Cross-cultural adaptations of the Family Resilience Assessment Scale: a systematic review protocol of measurement properties
Bibliographic record
Abstract
OBJECTIVE: This review aims to critically appraise the measurement properties and adaptation processes of all cross-cultural adaptations of the Family Resilience Assessment Scale. BACKGROUND: A number of family resilience instruments have been developed over the past decade; however, the Family Resilience Assessment Scale reports the best psychometric properties among populations with health issues. Since its publication in 2005, numerous translations and adaptations have been undertaken to use this scale with culturally diverse populations. A systematic review of the properties of the Family Resilience Assessment Scale's cross-cultural adaptations is needed to evaluate the adapted versions' quality (validity, reliability, and responsiveness). INCLUSION CRITERIA: This review will consider validation and cross-cultural adaptation studies of the Family Resilience Assessment Scale as well as research publications reporting psychometric properties of cross-cultural adaptations in specific populations. METHODS: Nine databases will be consulted: CINAHL, PubMed, Embase, PsycINFO, PubPsych, Health and Psychosocial Instruments database, ProQuest Dissertations and Theses, ScienceDirect, and Web of Science. The search will be limited to publications since 2005 without language restrictions. Articles will be screened by two independent reviewers and will undergo risk of bias assessment. The measurement properties of retrieved instruments will be assessed following COSMIN guidelines. Data extraction will be piloted and completed by two independent reviewers using an adapted extraction form. Psychometric properties will be reported in a narrative synthesis and supported by a summary table. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42020219938.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.134 | 0.175 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".