Integrating Sexual and Reproductive Health Equity Into Public Health Goals and Metrics: Comparative Analysis of Healthy People 2030’s Approach and a Person-Centered Approach to Contraceptive Access Using Population-Based Data
Notice bibliographique
Résumé
BACKGROUND: The Healthy People initiative is a national effort to lay out public health goals in the United States every decade. In its latest iteration, Healthy People 2030, key goals related to contraception focus on increasing the use of effective birth control (contraceptive methods classified as most or moderately effective for pregnancy prevention) among women at risk of unintended pregnancy. This narrow focus is misaligned with sexual and reproductive health equity, which recognizes that individuals' self-defined contraceptive needs are critical for monitoring contraceptive access and designing policy and programmatic strategies to increase access. OBJECTIVE: We aimed to compare 2 population-level metrics of contraceptive access: a conventional metric, use of contraceptive methods considered most or moderately effective for pregnancy prevention among those considered at risk of unintended pregnancy (approximating the Healthy People 2030 approach), and a person-centered metric, use of preferred contraceptive method among current and prospective contraceptive users. METHODS: We used nationally representative data collected in 2022 to construct the 2 metrics of contraceptive access; the overall sample included individuals assigned female at birth not using female sterilization or otherwise infecund and who were not pregnant or trying to become pregnant (unweighted N=2760; population estimate: 43.9 million). We conducted a comparative analysis to examine the convergence and divergence of the metrics by examining whether individuals met the inclusion criteria for the denominators of both metrics, neither metric, only the conventional metric, or only the person-centered metric. RESULTS: Comparing the 2 approaches to measuring contraceptive access, we found that 79% of respondents were either included in or excluded from both metrics (reflecting that the metrics converged when individuals were treated the same by both). The remaining 21% represented divergence in the metrics, with an estimated 5.7 million individuals who did not want to use contraception included only in the conventional metric denominator and an estimated 3.5 million individuals who were using or wanted to use contraception but had never had penile-vaginal sex included only in the person-centered metric denominator. Among those included only in the conventional metric, 100% were content nonusers-individuals who were not using contraception, nor did they want to. Among those included only in the person-centered metric, 68% were currently using contraception. Despite their current or desired contraceptive use, these individuals were excluded from the conventional metric because they had never had penile-vaginal sex. CONCLUSIONS: Our analysis highlights that a frequently used metric of contraceptive access misses the needs of millions of people by simultaneously including content nonusers and excluding those who are using or want to use contraception who have never had sex. Documenting and quantifying the gap between current approaches to assessing contraceptive access and more person-centered ones helps clearly identify where programmatic and policy efforts should focus going forward.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».