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Record W2783518145 · doi:10.4103/atmph.atmph_589_17

The relationship of alexithymia with depression, anxiety, stress, and fatigue among people under addiction treatment

2017· article· en· W2783518145 on OpenAlexaboutno aff
Shahrbanoo Ghahari, ShokoofehRostami Nezhad, MohammadMazloumi Rad, Nazanin Farrokhi, Fatemeh Viesy

Bibliographic record

VenueAnnals of Tropical Medicine and Public Health · 2017
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaAnxietyDepression (economics)PsychologyClinical psychologyAddictionPsychiatry

Abstract

fetched live from OpenAlex

Aim and Background: Addicted people suffer from many psychiatric disorders. Therefore, this study was conducted to examine the relationship of alexithymia with depression, anxiety, stress, and fatigue among people under addiction treatment referred to Addiction Treatment Centers in the west of Mazandaran, Iran. Materials and Methods: The research method is of correlational type. Statistical population of the study included all 20–50-year-old men referring to Addiction Treatment Centers in the west of Mazandaran. The study sample size included a cluster of 304 members who were randomly chosen among people referred to these centers at the first half of 2015. Sample members who participated in research filled out questionnaires such as Depression, Anxiety, Stress scale 21, Toronto Alexithymia Scale 20, and Fatigue Inventory of Chalder. The obtained data were analyzed using regression test through SPSS version 22 software. Findings: The findings indicated that there is a significant relationship between alexithymia with depression, anxiety, stress, and fatigue among people under addiction treatment (P

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.998

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 studies0.0010.001
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 head0.154
GPT teacher head0.422
Teacher spread0.268 · 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".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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