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Record W1513657261 · doi:10.1111/sjop.12226

Alexithymia and Early Maladaptive Schemas in chronic pain patients

2015· article· en· W1513657261 on OpenAlexaboutno aff
Anita Saariaho, Tom Saariaho, Aino K. Mattila, Max Karukivi, Matti Joukamaa

Bibliographic record

VenueScandinavian Journal of Psychology · 2015
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersSigne ja Ane Gyllenbergin Säätiö
KeywordsAlexithymiaPsychologyClinical psychologyChronic painToronto Alexithymia ScalePsychological interventionDepression (economics)Beck Depression InventoryPain catastrophizingSchema (genetic algorithms)PsychiatryAnxiety

Abstract

fetched live from OpenAlex

Psychological factors have an impact on subjective pain experience. The aim of this study was to explore the occurrence of alexithymia and Early Maladaptive Schemas in a sample of 271 first visit chronic pain patients of six pain clinics. The patients completed the study questionnaire consisting of the Toronto Alexithymia Scale-20, the Finnish version of the Young Schema Questionnaire short form-extended, the Beck Depression Inventory-II, and pain variables. Alexithymic patients scored higher on Early Maladaptive Schemas and had more pain intensity, pain disability and depression than nonalexithymic patients. Both alexithymia and depression correlated significantly with most Early Maladaptive Schemas. The co-occurrence of alexithymia, Early Maladaptive Schemas and depression seems to worsen the pain experience. Screening of alexithymia, depression and Early Maladaptive Schemas may help to plan psychological treatment interventions for chronic pain patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2015
Admission routes1
Has abstractyes

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