Preconception Care: A Concept Analysis of an Evolving Paradigm
Bibliographic record
Abstract
AIM(S): To clarify the concept of preconception care and develop a precise and inclusive definition to improve its implementation and impact on reproductive health outcomes. DESIGN: This concept analysis paper employs Rodgers' evolutionary method to analyse the concept of preconception care, examining its historical evolution, attributes, antecedents and consequences. METHODS: A comprehensive literature review was conducted using databases such as Cumulative Index to Nursing and Allied Health Literature, Scopus, MEDLINE and Google Scholar, covering publications from 2012 to 2024. Data extraction involved identifying surrogate and related terms, attributes, antecedents and consequences of preconception care. A total of 1520 publications were retrieved, with 166 meeting eligibility criteria. Using systematic random sampling, 40 articles were selected for in-depth analysis. RESULTS: The analysis revealed that preconception care encompasses several attributes: period-related (biological, individual, public health and intergenerational), target population-related (individual, public and intergenerational) and pathway-related (universal, targeted and comprehensive). Antecedents include desires for a healthy baby and family planning decisions. Consequently, it improves pregnancy outcomes and health equity and enhances community and intergenerational health. The proposed operational definition highlights preconception care as a proactive strategy to optimise health before pregnancy through targeted and inclusive interventions. CONCLUSION: Preconception care is a dynamic and multifaceted process that extends from immediate preconception periods to long-term health considerations. Addressing diverse needs and effectively improving health outcomes requires a tailored approach considering individual, public and intergenerational perspectives. IMPLICATIONS FOR PROFESSIONS AND PATIENT CARE: A transparent and inclusive definition of preconception care will enable healthcare professionals, particularly nurses, to deliver more effective, culturally sensitive and equitable care. It will support advocacy for policy changes, resource allocation and educational initiatives to enhance preconception health. IMPACT: Addressing preconception care's complexities and diverse needs will foster a more comprehensive understanding and implementation of preconception care, ultimately improving reproductive health outcomes and promoting health equity across generations. PATIENT OR PUBLIC CONTRIBUTION: As this concept analysis was derived from published articles, patients or the public were not involved in the study's design, conduct or reporting.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".