Factors influencing men’s involvement in antenatal care services: a cross-sectional study in a low resource setting, Central Tanzania
Bibliographic record
Abstract
BACKGROUND: Men's involvement can impact the delays in the decision to seek health care and in reaching a health facility, which are contributing causes for increased maternal mortality. Despite of the call to involve men in antenatal care, their participation is not well understood. This study aimed to determine the level of men's involvement in antenatal care and the factors influencing their involvement in these services. METHODS: A cross sectional study of 966 randomly selected men aged 18 years or older was conducted in Dodoma Region, from June 2014 to November 2015. Face to face interviews were conducted using a pretested structured questionnaire. The outcome variable was men's involvement and was constructed from four dichotomized items which were scored zero to two for low involvement and three to four for high involvement. A multiple logistic model was used to measure the factors influencing men's involvement in antenatal care services. RESULTS: The level of men's involvement in antenatal care was high (53.9%). Majority 89% of respondents made joint decisions on seeking antenatal care. More than half (63.4%) of respondents accompanied their partners to the antenatal clinic at least once. Less than a quarter (23.5%) of men was able to discuss issues related to pregnancy with their partner's health care providers. About 77.3% of respondents provided physical support to their partners during the antenatal period. Factors influencing men's involvement in antenatal care were occupation (AOR = 0.692, 95% CI = 0.511-0.936), ethnicity (AOR = 1.495, 95% CI = 1.066-2.097), religion (AOR = 1.826, 95% CI = 1.245-2.677), waiting time (AOR = 1.444, 95% CI = 1.094-1.906), information regarding men's involvement in antenatal care (AOR = 3.077, 95% CI = 2.076-4.562) and men's perception about theattitude of health care providers (AOR = 1.548, 95%CI = 1.090-2.199). CONCLUSION: Overall, more than half of respondents reported high involvement in antenatal care services. Access to information on men's involvement, religion, occupation, ethnicity, waiting time and men's perception about the attitude of care providers were significant factors influencing men's involvement in antenatal care services in this study. Health promotion is needed to empower men with essential information for meaningful involvement in antenatal care services.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".