MétaCan
Menu
Back to cohort
Record W2890417189 · doi:10.23749/mdl.v109i4.7101

Italian version of the Assessment of Interprofessional Team Collaboration Scale II (I-AITCS II): a multiphase study of validity and reliability amongst healthcare providers

2018· article· en· W2890417189 on OpenAlexaff
Rosario Caruso, Arianna Magon, Federica Dellafiore, Sara Griffini, Laura Milani, Alessandro Stievano, Carole Orchard

Bibliographic record

Venue˜La œMedicina del lavoro · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern University
Fundersnot available
KeywordsScale (ratio)Reliability (semiconductor)Health careValidityPsychologyNursingMedicinePsychometricsClinical psychologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop and validate an Italian version of the Assessment of Interprofessional Team Collaboration Scale II (I-AITCS II). METHODS: A multiphase validation study was conducted. The first phase was the AITCS-II translation from English into Italian to develop the first version of I-AITCS II for practitioners. The second phase was the study of I-AITCS II face and content validity, and the third phase was a cross-sectional data collection to provide evidence of construct validity using the psychometrics testing and the reliability assessment through the internal consistency study. RESULTS: The agreement for the forward-translation among researchers was high. The face and content validity were satisfactory. The underlying constructs of I-AITCS II were partnership, cooperation and coordination. Internal consistency was good for both scale and domains level. There were significant differences related to partnership in the comparison between settings. CONCLUSIONS: I-AITCS II showed evidence of validity and reliability. It will be useful to gather data to address programs aimed to enhance interprofessional team collaboration within the Italian healthcare contexts, and it could be used for cross-national researches.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.135
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.431
Teacher spread0.407 · 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

Citations29
Published2018
Admission routes1
Has abstractyes

Explore more

Same venue˜La œMedicina del lavoroSame topicInterprofessional Education and CollaborationFrench-language works237,207