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Record W4285089162 · doi:10.21203/rs.3.rs-1819412/v1

Translation and psychometric evaluation of the Alberta Continuity of Services Scale for Mental Health

2022· preprint· en· W4285089162 on OpenAlexaboutno aff
Felipe Agudelo‐Hernández, Helena Vélez-Botero, Rodrigo Rojas Andrade

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)Variance (accounting)Construct (python library)Context (archaeology)PsychologyExternal validityPopulationAdaptation (eye)Mental healthProcess (computing)Consistency (knowledge bases)Construct validityService (business)Social psychologyApplied psychologyComputer sciencePsychometricsGeographyClinical psychologyMedicineArtificial intelligenceMarketingBusinessCartographyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Introduction : The continuity of care and attention is considered as a process that involves an orderly attention, an uninterrupted movement of people among several elements of the system of provision of services. It does not exist enough evidence in terms of measurement instruments of this continuity in Latin America. Even globally it has been conceptualized that this matter has been abandoned repeatedly by the research teams, possibly due to the shortage of validated multidimensional measures and to the lack of studies designed to approach the inherent complexities of the service. Objective : describe the process of translation, cultural adaptation to Colombia, as well as the internal consistency and construct validity of the Alberta Continuity of Services Scale for Mental Health (ACSS-MH). Methods : This instrument was subdued to the evaluation of validity of the content by experts and this was applied to a rural population in a Colombian context. Were performed tests of internal consistency and construct validity for each of the parts of the scale. Results : Under the consensus of the expert, it is made changes on some items, looking for a better adaptability of the instrument to the linguistic characteristics of Spanish, without losing sight of the evaluation objective of each one of the items on the original questionnaire. The result of the analysis of part A converged in 5 components that explain the 69.69% of the variance with 24 Items; Similarly, the analysis of part B grouped 13 items into four components, which explain the 72.02% of the variance. Discussion : This scale could be implemented to improve the provision of mental health services in Latin American contexts, where continuity of care has presented significant difficulties.

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)0.025
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.284
GPT teacher head0.557
Teacher spread0.273 · 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 designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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