Evidence map›Paper›PMID 39635206›Full record

Trial reportFrontiers in public health2024

The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach.

Vanessa Juergensen, Lina-Jolien Peter, David Steyrl, Cindy Sumaly Lor, Anh Phi Bui, Thomas McLaren, Holger Muehlan, Samuel Tomczyk, Silke Schmidt, Georg Schomerus

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Frontiers in public health, 2024. 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. Trial
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.

Vanessa Juergensen *Department of Psychiatry and Psychotherapy, Medical Faculty, University Leipzig, Leipzig, Germany.
Lina-Jolien Peter *Department of Psychiatry and Psychotherapy, Medical Faculty, University Leipzig, Leipzig, Germany.
David SteyrlDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
Cindy Sumaly LorDepartment of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.
Anh Phi BuiDepartment of Psychiatry and Psychotherapy, Medical Faculty, University Leipzig, Leipzig, Germany.
Thomas McLarenDepartment of Health and Prevention, Institute of Psychology, University of Greifswald, Greifswald, Germany.
Holger MuehlanDepartment of Health and Prevention, Institute of Psychology, University of Greifswald, Greifswald, Germany.
Samuel TomczykDepartment of Health and Prevention, Institute of Psychology, University of Greifswald, Greifswald, Germany.
Silke SchmidtDepartment of Health and Prevention, Institute of Psychology, University of Greifswald, Greifswald, Germany.
Georg SchomerusDepartment of Psychiatry and Psychotherapy, Medical Faculty, University Leipzig, Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The goal of the study was to identify the most important influences on professional healthcare use of people with depressive symptoms. We incorporated findings from research areas of health behaviors, stigma, and motivation to predict the help-seeking process variables from a wide range of personal factors and attitudes. Methods: A sample of 1,368 adults with untreated depressive symptoms participated in an online survey with three-and six-month follow-ups. We conducted multiple linear regressions for (a) help-seeking attitudes, and (b) help-seeking intentions, and logistic regression for (c) help-seeking behavior with machine learning methods. Results: While self-stigma and treatment experience are important influences on help-seeking attitudes, complaint perception is relevant for intention. The best predictor for healthcare use remains the intention. Along the help-seeking process, we detected a shift of relevant factors from broader perceptions of mental illness and help-seeking to concrete suffering, i.e., subjective symptom perception. Conclusion: The results suggest a spectrum of influencing factors ranging from personal, self-determined factors to socially normalized factors. We discuss social influences on professional help-seeking and the use of combined public health programs and tailored help-seeking interventions. Clinical trial registration: German Clinical Trials Register (https://drks.de/search/en): Identifier DRKS00023557.

Indexed as

DepressionHelp-Seeking BehaviorMachine LearningPatient Acceptance of Health CareAdultFemaleGermanyHumansIntentionMaleMental Health ServicesMiddle AgedSocial StigmaSurveys and Questionnairesdepressive symptomshealthcare usehelp-seekingmachine learningmental illness stigma

Identifiers

PMID39635206
PMCPMC11615672

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.