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Record W2162009215 · doi:10.1159/000345357

Alexithymia and Health-Related Quality of Life in Patients with Dizziness

2012· article· en· W2162009215 on OpenAlexaboutno aff
Sonja von Rimscha, Hanspeter Moergeli, Steffi Weidt, Dominik Straumann, Stefan Hegemann, Michael Rufer

Bibliographic record

VenuePsychopathology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScalePsychologyAnxietyClinical psychologyQuality of life (healthcare)Psychological interventionDepression (economics)PsychiatryMental healthFeelingPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Alexithymia is a personality trait characterized by deficits in regulating, experiencing and verbalizing emotions and has been assumed to be associated with a tendency to express emotional arousal through somatization. Although such a tendency is often observed in patients with dizziness, the exact relationship of alexithymia to dizziness is not yet known. The aim of this study was to examine alexithymic characteristics in patients with dizziness and its relation to health-related quality of life (HRQoL). SAMPLING AND METHODS: We assessed 208 patients from an interdisciplinary center for vertigo and balance disorders for characteristics of alexithymia (20-item Toronto Alexithymia Scale), HRQoL (Short-Form 12 Health Survey, SF-12), dizziness (Dizziness Handicap Inventory), depression and anxiety (Hospital Anxiety and Depression Scale). Hierarchical regression analyses were used to evaluate the relationship between alexithymia, dizziness and HRQoL. RESULTS: We found that difficulties in identifying and describing feelings, two important factors of alexithymia, were significantly related to more severe symptoms of dizziness. More pronounced alexithymic characteristics were associated with lower HRQoL, especially in the mental dimension of the SF-12. The results remained significant after controlling for possibly confounding variables such as socioeconomic status and depression. CONCLUSIONS: These findings contribute to a better understanding of affect regulation in patients with dizziness, which is important for the development of psychotherapeutic interventions suitable for alexithymic patients with dizziness.

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 score0.001
Threshold uncertainty score0.305

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 studies0.0000.000
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 head0.045
GPT teacher head0.313
Teacher spread0.269 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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