Measuring Technology-Facilitated Sexual Violence and Abuse in the Chinese Context: Development Study and Content Validity Analysis
Notice bibliographique
Résumé
BACKGROUND: Technology-facilitated sexual violence and abuse (TFSVA) encompasses a range of behaviors where digital technologies are used to enable both virtual and in-person sexual violence. Given that TFSVA is an emerging and continually evolving form of sexual abuse, it has been challenging to establish a universally accepted definition or to develop standardized measures for its assessment. OBJECTIVE: This study aimed to address the significant gap in research on TFSVA within the Chinese context. Specifically, it sought to develop a TFSVA measurement tool with robust content validity, tailored for use in subsequent epidemiological studies within the Chinese context. METHODS: The first step in developing the measurement approach for TFSVA victimization and perpetration was to conduct a thorough literature review of existing empirical research on TFSVA and relevant measurement tools. After the initial generation of items, all the items were reviewed by an expert panel to assess the face validity. The measurement items were further reviewed by potential research participants, who were recruited through snowball sampling via online platforms. The assessment results were quantified by computing the content validity index (CVI). The participants were asked to rate each scale item in terms of its relevance, appropriateness, and clarity regarding the topic. RESULTS: The questionnaire was reviewed by 24 lay experts, with a mean age of 27.96 years. They represented different genders and sexual orientations. The final questionnaire contained a total of 89 items. Three key domains were identified to construct the questionnaire, which included image-based sexual abuse, nonimage-based TFSVA, and online-initiated physical sexual violence. The overall scale CVI values of relevance, appropriateness, and clarity for the scale were 0.90, 0.96, and 0.97, respectively, which indicated high content validity for all the instrument items. To ensure the measurement accurately reflects the experiences of diverse demographic groups, the content validity was further analyzed by gender and sexual orientation. This analysis revealed variations in item validity among participants from different genders and sexual orientations. For instance, heterosexual male respondents showed a particularly low CVI for relevance of 0.20 in the items related to nudity, including "male's chest/nipples are visible" and "the person is sexually suggestive." This underscored the importance of an inclusive approach when developing a measurement for TFSVA. CONCLUSIONS: This study greatly advances the assessment of TFSVA by examining the content validity of our newly developed measurement. The findings revealed that our measurement tool demonstrated adequate content validity, thereby providing a strong foundation for assessing TFSVA within the Chinese context. Implementing this tool is anticipated to enhance our understanding of TFSVA and aid in the development of effective interventions to combat this form of abuse.
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 | 0,014 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».