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Record W2124629692 · doi:10.5539/gjhs.v6n2p203

Psychological Symptoms in Family Members of Brain Death Patients in Intensive Care Unit in Kerman, Iran

2014· article· en· W2124629692 on OpenAlexvenueno aff
Hakimeh Hosseinrezaei, Motahare Pilevarzadeh, Masoud Amiri, Hossin Rafiei, Sedigheh Taghati, Mosadegheh Naderi, Mohammad Moradalizadeh, Milad Askarpoor

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyDepression (economics)MedicineIntensive care unitPsychiatryFamily memberDeath anxietyFamily medicine

Abstract

fetched live from OpenAlex

AIM: Having patients in Intensive Care Unit (ICU) remains an extremely stressful live event for family members, especially for those having to confront with brain death patients. The aim of present study was to determine the prevalence of depression, anxiety and stress among relatives of brain dead patients in ICU in Kerman, Iran. METHODS: In a cross-sectional study, using DASS- 42 questionnaire, the symptoms of depression, anxiety and stress of family members of brain death patients were explored in Kerman, Iran. RESULTS: Of 244 eligible family members, 224 participated in this study (response rate of 91%). Generally, 76.8%, 75% and 70.1% of family members reported some levels of anxiety, depression and stress, respectively. More specifically, the rate of severe levels of anxiety, depression and stress among the participants were 48.7%, 33%, and 20.1% respectively. CONCLUSION: Prevalence of depression, anxiety and stress in family members of brain death patients in ICU remains high. Health care team members, especially nurses, should be aware and could consider this issue in the caring of family members of brain death patients.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.449
Teacher spread0.338 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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