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Record W3109486801 · doi:10.1080/07347324.2020.1846478

Self-Esteem in 12-Step Recovery; Theoretical History, Evidence, and Implications for Future Research

2020· article· en· W3109486801 on OpenAlexaff
Austin Brown, Mariah Brennan Nanni, Onawa LaBelle

Bibliographic record

VenueAlcoholism Treatment Quarterly · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSelf-esteemPsychologySocial psychologyClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Recovery from substance use disorder is a complex process whereby an interplay of personal strengths, interpersonal relationships, and contextual factors come together to make recovery possible. New and emerging theories and definitions of recovery are prompting recovery-informed research that places a premium on operationalizing known features of the recovery process into new instruments and methods. We hypothesize that self-esteem plays a central role in the recovery process such that it may one day serve as a benchmark of recovery growth and progress. In this article, we use a secondary analysis of an existing dataset to examine self-esteem as a central intrapersonal variable in a sample of people in recovery from substance use disorder (N = 113) and identify correlates with psychological and personality factors associated with recovery. Our findings provide additional evidence that self-esteem, and correlates of self-esteem, may represent a bundle of intrapersonal psychosocial variables that should be considered as essential constructs within recovery-related research, therapeutic technique, and treatment outcome expectancies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.758

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.410
GPT teacher head0.477
Teacher spread0.067 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2020
Admission routes1
Has abstractyes

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