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Record W2414900040 · doi:10.3109/13561820.2016.1159184

Preliminary testing of the Swedish version of the Assessment of Interprofessional Team Collaboration Scale (AITCS-S)

2016· article· en· W2414900040 on OpenAlexaff
Therese Hellman, Irene Jensen, Carole Orchard, Gunnar Bergström

Bibliographic record

VenueJournal of Interprofessional Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern University
Fundersnot available
KeywordsIntraclass correlationScale (ratio)Content validityPsychologyFace validityCeiling effectRehabilitationReliability (semiconductor)Health careApplied psychologyInternal consistencyTest (biology)PsychometricsNursingMedical educationMedicineClinical psychologyPhysical therapyAlternative medicine

Abstract

fetched live from OpenAlex

Interprofessional collaboration might improve healthcare processes and outcomes; however, it has been found that most instruments that aim to measure collaboration have undergone limited testing. The assessment of interprofessional team collaboration scale (AITCS) is one questionnaire that aims to evaluate collaboration, but it has not yet been extensively tested. The aim of this study was to translate and to cross-culturally adapt the AITCS for use in Sweden, to describe floor and ceiling values, and to investigate the AITCS in terms of reliability, face, and content validity. The study included a total of 349 participants working in team-based pain rehabilitation. The participants were asked to fill in the Swedish version of the AITCS (AITCS-S) at baseline. Of these, 73 participants also completed the AITCS-S two weeks later. The results showed that the content and face validity were good. Internal consistency varied from 0.79 to 0.96 and judged to be acceptable to excellent. Test-retest stability showed excellent stability with intraclass correlation values above 0.75 for all subscales. This study concludes that the Swedish version of the AITCS is a reliable and valid questionnaire. Further psychometric investigations might be undertaken in order to attempt to develop shorter versions of the AITCS-S.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.411
Teacher spread0.393 · 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

Citations25
Published2016
Admission routes1
Has abstractyes

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