Journal of the American Medical Informatics Association· 2018Q1· Derleme
Sağlık hizmetlerinde konuşma ajanları: sistematik bir derleme
Conversational agents in healthcare: a systematic review
- 1.344atıf
- Q1SCImago
- 2018yıl
Kısa özet
Sağlık amaçlı konuşma ajanlarına ilişkin 17 çalışmanın (14 ajan) sistematik incelemesi, çoğunlukla yarı-deneysel tasarımlarla değerlendirildiğini ve yalnızca bir RKÇ'nin depresyon belirtilerinde anlamlı bir azalma gösterdiğini (etki büyüklüğü d=0.44, p=.04) ortaya koymuştur.
Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.
Ana noktalar
- Derlemeye 17 makale ve 14 konuşma ajanı dahil edildi.
- Ajanların çoğu sonlu durum veya çerçeve tabanlı diyalog yönetimi kullandı.
- Ajanların yarısı tüketici öz bakım görevlerini destekledi.
- Yalnızca bir RKÇ, depresyon belirtilerinde anlamlı bir azalma gösterdi (d=0.44, p=.04).
- Hasta güvenliği nadiren değerlendirildi.
Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.
Özet (abstract)
Objective: Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes. Methods: We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen's kappa measured inter-coder agreement. Results: The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies. Conclusions: The use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental designs and standardized reporting. Protocol Registration: The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.
Yazarların özeti; kaynağından alınmıştır. Journal of the American Medical Informatics Association, 2018 · DOI ↗
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Alan: Uygulamalı Psikoloji
Applied PsychologyPsychology