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Record W2556772291 · doi:10.25112/rp.v1i0.431

Using Acceptance and Mindfulness to Reduce Procrastination Among University Students: Results from a Pilot Study

2016· article· en· W2556772291 on OpenAlexaff
Frédérick Dionne

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsProcrastinationMindfulnessPsychologyApplied psychologyMedical educationSocial psychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

"Academic procrastination, the irrational tendency to delay the beginning and/or end of an academic task, is a pervasive problem for a significant number of university students. There are several cognitive and behavioral therapy (CBT) interventions for procrastination that exist but there is a lack of outcome research. There has been a recent emergence of new CBT approaches, such as Acceptance and Commitment Therapy (ACT) that use acceptance and mindfulness methods to promote behavioral change. These approaches are particularly well suited for addressing procrastination. The purpose of this article is to present data from a pilot study using acceptance and mindfulness techniques in a group intervention with university students. The hypothesis is that that the intervention would reduce procrastination and improve acceptance and mindfulness related variables. Results show that the intervention helped reduce procrastination and increase mindfulness. The intervention was also proven to be acceptable and feasible for a university student population. Future research directions and implications 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 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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.288
GPT teacher head0.548
Teacher spread0.260 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

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