Evidence map›Paper›PMID 41071404›Full record

ReviewJournal of clinical psychology in medical settings2025

Artificial Intelligence in and Beyond Healthcare Psychology.

Dong Y Han

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of clinical psychology in medical settings, 2025. 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

1 author.

Dong Y HanDepartments of Neurology, Neurosurgery, and Physical Medicine & Rehabilitation, University of Kentucky College of Medicine, Lexington, KY, United States. d.han@uky.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence (AI) has been developed through interdisciplinary efforts since the 1940s, but generative AI and Large Language Models (LLMs) gained unprecedented attention with the launch of ChatGPT by OpenAI in late 2022. As these AI tools have become globally ubiquitous, significant implications arise for clinicians within and beyond healthcare settings. The simulation or emulation of human intelligence through coded heuristics now permeates clinical domains, creating new opportunities alongside ethical challenges that require careful exploration. For healthcare psychologists, regardless of specialty, it has become a priority to remain at the forefront of these technological advances. This includes developing literacy not only in psychological emulation software but also in the rapidly growing hardware that supports AI. Well-informed clinicians must act as responsible stewards of this advancing technology and its application in healthcare. These responsibilities must be approached through the lens of both existing and evolving ethical standards in human psychology. Although these tasks may seem daunting, the urgency, opportunities, and necessity for healthcare psychologists to engage thoughtfully with AI are clear. This engagement ensures that patient care benefits from innovation while upholding ethical principles. Said opportunities and the urgency for healthcare psychologists are discussed.

Indexed as

Artificial IntelligencePsychology, ClinicalHumansAIArtificial intelligenceClinical psychologyMental healthNeuroethics

Identifiers

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.