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Record W2997196986 · doi:10.1186/s12889-019-8059-4

Designing an intervention to improve sexual health service use among university undergraduate students: a mixed methods study guided by the behaviour change wheel

2019· article· en· W2997196986 on OpenAlexafffund
Christine Cassidy, Audrey Steenbeek, Donald B. Langille, Ruth Martin‐Misener, Janet Curran

Bibliographic record

VenueBMC Public Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchDalhousie University
KeywordsBiostatisticsMedicinePublic healthIntervention (counseling)Sexual behaviorReproductive healthMedical educationFamily medicineNursingEnvironmental healthClinical psychologyPopulation

Abstract

fetched live from OpenAlex

INTRODUCTION: University undergraduate students are within the population at highest risk for acquiring sexually transmitted infections, unplanned pregnancy, and other negative health outcomes. Despite the availability of sexual health services at university health centres, many students delay or avoid seeking care. In this study, we describe how the Behaviour Change Wheel was used as a systematic approach to design an intervention to improve sexual health service use among university undergraduate students. METHODS: This paper describes the intervention development phase of a three-phased, sequential explanatory mixed methods study. Phases one and two included a quantitative and qualitative study that aimed to better understand students' use of sexual health services. In phase three, we followed the Behaviour Change Wheel to integrate the quantitative and qualitative findings and conduct stakeholder consultation meetings to select intervention strategies, including intervention functions and behaviour change techniques. RESULTS: Key linkages between opportunity and motivation were found to influence students' access of sexual health services. Stakeholders identified six intervention functions (education, environmental restructuring, enablement, modelling, persuasion, and incentivization) and 15 behaviour change techniques (information about health consequences, information about social and environmental consequences, feedback on behaviour, feedback on outcomes of behaviour, prompts/cues, self-monitoring of behaviour, adding objects to the environment, goal setting, problem solving, action planning, restructuring the social environment, restructuring the physical environment, demonstration of the behaviour, social support, credible source) as relevant to include in a toolbox of intervention strategies to improve sexual health service use. CONCLUSIONS: This study details the use of the Behaviour Change Wheel to develop an intervention aimed at improving university students' use of sexual health services. The Behaviour Change Wheel provided a comprehensive framework for integrating multiple sources of data to inform the selection of intervention strategies. Stakeholders can use these strategies to design and implement sexual health service interventions that are feasible within the context of their health centre. Future research is needed to test the effectiveness of the strategies at changing university students' sexual health behaviour.

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)0.029
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.306
GPT teacher head0.511
Teacher spread0.205 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations20
Published2019
Admission routes2
Has abstractyes

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