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Record W4386375469 · doi:10.21203/rs.3.rs-3230563/v1

Awareness, Attitudes, and Help-Seeking Intention Towards Perinatal Depression Among Women from Different Ethnic Groups in Western Rural China

2023· preprint· en· W4386375469 on OpenAlexaboutno aff
Chunyan Deng, Bin Yan, Xingmei Du, Xiao Yan, Yan Li, Shuyan Luo, Feng Jiao, Rui Deng, Yuan Huang

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaChina Medical Board
KeywordsEthnic groupDepression (economics)ChinaChildbirthMental healthLogistic regressionInterpersonal communicationHelp-seekingMedicineQuarter (Canadian coin)DemographyPsychologyPsychiatryClinical psychologyPregnancySocial psychologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Abstract Background Despite the high prevalence of perinatal depression in China, the underutilization of mental health services remains. This study aimed at understanding the awareness, attitudes, and help-seeking intentions towards perinatal depression among women from different ethnic groups in western rural China. Methods A cross-sectional survey was conducted in a rural county of Yunnan Province in May 2022. Pregnant women and women within one year after childbirth were selected. Chi-square tests, Fisher's exact probability analyses and multiple logistic regression models were employed to investigate the determinants of women's help-seeking intentions concerning perinatal depression. Results A total of 1,217 women participated in the survey and 1,152 were included for analysis, including 464 Hanwomen (40.28%), 498 Zhuang women (43.23%), and 190 from other ethnic minorities (16.49%). There were 12.67% of women detected with perinatal depressive symptoms, while 13.89% reporting they had experienced negative emotions for more than two weeks. Among women who had negative emotions history, just 4.38% had utilized mental health services. Over a quarter (26.91%)of women had never heard of depression, and nearly half were unawareof the available treatments (49.57%) or the facilities where they could seek treatment for depression (55.21%). The most participants (84.55%) reported that they would seek help for depression if needed. For those women who displayed a willingness to seek help, 75.36% prefer to seek support from interpersonal sources and 72.07% favored consulting professionals. Factors influencing help-seeking intentions differed across different ethnic groups. Hanwomen with beliefs about the preventability and curability of depression (OR=2.679, 95%CI: 1.329-5.401) were more likely to seek help from professionals. Zhuangwomen with stronger family support were associated with a greater likelihood of seeking help (OR=2.660, 95%CI: 1.087-6.508). Other ethnic minority women with salaried employment reflected a lower potential to seek help (OR=0.044, 95%CI: 0.005-0.403). Conclusion Women from different ethnic groups in western rural China had a low level of awareness of perinatal depression and mental health services. It is of great necessity to implement educational campaigns and supportive interventions aimed at addressing the social and psychological vulnerabilities of women and attending to the unique needs of ethnic females.

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)0.001
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 score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.083
GPT teacher head0.420
Teacher spread0.337 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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