Psychometric Properties of the Connor-Davidson Resilience Scale for South America (CD-RISC-25SA) in Peruvian Adolescents
Bibliographic record
Abstract
Resilience describes the ability of someone to adapt to adverse life experiences by adjusting to demands with behavioral flexibility. When encountering crisis situations, resilient people typically spring back emotionally with increased strength and internal composure. Measuring resilience is important for assessing the ability of adolescents to respond to adverse situations. The objective of this study was to evaluate the psychometric performance of the Spanish version of the Connor-Davidson Resilience Scale (CD-RISC) © for South America (CD-RISC-25SA) in a population of vulnerable Peruvian adolescents. This study used a cross-sectional design to measure sociodemographic variables and resilience. Participants were 451 adolescents living in a shelter in Lima, Perú. Face and content validity were established by expert panel, construct validity was evaluated with exploratory and confirmatory factor analysis, and internal consistency was assessed with Cronbach’s alpha. The analysis resulted in a four-dimensional model with 22 items explaining almost 27% of the variance with a Cronbach’s alpha of 0.90. The dimensions included self-confidence and self-trust from previous experiences, internal resources to cope with difficult situations, personal competence and tenacity, and self-regulation with external resources. Two of the 3 items eliminated from the instrument were related to the original dimension “spirituality influences” which may have been incorrectly translated and adapted without equivalence of meaning for cross-cultural research. The CD-RISC-25SA is not a stable multidimensional instrument for measuring resilience across the cultures and contexts of countries. However, the instrument appears to be stable for measuring resilience as a single dimension. For measuring resilience in the context of Peru, a four-dimensional model with 22 items was validated. Variations in the psychometric properties of translated instruments may result from not establishing the equivalence of meaning for each item before performing cross-cultural research. Researchers need to search for a more precise understanding of resilience as a universal concept transferable across borders and through translations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".