Evidence map›Paper›PMID 42193631›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

"I Don't Trust AI": A Generic Qualitative Analysis of College-Aged Mental Health Clients' Perceptions of Artificial Intelligence Used in Mental Health Counseling.

Daniel Bates, Carly Antor, Paige Kammeyer, William W Lorey, Timothy J Hakenewerth

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daniel BatesPsychology and Counseling Department, Truman State University, Kirksville, MO 63501, USA.ORCID 0000-0003-0964-4892
Carly AntorPsychology and Counseling Department, Truman State University, Kirksville, MO 63501, USA.
Paige KammeyerPsychology and Counseling Department, Truman State University, Kirksville, MO 63501, USA.
William W LoreyPsychology and Counseling Department, Truman State University, Kirksville, MO 63501, USA.ORCID 0009-0005-2637-9252
Timothy J HakenewerthCounseling and Social Work, University of Illinois Springfield, Springfield, IL 62703, USA.ORCID 0000-0001-8558-9894

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This qualitative study examined college-aged client perceptions of artificial intelligence (AI) in counseling services. AI technologies are beginning to appear in mental health treatment; it is important to understand client voices and perceptions. A generic qualitative descriptive design was used. Fourteen participants with recent counseling experience were recruited through purposive sampling from university channels. Data was collected via open-ended survey questions and analyzed using a six-phase reflexive thematic analysis. Trustworthiness was established through multiple strategies including peer debriefing, audit trails, reflexivity practices, and prolonged engagement with data. Six major themes emerged: (1) conditional acceptance of AI for non-clinical tasks, (2) concerns about data security and privacy, (3) valuing the human core of counseling, (4) preference for human judgment in crisis situations, (5) expectation of informed consent and transparency, and (6) cautious optimism contingent on evidence and safeguards. Findings suggest that AI implementation in counseling should follow an adjunctive rather than replacement model, with careful attention to maintaining therapeutic alliance and protecting client privacy. Implications for counseling practice, training, and policy development are discussed.

Indexed as

artificial intelligenceclient perspectivescounselingmental health technologyqualitative research

Identifiers

PMID42193631
PMCPMC13203814

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.