Evidence map›Paper›PMID 40138692›Full record

ArticleJMIR formative research2025

Patients' and Health Care Professionals' Expectations of Virtual Therapeutic Agents in Outpatient Aftercare: Qualitative Survey Study.

Diana Immel, Bernhard Hilpert, Patricia Schwarz, Andreas Hein, Patrick Gebhard, Simon Barton, René Hurlemann

Abstract read
In one paragraph

Article in JMIR formative research, 2025. 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. Article
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

7 authors.

Diana ImmelDepartment of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.ORCID 0009-0002-2438-5227
Bernhard HilpertAffective Computing Group, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, German Research Center for Artificial Intelligence, Kaiserslautern, Germany.ORCID 0000-0002-0011-2905
Patricia SchwarzAssistance Systems and Medical Device Technology, Department for Health Services Research, School of Medicine & Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.ORCID 0009-0004-2026-3016
Andreas HeinAssistance Systems and Medical Device Technology, Department for Health Services Research, School of Medicine & Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.ORCID 0000-0001-8846-2282
Patrick GebhardAffective Computing Group, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, German Research Center for Artificial Intelligence, Kaiserslautern, Germany.ORCID 0000-0002-5566-4520
Simon Barton *Department of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.ORCID 0009-0002-7810-9690
René Hurlemann *Department of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.ORCID 0000-0003-2628-565X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression is a serious mental health condition that can have a profound impact on the individual experiencing the disorder and those providing care. While psychotherapy and medication can be effective, there are gaps in current approaches, particularly in outpatient care. This phase is often associated with a high risk of relapse and readmission, and patients often report a lack of support. Socially interactive agents represent an innovative approach to the provision of assistance. Often powered by artificial intelligence, these virtual agents can interact socially and elicit humanlike emotions. In health care, they are used as virtual therapeutic assistants to fill gaps in outpatient aftercare.

objectiveWe aimed to explore the expectations of patients with depression and health care professionals by conducting a qualitative survey. Our analysis focused on research questions related to the appearance and role of the assistant, the assistant-patient interaction (time of interaction, skills and abilities of the assistant, and modes of interaction) and the therapist-assistant interaction.

methodsA 2-part qualitative study was conducted to explore the perspectives of the 2 groups (patients and care providers). In the first step, care providers (n=30) were recruited during a regional offline meeting. After a short presentation, they were given a link and were asked to complete a semistructured web-based questionnaire. Next, patients (n=20) were recruited from a clinic and were interviewed in a semistructured face-to-face interview.

resultsThe survey findings suggested that the assistant should be a multimodal communicator (voice, facial expressions, and gestures) and counteract negative self-evaluation. Most participants preferred a female assistant or wanted the option to choose the gender. In total, 24 (80%) health care professionals wanted a selectable option, while patients exhibited a marked preference for a female or diverse assistant. Regrading patient-assistant interaction, the assistant was seen as a proactive recipient of information, and the patient as a passive one. Gaps in aftercare could be filled by the unlimited availability of the assistant. However, patients should retain their autonomy to avoid dependency. The monitoring of health status was viewed positively by both groups. A biofeedback function was desired to detect early warning signs of disease. When appropriate to the situation, a sense of humor in the assistant was desirable. The desired skills of the assistant can be summarized as providing structure and emotional support, especially warmth and competence to build trust. Consistency was important for the caregiver to appear authentic. Regarding the assistant-care provider interaction, 3 key areas were identified: objective patient status measurement, emergency suicide prevention, and an information tool and decision support system for health care professionals.

conclusionsOverall, the survey conducted provides innovative guidelines for the development of virtual therapeutic assistants to fill the gaps in patient aftercare.

Indexed as

AftercareAmbulatory CareAttitude of Health PersonnelDepressionHealth PersonnelOutpatientsAdultFemaleHumansMaleMiddle AgedQualitative ResearchSurveys and Questionnairesartificial intelligencedepressiondigital health caredigital interventiondigital technologye-mental healthmajor depressive disordermental disordermental illnessoutpatient aftercarepublic healthsocially interactive agentsuicidal ideationsuicide preventionvirtual therapeutic assistant

Identifiers

PMID40138692
PMCPMC11982758

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.