Trial reportJournal of medical Internet research2013
Participants, usage, and use patterns of a web-based intervention for the prevention of depression within a randomized controlled trial.
Trial report in Journal of medical Internet research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled 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.
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.
Who cites it
50 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review.Journal of medical Internet research · 2023Pooled it
- Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores.Journal of medical Internet research · 2022Pooled it
- Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence.Journal of medical Internet research · 2017Pooled it
- The Use of Mobile Apps and SMS Messaging as Physical and Mental Health Interventions: Systematic Review.Journal of medical Internet research · 2017Pooled it
- Efficacy of a self-guided online resilience intervention for improving mental health among university students: A randomized controlled trial.Scientific reports · 2026Trial
- Exploring engagement with a web-based self-directed psychoeducational program for advanced cancer patients and their caregivers (iFOCUS): A sub study analysis of the DIAdIC trial.Palliative medicine · 2026Trial
- A Universal Digital Stress Management Intervention for Employees: Randomized Controlled Trial with Health-Economic Evaluation.Journal of medical Internet research · 2024Trial
- Factors Predicting Engagement of Older Adults With a Coach-Supported eHealth Intervention Promoting Lifestyle Change and Associations Between Engagement and Changes in Cardiovascular and Dementia Risk: Secondary Analysis of an 18-Month Multinational Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- Evaluating the efficacy of the Family Check-Up Online: A school-based, eHealth model for the prevention of problem behavior during the middle school years.Development and psychopathology · 2019Trial
- Guided Self-Help Works: Randomized Waitlist Controlled Trial of Pacifica, a Mobile App Integrating Cognitive Behavioral Therapy and Mindfulness for Stress, Anxiety, and Depression.Journal of medical Internet research · 2019Trial
- Turning Good Intentions Into Actions by Using the Health Action Process Approach to Predict Adherence to Internet-Based Depression Prevention: Secondary Analysis of a Randomized Controlled Trial.Journal of medical Internet research · 2018Trial
- Customized recommendations and reminder text messages for automated, computer-based treatment during methadone.Experimental and clinical psychopharmacology · 2017Trial
- The impact of psychological user characteristics on adherence to an mHealth intervention among women in their postpartum period.Internet interventions · 2026Article
- Designing a Self-Guided Digital Intervention for Self-Management of Shoulder Pain in People Living With Spinal Cord Injury: Tutorial on Using a Person-Based Approach.JMIR mHealth and uHealth · 2026Article
- Designing a Visual Analytics Tool to Support Data Analysis Tasks of Digital Mental Health Interventions: Case Study.JMIR human factors · 2025Article
- Predicting Early Dropout in a Digital Tobacco Cessation Intervention: Replication and Extension Study.Journal of medical Internet research · 2024Article
- Group, Blended and Individual, Unguided Online Delivery of Mindfulness-Based Cognitive Therapy for People With Cancer: Feasibility Uncontrolled Trial.JMIR formative research · 2024Article
- Digital Interventions to Enhance Readiness for Psychological Therapy: Scoping Review.Journal of medical Internet research · 2022Article
- Usage Intensity of a Relapse Prevention Program and Its Relation to Symptom Severity in Remitted Patients With Anxiety and Depression: Pre-Post Study.JMIR mental health · 2022Article
- Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years.Journal of affective disorders · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough Web-based interventions have been shown to be effective, they are not widely implemented in regular care. Nonadherence (ie, participants not following the intervention protocol) is an issue. By studying the way Web-based interventions are used and whether there are differences between adherers (ie, participants that started all 9 lessons) and nonadherers, more insight can be gained into the process of adherence.
objectiveThe aims of this study were to (1) describe the characteristics of participants and investigate their relationship with adherence, (2) investigate the utilization of the different features of the intervention and possible differences between adherers and nonadherers, and (3) identify what use patterns emerge and whether there are differences between adherers and nonadherers.
methodsData were used from 206 participants that used the Web-based intervention Living to the full, a Web-based intervention for the prevention of depression employing both a fully automated and human-supported format. Demographic and baseline characteristics of participants were collected by using an online survey. Log data were collected within the Web-based intervention itself. Both quantitative and qualitative analyses were performed.
resultsIn all, 118 participants fully adhered to the intervention (ie, started all 9 lessons). Participants with an ethnicity other than Dutch were more often adherers (χ²₁=5.5, P=.02), and nonadherers used the Internet more hours per day on average (F₁,₂₀₃=3.918, P=.049). A logistic regression showed that being female (OR 2.02, 95% CI 1.01-4.04; P=.046) and having a higher need for cognition (OR 1.02; 95% CI 1.00-1.05; P=.02) increased the odds of adhering to the intervention. Overall, participants logged in an average of 4 times per lesson, but adherers logged in significantly more times per lesson than nonadherers (F₁,₂₀₄=20.710; P<.001). For use patterns, we saw that early nonadherers seemed to use fewer sessions and spend less time than late nonadherers and adherers, and fewer sessions to complete the lesson than adherers. Furthermore, late nonadherers seemed to have a shorter total duration of sessions than adherers.
conclusionsBy using log data combined with baseline characteristics of participants, we extracted valuable lessons for redesign of this intervention and the design of Web-based interventions in general. First, although characteristics of respondents can significantly predict adherence, their predictive value is small. Second, it is important to design Web-based interventions to foster adherence and usage of all features in an intervention.
trial registrationDutch Trial Register Number: NTR3007; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3007 (Archived by WebCite at http://www.webcitation.org/6ILhI3rd8).
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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.