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Record W628235689 · doi:10.25365/thesis.14678

Alexithymie bei Frauen mit Inkontinenz: TAS versus LEAS!

2011· article· de· W628235689 on OpenAlexaboutno aff
Beatrice Strock

Bibliographic record

VenueUniversity of Vienna · 2011
Typearticle
Languagede
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsGynecologyPolitical sciencePsychologyMedicine

Abstract

fetched live from OpenAlex

Bei 165 Inkontinenzpatientinnen (Dranginkontinenz, Mischinkontinenz, Stressinkontinenz, Deszensus) wurde mit der Toronto Alexithymia Scale (TAS-26) und dem Levels of Emotional Awarenesse Scale (LEAS) die Alexithymie, mit dem Beck Depressions Inventar (BDI) die Depression, dem State-Trait-Anxiety Inventory (STAI) die Ängstlichkeit und dem Kings Health Questionnaire die Lebensqualität erhoben. Folgende Hypothesen resultierten als nicht signifikant: * Die 4 Diagnosegruppen unterschieden sich in der TAS-26 nicht in ihrer alexithymen Ausprägung * Die 4 Diagnosegruppen unterschieden sich in der STAI nicht in ihrer Ängstlichkeit * Die 4 Diagnosegruppen unterschieden sich im Kings Health Questionnnaire nicht in ihrer Lebensqualität Folgende Hypothesen resultierten als signifikant: * Die Gruppe der Deszensus Patientinnen hatte signifikant niedrigere emotionale Entwicklungswerte (p = 0.012) in der LEAS als die 3 anderen Diagnosegruppen. Das eta2 von 0.102 entspricht einem tendenziell hohen Effekt. Somit ist dieser Unterschied klinisch relevant. * Die Gruppe der Mischinkontinenzpatientinnen war signifikant depressiver (p = 0.039) als die Gruppe der Deszensus Patientinnen. Mit einem eta2 von 0.067 entspricht dieser Unterschied einem mittel starken Effekt und ist somit klinisch relevant. * Die TAS-26 korreliert mit der STAI und dem BDI, nicht so die LEAS- Dieses Ergebnis wirft die messmethodisch Frage auf ob beide Instrumente nicht unterschiedliche Konstrukte messen?

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)0.001
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
Metaresearch0.0010.002
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)0.0020.000

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 head0.040
GPT teacher head0.231
Teacher spread0.191 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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