A Web-Delivered Acceptance and Commitment Therapy Intervention With Email Reminders to Enhance Subjective Well-Being and Encourage Engagement With Lifestyle Behavior Change in Health Care Staff: Randomized Cluster Feasibility Stud
Bibliographic record
Abstract
BACKGROUND: Poor mental health and emotional well-being can negatively impact ability to engage in healthy lifestyle behavior change. Health care staff have higher rates of sickness and absence than other public sector staff, which has implications at both individual and societal levels. Individual efforts to self-manage health and well-being which add to the UK mental health prevention agenda need to be supported. OBJECTIVE: The objective of this study was to establish the feasibility and acceptability of the inclusion of a self-guided, automated, web-based acceptance and commitment therapy intervention in an existing health promotion program, to improve subjective well-being and encourage engagement with lifestyle behavior change. METHODS: For this 12-week, 4-armed, randomized controlled cluster feasibility study, we recruited participants offline and randomly allocated them to 1 of 3 intervention arms or control (no well-being intervention) using an automated web-based allocation procedure. Eligibility criteria were current health care staff in 1 Welsh health board, age≥18 years, ability to read English, and ability to provide consent. The primary researcher was blinded to cluster allocation. Feasibility outcomes were randomization procedure, acceptance of intervention, and adherence to and engagement with the wider program. We evaluated health and well-being data via self-assessment at 2 time points, registration and postintervention, using the 14-item Warwick-Edinburgh Mental Well-Being Scale, the 4-item Patient Health Questionnaire, and the 7-item Acceptance and Action Questionnaire-Revised. RESULTS: Of 124 participants who provided consent and were randomly allocated, 103 completed full registration and engaged with the program. Most participants (76/103) enrolled in at least one health behavior change module, and 43% (41/96) of those randomly allocated to an intervention arm enrolled in the well-being module. Adherence and engagement was low (7/103, 6.8%), but qualitative feedback was positive. CONCLUSIONS: The procedure and randomization process proved feasible, and the addition of the well-being module proved acceptable to health care staff. However, participant engagement was limited, and no one completed the full 12-week program. User feedback should be used to develop the intervention to address poor engagement. Effectiveness should then be evaluated in a full-scale randomized controlled trial, which would be feasible with additional recruitment. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number (ISRCTN) 50074817; http://www.isrctn.com/ISRCTN50074817.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".