Evidence map›Paper›PMID 42507998›Full record

ArticleJournal of medical Internet research2026

Artificial Intelligence in Spiritual Care: Modified Delphi Study.

Fabian Winiger, C Estelle Smith, Shadi Nourriz, Csaba Szilagyi, Annette Haußmann

Abstract read
In one paragraph

Article in Journal of medical Internet research, 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.

Fabian WinigerURPP Digital Religion(s), University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-3799-4523
C Estelle SmithDepartment of Computer Science, Colorado School of Mines, Golden, CO, United States.ORCID https://orcid.org/0000-0002-4981-7105
Shadi NourrizDepartment of Computer Science, Colorado School of Mines, Golden, CO, United States.ORCID https://orcid.org/0009-0004-1873-6750
Csaba SzilagyiTransforming Chaplaincy, Rush University, Chicago, IL, United States.ORCID https://orcid.org/0000-0002-0413-3025
Annette HaußmannFaculty of Theology, Heidelberg University, Heidelberg, Baden-Wurttemberg, Germany.ORCID https://orcid.org/0000-0003-1506-6822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpiritual care providers are increasingly challenged to address the introduction of AI within the ethical, theological, and organizational bounds of their employers and religious or worldview communities. However, empirical data on professional perspectives regarding AI implementation in spiritual care remain scarce.

objectiveThis study aimed to conduct the first empirical investigation of AI use cases, risks and benefits, theological and ethical considerations, and relevant professional competencies from a multistakeholder expert perspective.

methodsAn international, multistakeholder modified Delphi study was conducted in 2 rounds. A purposive sample of 149 subject experts was recruited. Panelists rated 213 items spanning task assistance and substitution, risks and benefits, theological and ethical considerations, limits, and competencies. Consensus was defined using combined measures of variance and directionality. Exploratory subgroup analyses assessed whether ratings differed across professional and demographic groups.

resultsRound 1 was completed by 102 of 149 invited panelists (response rate 68.5%); round 2 was completed by 83 panelists (response rate 81.4%). In round 2, strong agreement emerged that AI can currently assist with or enhance administrative and routine tasks (77/81, 95.1%), informational tasks (74/79, 93.7%), documentation (67/80, 83.8%), and spiritual care research (65/77, 84.4%). Agreement was lower for relational, patient-facing tasks such as creating supportive spaces (30/69, 43.5%), direct patient engagement (32/76, 42.1%), and conducting ritual tasks (32/76, 42.1%). Panelists favored AI assistance over substitution and rated the future potential of AI above its current capabilities. The highest-ranked benefit that reached consensus was improved screening and triage; the highest-ranked risk was loss of human connection. Overall, 45.8% (38/83) of panelists judged the benefits of AI in spiritual care to outweigh the risks. The panel converged strongly on professional limits but was more divided on the underlying theological and ethical objections. The most strongly endorsed competencies were judging AI's applicability and the boundaries of its use, safeguarding patient privacy and data, and assessing and mitigating risks. Subgroup analyses produced few robust differences.

conclusionsThis study provides the first task-level map of expert opinion on AI in spiritual care, suggesting that current expert views are task-specific, future-oriented, and conditional. AI is seen as capable of assisting with administrative, informational, documentation, and research tasks. Direct relational care is widely regarded as a primarily human responsibility, and several tasks that experts judged AI capable of assisting with or substituting remain ethically complex. Experts converged on practical safeguards, including human oversight, evidence-based implementation, privacy protection, and limits on AI decision-making, and on required competencies, even as the theological and ethical rationales behind them remained contested. This suggests that professional guidance may be achievable at an early stage of AI adoption and can inform future research, guideline development, and curriculum design.

Indexed as

Artificial IntelligenceSpiritualityDelphi TechniqueFemaleHumansMaleAIartificial intelligencechaplaincyconsensusDelphihealth careprofessional competencespiritual care

Identifiers

PMID42507998
PMCPMC13458354

What OpenQuestion holds

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LicenceCC BY
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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.