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Record W1422950665 · doi:10.3233/zmp-2008-17_4_03

Die Entwicklung und Evaluation von Interventionen zur Förderung Partizipativer Entscheidungsfindung – Rahmenkonzept und Messinstrumente

2008· article· en· W1422950665 on OpenAlex
Daniela Simón, Andreas Loh, Martin Härter

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZeitschrift für Medizinische Psychologie · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

In recent years shared decision making (SDM) has gained importance as an appropriate approach for patient-physician communication and health related decision-making. The benefits of SDMconcerning patient satisfaction, treatment adherence or reduction of decisional conflict have been shown in several studies using interventional approaches on both the patients’ and physicians’ side. This article introduces the Ottawa Decision Support Framework (ODSF) as a theory-based guidance for the design and evaluation of SDM interventions such as patient decision aids, training of health professionals or patient education. Its key elements are assessment of decisional needs, provision of decision support and evaluation of decision process and outcome. In addition this article presents an allocation of available psychometric instruments for measuring dimensions of the framework. Most of them stem from Englishspeaking countries and have been translated into German. The Ottawa Decision Support Framework can be used for the development of SDM interventions and associated evaluation strategies. Evaluation measures can be chosen from a variety of instruments, yet many of them still need to show their psychometric quality in further studies.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.406
GPT teacher head0.535
Teacher spread0.129 · 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