Characteristics, Barriers, and Facilitators of Virtual Decision-Making Capacity Assessments During the COVID-19 Pandemic: Online Survey
Notice bibliographique
Résumé
BACKGROUND: With a growing older adult population, the number of persons with dementia is expected to rise. Consequently, the number of persons needing decision-making capacity assessments (DMCA) will increase. The COVID-19 pandemic has impacted how we deliver patient care including DMCAs with a much more rapid shift to virtual assessments. Virtual DMCAs offer patients and health care professionals distinct advantages over in-person delivery by improving reach, access, and timely provision of health care. However, questions have arisen as to whether DMCAs can be effectively conducted virtually. OBJECTIVE: This study aimed to determine the characteristics, barriers, and facilitators of conducting virtual DMCA during the COVID-19 pandemic. METHODS: We conducted an online survey among health care providers who perform DMCAs in Alberta from March 2022 to February 2023. The survey consisted of 25 questions on demographics, preferences, and experience in conducting DMCAs virtually, and risks and barriers to doing virtual DMCAs. The data were analyzed using descriptive statistics. RESULTS: There were 31 respondents with a mean age of 51.1 (SD 12.7) years. The respondents consisted of physicians (45.2%, 14/31), occupational therapists (29%, 9/31), and social workers (16.1%, 5/31), with a majority (93.6%, 29/31) based in Edmonton. The mean number of years of experience conducting DMCAs was 12.3 (SD 10.7), with a median of 8 DMCAs (IQR 18.5) conducted per year. Most respondents conduct capacity interviews, with a majority (55.2%, 16/29) being associated primarily with acute care services. Furthermore, 54.8% (17/31) were interested in conducting DMCAs virtually; however, only 25.8% (8/31) had administered DMCAs virtually. Barriers and facilitators to virtual DMCAs relate to patients' characteristics and environment (such as communication difficulties, hearing or visual impairment, language barriers, ease of use of technology, or cognitive impairment), technology and technical support (need for technical support in both the client's and assessor's sides, the unreliability of internet connection in rural settings, and the availability of high-fidelity equipment), and assessors' ability to perform DMCA's virtually (ability to observe body language, interact with the client physically when needed, and build rapport can all be affected when conducting a DMCA virtually). In terms of implications for clinical practice, it is recommended that the patient or caregiver be familiar with technology, have a stable internet connection, use a private room, not be recorded, use a standardized assessment template, and have a backup plan in case of technical difficulties. CONCLUSIONS: Conducting DMCAs virtually is a relatively infrequent undertaking. Barriers and facilitators to adequate assessment need to be addressed given that virtual assessments are time-saving and expand reach.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 | 0,001 |
| 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 ».