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Record W4322708725 · doi:10.4103/jfmpc.jfmpc_1090_22

Men’s knowledge of preconception health: A systematic review

2023· review· en· W4322708725 on OpenAlexaboutno aff
Zeinab Rabiei, Mohammad Shariati, Nasser Mogharabian, Rahim Tahmasebi, Ashraf Ghiasi, Zahra Motaghi

Bibliographic record

VenueJournal of Family Medicine and Primary Care · 2023
Typereview
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineScopusReproductive healthCritical appraisalSystematic reviewFamily medicineInclusion (mineral)Alternative medicineMEDLINEGerontologyEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

Preconception health is defined as the physical and psychological well-being of women and men throughout their reproductive life. It is a method that raises healthy fertility and focuses on activities that persons can take to minimize risks, raise healthy lifestyles, and increase preparation for pregnancy. The purpose of this systematic review study was to assess men's knowledge of preconception health. Electronic databases, including Web of Science, PubMed, Scopus, Sciencedirect, ProQuest, Cochrane, SAGE, Springer, Google Scholar, were searched for published studies from 2000 to March 2021 to identify the studies carried out on men's knowledge of preconception health. The quality assessment was done using the critical appraisal skills program tool for qualitative studies and the Newcastle-Ottawa scale for cross-sectional studies. Of the 1195 references identified in the initial search, 11 studies met the inclusion criteria. Because of the diversity in the study design and the data collection tools used in studies, meta-analysis was impossible. All the studies of the present systematic review found that men's preconception health knowledge is poor. This systematic review showed that men's preconception health knowledge is low. Due to the limited studies of men's knowledge about the importance of optimizing their health before pregnancy, further study of the issue is still required.

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)0.005
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.276
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.430
GPT teacher head0.560
Teacher spread0.129 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations24
Published2023
Admission routes1
Has abstractyes

Explore more

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