Evidence map›Paper›PMID 42814992›Full record

ArticleJMIR AI2026

Navigating AI in Mental Health Care and Psychotherapy: Proposing the GUIDE Framework.

Grant H Brenner, Timothy Gutwald, Jacqueline Ourman, Rachel Wood

Abstract read
In one paragraph

Article in JMIR AI, 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

4 authors.

Grant H BrennerBrighter NeuroTherapeutics, New York, NY, United States.ORCID https://orcid.org/0009-0005-6498-9529
Timothy GutwaldElevare Law, Richmond, VA, United States.ORCID https://orcid.org/0009-0001-3769-5323
Jacqueline OurmanValues Aligned Therapy, New York, NY, United States.ORCID https://orcid.org/0009-0009-4824-1827
Rachel WoodAI Mental Health Collective, Colorado Springs, CO, United States.ORCID https://orcid.org/0009-0002-2312-309X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI is already in the mental health consulting room, whether clinicians invite it or not. OpenAI reports more than 800 million regular users of ChatGPT and more than 40 million people turning to the platform daily for health questions, yet the evidence remains limited on the clinical efficacy of large language model-based mental health chatbots. Professional guidance and regulation remain fragmented. Clinicians are therefore practicing in a gap between a patient reality that cannot be ignored and a professional infrastructure not yet built. We argue that neither enthusiastic adoption nor principled abstention is sufficient in the current environment. The clinician who refuses to discuss clinically material patient AI use is not preventing that use; they may lose visibility into a factor materially affecting the therapeutic process. The clinician who adopts AI without structured evaluation exposes patients and practice to avoidable harm. The stance we propose is structured harm reduction within the therapeutic relationship: inviting discussion at intake, integrating material use into case formulation, discussing benefits and limits, establishing crisis boundaries, monitoring throughout treatment, and addressing termination planning. Clinician-initiated use is a separate choice requiring evidence, consent when applicable, privacy safeguards, and accountability. We propose a phased clinical framework spanning preintake to termination anchored by the gather, understand, inform, document, and evaluate (GUIDE) mnemonic as an operational wrapper for daily practice. GUIDE and the phased framework are conceptual, unvalidated proposals. We distinguish ethical recommendations, established legal duties, and predicted standards; scope the legal discussion to the United States; integrate equity and subgroup performance; and offer proportionate implementation. The patients who seek care in an AI-saturated world deserve professional infrastructure capable of holding innovation and patient protection in informed balance.

Indexed as

AIartificial intelligenceclinical ethicsclinical frameworkdigital therapeuticsharm reductioninformed consentlarge language modelsmental healthpsychotherapyshared decision-making

Identifiers

PMID42814992
PMCPMC13669700

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.