Evidence map›Paper›PMID 39402505›Full record

ArticleBMC psychiatry2024

Gender differences in preferences for mental health apps in the general population - a choice-based conjoint analysis from Germany.

Inga Jagemann, Manuel Stegemann, Ruth von Brachel, Gerrit Hirschfeld

Abstract read
In one paragraph

Article in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
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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.

Inga JagemannSchool of Business, University of Applied Sciences and Arts Bielefeld, Interaktion 1, 33619, Bielefeld, Germany. inga.jagemann@hsbi.de.
Manuel StegemannSchool of Business, University of Applied Sciences and Arts Bielefeld, Interaktion 1, 33619, Bielefeld, Germany.
Ruth von BrachelMental Health Research and Treatment Centre Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.
Gerrit HirschfeldSchool of Business, University of Applied Sciences and Arts Bielefeld, Interaktion 1, 33619, Bielefeld, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMen and women differ in the mental health issues they typically face. This study aims to describe gender differences in preferences for mental health treatment options and specifically tries to identify participants who prefer AI-based therapy over traditional face-to-face therapy.

methodA nationally representative sample of 2,108 participants (53% female) aged 18 to 74 years completed a choice-based conjoint analysis (CBCA). Within the CBCA, participants evaluated twenty choice sets, each describing three treatment variants in terms of provider, content, costs, and waiting time.

resultsCosts (relative importance [RI] = 55%) emerged as the most critical factor when choosing between treatment options, followed by provider (RI = 31%), content (RI = 10%), and waiting time (RI = 4%). Small yet statistically significant differences were observed between women and men. Women placed greater importance on the provider, while men placed greater importance on cost and waiting time. Age and previous experience with psychotherapy and with mental health apps were systematically related to individual preferences but did not alter gender effects. Only a minority (approximately 8%) of participants preferred AI-based treatment to traditional therapy.

conclusionsOverall, affordable mental health treatments performed by human therapists are consistently favored by both men and women. AI-driven mental health apps should align with user preferences to address psychologist shortages. However, it is uncertain whether they alone can meet the rising demand, highlighting the need for alternative solutions.

Indexed as

Choice BehaviorMobile ApplicationsPatient PreferenceAdolescentAdultAgedFemaleGermanyHumansMaleMental DisordersMental Health ServicesMiddle AgedPsychotherapySex FactorsYoung AdultArtificial intelligenceDiscrete choice experimentGender preferencesMental health treatment

Identifiers

PMID39402505
PMCPMC11475598

What OpenQuestion holds

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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.