Evidence map›Paper›PMID 41490401›Full record

ArticleJMIR mental health2026

Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Health Care: Qualitative Study.

Kristin M Kostick-Quenet, Meghan E Hurley, Syed Ayaz, John D Herrington, Casey J Zampella, Julia Parish-Morris, Birkan Tunç, Gabriel Lázaro-Muñoz, Jennifer Blumenthal-Barby, Eric A Storch

Abstract read
In one paragraph

Article in JMIR mental health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Towards Human-Centered Digital Health Interventions.The Psychiatric clinics of North America · 2026
    Review
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

10 authors.

Kristin M Kostick-QuenetCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.ORCID https://orcid.org/0000-0003-2510-0174
Meghan E HurleyCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.ORCID https://orcid.org/0000-0002-0418-8691
Syed AyazCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.ORCID https://orcid.org/0009-0007-9186-4187
John D HerringtonDepartment of Child and Adolescent Psychiatry and Behavioral Sciences, Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-9720-3917
Casey J ZampellaDepartment of Child and Adolescent Psychiatry and Behavioral Sciences, Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-7973-8520
Julia Parish-MorrisDepartment of Child and Adolescent Psychiatry and Behavioral Sciences, Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0001-9633-2904
Birkan TunçDepartment of Child and Adolescent Psychiatry and Behavioral Sciences, Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-2294-4024
Gabriel Lázaro-MuñozDepartment of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States.ORCID https://orcid.org/0000-0003-1933-9453
Jennifer Blumenthal-BarbyCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States.ORCID https://orcid.org/0000-0003-1054-619X
Eric A StorchMenninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States.ORCID https://orcid.org/0000-0002-7631-3703

Funding

Ethical and Human Factors Impacting Successful Translation of Perceptual Computing to Improve Clinical CareR01TR004243 · NCATS · BAYLOR COLLEGE OF MEDICINE · PI HERRINGTON, JOHN DAVID, KOSTICK, KRISTIN MARIE · 2022 to 2025
$2.0M
NCATS NIH HHS R01 TR004243
6 · The paper itself

Abstract

backgroundComputer perception (CP) technologies-including digital phenotyping, affective computing, and related passive sensing approaches-offer unprecedented opportunities to personalize health care, especially mental health care, yet they also provoke concerns about privacy, bias, and the erosion of empathic, relationship-centered practice. At present, it remains elusive what stakeholders who design, deploy, and experience these tools in real-world settings perceive as the risks and benefits of CP technologies.

objectiveThis study aims to explore key stakeholder perspectives on the potential benefits, risks, and concerns associated with integrating CP technologies into patient care. A better understanding of these concerns is crucial for responding to and mitigating such concerns via design implementation strategies that augment, rather than compromise, patient-centered and humanistic care and associated outcomes.

methodsWe conducted in-depth, semistructured interviews with 102 stakeholders involved at key points in CP's development and implementation: adolescent patients (n=20) and their caregivers (n=20); frontline clinicians (n=20); technology developers (n=21); and ethics, legal, policy, or philosophy scholars (n=21). Interviews (~ 45 minutes each) explored perceived benefits, risks, and implementation challenges of CP in clinical care. Transcripts underwent thematic analysis by a multidisciplinary team; reliability was enhanced through double coding and consensus adjudication.

resultsStakeholders raised concerns across 7 themes: (1) Data Privacy and Protection (88/102, 86.3%); (2) Trustworthiness and Integrity of CP Technologies (72/102, 70.6%); (3) direct and indirect Patient Harms (65/102, 63.7%); (4) Utility and Implementation Challenges (60/102, 58.8%); (5) Patient-Specific Relevance (24/102, 23.5%); (6) Regulation and Governance (17/102, 16.7%); and (7) Philosophical Critiques of reductionism (13/102, 12.7%). A cross-cutting insight was the primacy of context and subjective meaning in determining whether CP outputs are clinically valid and actionable. Participants warned that without attention to these factors, algorithms risk misclassification and dehumanization of care.

conclusionsTo operationalize humanistic safeguards, we propose "personalized road maps": co-designed plans that predetermine which metrics will be monitored, how and when feedback is shared, thresholds for clinical action, and procedures for reconciling discrepancies between algorithmic inferences and lived experience. Road maps embed patient education, dynamic consent, and tailored feedback, thereby aligning CP deployment with patient autonomy, therapeutic alliance, and ethical transparency. This multistakeholder study provides the first comprehensive, evidence-based account of relational, technical, and governance challenges raised by CP tools in clinical care. By translating these insights into personalized road maps, we offer a practical framework for developers, clinicians, and policy makers seeking to harness continuous behavioral data while preserving the humanistic core of care.

Indexed as

HumanismStakeholder ParticipationAdolescentAdultFemaleHumansMaleQualitative Researchaffective computingartificial intelligencecomputer perceptionconsentcontextdigital phenotypingethicshumanistic carestakeholder engagement

Identifiers

PMID41490401
PMCPMC12817037

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.