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Record W4402017306 · doi:10.1136/bmjopen-2024-084916

Addressing mental illness stigma in German higher education: study protocol for a mixed-methods evaluation of a psychosocial setting-based intervention

2024· article· en· W4402017306 on OpenAlexaffabout
Emily Nething, Elena Stoll, Keith S. Dobson, Andrew C. H. Szeto, Samuel Tomczyk

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicinePsychosocialStigma (botany)Mental illnessGermanIntervention (counseling)Protocol (science)Mental healthPsychiatryFamily medicineClinical psychologyAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Mental illness stigma is associated with a range of negative consequences, such as reduced help-seeking for mental health problems. Since stigma affects individual, social, and structural aspects, multilevel interventions such as the Canadian programme The Working Mind have been proven to be the most effective. Given the solid evidence base for The Working Mind, it is our aim to implement and evaluate culturally adapted versions of the programme in German higher education, targeting students, employees and managers. METHODS AND ANALYSIS: We will evaluate the programme with regard to its effect on mental illness stigma, openness to mental health problems, willingness to seek help, and positive mental health outcomes. Further, we will investigate the programme's effectiveness dependent on gender and personal values, various mechanisms of change, and factors facilitating and hindering implementation. The study uses a sequential explanatory mixed-methods evaluation design (QUAN → qual) that consists of three steps: (1) quasi-experimental online survey with programme participants, (2) focus groups with programme participants, and (3) qualitative interviews with programme stakeholders. The quantitative data collected in step 1 will be analysed using 2×3 analysis of variances and a parallel multiple mediation analysis. The results will inform the qualitative data to be collected in steps 2 and 3, which will be analysed using qualitative content analysis. ETHICS AND DISSEMINATION: The study was approved by the local Ethics Committee (Ethics Committee of University Medicine Greifswald; BB 098/23). Participants have to provide written consent before taking part in a focus group or interview. As for the online survey, participants have to give their consent by agreeing to an online data protection form before they can start completing the survey. We will publish central results and the anonymised data in an Open Access Journal. Further, the statistical code will be included as a supplement to the paper(s) documenting the results of the study. TRIAL REGISTRATION NUMBER: DRKS00033523.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.052
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.023
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0040.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0520.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.336
GPT teacher head0.686
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes2
Has abstractyes

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