MétaCan
Menu
Back to cohort
Record W7111798423

The integration of family planning services with other MNCH services in public facilities, district Quetta, Balochistan: A mixed-method research

2021· article· W7111798423 on OpenAlexaboutno aff

Bibliographic record

VenueeCommons - AKU (Aga Khan University) · 2021
Typearticle
Language
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsFamily planningPsychological interventionReproductive healthPublic healthFertilityPopulationQuarter (Canadian coin)Qualitative researchService delivery framework
DOInot available

Abstract

fetched live from OpenAlex

Family planning offers extremely effective, yet under-utilized means and interventions for achieving significant reductions in maternal and child mortality rates. In Pakistan, the uptake has been growing in many provinces across the country. It has been shown that a notable proportion of men and women of reproductive age in Balochistan, Pakistan, wish to avoid the high-risk fertility behaviors that threaten maternal and child health. Specifically, it is estimated that 45% of females wish to limit or delay births by two years, while 39% of men also share this desire (PDHS 2013). Nearly a quarter of married females are also undecided concerning whether to and when to have a child. This study identified the gaps necessary to assess the current level of integration family planning services, within Maternal, Newborn, and Child Health Innovation (MNCH) services in public health facilities, with the aim to reduce maternal mortality, infant Mortality, under-five mortality, unmet reproductive needs, and to improve the quality of services, in District Quetta of Balochistan. This study can be used as example for future interventions for strengthening integration to provide cost effective and modern methods for uplifting current health framework in Balochistan. Methodology: This study is a descriptive cross-sectional, exploratory, sequential mix-method study. The quantitative portion of the study encompassed 26 facility checklists, from selected 30 public health facilities of District Quetta, for evaluating the current level of family planning and MNCH service integration. In the sample, 81 of 102 selected female client exit interviews reported availing MNCH services. The qualitative portion of the study comprised of 13 in-depth interviews with service providers and program managers to record their perceptions of the integration of the services. Results: This research uncovered the service provider’s and program organizer's perspectives with respect to current level of integration in government-run public health facilities. This study documented the possible impacts, gaps, and assessed the current level of integration of family planning and MNCH services. Thus, recommendations to service providers, and policy makers to foster inventive interventions were provided, as well as policy formulations to advance the integrated services in District Quetta of Balochistan were noted. Conclusion: This research was conducted to determine the current level of integration of the family planning program within MNCH services in Quetta, Balochistan. Results of this study show that policies of the family planning program and available resources are not up to the satisfactory level. Due to improper implementation of family planning program, and indecorous distribution of resources, an increasing dissatisfaction among clients and health care workers exists. There is dire need for the involvement of the government, NGOs, and donors to foster the family planning program in Balochistan. There is also a need for significant action to be taken to fix the understated health system, in an attempt to focus on the six health building blocks, which can shape the structure for integration of family planning within MNCH. The robust relationship amongst all six blocks of health suggests that only health system strengthening can better integrate family planning within MNCH in Balochistan.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.314
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueeCommons - AKU (Aga Khan University)Same topicGlobal Maternal and Child HealthFrench-language works237,207