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Record W2952154595 · doi:10.5430/jnep.v9n9p73

Treatment outcome indicators of schizophrenia according to Brazilian family caregivers and outpatients

2019· article· en· W2952154595 on OpenAlexvenueno aff
Marcos Hirata Soares, Adriano Luiz da Costa Farinasso, Fernanda Ferreira Machado, Layla Karina Ferrari Ramos, Cristiane De Souza Gonçalves

Bibliographic record

VenueJournal of Nursing Education and Practice · 2019
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialInterviewMental healthPerspective (graphical)PerceptionSchizophrenia (object-oriented programming)PsychologyFamily caregiversPsychiatryClinical psychologyMedicineNursing

Abstract

fetched live from OpenAlex

Background and objective: The need to measure treatment outcomes in mental health services from the perspective of users and family members has been highlighted in the literature as a fundamental aspect to improve the care provided. The objective of this study was to measure the treatment outcome provided by a Brazilian Psychosocial Care Center from the perspective of outpatients and their family members.Methods: A correlational study was performed with 84 outpatients and 40 family members, between 2015 and 2016, interviewing them using the Satisfaction (SATIS-BR), Perception of Change (PCS), Independent Living Skills (ILSS) and Family Burden (FBIS-BR) scales.Results: There was a high index of satisfaction with the mental health service, with a mean of 4.23 for the users interviewed and 4.36 for the family members. The perception of change presented a mean of 2.58 for the patients and 2.19 for the family members. The independent living ability presented a mean of 2.52.Conclusions: The high indices of satisfaction suggest successes, as well as points to be improved in the mental health policy implemented in the municipality. However, reintegration into the labor market was presented as an aspect with a need for investments through health and labor policies, since it was related to the subjective burden.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.050
GPT teacher head0.418
Teacher spread0.368 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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