The social robot will see you now: patient acceptability of social robots in managing heart failure
Notice bibliographique
Résumé
Abstract Background Social robots (SRs) are artificial agents embodied with human or animal features that can be embedded with technology to facilitate the remote monitoring of patients’ physiological and psychological health, aid with activities of daily living, provide rehabilitation services, and offer companionship. SRs may offer opportunities for improving the management of heart failure (HF), as these patients experience fluctuating and unpredictable functional impairment, and many are elderly and live alone (or with aging caregivers), with limited social support. It is not yet known whether patients with HF would be accepting of such technologies, which would ultimately influence their willingness to use SRs. Acceptability data are warranted to optimize the successful implementation of future social robotic interventions for patients with HF. Purpose The aim of this early-phase study was to quantify patients’ acceptability of SRs and to identify the sociodemographic and clinical characteristics (i.e., NYHA class) that are linked to patients’ acceptability. Methods Patients diagnosed with HF (NYHA class II, III, and IV) were recruited from a large cardiac teaching hospital. After viewing three videos profiling SRs, patients provided sociodemographic and clinical information, ranked their desired SR capabilities, and completed the validated Unified Theory of Acceptance and Use of Technology (UTAUT) 7-point Likert self-report questionnaire. Descriptive statistics were used to describe the sample, levels of acceptance, and desired capabilities of SRs. Pearson correlations and analysis of variance were used to determine associations between sociodemographic characteristics, NYHA class, and acceptance based on the UTAUT scale. Results The sample consisted of 81 patients with HF (M age= 65 years; 32% female; 87% white; 69.1% married or common-law; 25.9% rural residence; 79% NYHA class II and 21% NYHA class III). Scores on the UTAUT indicated moderate acceptance of SRs (M=4.5/7; SD=1.9); 42.1% of patients indicated that they would use an SR if it were available, whereas 21% noted they would not; 44.4% reported that a SR would help to improve their health, whereas 22.2% believed that an SR would not lead to improvements in their health. Acceptance rates did not differ significantly by age, sex, ethnicity, education, marital status, remoteness, or NYHA class. The most desired capabilities of SRs were monitoring blood pressure, heart rhythm, and vital signs. The least desired were administering IV medications, performing nasal or oral swabs, or assisting with eating, bathing, or dressing. Conclusion The adoption of SRs in patients’ homes to support HF-management is a potentially acceptable option for patients with HF. Acceptance rates are not linked to key sociodemographic factors; it is possible that other pertinent clinical, psychosocial, or environmental factors are more important drivers of SR acceptance, but this remains to be tested.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».