Exploratory factor and confirmatory analyses of the polycystic ovary syndrome health-related quality of life questionnaire (PCOSQ-50).

BACKGROUND: A condition-specific instrument is necessary to measure the health-related quality of life among those with polycystic ovary syndrome (PCOS), the most common chronic endocrinopathy among women. The first instrument was developed in 1988, followed by several revisions. However, further recommendations from all versions include additional application and measurement among different cultural populations of women with PCOS and psychometric testing based on use among larger samples of women with PCOS. Thus, the purpose of this study was to explore the factor structure of the Polycystic Ovary Syndrome Questionnaire (PCOSQ-50) using an international cross-sectional survey data from women with PCOS aged 18-42 years. METHODS: Using data from the largest known international cross-sectional study of women with PCOS aged 18-42 years (n = 935) to date, exploratory factor and confirmatory analyses were conducted for the PCOSQ-50, followed by factor labeling using a thematic analysis approach. RESULTS: Respondents were 31.0 ± 5.8 years of age, mostly White (72%), well-educated (56% had a college degree), married (69%), and employed full-time (65%). Three-quarters (74%) of the sample had one or more chronic conditions in addition to PCOS. Approximately 20% of the respondents originated from countries such as the United Kingdom, Australia, South Africa, etc. The PCOSQ-50 demonstrated good reliability but may be best described using a 7-factor model. The 7-factor model revealed goodness-of-fit. Thematic analysis suggested the following labels of those seven factors: hirsutism, fertility, isolation/trepidation, sexual function, self-esteem, emotional, and obesity. CONCLUSION: More research is needed to adapt the current PCOSQ-50, as well as to create an age-appropriate PCOS-specific HRQoL instrument for peri-postmenopausal women with PCOS.

Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step.

The characterization of human behavior in real-world contexts is critical for developing a comprehensive model of human health. Recent technological advancements have enabled wearables and sensors to passively and unobtrusively record and presumably quantify human behavior. Better understanding human activities in unobtrusive and passive ways is an indispensable tool in understanding the relationship between behavioral determinants of health and diseases. Adult individuals (N = 60) emulated the behaviors of smoking, exercising, eating, and medication (pill) taking in a laboratory setting while equipped with smartwatches that captured accelerometer data. The collected data underwent expert annotation and was used to train a deep neural network integrating convolutional and long short-term memory architectures to effectively segment time series into discrete activities. An average macro-F1 score of at least 85.1 resulted from a rigorous leave-one-subject-out cross-validation procedure conducted across participants. The score indicates the method's high performance and potential for real-world applications, such as identifying health behaviors and informing strategies to influence health. Collectively, we demonstrated the potential of AI and its contributing role to healthcare during the early phases of diagnosis, prognosis, and/or intervention. From predictive analytics to personalized treatment plans, AI has the potential to assist healthcare professionals in making informed decisions, leading to more efficient and tailored patient care.

Exploring the Experiential Journey of Women with PCOS Across the Lifespan: A Qualitative Inquiry.

Introduction: Peri-postmenopausal women with the chronic condition polycystic ovary syndrome (PCOS) remain at cardiometabolic risk and/or subsist with established comorbidity while continuing to manage persistent PCOS signs and symptoms, such as hirsutism. Thus, PCOS transcends the reproductive years, yet there is sparse scientific literature on the peri-postmenopausal years of women with PCOS. Purpose: To explore how peri-postmenopausal women's perceptions about PCOS have changed over the lifespan since their PCOS diagnosis. Methods: A cross-sectional survey with one qualitative question was conducted via Research Electronic Data Capture (REDCap) among women with PCOS aged ≥43 years, who were all recruited from PCOS-specific Facebook pages. Of the 107 women completing the survey, 72 substantively answered the qualitative question. The qualitative responses were analyzed using the steps of reflexive thematic analysis. Themes were interpreted and discussed through the lens of the bioecological conceptual model. Results: Respondents were 47.6 (±4.1) years of age, primarily White (87.5%), employed full time (65.3%), and married (75%) with children (68%). Four overall themes were identified: 1) dismissal 2) information desert, 3) PCOS experience over the lifespan, and 4) mindset. Conclusion: The study findings illustrated the unique healthcare needs among peri-postmenopausal women with PCOS. Further research is needed to further explore their healthcare concerns and psychosocial needs followed by studies that develop and assess interventions that promote symptom and adaptive coping strategies across their lifespan.