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Record W2095618120 · doi:10.5539/gjhs.v4n1p3

The Effect of Omega-3 Fatty Acids on Psychophysiological Assessment for the Secondary Prevention of Posttraumatic Stress Disorder: An Open-Label Pilot Study

2011· article· en· W2095618120 on OpenAlexvenueno aff
Kenta Matsumura, Hiroko Noguchi, Daisuke Nishi, Yutaka Matsuoka

Bibliographic record

VenueGlobal Journal of Health Science · 2011
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
FundersCore Research for Evolutional Science and Technology
KeywordsNomothetic and idiographicReactivity (psychology)Posttraumatic stressSkin conductanceHeart rateRandomized controlled trialPsychologyStressorTraumatic stressBlood pressureClinical psychologyPsychiatryInternal medicineMedicine

Abstract

fetched live from OpenAlex

Our recent pilot study has shown that the supplementation of omega-3 fatty acids (fish oil) immediately after a traumatic event may be effective toward the secondary prevention of post-traumatic disorder (PTSD). To lay the groundwork for addressing the mechanism by which omega-3 fatty acids can prevent PTSD, we analyzed its psychophysiological data. The psychophysiological data included heart rate, skin conductance, and continuous blood pressure during patient subjection to startling tones and idiographic trauma-related cues. Of the 8 patients, 1 met the diagnostic criteria for PTSD. Compared to the seven patients without PTSD, one patient with PTSD showed relatively large reactivity to the startle tones. In contrast, this patient did not show large reactivity to the trauma-related cue during script-driven imagery. The combination of psychophysiological measurements in our randomized control trial should shed light on the underlying mechanisms by which omega-3 fatty acids can prevent PTSD.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.121
GPT teacher head0.467
Teacher spread0.346 · 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 designNon-randomized trial
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

Citations9
Published2011
Admission routes1
Has abstractyes

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