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Record W6977473190 · doi:10.6084/m9.figshare.c.6700959

Exploring the accuracy of self-reported maternal and newborn care in select studies from low and middle-income country settings: do respondent and facility characteristics affect measurement?

2024· other· en· W6977473190 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsRespondentPsychological interventionIntervention (counseling)Bivariate analysisReceiptAffect (linguistics)UnivariateHealth care

Abstract

fetched live from OpenAlex

Abstract Background Accurate data on the receipt of essential maternal and newborn health interventions is necessary to interpret and address gaps in effective coverage. Validation results of commonly used content and quality of care indicators routinely implemented in international survey programs vary across settings. We assessed how respondent and facility characteristics influenced the accuracy of women’s recall of interventions received in the antenatal and postnatal periods. Methods We synthesized reporting accuracy using data from a known sample of validation studies conducted in Sub-Saharan Africa and Southeast Asia, which assessed the validity of women’s self-report of received antenatal care (ANC) (N = 3 studies, 3,169 participants) and postnatal care (PNC) (N = 5 studies, 2,462 participants) compared to direct observation. For each study, indicator sensitivity and specificity are presented with 95% confidence intervals. Univariate fixed effects and bivariate random effects models were used to examine whether respondent characteristics (e.g., age group, parity, education level), facility quality, or intervention coverage level influenced the accuracy of women’s recall of whether interventions were received. Results Intervention coverage was associated with reporting accuracy across studies for the majority (9 of 12) of PNC indicators. Increasing intervention coverage was associated with poorer specificity for 8 indicators and improved sensitivity for 6 indicators. Reporting accuracy for ANC or PNC indicators did not consistently differ by any other respondent or facility characteristic. Conclusions High intervention coverage may contribute to higher false positive reporting (poorer specificity) among women who receive facility-based maternal and newborn care while low intervention coverage may contribute to false negative reporting (lower sensitivity). While replication in other country and facility settings is warranted, results suggest that monitoring efforts should consider the context of care when interpreting national estimates of intervention coverage.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.096
GPT teacher head0.291
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2024
Admission routes1
Has abstractyes

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