Menopause experience in First Nations women and initiatives for menopause symptom awareness; a community-based participatory research approach
Bibliographic record
Abstract
BACKGROUND: Little research has been conducted about menopause in First Nations women. In response to the wishes of Cree women living in Maskwacis, Alberta, to start a dialogue on menopause, we undertook community-based participatory research (CBPR) to explore menopause experience and raise awareness of menopause symptoms in the community. METHODS: The research adhered to the principles of Ownership, Control, Access and Possession (OCAP™) and was guided by the interest of the participating women. Local women (target age 40-65 years) were invited to participate in workshops using word-of-mouth and community posters in health centers. Five research workshops were held in community settings, attended by experienced women's health researchers and consenting women. The participants guided the informal discussions. They also completed questionnaires which included menopause-related quality of life. The researchers used extensive hand-written field notes to record data; qualitative content analysis was applied to identify themes. Simple descriptive analysis was used for the questionnaire results. The findings were discussed at a community feedback session and laid the basis for further knowledge translation initiatives. RESULTS: The five workshops included a total of 37, mostly post-menopausal women with 6-11 women/workshop. The main discussion themes were: "experiences of menopause symptoms" including their impact on quality of life; "menopause knowledge prior to their own experience" with most women feeling that they had insufficient information before menopause; "menopause symptom management" which mainly included practical strategies; "impact of menopause on family members" which was of prime concern with uncontrollable mood changes affecting the whole family and sometimes causing matrimonial disharmony. Questionnaire responses corroborated the workshop discussions. Knowledge translation of the research findings produced two information pamphlets specifically for the Maskwacis community: one for husband/partner, the other for women and family members. These pamphlets have been distributed in all areas of the community. CONCLUSION: This CBPR project addressed a topic identified by the community as being important. Community members developed informative pamphlets in response to the women's concern of lack of understanding for menopause symptoms among families. This simple solution has been widely accepted by community members, opening the possibility of wider discussion about menopause.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".