistic regression analysis was used to explore predictors of treatment completion. In the RCT sample, we additionally measured reasons for noncompletion and participants' suggestions to enhance treatment adherence. The qualitative data were analyzed using thematic analysis.

resultsThe open-access and RCT group differed significantly in the percentage of treatment completers (273/780, 35.0% vs 65/144, 45%, χ(2) (1) = 5.4, P = .02). Logistic regression analysis revealed a significant contribution of treatment readiness, gender, education level, age, baseline alcohol consumption, and readiness to change to predict treatment completion. The key reasons for noncompletion were personal reasons, dissatisfaction with the intervention, and satisfaction with their own improvement. The main suggestions for boosting strategies involved email notification and more flexibility in the intervention.

conclusionsThe challenge of Web-based alcohol treatment programs no longer seems to be their effectiveness but keeping participants involved until the end of the treatment program. Further research should investigate whether the suggested strategies to improve adherence decrease attrition rates in Web-based interventions. If we can succeed in improving attrition rates, the success of Web-based alcohol interventions will also improve and, as a consequence, their public health impact will increase. TRIAL: International Standard Randomized Controlled Trial Number (ISRCTN): 39104853; http://www.controlled-trials.com/ISRCTN39104853 (Archived by WebCite at http://www.webcitation.org/63IKDul1T).

Indexed as

InternetPatient CompliancePatient DropoutsAdultAgedAlcohol DrinkingAlcoholismFemaleHumansLogistic ModelsMaleMiddle AgedNetherlandsOutcome Assessment, Health CareTelemedicineYoung Adult

Identifiers

PMID22201703
PMCPMC3278103

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.