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Record W7060917799

O cuidado familiar à pessoa idosa com transtorno mental: Modelo Calgary de avaliação da família

2020· dissertation· pt· W7060917799 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2020
Typedissertation
Languagept
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGenogramData collectionPresentation (obstetrics)Qualitative researchElderly peopleParticipant observationQualitative analysis
DOInot available

Abstract

fetched live from OpenAlex

Descriptive-exploratory research with a qualitative approach in order to analyze family care provided to elderly people with mental disorders. The study was carried out in one of the nine regional offices in the city of Belo Horizonte, with 326 elderly participants attended at CERSAM, between July 2017 and June 2019, and seven relatives of three of those elderly people who were being treated at the service. Data collection took place in three stages: document analysis on physical records, for data collection at CERSAM, with subsequent drawing carried out among the elderly undergoing treatment, followed by document analysis on the municipality's Health Management Information System and, for Finally, semi-structured interviews with family members, at home. To organize the data collected during document analysis, Excel tables and the digitization of some documents were used by the CamScanner application. The interviews were recorded, transcribed and coded. The analysis steps proposed by Yin (2005) followed, of examining, categorizing and recombining the evidence to address the study's propositions. It should be noted that the Calgary Family Assessment Model (MCAF) was used as a theoretical-methodological framework for the study, from the elaboration of the interview script to the case analysis, using the graphic representations of genogram and ecomap in the presentation of the results. Ethical precepts were respected and the names described in the work are fictitious. The results were presented in five chapters, including the characterization of the 326 elderly people attended at CERSAM, 63,2% of whom were female, with an average age of 68,06, aged between 60 and 94 years old, with a predominance of the 60 to 69 years in 65,64%. As for education, 43,75% had between one and four years of study, 45,3% were married, 46,11% were housewives and 35% retired, and 32,82% had long-term follow-up at CERSAM. The three cases had similarities in the family configuration: two were extended families and one consanguineous, with great influence of siblings in the care. The diagnoses of mental disorder occurred after the age of thirty, in the cases of Rosa and Lorenzo, and before the age of 25, in the case of Alvarez. The prevalence of diagnoses of mental disorders in other family members in the three cases is emphasized, all of them being brothers of the elderly. The three were young elderly and only Rosa had other chronic pathologies that triggered dependency, although their dependence was related to instability associated with mental disorder. This fact, which together with the family's lack of preparation and knowledge about the disease, worsened the burden and prevalence of negative bonds in the family of this elderly woman. For family care for the elderly with a mental disorder, there were needs to adapt the family, with stability, organization and dedication to know the disease and the elderly themselves. There was also a lack of support for health and social services in the care of the elderly with mental disorders and their families. It is expected that this study will contribute to the knowledge about the care of family members to this public, and to mobilize the State through policies and services of continuous care. Also, to direct the actions of health professionals, especially nurses, with the use of the MCAF, for planning interventions, guidelines and preparing a care plan for the elderly and family caregivers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0030.003
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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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