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Record W4408502646 · doi:10.2196/70226

Development of a Qigong Used for Insomnia Therapy (QUIT) Program for Improving Sleep Quality and Blood Pressure in Chinese Women With Menopause: Pre-Post Pilot Test of Feasibility

2025· article· en· W4408502646 on OpenAlexvenueno aff
Wen Li

Bibliographic record

VenueAsian/Pacific Island Nursing Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSleep qualityInsomniaMenopausePhysical therapyBlood pressureTest (biology)Sleep (system call)Internal medicinePsychiatryComputer science

Abstract

fetched live from OpenAlex

Background: Around 20%-50% of Chinese menopausal women experience insomnia, which is associated with elevated blood pressure (BP). Despite this, the population remains understudied. Qigong, a simple form of Chinese exercise, has been shown to improve insomnia and BP but has not been explicitly used to address menopausal symptoms in Chinese women. This study aims to test the feasibility of a Qigong-based intervention in enhancing sleep quality and BP control in this population. Objective: This study aimed to develop and pilot test the feasibility of a culturally sensitive Qigong Used for Insomnia Therapy (QUIT) intervention in improving sleep quality and BP among Chinese menopausal women. Methods: From August 2023 to May 2024, this study used a 1-group pretest-posttest design (N=22) to evaluate the QUIT intervention. The intervention consisted of a 10-minute Qigong demonstration video, a 10-minute practice and return demonstration and a 5-minute insomnia counseling session at baseline. Participants were instructed to engage in daily 10-minute Qigong practice for 1 month. Outcome measures, including sleep quality and BP, were assessed at baseline and at the 1-month follow-up. Data on demographics were collected via self-reported questionnaires. At the end of the study, participants were interviewed using semistructured questions to assess their perception of the intervention's feasibility. Qualitative data were analyzed using content analysis, with interviews transcribed and coded independently by the principal investigator and research assistant. Categories related to feasibility, adherence, and barriers were identified. Quantitative data were analyzed using SPSS 27.0 (IBM Corp), using descriptive statistics and paired sample t tests to assess changes in sleep quality and BP, with statistical significance set at .05. Results: The mean age of participants was 53.78 (SD 8.79, range 42-74) years. Most participants lived with relatives or friends (20/22, 91%), were employed (16/22, 73%), were married (19/22, 86%), and had at least high school education (19/22, 86%). The mean 23-item Sleep Quality Scale score significantly improved from 18.59 (SD 11.41) at baseline to 15.64 (SD 9.65; mean difference 2.96, SD 7.04; t21=1.97, P=.03) after 1 month, indicating better sleep quality (the 23-item Sleep Quality Scale was reversely scored). There was a trend toward reduced systolic BP from 115.47 (SD 14.95) at baseline to 113.59 (SD 13.93; mean difference -0.89, SD 1.64; t21=-1.15, P=.26) after 1 month. Diastolic BP also improved from 74.69 (SD 10.81) at baseline to 71.41 (SD 16.82) at 1 month (mean difference -3.28, SD 4.04; t21=-0.81, P=.43). Conclusions: The QUIT intervention was culturally sensitive, low-cost, and easy to implement. It showed significant improvements in sleep quality and trends toward reduced BP in Chinese menopausal women. Further investigation is recommended to further test the QUIT intervention to establish a robust program across different states. Once validated, the QUIT intervention may be implemented in various clinical settings to help Chinese menopausal women achieve optimal sleep quality and BP management.

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 score0.432
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.028
GPT teacher head0.361
Teacher spread0.333 · 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
Published2025
Admission routes1
Has abstractyes

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