MétaCan
Menu
Back to cohort
Record W3132754405 · doi:10.5539/jedp.v11n1p28

The Effects of Dichotomous Thinking on Depression in Japanese College Students

2021· article· en· W3132754405 on OpenAlexvenueno aff
Takeyasu Kawabata, Naohiko Abe, Takafumi Wakai

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyRuminationDepression (economics)Clinical psychologyDistressPsychological interventionTest (biology)CognitionDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the effect of dichotomous thinking on depression. We attempted to test the following hypotheses: 1) dichotomous thinking increases depression, and 2) dichotomous thinking has two routes to increase depression—direct, associative processing, and indirect, reflective processing. Two hundred Japanese college students (Males: 107, Females: 93, M age= 20.02 ± 1.42) were asked to complete the Dichotomous Thinking Inventory, which consists of three subscales: dichotomous belief, profit-and-loss thinking, and preference for dichotomy; the Kessler 6 Distress Scale; and the Japanese version of the Rumination-reflection Questionnaire. We conducted structural equation modelling to test the hypotheses. The results supported the hypotheses and indicated that dichotomous thinking increased depression. There were two different routes: dichotomous belief directly increased depression and profit-and-loss thinking indirectly increased depression by way of rumination. There are some implications of the findings. This study suggests that cognitive distortions might causes depression from two paths and practical interventions might also have two different routes or approaches to depression.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.044
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.019
GPT teacher head0.372
Teacher spread0.354 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Educational and Developmental PsychologySame topicAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesFrench-language works237,207