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The Role of Sociodemographic, Clinical, Psychological, and Emotional Characteristics in the Shaping of the Motivation for Change and Readiness for Treatment in Patients with Alcohol Dependence

2024· article· en· W4403400763 on OpenAlexaboutno aff
Д. И. Громыко, A. I. Nechaeva, Yu. V. Alekseeva, D. I. Tikhomirov, А. С. Киселев, Evgeny Krupitsky, R. D. Ilyuk

Bibliographic record

VenueMedicina · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyClinical psychologyPsychotherapistDevelopmental psychology

Abstract

fetched live from OpenAlex

Introduction. Motivation for treatment is a complex and multidimensional phenomenon significantly impacting the effectiveness of medical assistance for patients with addictive disorders. An integrative assessment of biopsychosocial functioning and systematic analysis of the factors determining readiness for treatment are important directions of research aimed at understanding the formation of motivational processes in patients with alcohol dependence. Aim of the study is to determine sociodemographic, clinical, psychological and emotional characteristics of patients with alcohol dependence and with varying levels of motivation for treatment, as well as to identify predictors of readiness for change and treatment. Methods and Materials. A total of 138 patients with alcohol use disorder (F10.20; F10.21) were recruited for this cross-sectional study. Research instruments included: patients’ clinical charts, «The Stages of Change Readiness and Treatment Eagerness Scale» (SOCRATES), Differential Emotions Scale (DES), The State-Trait Anxiety Inventory (STAI), Hamilton Depression Rating Scale (HDRS), and State-Trait Anger Expression Inventory (STAXI), Attitude toward the disorder (TOBOL), Toronto Alexithymia Scale (TAS), Tests of anticipatory validity (TASPK), and Purpose-in-Life test (PIL). Results. The median age of the subjects was 27.0 years [20.0; 35.0]. Patients with low motivation for treatment (LMT), compared to subjects with medium (MMT) and high (HMT) motivation scores, were younger, displayed greater negative attitudes toward relatives, had shorter durations of substance use disorder and withdrawal symptoms, and reported fewer treatments and spontaneous remissions (p≤0.05). HMT patients had skilled jobs, longer duration of remission after treatment, and a higher ratio of remission duration to disease duration compared to LMT and MMT patients (p≤0.05). In contrast to the MMT group, the LMT participants demonstrated significantly higher levels of the emotion of contempt, alexithymia and a neurasthenic attitude toward the disorder (p≤0.05). Subjects with HMT, as opposed to LMT and MMT, had significantly lower levels of «depression», «trait anger», «trait anxiety»; while the levels of the emotion «surprise», «trait-situational anticipatory validity», «general anticipatory validity», «life performance», «I-locus of control» were significantly higher (p≤0.05). The following predictors for the readiness for change and treatment were identified: ratio of remission duration to disease duration (B1 = 57.05), skilled occupation (B2 = 2.10), emotions «surprise» (DES) (B3 = 1.81) and «contempt» (DES) (B4 = -1, 11), «trait anger» (STAXI) (B5 = -1, 72), neurasthenic attitude toward the disorder (TOBOL) (B6 = – 0.31), «general anticipatory validity» (TASPK) (B7 = 1.93), (B1, B2, .... , Bn – numbers and coefficients of predictors; multiple regression equation constant B0 = 92.35; adjusted R2 = 0.753). Conclusion. A benign course of alcohol use disorder progression, employment in a skilled job, prognostic abilities in assessing the development of life situations, and personal responsibility for one's life, as well as higher level of the emotion of surprise and low levels of anxiety, depression, anger, contempt, alexithymia, and neurasthenia, increase motivation for change and treatment in individuals with alcohol dependence.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.113

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)0.0000.000

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 head0.127
GPT teacher head0.413
Teacher spread0.286 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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