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Record W2955983405 · doi:10.1080/13651501.2019.1617883

Where does it hurt? Location of pain, psychological distress, and alexithymia among outpatients seeking psychotherapy

2019· article· en· W2955983405 on OpenAlexafffundabout
Megumi Iyar, David Kealy, Zarina A. Giannone, John S. Ogrodniczuk, Allan Abbass, Anthony S. Joyce

Bibliographic record

VenueInternational Journal of Psychiatry in Clinical Practice · 2019
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of AlbertaDalhousie UniversitySt. Paul's HospitalUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersDalhousie UniversityNova Scotia Department of Health and Wellness
KeywordsAlexithymiaAnxietyPsychiatryToronto Alexithymia ScaleDepression (economics)DistressPsychologyClinical psychologyPsychological painPain catastrophizingChronic painMedicine

Abstract

fetched live from OpenAlex

Objectives: Physical pain is prevalent among psychiatric outpatients, yet there has been little research regarding the types of pain reported. The purpose of this study was to survey outpatients seeking psychotherapy regarding pain locations and to examine associations between number of pain locations and psychiatric distress and alexithymia.Methods: Two hundred and seventeen patients were recruited from three Canadian hospitals that offer outpatient psychiatry services and short-term therapies. Participants were surveyed about their current physical pain using the Brief Pain Inventory. Participants also completed measures of psychiatric distress (Brief Symptom Inventory-18) and alexithymia (Toronto Alexithymia Scale-20).Results: The three most commonly reported pain locations were lower back, head, and neck. Findings revealed that anxiety, depression and alexithymia were associated with number of reported pain locations. Specifically, participants with three or more pain locations reported significantly higher depression, anxiety and alexithymia in comparison to those with no pain.Conclusions: Back, head and neck pains are highly prevalent among psychiatric outpatients. Multiple pain sites may reflect higher levels of psychiatric distress and greater impairment in emotional processing among psychiatric outpatients.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.021
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.024
GPT teacher head0.404
Teacher spread0.380 · 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

Citations5
Published2019
Admission routes3
Has abstractyes

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