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Record W2905610537

Propiedades psicométricas del CERI y CERM en estudiantes universitarios de Lima

2018· dissertation· es· W2905610537 on OpenAlexaboutno aff
Larco Avendaño, Lucía Leonor

Bibliographic record

VenuePontificia Universidad Católica del Perú · 2018
Typedissertation
Languagees
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyHumanitiesDiscriminant validityInternal consistencyClinical psychologyPsychometricsArt
DOInot available

Abstract

fetched live from OpenAlex

The study focuses on the psychometric properties of the Internet Experiences Questionnaire (CERI) and the Cell pone Experiences Questionnaire (CERM) in 508 students of a private college in Lima. The instruments to determine convergent and discriminant validity of the scales were the Internet addiction scale of Lima (EAIL), The Zung Self-Rating Depression Scale (SDS), The State-Trait Anxiety Inventory (STAI), and the Toronto Alexithymia Scale (TAS-20). For evidence of criterion validity, comparisons were made with the daily hours of Internet and cell phone use. Results from the factorial analysis of CERI reveal a two dimensional structure with a 33.47% of explained variation. In addition, the reliability analysis shows a suitable internal consistency of .73 for the total score of the scale, and questionable for the areas with values of .69 and .62. The results from the factorial analysis of CERM reveal one dimensional structure with a 37.76% of explained variation. The reliability analysis shows a suitable internal consistency of .81. Significant, direct and large correlations of CERI and CERM with EAIL and significant, direct and medium correlations of CERI and CERM with SDS, STAI and TAS-20. The comparison of CERI, its two areas and CERM with the hours of Internet connection and cell phone use was significant and small for CERI, its first area and CERM. With this, CERI can’t show that has adequate psychometric properties the measure the Internet problematic use, but it is confirmed that CERM is an instrument with adequate psychometric properties to evaluate cell phone’s problematic use.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.292
Teacher spread0.280 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations0
Published2018
Admission routes1
Has abstractyes

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