This paper is in the following e-collection/theme issue:

Chatbots and Conversational Agents (188) Usability and Technology Use Studies with Elder Subjects (100)

Published on in Vol 22 , No 5 (2020) :May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16794, first published .
Usability, Acceptability, and Effectiveness of Web-Based Conversational Agents to Facilitate Problem Solving in Older Adults: Controlled Study

Usability, Acceptability, and Effectiveness of Web-Based Conversational Agents to Facilitate Problem Solving in Older Adults: Controlled Study

Usability, Acceptability, and Effectiveness of Web-Based Conversational Agents to Facilitate Problem Solving in Older Adults: Controlled Study

Authors of this article:

Matthew Russell Bennion 1 Author Orcid Image ;   Gillian E Hardy 1 Author Orcid Image ;   Roger K Moore 2 Author Orcid Image ;   Stephen Kellett 1 Author Orcid Image ;   Abigail Millings 1 Author Orcid Image
Article Authors Cited by (15) Tweetations (46) Metrics

Journals

  1. Simmonds-Buckley M, Bennion M, Kellett S, Millings A, Hardy G, Moore R. Acceptability and Effectiveness of NHS-Recommended e-Therapies for Depression, Anxiety, and Stress: Meta-Analysis. Journal of Medical Internet Research 2020;22(10):e17049 View
  2. Mansell W. The perceptual control model of psychopathology. Current Opinion in Psychology 2021;41:15 View
  3. He Y, Yang L, Li T, Qian C, Su Z, Zhang Q, Hou X. Conversational agent interventions for mental health problems: a systematic review and meta-analysis of randomized controlled trials (Preprint). Journal of Medical Internet Research 2022 View
  4. He Y, Yang L, Zhu X, Wu B, Zhang S, Qian C, Tian T. Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(11):e40719 View
  5. To Q, Green C, Vandelanotte C. Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study. JMIR mHealth and uHealth 2021;9(11):e28577 View
  6. Boggiss A, Consedine N, Hopkins S, Silvester C, Jefferies C, Hofman P, Serlachius A. A Self-Compassion Chatbot to Improve the Wellbeing of Adolescents with Type 1 Diabetes During the COVID-19 Pandemic: What do Adolescents and their Healthcare Professionals Want? (Preprint). JMIR Diabetes 2022 View
  7. Gudala M, Ross M, Mogalla S, Lyons M, Ramaswamy P, Roberts K. Benefits of, Barriers to, and Needs for an Artificial Intelligence–Powered Medication Information Voice Chatbot for Older Adults: Interview Study With Geriatrics Experts. JMIR Aging 2022;5(2):e32169 View
  8. Danieli M, Ciulli T, Mousavi S, Riccardi G. A Conversational Artificial Intelligence Agent for a Mental Health Care App: Evaluation Study of Its Participatory Design. JMIR Formative Research 2021;5(12):e30053 View
  9. Smrke U, Plohl N, Mlakar I. Aging Adults’ Motivation to Use Embodied Conversational Agents in Instrumental Activities of Daily Living: Results of Latent Profile Analysis. International Journal of Environmental Research and Public Health 2022;19(4):2373 View
  10. Budler L, Gosak L, Stiglic G. Review of artificial intelligence‐based question‐answering systems in healthcare. WIREs Data Mining and Knowledge Discovery 2023;13(2) View
  11. Astell A, Andrews J, Bennion M, Clayton D. Technology for Healthy Aging and Wellbeing: Co-producing Solutions. Frontiers in Psychology 2021;12 View
  12. Martinengo L, Jabir A, Goh W, Lo N, Ho M, Kowatsch T, Atun R, Michie S, Tudor Car L. Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory. Journal of Medical Internet Research 2022;24(10):e39243 View

Books/Policy Documents

  1. Liu Y, Verma R, Theng Y. Aging. View
  2. Bastardo R, Pavão J, Rocha N. Information Systems and Technologies. View