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Record W2799524285 · doi:10.1080/00220671.2018.1448749

Evaluating the effectiveness of a mindfulness coloring activity for test anxiety in children

2018· article· en· W2799524285 on OpenAlexaff
Dana Carsley, Nancy L. Heath

Bibliographic record

VenueThe Journal of Educational Research · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsMindfulnessPsychologyClinical psychologyAnxietyPsychological interventionIntervention (counseling)Test (biology)CorrelationPsychiatry

Abstract

fetched live from OpenAlex

The authors investigated the effectiveness of a mindfulness art activity compared with a free draw/coloring activity on test anxiety in children. The sample consisted of 152 students (50% female; Mage = 10.38 years, SD = 0.88 years) randomly assigned to a mindful (n = 76) or free (n = 76) group. Participants completed a standardized measure of anxiety and state mindfulness before and after the coloring activity, immediately before a spelling test, as well as a measure of dispositional mindfulness. Results revealed an overall significant decrease in test anxiety and an overall significant increase in state mindfulness following the interventions. Furthermore, although a significant negative correlation was found between dispositional mindfulness and change in state mindfulness pre- and post-coloring intervention, a significant positive correlation was found between dispositional mindfulness and pre-intervention state mindfulness, suggesting a possible ceiling effect. Explanations for these findings and implications for school personnel and future research are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0020.000

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 head0.257
GPT teacher head0.507
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2018
Admission routes1
Has abstractyes

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