ArticleJMIR formative research2026
Real-World Use of a Mental Health AI Companion: Multiple Methods Study.
Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid acceleration of large language models (LLMs) creates opportunities to expand the accessibility of mental health support; however, general artificial intelligence (AI) tools lack safety guardrails, evidence-based practices, and medical regulation compliance, which may result in misinformation and failing to escalate care in crises. In contrast, Ebb, Headspace's conversational AI tool (CAI tool), was purpose-built by clinical psychologists and research experts using motivational interviewing techniques for subclinical guidance, incorporating clinically backed safety mechanisms.
objectiveThis study aimed to (1) understand Headspace members' sentiment toward AI and expectations for a mental health CAI tool, (2) evaluate real-world use of Headspace's CAI tool, and (3) understand how members perceive a CAI tool fitting into their mental health journey.
methodsThis was a multiple method study using three data sources including Headspace members: (1) cross-sectional survey (n=482) assessing demographics, AI use, and the Artificial Intelligence Attitude Scale-4 (AIAS-4); (2) real-world engagement descriptive analysis (n=393,969) assessing session and message counts, retention, and conversation themes; and (3) diary study (n=15) exploring the CAI tool's role within members' mental health journey. App engagement was compared between CAI tool 1.0 and CAI tool 2.0, where CAI tool 2.0 featured enhanced LLM conversational prompts, comprehensive memory, woven content recommendations, and more robust safety detection.
resultsWhile the majority of survey respondents used and would continue to use general AI tools, overall attitudes toward AI remained neutral (AIAS-4 mean 5.7, SD 2.2, range 1-10). Survey results suggest that members viewed the CAI tool as a guide to navigate to mental health resources and Headspace content and provide in-the-moment support. Members emphasized the need for data safety and ethics transparency, clinical guidelines structure, and for the CAI tool to be a resource in addition to human-delivered mental health care, not a replacement. Real-world CAI tool use showed strong engagement across 393,969 Headspace members. The product evolution to CAI tool 2.0 led to increased retention (77,894/153,249, 50.8% completed 2 sessions within 7 days vs 68,701/240,720, 28.5% for CAI tool 1.0) and higher positive conversation ratings (37,819/40,449, 93.5% vs 94,308/104,323, 90.4%). Retained CAI tool 2.0 users showed greater retention (6.1 sessions per user) compared to all CAI tool 2.0 users (2.9 sessions per user) and CAI tool 1.0 (2.4 sessions per user). Diary study results suggest that members imagined using the CAI tool when feeling stress or anxiety and during morning routines, commutes, or while winding down at night.
conclusionsResults emphasize the necessity of research-backed, purpose-built mental health AI products with minimum viable safeguards, including (1) transparent labeling of intended use, benefits, and limitations; (2) safety by design principles to monitor for overuse, detect risk, and flag needs for escalation; and (3) child and adolescent safeguards.
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