The MyRelief Digital Educational Self-Management Program for Persistent Low Back Pain: Feasibility Uncontrolled Trial
Notice bibliographique
Résumé
Background: Low back pain (LBP) is a leading cause of work absence globally. Digital interventions have the potential to increase access to self-management support for individuals with persistent LBP. Objective: This study aims to evaluate the feasibility, usability, and acceptability of a digital educational program (MyRelief) designed to support self-management strategies for people with persistent LBP. Methods: A prospective uncontrolled feasibility study was conducted across 4 countries (Italy, Portugal, Sweden, and the United Kingdom) between 2020 and 2021. Adults in employment with nonspecific persistent LBP (>3 mo) with access to the internet were eligible to participate. Participants were given access to MyRelief, an 8-unit evidence-based educational self-management program. The feasibility of the MyRelief program was assessed using recruitment rates, an a priori success threshold of >70% of the target sample (50 participants), and a retention <35% dropout rate. Pre- and postintervention measures of functional disability were assessed using the Oswestry Disability Index (ODI), and health-related quality of life using the 5-level EuroQol questionnaire. Additional postintervention measures included the Patient Enablement Instrument and the System Usability Scale. Quantitative data were analyzed descriptively, and qualitative feedback was analyzed using a reflexive analytical approach. Results: The recruitment feasibility threshold was met, and 40/50 (80%) participants (19 male and 21 female; mean age 57 years) were enrolled in the study. A total of 17 participants (11 male and 6 female) completed both the baseline and 12-week follow-up questionnaires. This represented a retention rate of 42.5% (17/40) and a dropout rate of 57.5%, which did not meet the a priori criteria of <35% dropouts. Approximately half of the participants presented with low baseline disability scores (mean ODI 24.0; 95% CI 18-31) with no significant change at follow-up (mean ODI 23.9; 95% CI 16-31). The 5-level EuroQol questionnaire scores improved from 0.68 (95% CI 0.608-0.76) to 0.72 (95% CI 0.66-0.79), indicating a clinically significant change. Patient Enablement Instrument scores postintervention were high (mean 5.31), indicating good perceived enablement. The mean System Usability Scale score was 72.4 (95% CI 67.5-73.3), indicating a good level of perceived ease-of-use. Overall, the quality of outcome measure completion was high (100%). Qualitative feedback indicated areas for improvement relating to challenges around access and navigation within the website. Conclusions: The MyRelief study demonstrated feasibility in terms of recruitment but not retention. However, low baseline disability levels are not representative of the wider persistent LBP population. Future studies should broaden recruitment strategies, in particular, by recruiting from health care settings to improve representativeness. Although usability met industry standards, qualitative feedback suggests that navigation and accessibility require further optimization to better align with end user preferences for digital health interventions.
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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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».