Assessing the health care needs of women in rural British Columbia: development and validation of a survey tool.
Bibliographic record
Abstract
OBJECTIVE: To design reliable survey instruments to evaluate needs and expectations for provision of women's health services in rural communities in British Columbia (BC). These tools will aim to plan programming for, and evaluate effectiveness of, a women's health enhanced skills residency program at the University of British Columbia. DESIGN: A qualitative design that included administration of written surveys and on-site interviews in several rural communities. SETTING: Three communities participated in initial questionnaire and interview administration. A fourth community participated in the second interview iteration. Participating communities did not have obstetrician-gynecologists but did have hospitals capable of supporting outpatient specialized women's health procedural care. PARTICIPANTS: Community physicians, leaders of community groups serving women, and allied health providers, in Vancouver Island, Southeast Interior BC, and Northern BC. METHODS: Two preliminary questionnaires were developed to assess local specialized women's health services based on the curriculum of the enhanced skills training program; one was designed for physicians and the other for women's community group leaders and aboriginal health and community group leaders. Interview questions were designed to ensure the survey could be understood and to identify important areas of women's health not included on the initial questionnaires. Results were analyzed using quantitative and qualitative methods, and a second draft of the questionnaires was developed for a second iteration of interviews. MAIN FINDINGS: Clarity and comprehension of questionnaires were good; however, nonphysician participants answered that they were unsure on many questions pertaining to specific services. Topics identified as important and missing from questionnaires included violence and mental health. A second version of the questionnaires was shown to have addressed these concerns. CONCLUSION: Through iterations of pilot testing, we created 2 validated survey instruments for implementation as a component of program evaluation. Testing in remote locations highlighted unique rural concerns, such that University of British Columbia health care professional training will now better serve BC community needs.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".