Table 1.
Study | Study Design and Methodology | Participant Characteristics | Outcomes |
Baskar et al, 201523 | Quasi-experimental + interviews 11 older adults and 2 health professionals played the role of a fictitious persona while interacting with the agent for ~10 minutes followed by an interview. |
Age: N/A Gender: 55% female Race: N/A Baseline Clinical Characteristics: N/A |
|
Elmasri et al, 201624 | Quasi-experimental + interviews 17 participants interacted with the agent to explore their alcohol consumption for ~10 minutes followed by a survey and interview. |
Age: 18-25 Gender: 41% female Race: N/A Baseline Clinical Characteristics: <5 drinks/day |
|
Fitzpatrick et al, 201726 | RCT 70 participants were randomly assigned to Woebot or directed to a National Institute of Mental Health ebook for 2 weeks. Surveys were completed at baseline and post-intervention. |
Age: 18-28 Gender: 67% female Race: 79% Caucasian Baseline Clinical Characteristics: 46% had moderately-severe or severe PHQ-9 depression scores; 74% had severe GAD-7 anxiety scores |
|
Gaffney et al, 201325 | RCT 48 participants were randomly assigned to MYLO or ELIZA to discuss a current problem for ~20 minutes. Surveys were completed at baseline, post-intervention, and 2-week follow-up. |
Age: 18-32 Gender: 79% female Race: N/A Baseline Clinical Characteristics: N/A |
|
Kazemi et al, 201427 | Focus groups 26 participants were placed into one of four focus group sessions to determine their views of mHealth technology to deliver an alcohol-related intervention. |
Age: 18-20 Gender: 73% female Race: 70% Caucasian Baseline Clinical Characteristics: N/A |
|
Ly et al, 201728 | RCT + interviews 28 participants were randomly assigned to Shim or a wait list control group for 2 weeks. Surveys were completed at baseline and post-intervention. 9 participants from the intervention group were selected for a semi-structured interview. |
Age: 20-49 Gender: 54% female Race: N/A Baseline Clinical Characteristics: N/A |
|
Schroeder et al, 201829 | RCT 84 participants were randomized into two messaging groups (semi-personalized messages or non-personalized messages). Participants completed weekly surveys over the 4-week study. |
Age: 18-63 Gender: 89% female Race: N/A Baseline Clinical Characteristics: 83% had an anxiety disorder on the Overall Anxiety Severity and Impairment Scale; 68% had moderate to severe range of depression on PHQ-9 |
|
Stein et al, 201730 | Quasi-experimental 159 participants interacted with Lark for up to 16 weeks followed by a survey. |
Age: 18-76 Gender: 75% female Race: N/A Baseline Clinical Characteristics: BMI>25kg/m2 |
|
Tsiourti et al, 201431 | Focus group + interviews 20 older adults and 14 health professionals participated in two focus groups and an interview to assess acceptance and expectations. |
Age: 65-92 Gender: 65% female Race: N/A Baseline Clinical Characteristics: N/A |
|
van Heerden et al, 201732 | Quasi-experimental + interviews 10 Participants interacted with Lwazi/Nolwazi for ~25 minutes and provided feedback. |
Age: 30 (average) Gender: 50% female Race: N/A Baseline Clinical Characteristics: N/A |
|
Wang et al, 201833 | Quasi-experimental 401 participants were placed into WeChat groups with an agent or received smoking cessation tips over the 8-week study. Participants completed weekly surveys. |
Age: 33 (average) Gender: 40% female Race: N/A Baseline Clinical Characteristics: Smoked in the past 7 days |
|
Watson et al, 201234 | RCT 70 participants were given a pedometer and randomly assigned to a conversational agent or access to website for 12 weeks. Surveys were completed at baseline and post-intervention. |
Age: 42 (average) Gender: 84% female Race: 76% Caucasian Baseline Clinical Characteristics: BMI between 25-35kg/m2 |
|
*Abbreviations: N/A: data not available in manuscript; RCT: randomized controlled trial; BMI: body mass index