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Record W3037324167 · doi:10.5604/01.3001.0014.1510

Validation of the Polish version of the Self-reported Experiences of Activity Settings (SEAS) questionnaire

2020· article· en· W3037324167 on OpenAlexaff
Aleksandra Kulis, Beata Batorowicz, Urszula Chrabota

Bibliographic record

VenueRehabilitacja Medyczna · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsQueen's University
Fundersnot available
KeywordsCronbach's alphaPsychologyQuestionnaireIndex (typography)PolishTest (biology)Clinical psychologyPsychometricsSociologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Introduction: Despite the growing interest in various forms of leisure time management and their influence on various aspects of human life, still not enough attention is paid to understanding individual experiences of participation in classes. It is important not only what we do, but also how the activity affects overall well-being, functioning and role play in society. Objective: The aim of this work is to present the process of validation of the Polish version of the Self-reported Experiences of Activity Settings (SEAS) questionnaire. Material and methods: The study was conducted in a group of 153 people aged 10-22 years (mean 15.5 ± 3.3). The study participants were divided into four groups. The process of translation and cultural adaptation was carried out according to international rules developed by ISPOR. Results: The alpha Cronbach index for the whole questionnaire was 0.953. The internal alpha Cronbach index for question groups in the Polish version of the TeDeMAR questionnaire was higher or equal to 0.70 and close to the values of this index in the English version of the questionnaire. The results of the constancy test performed in group 4 showed no statistically significant differences (p>0.05) between the individual question groups. Conclusions: The TeDeMAR questionnaire, as the Polish version of the SEAS questionnaire, met all validation criteria.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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