Prevalence and correlates of body dysmorphic disorder in health club users in the presence vs absence of eating disorder symptomology.

PURPOSE: Body dysmorphic disorder (BDD) has been consistently linked with eating disorders, however studies that stratify associations between BDD in subjects with and without eating disorder symptomology are sparse. It was, therefore, the aim of this study to assess correlates of BDD (including social media use, motivations for exercise, exercise addiction, and sexuality) stratified by eating disorder symptomology. METHODS: Cross-sectional study of 1665 health club users recruited online completed a battery of surveys. BDD prevalence rates were calculated and logistic regression models were created in two sub-samples: indicated or no-indicated eating disorder symptomology. RESULTS: The key findings showed the prevalence of BDD in participants with indicated-eating disorder symptomology was significantly higher than in participants without indicated-eating disorder symptomology, yielding an odds ratio of 12.23. Furthermore, several correlates were associated with BDD only participants with an absence of eating disorder symptomology (gender, BMI, exercise addiction, exercising for mood improvement, attractiveness and tone), with others being significantly associated with BDD in participants in the presence of indicated eating disorders symptomology (exercising for health and enjoyment, relationship status, and ethnicity). CONCLUSIONS: This study provides more evidence of the complex relationship that exists between BDD and eating disorders. Furthermore, it is recommended that practitioners working with BDD subjects should screen for eating disorders due to the high morbidity associated with eating disorders. LEVEL OF EVIDENCE: Level III: case-control analytic study.

Sexual activity and cognitive decline in older age: a prospective cohort study.

BACKGROUND: To explore the association between sexual activity and change in cognitive function over 4 years in a representative sample of older adults in England. METHODS: Data were from 1963 men and 2513 women participating in Wave 6 (2012/2013) and Wave 8 (2016/2017) of the English Longitudinal Study of Ageing. Participants reported whether or not they had engaged in any sexual activity in the last year. Cognitive function was assessed with tests of immediate and delayed recall. Adjusted general linear models were used to test associations between sexual activity and changes in cognitive function. RESULTS: Men who were sexually active at baseline had better preservation in immediate (0.18 points, 95% CI 0.07-0.29, p = 0.002) and delayed recall (0.19 points, 95% CI 0.08-0.29, p = 0.001) over 4-year follow-up. No significant associations were observed for women. DISCUSSION: Strengths of this study include large, representative sample, longitudinal design and adjustment for a wide range of potential confounders. The observational nature of our study means we cannot deduce the exact direction of effect of our findings. In addition, cognitive ability test scores in older people may reflect not only a possible decline, but also their peak prior cognitive ability; but we did not have any information regarding the trajectories of their cognitive function during the lifespan. CONCLUSION: Health practitioners should be encouraged to screen older men relating to their sexual activity to identify those who may be at risk of cognitive decline. Older men will be heartened to know that sexual activity may aid in the prevention of age-related decline in cognition.

Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps.

PURPOSE OF REVIEW: As rates of suicide continue to rise, there is urgent need for innovative approaches to better understand, predict, and care for those at high risk of suicide. Numerous mobile and sensor technology solutions have already been proposed, are in development, or are already available today. This review seeks to assess their clinical evidence and help the reader understand the current state of the field. RECENT FINDINGS: Advances in smartphone sensing, machine learning methods, and mobile apps directed towards reducing suicide offer promising evidence; however, most of these innovative approaches are still nascent. Further replication and validation of preliminary results is needed. Whereas numerous promising mobile and sensor technology based solutions for real time understanding, predicting, and caring for those at highest risk of suicide are being studied today, their clinical utility remains largely unproven. However, given both the rapid pace and vast scale of current research efforts, we expect clinicians will soon see useful and impactful digital tools for this space within the next 2 to 5 years.

Patterning Networks of Grade IV Glioblastoma on Silicon Chip.

Glioblastoma (GBM) is the most aggressive high-grade brain cancer with a median survival time of <15 months. Due to GBMs fast and infiltrative growth patient prognosis is poor with recurrence after treatment common. Investigating GBMs ability to communicate, specifically via Ca2+ signaling, within its functional tumour networks may unlock new therapeutics to reduce the rapid infiltration and growth which currently makes treatment ineffective. This work aims to produce patterned networks of GBM cells such that the Ca2+ communication at a network level can be repeatedly and reliably investigated.

Exploring the Association Between Electronic Wearable Device Use and Levels of Physical Activity Among Individuals With Depression and Anxiety: A Population Level Study.

Aim: The present study aimed to investigate the cross-sectional association between self-reported use of electronic wearable devices (EWDs) and the levels of physical activity among a representative sample of adults with depression and anxiety in the United States. Methods: For this cross-sectional study, data were pooled from the Health Information National Trends Survey 2019. A sample of 1,139 adults with self-reported depression and anxiety (60.9% women; mean age of 52.5 years) was analyzed. The levels of physical activity and prevalence of EWD utilization were self-reported. The chi-square tests were used to compare individual characteristics through the use of EWDs. Multivariable logistic regression was employed to investigate the association between EWDs and physical activity levels while adjusting for sociodemographic and health-related factors. Results: From the 1,139 adults with self-reported depression and anxiety, 261 (weighted percentage 28.1%) endorsed using EWD in the last year. After adjusting for covariates, the use of EWDs was only significantly associated with a higher odds of reporting intention to lose weight (OR 2.12; 95% CI 1.04, 4.35; p = 0.04). We found no association between the use of EWDs and meeting the national weekly recommendation for physical activity or resistance/strength exercise training. Conclusion: About three in 10 adults suffering from depression and anxiety in the United States reported using EWDs in the last year. The current study findings indicate that among people living with mental illness, EWD use is associated with higher odds of weight loss intent suggesting that EWDs may serve as an opening for the clinical interactions around physical health through identifying patients primed for behavior change. Further large-scale studies using randomized trial designs are needed to examine the causal relationships between EWDs and the physical activity of people with mental health conditions.