The effectiveness of mobile app usage in facilitating weight loss: An observational study.

Aim: With increasing rates of global obesity and associated health issues, there is an ever-increasing need for weight management solutions to be more accessible. Mobile applications offer accessible support systems and have the potential to offer a viable and effective weight management solution as an alternative to traditional healthcare models. Objective: To evaluate the effectiveness of the SIMPLE mobile application for time-restricted eating in achieving weight loss (WL). Methods: User data were analyzed between January 2021 and January 2023. In-app activity was calculated as the proportion of active days over 12, 26 and 52 weeks. A day is considered active if it contains at least one in-app action (e.g., logging weight, food, fasting, or physical activity). Users were categorized into four in-app activity levels: inactive (in-app activity <33%), medium activity (33%-66%), high activity (66%-99%), and maximal activity (100%). Weight change among in-app activity groups was assessed at 12, 26, and 52 weeks. Results: Out of 53,482 users, a positive association was found between the use of the SIMPLE app and WL. Active app users lost more weight than their less active counterparts. Active users had a median WL of 4.20%, 5.04%, and 3.86% at 12, 26, and 52 weeks, respectively. A larger percentage of active users-up to 50.26%-achieved clinically significant WL (≥5%) when compared to inactive users. A dose-response relationship between WL and app usage was found after adjusting for gender, age, and initial Body Mass Index; a 10% increase in app activity correlated with increased WL by 0.43, 0.66 and 0.69 kg at 12, 26, and 52 weeks, respectively. Conclusions: The study demonstrates that the SIMPLE app enables effective WL directly associated with the level of app engagement. Mobile health applications offer an accessible and effective weight management solution and should be considered when supporting adults to lose weight.

Longitudinal associations between women's cycle characteristics and sexual motivation using Flo cycle tracking data.

In the current research, we used data from a sample of 16,327 menstrual cycle tracking app users to examine the association between menstrual cycle characteristics and sexual motivation tracked over 10 months of app use. Guided by past work that finds links between menstrual cycle characteristics related to conception risk and sexual motivation, we found that (a) between-women, shorter (r = - 0.04, p = 0.007), more regular cycles predicted small increases in sexual motivation (r = - 0.04, p = 0.001); (b) within-women, shorter cycles predicted greater sexual motivation that month (r = - 0.04, p < 0.001) and (c) the next month (ßs: - 0.10 to - 0.06, ps < 0.001), but (d) changes in sexual motivation did not reliably precede changes in cycle length (ßs: - 0.01 to 0.02, ps > 0.15). Within-woman analyses also revealed that (e) shorter cycles were followed by more frequent reports of fatigue (ß = - 0.06, p < 0.001), insomnia (ß = - 0.03, p < 0.001), and food cravings (ß = - 0.04, p < 0.001). Together, results suggest that menstrual cycles characteristics and sexual motivation may covary together in ways that reflect changing investments in reproduction. Small effect sizes and lack of experimental control warrant cautious interpretations of results.

Premenstrual symptoms across the lifespan in an international sample: data from a mobile application.

Premenstrual symptoms, including physical and mood symptoms, affect a large proportion of women worldwide. Data on premenstrual symptoms across nations and age groups is limited. In the present study, we leveraged a large international dataset to explore patterns in premenstrual symptom frequency with age. A survey was administered to users of the Flo mobile application (app), aged 18 to 55. The survey queried app users about a range of premenstrual symptoms. Respondents were asked whether they experienced each symptom every menstrual cycle, some cycles, or never. Age was also captured and categorized as 18-27, 28-37, 38-47, 48-55. Data was summarized and Pearson's chi square test for count data assessed differences in symptom frequency by age group. A sample of 238,114 app users from 140 countries responded to the survey. The most common symptoms reported were food cravings (85.28%), mood swings or anxiety (64.18%), and fatigue (57.3%). Absentmindedness, low libido, sleep changes, gastrointestinal symptoms, weight gain, headaches, sweating or hot flashes, fatigue, hair changes, rashes, and swelling were significantly more frequent with increasing age (p's < 0.001). Mood swings and anxiety did not vary by age group. Of the respondents, 28.61% reported that premenstrual symptoms interfered with their everyday life each menstrual cycle. In a large international sample, the majority of women reported premenstrual food cravings, mood changes, and fatigue every menstrual cycle. Mood symptoms did not vary by age group, suggesting that premenstrual mood changes are a persistent issue among women of reproductive age.

Rates of self-reported postpartum depressive symptoms in the United States before and after the start of the COVID-19 pandemic.

BACKGROUND: This study aimed to determine the relationship between the start of the COVID-19 pandemic and changes in postpartum depressive symptoms (PDS) in individuals in the United States. Further analyses explored how these changes related to state-level measures of pandemic severity, economic hardship, and social isolation. METHODS: Data were collected from users of the Flo mobile health application who completed a survey about their mood within 90 days of giving birth. Analyses assessed changes in national and state-level self-reported PDS from a pre-pandemic period (N = 159,478) to a pandemic period (N = 118,622). Linear regression determined which state-level pandemic severity or economic factors were associated with changes in PDS. RESULTS: National rates of PDS increased from 6.5% (pre-pandemic) to 6.9% (pandemic). There was a significant increase in PDS over the course of the pandemic timeframe. Linear regressions revealed a negative association between percent change in PDS across states and COVID-19 deaths per 100 K residents as well as 2020 women's unemployment rate. There was no association between change in PDS and COVID-19 cases per 100 K residents, percent job loss, percent change in women's unemployment rate, or percentage of population staying at home. CONCLUSIONS: There was a national increase in PDS that worsened over the course of a year following the start of the COVID-19 pandemic. States with a greater increase in PDS tended to show overall fewer deaths from COVID-19 and lower women's unemployment rates. Further work is needed to identify what individual-level factors may be driving these differences.

Risk factors associated with postpartum depressive symptoms: A multinational study.

OBJECTIVE: To evaluate the association between maternal age, parity, gestational number (singleton vs twin), newborn gender and self-reported postpartum depressive symptoms (PDS) in a large multinational sample using survey data from a digital telephone application. METHODS: Women using the Flo app answered a survey (available in 10 languages) from January 2018 to April 2020. A survey question asking about emotional state was used to determine the presence of PDS. Chi-squared statistics were used to compare groups. A weighted mean prevalence was calculated based upon the socioeconomic status and reproductive population of each country in 2020. RESULTS: Over a million women from 138 countries participated. Of all respondents, 9.4% endorsed PDS. The weighted mean prevalence of PDS was 11%. We found that PDS decreased with advancing age. First-time mothers reported higher rates of PDS. Twin births were associated with a higher symptom burden than singleton births and mothers of twins in the oldest age group reported the greatest burden. We did not find a clinically significant difference in rates of PDS between mothers of singleton girls and boys. CONCLUSIONS: To our knowledge, this study is the first to examine risk factors for postpartum symptoms using the same survey across a large international population. These results can further research and clinical aims to identify and treat maternal depression more effectively. LIMITATIONS: Data was aggregated, thereby limiting analysis of individual associations. The survey was self-report and not diagnostic for postpartum depression. Generalizability of risks of postpartum depression should be approached with caution.

Characterization of polycystic ovary syndrome among Flo app users around the world.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex and multi-faceted endocrine disorder that affects 5-20% of women. Literature is limited regarding potentially differing PCOS phenotypes among women around the world. OBJECTIVE: To use Flo app technology to understand the multifaceted characteristics of PCOS across several countries and identify contributing risk factors to the development of this condition. STUDY DESIGN: Flo is a widely used female health and wellbeing app with period tracking functionality that provides a globally representative and medically unbiased perspective on PCOS symptomatology. A chatbot dialog on PCOS was subsequently administered on the Flo application (app) to users from 142 countries (with at least 100 respondents) who have the app running in English during September-October 2019. RESULTS: For analyses, we selected the five countries with the greatest number of respondents: US (n = 243,238), UK (n = 68,325), India (n = 40,092), Philippines (n = 35,131), and Australia (n = 29,926). Bloating was the most frequently reported symptom among PCOS-positive women and appeared to be the main predictor of PCOS in our model (odds ratio 3·76 [95% CI 3·60-3·94]; p < 0·0001). Additional top predictors of PCOS are high blood cholesterol and glucose levels. As BMI increased, the percentage of women who reported a physician-confirmed PCOS diagnosis also increased. However, women in India did not follow this trend. CONCLUSION: Our findings are based on the largest known PCOS dataset and indicate that symptoms are more complex than previously understood. The most frequently reported symptoms (bloating, facial hirsutism, irregular cycles, hyperpigmentation, and baldness) are broader than those included in the Rotterdam criteria. Future work should reevaluate and refine the criteria utilized in PCOS diagnosis.