Provision of online HIV-related information to gay, bisexual and other men who have sex with men: a health literacy-informed critical appraisal of Canadian agency websites
Bibliographic record
Abstract
Background: HIV risk and prevention information is increasingly complex and poses challenges for gay, bisexual and other men who have sex with men (GBMSM) seeking to find, understand and apply this information. A directed content analysis of Canadian HIV websites to see what information is provided, how it is presented and experienced by users, was conducted. Methods: Eligible sites provided information relevant for GBMSM on HIV risk or prevention, were from community or government agencies, and were aimed at the public. Sites were found by using a Google search using French and English search terms, from expert suggestions and a review of links. Eligibility and content for review was determined by two reviewers, and coded using a standardised form. Reading grade level and usability scores were assessed through Flesch-Kincaid and LIDA instruments. Results: Of 50 eligible sites, 78% were from community agencies and 26% were focussed on GBMSM. Overall, fewer websites contained information on more recent biomedical advances (e.g. pre-exposure prophylaxis, 10%) or community-based prevention strategies (e.g. seroadaptive positioning, 10%). Many sites had high reading levels, used technical language and relied on text and prose. And 44% of websites had no interactive features and most had poor usability scores for engageability. Conclusions: Overall, less information about emerging topics and a reliance on text with high reading requirements was observed. Our study speaks to potential challenges for agency website operators to maintain information relevant to GBMSM which is up-to-date, understandable for a range of health literacy skills and optimises user experience.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.138 | 0.322 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.026 | 0.029 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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 source (direct Gemma or distilled Codex), 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".