Measuring disrespect and abuse during childbirth in a high-resource country: Development and validation of a German self-report tool
Notice bibliographique
Résumé
INTRODUCTION: Increasing evidence on disrespect and abuse during childbirth has led to growing concern about the quality of care childbearing women are experiencing. To provide quantitative evidence of disrespect and abuse during childbirth services in Germany a validated measurement tool is needed. RESEARCH AIM: The aim of this research project was the development and psychometric validation of a survey tool in the German language that measures disrespect and abuse of women during childbirth. METHODS: A survey tool was created including the following measures: German adaptations of the short and long form of the "Mothers on Respect" (MOR) index (MOR-7 and MOR-G); the "Mothers' Autonomy in Decision Making" (MADM) scale; a mistreatment-index (MIST-I) comprising indicators of mistreatment during childbirth; and a set of items that measure experiences of discrimination during maternity care. Internal consistency reliability and construct validity of the scales were assessed using Cronbach's alpha, unweighted least squares factor analysis and non-parametric correlation analysis with a scale that measures a related construct, the Posttraumatic Symptom Scale - Self Report (PSS-SR) scale. We distributed the survey online, recruiting through snowball sampling via social media. A selection bias towards women who had experienced disrespect and abuse during their birth was intended and expedient for tool validation. The final sample of participants (n = 2045) had given birth in Germany between 2009 and 2018. FINDINGS: More than 77% of the study participants reported at least one form of mistreatment with non-consented care being the most commonly reported type of mistreatment, followed by physical violence, violation of physical privacy, verbal abuse and neglect. All included scales showed good psychometric properties with high Cronbach's alphas (0.95 for both MOR versions and 0.96 for MADM). Factor analysis generated one factor scales with high factor loadings (0.75 to 0.92 for MOR-7; 0.37 to 0.90 for MOR-G and 0.83 to 0.92 for MADM). MOR-7, MOR-G, MADM and MIST-I scores were significantly (p<0.001) correlated with PSS-SR scores (Spearman's rho -0.70, -0.61 and 0.68 for MOR-G, MADM and the MIST-I, respectively). CONCLUSIONS: This study presents a valid and reliable instrument for the quantitative assessment of disrespect and abuse during childbirth in Germany. Childbearing women's experiences of disrespect and abuse are a relevant phenomenon in German hospital based maternity care. Disrespect and abuse during childbirth appear to contribute to post-traumatic symptoms and may be associated with severe mental health problems postpartum.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».