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Record W7015419505

Svensk version av Canadian Physiotherapists Arthritis Care Survey – validering och test-retest reliabilitet för användning i primärvården

2016· dissertation· en· W7015419505 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Archive (Karolinska Institutet) · 2016
Typedissertation
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupContent validityFace validityPrimary careCertificationReliability (semiconductor)ArthritisPrimary health care
DOInot available

Abstract

fetched live from OpenAlex

Patients with arthritis are often treated in a primary care setting. To study perceived knowledge and skills in arthritis care the questionnaire "Swedish version of the Canadian Physiotherapists Arthritis Care Survey" has been developed for use in rheumatology specialist care. The aim was to study whether the questionnaire were valid and reliable also for use in primary care. To assess face and content validity a focus group of eight physiotherapists working in primary care served as an expert panel. Test-retest was studied in a group of 30 physiotherapists working in primary health care and calculated with ICC /kappa. After some revision, the focus group gave the questionnaire face and content validity. Based on the focus group discussions questions not supported by the aim were removed (content of rheumatology training, certification and extended scope of practice) and four items added concerning recent education and perceived needs in the field. 95% (122/128) of
\nthe questions in the revised questionnaire achieved a "fair to good" or "excellent" test-retest reliability (37% and 58%), while 5% (6/128) were classified as "poor". In summary, the questionnaire showed acceptable validity and reliability for most questions. Some of the questions need revision before the questionnaire is used in primary care.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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