PROTOCOL: Psychometric properties of instruments for measuring elder abuse and neglect in community and institutional settings: A systematic review
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Background: The psychometric properties of elder abuse measurement instruments have not been well-studied. Poor psychometric properties of elder abuse measurement instruments may contribute to the inconsistency of elder abuse prevalence estimates and uncertainty about the magnitude of the problem at the national, regional, and global levels. Objectives: The present review will utilise the COSMIN taxonomy on the quality of outcome measures to identify and review the instruments used in measuring elder abuse, assess the instrument's measurement properties, and identify the definitions of elder abuse and abuse subtypes measured by the instrument. Search Methods: Searches will be conducted in the following online databases: Ageline, ASSIA, CINAHL, CNKI, EMBASE, Google Scholar, LILACS, Proquest Dissertation & Theses Global, PsycINFO, PubMed, SciELO, Scopus, Sociological Abstract and WHO Index Medicus. Relevant studies will also be identified by searching the grey literature from several resources such as OpenAIRE, BASE, OISter and Age Concern NZPotential studies by searching the references of related reviews. We will contact experts who have conducted similar work or are currently conducting ongoing studies. Enquiries will also be sent to the relevant authors if any important data is missing, incomplete or unclear. Selection Criteria: All quantitative, qualitative (that address face and content validity), and mixed-method empirical studies published in peer-reviewed journals or the grey literature will be included in this review. Studies will be included if they are primary studies that (1) evaluate one or more psychometric properties; (2) contain information on instrument development, or (3) perform content validity of the instruments designed to measure elder abuse in the community or institutional settings. Studies should describe at least one of the psychometric properties, such as reliability, validity and responsiveness. Study participants represent the population of interest, including males and females aged 60 or older in community or institutional settings (i.e., nursing homes, long-term care facilities, assisted living, residential care institutions, and residential facilities). Data Collection and Analysis: Screening of titles, abstracts, and full texts of the selected studies will be evaluated based on the preset inclusion criteria by two reviewers. Two reviewers will be assessing the quality appraisal of each study using the COSMIN Risk of Bias checklist and the overall quality of evidence of each psychometric property of the instrument against the updated criteria of good measurement properties. Any dispute between the two reviewers will be resolved through discussions or consensus with a third reviewer. The overall quality of the measurement instrument will be graded using a modified GRADE approach. Data extraction will be performed using the data extraction forms adapted from the COSMIN Guideline for Systematic Reviews of Outcome Measurement Instruments. The information includes the characteristic of included instruments (name, adaptation, language used, translation and country of origin), characteristics of the tested population, psychometric properties listed in the COSMIN criteria, including details on the instrument development, content validity, structural validity, internal consistency, cross-cultural validity/measurement invariance, reliability, measurement error, criterion validity, hypotheses testing for construct validity, responsiveness and interoperability. We will perform a meta-analysis to pool psychometric properties parameters (where possible) or summarise qualitatively.
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.
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 | 0,016 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,009 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 découle