Challenges and Implications for Menopausal Health and Help-Seeking Behaviors in Midlife Women From the United States and China in Light of the COVID-19 Pandemic: Web-Based Panel Surveys
Bibliographic record
Abstract
BACKGROUND: The global population of women of menopausal age is quickly increasing. The COVID-19 pandemic has led to an accelerated increase in the use of telehealth services, especially technological solutions targeting women's health. Understanding the factors behind midlife women's help-seeking behaviors amidst the pandemic will assist in the development of person-centered holistic telehealth solutions targeting menopausal and postreproductive health. OBJECTIVE: This study aimed to compare the factors underlying help-seeking for menopausal distress among midlife women in the United States and China. METHODS: We conducted 2 web-based panel surveys in the United States using Amazon Mechanical Turk and in China using Credamo between July and October 2022. A total of 1002 American and 860 Chinese women aged between 40 and 65 years took part in the survey. The survey was designed based on the Health Belief Model with questions related to their menopausal knowledge, perceived severity of menopausal symptoms, perceived susceptibility to menopausal distress, perceived benefits of help-seeking, perceived COVID-19- and non-COVID-19-related barriers against help-seeking, self-efficacy, and motivation to seek help. Structural equations models were fitted for the data using full information maximum likelihood to manage missing data. RESULTS: Knowledge was not directly related to help-seeking motivation in both samples. Among the Chinese sample, knowledge was negatively related to perceived severity but positively related to COVID-19-related barriers; in turn, higher perceived severity, benefits, COVID-19-related barriers, and self-efficacy and lower non-COVID-19-related barriers were related to more motivation to seek help. In the US sample, knowledge was negatively related to perceived severity, susceptibility, benefits, barriers (COVID-19- and non-COVID-19-related), and self-efficacy; in turn, higher self-efficacy, COVID-19-related barriers, and benefits were associated with more help-seeking motivation. The factors explained 53% and 45.3% of the variance of help-seeking motivation among the American and Chinese participants, respectively. CONCLUSIONS: This study revealed disparate pathways between knowledge, health beliefs, and the motivation for help-seeking among American and Chinese midlife women with respect to menopausal distress. Our findings show that knowledge may not directly influence help-seeking motivation. Instead, perceived benefits and self-efficacy consistently predicted help-seeking motivation. Interestingly, concern over COVID-19 infection was related to higher help-seeking motivation in both samples. Hence, our findings recommend the further development of telehealth services to (1) develop content beyond health education and symptom management that serves to enhance the perceived benefits of addressing women's multidimensional menopausal health needs, (2) facilitate patient-care provider communication with a focus on self-efficacy and a propensity to engage in help-seeking behaviors, and (3) target women who have greater midlife health concerns in the postpandemic era.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".