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Record W2609128069 · doi:10.14740/jocmr3009w

Effect of Acupressure, Acupuncture and Moxibustion in Women With Pregnancy-Related Anxiety and Previous Depression: A Preliminary Study

2017· article· en· W2609128069 on OpenAlexvenueno aff
Shunji Suzuki, Chiharu Tobe

Bibliographic record

VenueJournal of Clinical Medicine Research · 2017
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcupressureMoxibustionAnxietyAcupunctureDepression (economics)PregnancyTraditional medicineObstetricsPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In this preliminary study, we examined the effect of acupressure, acupuncture and moxibustion (oriental treatments) to prevent of the relapse/deterioration of perinatal depression in women with pregnancy-related anxiety and previous depression. METHODS AND RESULTS: Between 2014 and 2016, there were 48 women with pregnancy-related anxiety and previous depression who had delivery at ≥ 22 weeks' gestation in our institute. Of these, oriental treatments were performed in eight and two women (totally 10, 21%) during pregnancy and postpartum, respectively. One of the 10 (10%) who received oriental treatments admitted depressive symptoms during pregnancy or postpartum, while 18 of the rest 38 who did not receive oriental treatments admitted depressive symptoms (47%, P = 0.065). CONCLUSION: The oriental treatments may be useful for pregnant women who need perinatal mental health care.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.074
GPT teacher head0.498
Teacher spread0.424 · 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

Citations15
Published2017
Admission routes1
Has abstractyes

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