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Record W2551917794 · doi:10.4236/psych.2016.712144

From Life’s Difficulties to Posttraumatic Growth: How Do We Get There?

2016· article· en· W2551917794 on OpenAlexaff
Michelle Redekop, Mitchell Clark

Bibliographic record

VenuePsychology · 2016
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMount Royal University
Fundersnot available
KeywordsMindfulnessPosttraumatic growthPsychologyModerationPsychotherapistClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

The concept of posttraumatic growth (PTG) suggests that the aftermath of difficult life experiences does not always pose negative consequences. In fact, there are positive outcomes, such as deepened relationships with others and a more positive self-image (Tedeschi & Calhoun, 2004). The current study assessed the relationship among difficult life experiences, mindfulness and posttraumatic growth. In order to explore the relationship among these concepts, 152 Mount Royal University students completed a battery of surveys on the current topics. Regression analyses revealed significant moderation effects for the mindfulness facets of observing, nonreacting and nonjudging. These results give some initial evidence for the life’s difficulties and PTG by using mindfulness skills. The interplay between PTG and mindfulness is relevant for clinicians dealing with populations with PTSD and adds to the literature on methods for encouraging growth.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.997

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)0.0030.008

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 head0.048
GPT teacher head0.391
Teacher spread0.344 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2016
Admission routes1
Has abstractyes

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