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Enregistrement W4402715676 · doi:10.33137/cpoj.v7i1.43790

EXPLORING FACTORS FOR PRESCRIPTION AND VALIDATION OF ACTUATED UPPER LIMB DEVICES: A CROSS-SECTIONAL SURVEY OF ALLIED HEALTH PROFESSIONALS

2024· article· en· W4402715676 sur OpenAlexvenueaboutno aff
Angel Galbert, Arjan Buis

Notice bibliographique

RevueCanadian Prosthetics & Orthotics Journal · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueProsthetics and Rehabilitation Robotics
Établissements canadiensnon disponible
Organismes subventionnairesEngineering and Physical Sciences Research Council
Mots-clésThematic analysisMedicineAssistive technologyCross-sectional studyMedical prescriptionAssistive deviceHealth carePsychologyPhysical medicine and rehabilitationNursingQualitative researchComputer scienceHuman–computer interaction

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Actuated devices can be beneficial for individuals with upper limb muscle weakness, offering extra force and grip. Utilising this type of assistive device can facilitate daily activities, thereby enhancing independence and overall quality of life. The development of actuated assistive devices has been growing, and current literature shows promise in their clinical use. However, they are not yet medically recommended by global guidelines and councils. Studies have suggested why assistive devices have barriers to access, but actuated devices have not been a focus in these discussions. OBJECTIVE(S): To address this issue, a survey was conducted among professionals who prescribe and assess upper limb assistive devices. The survey aimed to gather their opinions and quantify the factors that might contribute to the limited use of actuated devices in the field. METHODOLOGY: A web-based cross-sectional study was designed using Qualtrics, contained 25 items and was conducted between October 2023 and January 2024. The survey was piloted, validated, and ethically approved. Results were statistically analysed, and open questions underwent thematic analysis. FINDINGS: 87 Allied Health Professionals (AHPs) contributed to the survey, with a completion rate of 69% (60/87). Survey respondents predominately worked from the USA (72%). The survey revealed that 66% of respondents felt they did not have sufficient access to assistive devices and 58% indicated that outcome measures could be improved. They also noted that actuated devices needed to better meet user-centric needs. Barriers to prescribing these devices included a lack of awareness, experience and standardised prescription methods. In addition, the limited time with patients made decision-making and validation of an actuated device difficult. CONCLUSION: AHP’s have experience prescribing assistive devices but do not have access, knowledge, or clinical methods to assess the use of actuated devices. Future designs for actuated devices should focus on wearability, comfort, user satisfaction, safety and ease of use. Layman's Abstract Powered support devices can be helpful for persons with muscle weakness in their arms. These devices can provide support by giving additional strength to the hands. This helps with everyday tasks such as self-care, which in turn also improves quality of life. The development of powered and motorized assistive devices has been growing and current research shows promise in their clinical use. Yet they are not medically recommended by global guidelines and councils. Studies have suggested why all assistive devices have barriers to access, but powered devices have not been a focus in these discussions. This study aims to explore which devices medical professionals use, their opinions on them and how they test them using outcome measures. The survey included 25 questions which were assessed by external researchers and clinicians. The survey was also ethically approved. Overall, 60 people completed the survey. Occupational therapists and hand therapists responded the most and tended to be from the USA. Factors such as lack of awareness, access, and prescription methods were described as barriers to providing powered devices. In addition, the design of the device, function and relevance were concerns. 58% of respondents voted that outcome measures could also be improved. Therefore, prescribers and assessors of assistive devices do not have access to and awareness of current powered devices. Results also showed the function of these devices did not match respondents' opinions on the wearer's needs. The priority should be to make devices that are comfortable and easy to use. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/43790/33062 How To Cite: Galbert A, Buis A. Exploring factors for prescription and validation of actuated upper limb devices: A cross-sectional survey of allied health professionals. Canadian Prosthetics & Orthotics Journal. 2024; Volume 7, Issue 1, No.4. https://doi.org/10.33137/cpoj.v7i1.43790 Corresponding Author: Professor Arjan Buis, PhDDepartment of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, Scotland.E-Mail: arjan.buis@strath.ac.ukORCID ID: https://orcid.org/0000-0003-3947-293X

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,070
Score d'incertitude au seuil0,634

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,098
Tête enseignante GPT0,314
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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