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Record W4281297291 · doi:10.1027/1015-5759/a000712

Measuring Italian Resilience

2022· article· en· W4281297291 on OpenAlexaffabout
Chloé Lau, Francesca Chiesi, Catherine Li, Donald H. Saklofske

Bibliographic record

VenueEuropean Journal of Psychological Assessment · 2022
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyConvergent validityConfirmatory factor analysisExtraversion and introversionBig Five personality traitsMeasurement invariancePersonalityPsychological resilienceTemperamentTraitIncremental validityEmotionalityDevelopmental psychologyCriterion validityOptimismConstruct validitySocial psychologyPsychometricsStructural equation modelingInternal consistencyStatistics

Abstract

fetched live from OpenAlex

Abstract: The Essential Resilience Scale (ERS) measures global trait resilience and three factors of physical, emotional, and social resilience. This study developed an Italian adaptation of the ERS and recruited participants from Italy ( N = 500) to complete the measure along with criterion validity measures of broad personality traits and related psychological concepts. Confirmatory factor analysis (CFA) demonstrated robust evidence for a well-fitting three-factor model of the ERS, with items strongly loading onto their respective latent factors. Utilizing Samejima’s graded response model, most item discrimination values were moderate-to-high, and category threshold parameters were well-distributed throughout the latent continuum. The ERS showed correlations in the expected directions with extraversion, emotionality, optimism, mastery, resilience, behavioral activation, behavioral inhibition, stress, and well-being. Cultural invariance was supported (at the scale- and item-level) with multigroup CFA and differential item functioning (DIF) with a sample of Canadian English speakers ( N = 874). Findings evinced the internal consistency (i.e., total MacDonald’s ω), factorial validity (i.e., three-factor CFA), criterion validity (i.e., personality, temperament), and convergent validity (i.e., trait resilience and well-being) of the Italian ERS. Results suggest the Italian ERS can be applied for measuring resilience for future research studies in Italian-speaking populations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.115
GPT teacher head0.440
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

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