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Record W2435982538 · doi:10.1017/s1352465816000230

Self-Compassion: Evaluation of a Psychoeducational Website

2016· article· en· W2435982538 on OpenAlexaff
France Talbot, Judith Thériault, Douglas J. French

Bibliographic record

VenueBehavioural and Cognitive Psychotherapy · 2016
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsAtlantic Industries (Canada)Université de Moncton
Fundersnot available
KeywordsShameSelf-compassionRuminationPsychologyCompassionClinical psychologyPsychological interventionMental healthPsychotherapistMindfulnessSocial psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Low levels of self-compassion are associated with a number of mental health problems. Recent findings suggest that self-compassion can be significantly increased through traditional therapist led interventions such as Mindful Self-Compassion (MSC). AIMS: The goal of this study was to assess the impact of a psychoeducational website modeled on MSC on measured levels of self-compassion and two related constructs: shame and rumination. METHOD: Participants (N = 9) were recruited from a pool of university students and employees. Single case AB protocols were used. RESULTS: Analyses using the Critical Difference statistic revealed significant improvement in self-compassion and shame for the majority of participants, but limited changes in rumination. CONCLUSIONS: These preliminary findings suggest that self-compassion may be enhanced through the use of a psychoeducational website. It may be worthwhile to develop a structured internet-based treatment course for individuals who would not otherwise access traditional psychological services.

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)0.000
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 score0.801
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0380.000

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 head0.082
GPT teacher head0.394
Teacher spread0.312 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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