ArticleBMJ open2022
Digital cognitive behavioural therapy intervention in the workplace: study protocol for a feasibility randomised waitlist-controlled trial to improve employee mental well-being, engagement and productivity.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed, 5 citations in OpenAlex.
- Wearables in Healthcare Organizations: Implications for Occupational Health, Organizational Performance, and Economic Outcomes.Healthcare (Basel, Switzerland) · 2025Review
- Digital Training Program for Line Managers (Managing Minds at Work): Protocol for a Feasibility Pilot Cluster Randomized Controlled Trial.JMIR research protocols · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionOne in six workers experience some form of mental health problems at work costing the UK economy an estimated £70 billion/year. Digital interventions provide low cost and easily scalable delivery methods to implement psychological interventions in the workplace. This trial tests the feasibility of implementing a self-guided 8-week digital cognitive behavioural therapy intervention for subthreshold to clinical depression and/or anxiety versus waitlist control (ie, life as usual) in the workplace. METHODS AND ANALYSIS: Feasibility of implementation will be tested using a mixed-methods evaluation of the two-arm randomised waitlist-control trial. Evaluation will include examination of organisational buy-in, and the engagement of employees through the trial indicated by the completion of outcome measures. In addition, we also explore how participants use the platform, the appropriateness of the analysis both with reference to the outcome measures and linear modelling. Finally, we examine the acceptability of the intervention based on participants experiences using qualitative interviews. Assessments take place at baseline (T0), at 8 weeks post-treatment (T1), at short-term follow-up 4 weeks post-treatment (T2) and long-term follow-ups (6 and 12 months after-end of treatment). We will recruit from 1 July 2021 to 31 December 2021 for employees and self-employed workers with depression and anxiety symptoms (subclinical and clinical levels) who are not seeking or engaged in treatment at the time of the trial. ETHICS AND DISSEMINATION: Full approval was given by the University of Warwick Biomedical and Research Ethics Committee (BSREC 45/20-21). The current protocol version is 2.8 (August 2021). Publication of results in peer-reviewed journals will inform the scientific, clinical and business communities. We will disseminate results through webinars, conferences, newsletter as well as a lay summary of results on the study website (mhpp.me). TRIAL REGISTRATION NUMBER: ISRCTN31161020.
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Registered trials
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.