Background Individuals living with long-term physical health conditions frequently experience co-occurring mental health problems. This comorbidity has a significant impact on an individual’s levels of emotional distress, health outcomes, and associated health care utilization. As health care services struggle to meet demand and care increasingly moves to the community, digital tools are being promoted to support patients to self-manage their health. One such technology is the autonomous virtual agent (chatbot, conversational agent), which uses artificial intelligence (AI) to process the user’s written or spoken natural language and then to select or construct the corresponding appropriate responses. Objective This study aimed to co-design the content, functionality, and interface modalities of an autonomous virtual agent to support self-management for patients with an exemplar long-term condition (LTC; chronic pulmonary obstructive disease [COPD]) and then to assess the acceptability and system content. Methods We conducted 2 co-design workshops and a proof-of-concept implementation of an autonomous virtual agent with natural language processing capabilities. This implementation formed the basis for video-based scenario testing of acceptability with adults with a diagnosis of COPD and health professionals involved in their care. Results Adults (n=6) with a diagnosis of COPD and health professionals (n=5) specified 4 priority self-management scenarios for which they would like to receive support: at the time of diagnosis ( information provision ), during acute exacerbations ( crisis support ), during periods of low mood ( emotional support ), and for general self-management ( motivation ). From the scenario testing, 12 additional adults with COPD felt the system to be both acceptable and engaging, particularly with regard to internet-of-things capabilities. They felt the system would be particularly useful for individuals living alone. Conclusions Patients did not explicitly separate mental and physical health needs, although the content they developed for the virtual agent had a clear psychological approach. Supported self-management delivered via an autonomous virtual agent was acceptable to the participants. A co-design process has allowed the research team to identify key design principles, content, and functionality to underpin an autonomous agent for delivering self-management support to older adults living with COPD and potentially other LTCs.

Background The usability and effectiveness of conversational agents (chatbots) that deliver psychological therapies is under-researched. Objective This study aimed to compare the system usability, acceptability, and effectiveness in older adults of 2 Web-based conversational agents that differ in theoretical orientation and approach. Methods In a randomized study, 112 older adults were allocated to 1 of the following 2 fully automated interventions: Manage Your Life Online (MYLO; ie, a chatbot that mimics a therapist using a method of levels approach) and ELIZA (a chatbot that mimics a therapist using a humanistic counseling approach). The primary outcome was problem distress and resolution, with secondary outcome measures of system usability and clinical outcome. Results MYLO participants spent significantly longer interacting with the conversational agent. Posthoc tests indicated that MYLO participants had significantly lower problem distress at follow-up. There were no differences between MYLO and ELIZA in terms of problem resolution. MYLO was rated as significantly more helpful and likely to be used again. System usability of both the conversational agents was associated with helpfulness of the agents and the willingness of the participants to reuse. Adherence was high. A total of 12% (7/59) of the MYLO group did not carry out their conversation with the chatbot. Conclusions Controlled studies of chatbots need to be conducted in clinical populations across different age groups. The potential integration of chatbots into psychological care in routine services is discussed.

ObjectiveTo document the range of web and smartphone apps used and recommended for stress, anxiety or depression by the National Health Service (NHS) in England.DesignThe study was conducted using Freedom of Information (FOI) requests and systematic website searches.Data sourcesData were collected via FOI requests to NHS services between 13 February 2015 and 31 March 2015, and searches conducted on NHS apps library websites between 26 March 2015 and 2 November 2015.Data collection/extraction methodsData were compiled from responses to: (1) FOI requests sent to all Improving Access to Psychological Therapies (IAPT) services and NHS Mental Health Trusts in England and (2) NHS apps library search results.ResultsA total of 61 (54.95%) out of the then 111 IAPT service providers responded, accounting for 191 IAPT services, and all 51 of the then NHS Mental Health Trusts responded. The results were that 13 different web apps and 35 different smartphone apps for depression, anxiety or stress were available through either referral services or the online NHS Apps Libraries. The apps used and recommended vary by area and by point of access (online library/IAPT/trust).ConclusionsFuture research is required to establish the evidence base for the apps that are being used in the NHS in England. There is a need for service provision to be based on evidence and established guidelines.

ObjectiveTo document the quality of web and smartphone apps used and recommended for stress, anxiety or depression by examining the manner in which they were developed.DesignThe study was conducted using a survey sent to developers of National Health Service (NHS) e-therapies.Data sourcesData were collected via a survey sent out to NHS e-therapy developers during October 2015 and review of development company websites during October 2015.Data collection/extraction methodsData were compiled from responses to the survey and development company websites of the NHS e-therapies developers.ResultsA total of 36 (76.6%) out of the 48 app developers responded. One app was excluded due to its contact details and developer website being unidentifiable. Data from the missing 10 was determined from the app developer’s website. The results were that 12 out of 13 web apps and 20 out of 34 smartphone apps had clinical involvement in their development. Nine out of 13 web apps and nine out of 34 smartphone apps indicated academic involvement in their development. Twelve out of 13 web apps and nine out of 34 smartphone apps indicated published research evidence relating to their app. Ten out of 13 web apps and 10 out of 34 smartphone apps indicated having other evidence relating to their app. Nine out of 13 web apps and 19 out of 34 smartphone apps indicated having a psychological approach or theory behind their app.ConclusionsAs an increasing number of developers are looking to produce e-therapies for the NHS it is essential they apply clinical and academic best practices to ensure the creation of safe and effective apps.

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