MétaCan
Menu
Back to cohort
Record W2735687359 · doi:10.1080/1034912x.2017.1346236

Effects of a Mindfulness-Based Intervention on the Perception of Basic Psychological Need Satisfaction among Special Education Students

2017· article· en· W2735687359 on OpenAlexaff
Catherine Malboeuf‐Hurtubise, Mireille Joussemet, Geneviève Taylor, Éric Lacourse

Bibliographic record

VenueInternational Journal of Disability Development and Education · 2017
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalResearch Unit on Children's Psychosocial MaladjustmentUniversité du Québec en Outaouais
Fundersnot available
KeywordsMindfulnessPsychological interventionPsychologyPerceptionIntervention (counseling)Repeated measures designSpecial educationClinical psychologyApplied psychologyMathematics education

Abstract

fetched live from OpenAlex

Mindfulness-Based Interventions (MBIs) have been increasingly implemented in schools to foster better emotional regulation skills for students with special education needs such as learning disabilities (LDs). This pilot study aimed to evaluate the impact of a MBI on the need satisfaction of elementary students with severe LDs. A prospective quasi-experimental design involving one group and two time points was employed. A sample of 14 elementary school students from a severe LDs special education class participated in this project. Repeated-measures ANOVAs were conducted and revealed a significant reduction in need satisfaction, with a large effect size (η2 = .35). Contrary to our hypothesis, the MBI appeared to be negatively related to need satisfaction among participants. These results indicate that MBIs could be linked with better self-evaluation skills in students with severe LDs, which, in turn, may change (or increase the accuracy of) the perception that children have of their own need satisfaction.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.027
GPT teacher head0.386
Teacher spread0.358 · 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.

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

Citations30
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Disability Development and EducationSame topicMindfulness and Compassion InterventionsFrench-language works237,207