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Record W2594202115 · doi:10.11588/heidok.00010218

Mentales Training in der orthopädischen Rehabilitation nach Knieendoprothetik

2010· dissertation· de· W2594202115 on OpenAlexfundno aff
Marie Ottilie Frenkel

Bibliographic record

VenueheiDOK (Heidelberg University) · 2010
Typedissertation
Languagede
FieldHealth Professions
TopicMedical Practices and Rehabilitation
Canadian institutionsnot available
FundersMcMaster University
KeywordsGynecologyRehabilitationMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Mentales Training (Eberspächer, 1990, 2007) wird als kosteneffizientes zusätzliches Mittel in der orthopädischen und der neurologischen Rehabilitation propagiert. Es stimuliert Bewegungsrepräsentationen (Neuronale Simulationstheorie, Jeannerod, 1994) und kann dadurch den Rehabilitationsprozess unterstützen. Für Patienten nach Knieendoprothetik wurde ein Mentales Trainingsprogramm ergänzt durch Spiegeltherapie (Ramachandran, 2005) konzipiert. Mehrere Evaluationsstudien untersuchten seine Effektivität. Vorrangiges Ziel war die Verbesserung der Flexion. Der Therapieverlauf von 66 Patienten (M = 63,3 Jahre, SD = 9,04) wurde über ein halbes Jahr hinweg dokumentiert. Nach der Operation trainierten die Experimentalgruppen mental und mit Spiegel, während die Kontrollgruppen im gleichen Umfang, die gleichen Übungen rein physisch übten. In der nach Random-Anordnung durchgeführten Untersuchung mit 5-maliger Messwiederholung wurden u.a. die Kriterien Flexion, Gangbild, Symptome/Funktion und Krankheitsbewältigung erhoben. Die Experimentalgruppen zeichneten sich durch signifikant bessere Werte bzgl. der Flexion aus. Mentales Training ergänzt durch Spiegeltraining stellt für die Therapie in der orthopädischen Rehabilitation einen erfolgsversprechenden Bestandteil dar.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.349
Teacher spread0.317 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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