Barriers and enablers to sexual health service use among university students: a qualitative descriptive study using the Theoretical Domains Framework and COM-B model
Bibliographic record
Abstract
Abstract Background University students are within the age group at highest risk for acquiring sexually transmitted infections and other negative health outcomes. Despite the availability of sexual health services at university health centres to promote sexual health, many students delay or avoid seeking care. This study aimed to identify the perceived barriers and enablers to sexual health service use among university undergraduate students. Methods We used a qualitative descriptive design to conduct semi-structured focus groups and key informant interviews with university students, health care providers, and university administrators at two university health centres in Nova Scotia, Canada. The semi-structured focus group and interview guides were developed using the Theoretical Domains Framework and COM-B Model. Data were analyzed using a directed content analysis approach, followed by inductive thematic analysis. Results We conducted 6 focus groups with a total of 56 undergraduate students (aged 18–25) and 7 key informant interviews with clinicians and administrators. We identified 10 barriers and enablers to sexual health service use, under 7 TDF domains: knowledge; memory, attention and decision-making processes; social influences; environmental context and resources; beliefs about consequences; optimism; and emotion. Key linkages between students’ social opportunity and motivation were found to influence students’ access of sexual health services. Conclusions We identified barriers and enablers related to students’ capability, opportunity and motivation that influence sexual health service use. We will use these findings to design an intervention that targets the identified barriers and enablers to improve students’ use of sexual health services, and ultimately, their overall health and well-being.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".