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Record W2787324672 · doi:10.5539/gjhs.v10n3p33

Psychopharmacological Treatment for Posttraumatic Stress Disorders in Naval Military Subjects

2018· article· en· W2787324672 on OpenAlexvenueno aff
Anderson Díaz Pérez, Elvis Eliana Pinto Aragón, Carmenza Leonor Mendoza Cataño, Moraima Del Toro Rubio, Elkin Navarro Quiroz

Bibliographic record

VenueGlobal Journal of Health Science · 2018
Typearticle
Languageen
FieldPsychology
TopicStress and Burnout Research
Canadian institutionsnot available
Fundersnot available
KeywordsPosttraumatic stressAnxietyPsychiatryNavyClinical psychologyMedical recordMedicineDepression (economics)Military personnelPsychologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Posttraumatic Stress Disorder (PTSD) is a psychiatric syndrome known since 1980 with multiple names in the military field. Its etiology is multicausal, whose predominant factor is the lack of adaptation and managing with events considered traumatic. Objective. To describe the clinical characteristics such as the type of psychological and pharmacological treatment received by the naval military with diagnosis of Posttraumatic Stress Disorder at the Psychiatric Unit of Cartagena’s Naval Hospital.METHODOLOGY: A descriptive, retrospective cross-sectional study with an associative approach (Crosstabulation). The sample was 242 navy subjects with PTSD diagnosis. The information was collected with a data collection form of medical records. The information analysis was developed through the program SPSS ® 21.0. Chi2 and value of p≤0.05 calculation was applied through the crossing of variables.RESULTS: The most prevalent type of traumatic event was the one represented by combat with the presence of depressive disorders and anxiety with a value of p≤0.05.CONCLUSIONS: The PTSD severity is related to the severity of the event, in addition if the trumatic event was repetitive.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.084
GPT teacher head0.492
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

Citations0
Published2018
Admission routes1
Has abstractyes

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