Identifying Psychosocial, Self-Management, and Health Profiles Among Women With Chronic Pain Who Have Experienced Intimate Partner Violence and Those Who Have Not: Protocol for a 2-Phase Qualitative and Cross-Sectional Study Using AI Techniques
Notice bibliographique
Résumé
BACKGROUND: Women who experience intimate partner violence (IPV) are more likely to develop disabling chronic pain (CP). However, there is little information on what it means to live with CP while being exposed to IPV. In addition, despite well-established risk and protective factors for CP and its health outcomes, there are no data on whether these factors differ in women who have experienced IPV compared to those who have not. OBJECTIVE: Our aims are to understand the meaning and implications of living with CP for women who have experienced IPV compared to women with CP alone and to identify possible differences in risk and protective factors as well as health outcomes. METHODS: We have designed 2 studies to be conducted in 2 phases. The first phase will involve a qualitative study with a descriptive and exploratory design. Individual semistructured interviews will be conducted with at least 10 women with CP alone and with 10 women with CP who have experienced IPV. Reflexive thematic analysis will be used to examine participants' experiences, meanings, and realities. In the second phase, a cross-sectional study will be conducted with women with CP affected by IPV, including those currently experiencing IPV and those with past exposure to IPV, as well as women with CP who have never experienced IPV. A total of 359 women will complete various scales assessing risk and protective factors (eg, pain-related worrying and activity patterns) and health outcomes (eg, legal and illegal drug use and health care use). Data analysis will involve inferential statistics and machine learning. RESULTS: As of May 2025, we had contacted relevant associations to present the project and begin recruiting voluntary participants. We have conducted the pilot study to assure the adequacy of the questionnaire and usability or technical functionality of the web-based platform. The results are expected to be published starting in January 2026. CONCLUSIONS: This research addresses two urgent needs in pain research identified by the European Pain Federation: (1) expanding knowledge on CP management in relation to contextual factors; and (2) identifying specific psychosocial, self-management, and health profiles among women with CP who have experienced IPV and those who have not. This could provide valuable insights for personalizing pain management treatments. In addition, the findings may help identify women experiencing IPV who present to health care settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/66396.
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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 | 0,041 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,005 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,004 |
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 ».