The Web-Based Pain-at-Work Toolkit With Telephone Support for Employees With Chronic or Persistent Pain: Protocol for a Cluster Randomized Feasibility Trial
Notice bibliographique
Résumé
BACKGROUND: Chronic or persistent pain affects one's ability to work or be productive at work, generating high societal and economic burden. However, the provision of work-related advice and support for people with chronic pain is variable or lacking. The Pain-at-Work (PAW) Toolkit was cocreated with people who live with pain, health care professionals, and employers. It aims to increase knowledge about employee rights and how to access support for managing a painful chronic condition in the workplace and provides advice on lifestyle behaviors that facilitate the management of chronic pain. OBJECTIVE: We aimed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing access to the PAW Toolkit and telephone support calls from an occupational therapist (PAW) with treatment as usual (ie, standard support from their employer). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, and safety of this digital workplace health intervention. We will assess the candidate primary and secondary outcomes' feasibility and test research processes for a definitive trial. METHODS: This is an open-label, parallel 2-arm pragmatic feasibility cluster randomized controlled trial with exploratory health economics analysis and a nested qualitative interview study. We aim to recruit 120 participants from at least 8 workplace clusters (any type, >10 employees) in England. The recruitment of workplaces occurs via personal approach, and the recruitment of individual participants is web based. Eligible participants are vocationally active adults aged ≥18 years with internet access and self-reporting chronic pain interfering with their ability to undertake or enjoy productive work. A restricted 1:1 cluster-level randomization is used to allocate employment settings to PAW or treatment as usual; participants are unblinded to group allocation. Following site- and individual-level consent, participants complete a web-based baseline survey (time 0), including measures of work capacity, health and well-being, and health care resource use. Follow-up is performed at 3 months (time 1) and 6 months (time 2). Feasibility outcomes relate to recruitment; intervention fidelity (eg, delivery, reach, uptake, and engagement); retention; and follow-up. Qualitative evaluation (time 2) is mapped to the Capability, Opportunity, Motivation-Behavior model and will explore intervention acceptability to employees and employers, along with individual and contextual factors influencing the delivery and uptake of the intervention. RESULTS: Ethics approval was obtained in March 2023. Trial recruitment began in June 2023. CONCLUSIONS: The PAW Toolkit is the first evidence-based digital health intervention aimed at supporting the self-management of chronic or persistent pain at work. This study will inform the design of a definitive trial, including sample size estimation, approaches to cluster site identification, primary and secondary outcomes' selection, and the final health economic model. Findings will inform approaches for the future delivery of this digital health intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT05838677; https://clinicaltrials.gov/study/NCT05838677. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51474.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,047 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,004 |
| Méta-épidémiologie (sens large) | 0,011 | 0,006 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,086 | 0,017 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».