Barriers, Facilitators, and Requirements for a Telerehabilitation Aftercare Program for Patients After Occupational Injuries: Semistructured Interviews With Key Stakeholders
Notice bibliographique
Résumé
BACKGROUND: Patients with occupational injuries often receive multidisciplinary rehabilitation for a rapid return to work. Rehabilitation aftercare programs give patients the opportunity to help patients apply the progress they have made during the rehabilitation to their everyday activities. Telerehabilitation aftercare programs can help reduce barriers, such as lack of time due to other commitments, because they can be used regardless of time or location. Careful identification of barriers, facilitators, and design requirements with key stakeholders is a critical step in developing a telerehabilitation aftercare program. OBJECTIVE: This study aims to identify barriers, facilitators, and design requirements for a future telerehabilitation aftercare program for patients with occupational injuries from the perspective of the key stakeholders. METHODS: We used a literature review and expert recommendations to identify key stakeholders. We conducted semistructured interviews in person and via real-time video calls with 27 key stakeholders to collect data. Interviews were transcribed verbatim, and thematic analysis was applied. We selected key stakeholder statements about facilitators and barriers and categorized them as individual, technical, environmental, and organizational facilitators and barriers. We identified expressions that captured aspects that the telerehabilitation aftercare program should fulfill and clustered them into attributes and overarching values. We translated the attributes into one or more requirements and grouped them into content, functional, service, user experience, and work context requirements. RESULTS: The key stakeholders identified can be grouped into the following categories: patients, health care professionals, administrative personnel, and members of the telerehabilitation program design and development team. The most frequently reported facilitators of a future telerehabilitation aftercare program were time savings for patients, high motivation of the patients to participate in telerehabilitation aftercare program, high usability of the program, and regular in-person therapy meetings during the telerehabilitation aftercare program. The most frequently reported barriers were low digital affinity and skills of the patients and personnel, patients' lack of trust and acceptance of the telerehabilitation aftercare program, slow internet speed, program functionality problems (eg, application crashes or freezes), and inability of telerehabilitation to deliver certain elements of in-person rehabilitation aftercare such as monitoring exercise performance. In our study, the most common design requirements were reducing barriers and implementing facilitators. The 2 most frequently discussed overarching values were tailoring of telerehabilitation, such as a tailored exercise plan and tailored injury-related information, and social interaction, such as real-time psychotherapy and digital and in-person rehabilitation aftercare in a blended care approach. CONCLUSIONS: Key stakeholders reported on facilitators, barriers, and design requirements that should be considered throughout the development process. Tailoring telerehabilitation content was the key value for stakeholders to ensure the program could meet the needs of patients with different types of occupational injuries.
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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 | 0,030 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,008 | 0,004 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».