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Record W4414938565 · doi:10.2196/71425

Interventions to Prevent Sexual Harassment Against Nurses—StopSH: Protocol for an Intervention Development Study

2025· article· en· W4414938565 on OpenAlexvenueno aff
Milena Marta Bruschini, Maria Schubert

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionProtocol (science)Intervention (counseling)HarassmentMEDLINEIntervention mapping

Abstract

fetched live from OpenAlex

BACKGROUND: Patients' sexual harassment against nurses is a worldwide phenomenon. Some forms occur on a daily to weekly basis. Despite the known high prevalence and its negative consequences, there is still a lack of evidence-based measures to prevent patients' sexual harassment against nurses. Given the complexity of the problem, multidimensional interventions are required. OBJECTIVE: The main objective of the StopSH project is to develop an evidence-based, complex intervention package to prevent patients' sexual harassment against nurses and minimize its negative consequences for the acute care sector in the German-speaking part of Switzerland. METHODS: This project is an intervention development study with a multimethod design. It involves the participative development and testing of a complex intervention package in one to two Swiss hospitals as practice partners. The project is carried out in four project phases. First, a systematic scoping review will be conducted to identify and map existing interventions aimed at preventing sexual harassment of nurses or minimizing its consequences. The review will include interventions at the individual, organizational, and network levels of nurses. The problem and needs analysis form the second phase, where a cross-sectional web-based survey will be carried out among nurses in one to two partner hospitals. The aim is to assess the prevalence, forms, and perceived consequences of sexual harassment, as well as existing and desired strategies or support structures. The results will inform the development of the intervention package. As a third phase, a complex intervention package will be codeveloped using a participatory action research approach, based on the findings from the first two phases. This process will involve nurses, hospital management, human resources, and other relevant stakeholders to ensure contextual relevance and feasibility. Finally, during a feasibility assessment, the developed intervention package will be implemented and tested on two to three test wards within the partner hospitals. The mixed methods feasibility study will assess the acceptability, practicality, and preliminary effects of the intervention. Survey data, as well as contextual and observational data, will be collected. RESULTS: The project was launched in February 2024 and is scheduled to last for 5 years. As of August 2025, this project is in phase 2. Data collection is ongoing. The StopSH project is expected to develop and test a complex intervention package for the prevention of patients' sexual harassment against nurses. This intervention package is predicted to reduce the prevalence and negative effects of sexual harassment against nurses. CONCLUSIONS: The results of this project will provide important guidance for nurses, but also for their employers, and as such can contribute to the long-term reduction of sexual harassment against nurses. It lays the foundation for the development and adaptation of interventions in further nursing settings and other health care professions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71425.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.705
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.485
GPT teacher head0.678
Teacher spread0.193 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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