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Record W2769992926 · doi:10.5539/ijps.v9n4p76

Early Maladaptive Schemas and Academic Procrastination in Students: The Mediating Role of Perfectionism

2017· article· en· W2769992926 on OpenAlexvenueno aff
Mohammad Setayeshi Azhari

Bibliographic record

VenueInternational Journal of Psychological Studies · 2017
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProcrastinationPsychologyCronbach's alphaStructural equation modelingPerfectionism (psychology)Schema (genetic algorithms)Clinical psychologyAssociation (psychology)Developmental psychologySocial psychologyPsychometricsPsychotherapist

Abstract

fetched live from OpenAlex

Studies indicate that many students engage in procrastination, thus in this study the aim was to examine the structural relationship of early maladaptive schemas and academic procrastination with the mediating role of the perfectionism in students. The participants included 281 high school students (143 male, 138 female) that were chose by multistage cluster sampling method. Solomon and Rothblum’s academic procrastination scale with the Cronbach alpha coefficient 0.81 and Young early maladaptive schema questionnaire with the Cronbach alpha coefficient 0.93, and Positive and Negative Perfectionism questionnaire with the Cronbach alpha coefficient 0.86 were administered. Structural Equation Modeling (SEM) and Sobel tests were conducted to explore direct and indirect pathways of study’s model respectively. Results showed that early maladaptive schemas and academic procrastination are antecedents and consequences of perfectionism in students respectively. The results indicated that perfectionism has a significant mediating role on the relationship between early maladaptive schemas and academic procrastination. The findings of this study could help school counselors, education psychologist, and teachers to reduce student’s procrastination and academic problems.

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)0.002
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 score0.022
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.080
GPT teacher head0.464
Teacher spread0.384 · 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".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Psychological StudiesSame topicPerfectionism, Procrastination, Anxiety StudiesFrench-language works237,207