PreprintCited by 715Digital Mental Health InterventionsAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesMental Health Treatment and Access

Using Psychological Artificial Intelligence (Tess) to Relieve Symptoms of Depression and Anxiety: Randomized Controlled Trial (Preprint)

Open access
Fulmer, Russell, Joerin, Angela, Gentile, Breanna, Lakerink, Lysanne, Rauws, Michiel·2018·JMIR Mental Health

Preprint — published as 10.2196/mental.9782 · Paper page

Abstract

BACKGROUND: Students in need of mental health care face many barriers including cost, location, availability, and stigma. Studies show that computer-assisted therapy and 1 conversational chatbot delivering cognitive behavioral therapy (CBT) offer a less-intensive and more cost-effective alternative for treating depression and anxiety. Although CBT is one of the most effective treatment methods, applying an integrative approach has been linked to equally effective posttreatment improvement. Integrative psychological artificial intelligence (AI) offers a scalable solution as the demand for affordable, convenient, lasting, and secure support grows. OBJECTIVE: This study aimed to assess the feasibility and efficacy of using an integrative psychological AI, Tess, to reduce self-identified symptoms of depression and anxiety in college students. METHODS: In this randomized controlled trial, 75 participants were recruited from 15 universities across the United States. All participants completed Web-based surveys, including the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and Positive and Negative Affect Scale (PANAS) at baseline and 2 to 4 weeks later (T2). The 2 test groups consisted of 50 participants in total and were randomized to receive unlimited access to Tess for either 2 weeks (n=24) or 4 weeks (n=26). The information-only control group participants (n=24) received an electronic link to the National Institute of Mental Health’s (NIMH) eBook on depression among college students and were only granted access to Tess after completion of the study. RESULTS: A sample of 74 participants completed this study with 0% attrition from the test group and less than 1% attrition from the control group (1/24). The average age of participants was 22.9 years, with 70% of participants being female (52/74), mostly Asian (37/74, 51%), and white (32/74, 41%). Group 1 received unlimited access to Tess, with daily check-ins for 2 weeks. Group 2 received unlimited access to Tess with biweekly check-ins for 4 weeks. The information-only control group was provided with an electronic link to the NIMH’s eBook. Multivariate analysis of covariance was conducted. We used an alpha level of .05 for all statistical tests. Results revealed a statistically significant difference between the control group and group 1, such that group 1 reported a significant reduction in symptoms of depression as measured by the PHQ-9 (P=.03), whereas those in the control group did not. A statistically significant difference was found between the control group and both test groups 1 and 2 for symptoms of anxiety as measured by the GAD-7. Group 1 (P=.045) and group 2 (P=.02) reported a significant reduction in symptoms of anxiety, whereas the control group did not. A statistically significant difference was found on the PANAS between the control group and group 1 (P=.03) and suggests that Tess did impact scores. CONCLUSIONS: This study offers evidence that AI can serve as a cost-effective and accessible therapeutic agent. Although not designed to appropriate the role of a trained therapist, integrative psychological AI emerges as a feasible option for delivering support. CLINICALTRIAL: International Standard Randomized Controlled Trial Number: ISRCTN61214172; https://doi.org/10.1186/ISRCTN61214172.

AI snapshot

Written from the paper’s full text.

TL;DR

In a randomized controlled trial with 74 college students, the integrative psychological AI chatbot Tess reduced anxiety symptoms in both 2-week and 4-week access groups and reduced depression symptoms in the 2-week daily-check-in group compared with an information-only control. Tess users reported higher satisfaction and engagement, but the study used a nonclinical sample, had small groups, and did not collect follow-up data.

Key findings

  • Depression (PHQ-9): a statistically significant difference was found between the control group and group 1 (Tess for 2 weeks with daily check-ins), with group 1 showing reduced depressive symptoms while the control group’s symptoms increased; the Results section reports P=.02, while the Abstract reports P=.03.
  • Anxiety (GAD-7): significant differences were found between the control group and both Tess groups, with group 1 at P=.045 and group 2 at P=.02 showing reduced anxiety symptoms, whereas the control group did not.
  • PANAS: a statistically significant difference was found between the control group and group 1 (P=.03), suggesting Tess impacted scores.
  • Satisfaction and engagement: 86% (43/50) of Tess participants were overall satisfied versus 60% (14/24) of controls; 80% (40/50) learned something new from Tess versus 43% (10/24) from the eBook; test groups exchanged 14,238 messages total, with group 1 averaging 283 messages (SD 147.6) and group 2 averaging 286 messages (SD 104.6). The reported effect size for depression was Cohen d=0.68.

Methods

  • Randomized controlled trial: 75 participants signed consent and 74 completed; participants were recruited from 15 universities across the United States and randomized to an information-only control group (NIMH eBook; n=24), Tess group 1 (2 weeks unlimited access with daily check-ins; n=24), or Tess group 2 (4 weeks unlimited access with biweekly check-ins; n=26).
  • Measures: Web-based surveys including PHQ-9, GAD-7, and PANAS at baseline and 2 to 4 weeks later (T2); baseline mean PHQ-9 scores were 8.17 (control), 6.67 (group 1), and 7.04 (group 2), and baseline mean GAD-7 scores were 9.46, 6.71, and 7.5, respectively.
  • Analysis: SPSS was used; the paper describes a multivariate analysis of covariance in the Abstract and a multivariate analysis of covariance/MANOVA in the Methods, with an alpha level of .05 and post hoc Tukey tests.

Limitations

  • The paper states that generalizability is limited because socioeconomic status was not formally assessed, recruitment via social media may not represent all Tess users, group sizes were limited, no follow-up data assessed whether benefits were sustained, and the nonclinical sample had low baseline depression and anxiety scores, requiring further research in clinical populations.
  • The paper also states that the control group experienced a slight increase in anxiety and depression symptoms, suggesting the eBook was not sufficient support; emotion identification was limited to language; and system errors related to natural language processing or emotion mismatch could not be addressed during the study.
  • Evident from the text: the condition was not masked for service providers (Tess), and the paper reports inconsistent P values for the PHQ-9 result (Abstract P=.03 vs Results P=.02).

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.2196/preprints.9782

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 6 cited sources checked · 0 supported · 0 flagged

  • Finding

    Tess also affected PANAS scores relative to the control group.

    “A statistically significant difference was found on the PANAS between the control group and group 1 (P=.03) and suggests that Tess did impact scores.”
    Quote in the paperNot yet classified
  • Finding

    The study found a significant reduction in depression symptoms for the 2-week Tess group compared with the control group.

    “Results revealed a statistically significant difference between the control group and group 1, such that group 1 reported a significant reduction in symptoms of depression as measured by the PHQ-9 (P=.03), whereas those in the control group did not.”
    Quote in the paperNot yet classified
  • Finding

    The authors conclude that AI can be a cost-effective and accessible therapeutic agent and that integrative psychological AI is a feasible option for delivering support.

    “This study offers evidence that AI can serve as a cost-effective and accessible therapeutic agent. Although not designed to appropriate the role of a trained therapist, integrative psychological AI emerges as a feasible option for delivering support.”
    Quote in the paperNot yet classified
  • Finding

    Both Tess test groups showed significant reductions in anxiety symptoms compared with the control group.

    “A statistically significant difference was found between the control group and both test groups 1 and 2 for symptoms of anxiety as measured by the GAD-7. Group 1 (P=.045) and group 2 (P=.02) reported a significant reduction in symptoms of anxiety, whereas the control group did not.”
    Quote in the paperNot yet classified
  • Finding

    The results section reports that 74 participants completed the study and attrition was 0% in the test group and less than 1% in the control group.

    “A sample of 74 participants completed this study with 0% attrition from the test group and less than 1% attrition from the control group (1/24).”
    Quote in the paperNot yet classified

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Studies that ranked high for selective reporting bias tended to report only user satisfaction data and treatment adherence, despite their methods considering collection and assessment of psychiatric scale data and other effectiveness outcomes.

    “The studies that ranked high for selective reporting bias tended to report only user satisfaction data and treatment adherence, despite their methods considering the collection and assessment of psychiatric scale data and other effectiveness outcomes (29, 76, 79, 85–88, 92).”

    From Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review (2024) · cites this paper as [76]

    Split into 2 atoms — 0 confirmed, 1 partially supported, 1 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured
  • 12 of the included studies presented data on treatment dropout; online or remote psychotherapy interventions reported a dropout rate between 0% and 61%, psychoeducation between 4% and 60%, and no intervention between 5% and 34%.

    “12 of the included studies (41, 73–83) presented data on treatment dropout, online or remote psychotherapy interventions reported a dropout rate between 0% and 61%, psychoeducation a dropout rate between 4% and 60% and no intervention a dropout rate between 5% and 34%.”

    From Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review (2024) · cites this paper as [76]

    Methods > Ethics and Informed Consent reports 0% attrition in the Tess intervention groups and one dropout among 24 participants in the eBook control group, approximately 4%. This trial provides dropout data that could contribute to the cited ranges, but it does not report results for 12 studies or establish the full ranges for psychotherapy, psychoeducation, and no intervention. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • A minority of users, around 30% or less, thought that the tool did not understand them or found their interactions unhelpful or bothersome.

    “They also reported that a minority of users, around 30% or less, thought that the tool did not understand them or found their interactions unhelpful or bothersome (73, 74, 76–78, 80–82, 84, 90).”

    From Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review (2024) · cites this paper as [76]

    The Results > Analysis section reports that 11 of 50 Tess participants (22%) said the bot failed to understand some responses or became confused. It also reports content problems, but does not establish that 30% or fewer found their interactions unhelpful or bothersome; those descriptions are not reported as measured outcomes. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Previous systematic reviews and meta-analyses have shown significant reductions in symptoms for depression and other mental disorders while using mental health apps, some of which included CBT or gamification elements.

    “Additionally, previous systematic reviews and meta-analyses have shown significant reductions in symptoms for depression and other mental disorders while using mental health apps, some of which included cognitive behavioral therapy (CBT) or gamification elements [26,36,37,40,41].”

    From Examining the effectiveness of gamification in mental health apps for depression: Systematic review and meta-analysis (2021) · cites this paper as [36]

    The Introduction (Background; page unavailable) says CBT-delivering psychological AI has reduced depression and anxiety symptoms, and the Discussion (Comparison With Prior Work; page unavailable) reports significant reductions with Tess. But this source is a randomized trial, not a systematic review or meta-analysis of mental health apps, and the cited passages do not establish the claim about gamification elements. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • When used enough, chatbots can have positive mental health outcomes.

    “When used enough, there can be positive mental health outcomes16–19.”

Cites

Flagged first, then by citations

1 of the 41 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [28]Pichot T Dolan Y Solution-Focused Brief Therapy: Its Effective Use in Agency Settings. Haworth marriage and the family 2003 New York Routledge

Cited by

Sorted by citations

Authors
Fulmer, R., Joerin, A., Gentile, B., Lakerink, L., & Rauws, M.
Affiliations
  • Northwestern University (US)
  • xAI (United States) (US)
  • Saxion (NL)
Corresponding author
Fulmer, Russell
Venue
JMIR Mental Health
Published
2018-02-28
Volume
5
Issue
4
Pages
e64-e64
ISSN
2368-7959 (ISSN-L)
OpenAlex
W2889335577
Cited by
715
References
41
Citations by year
2026: 138 · 2025: 161 · 2024: 114 · 2023: 104 · 2022: 68 · 2021: 61 · 2020: 51 · 2019: 18
FWCI
41.30
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Mental Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
Keywords
depressive symptoms, anxiety symptoms, university students, cognitive behavioral therapy, digital mental health interventions, PHQ-9, GAD-7, PANAS, feasibility, treatment efficacy, student mental health

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