Prevalence of ALS in all 50 states in the United States, data from the National ALS Registry, 2011-2018.

Objective: To summarize the prevalence of ALS in all 50 states and Washington, DC in the United States from 2011 to 2018 using data collected and analyzed by the National ALS Registry. In October 2010, the federal Agency for Toxic Substances and Disease Registry (ATSDR) launched the congressionally mandated Registry to determine the incidence and prevalence of ALS within the USA, characterize the demographics of persons with ALS, and identify the potential risk factors for the disease. This is the first analysis of state-level ALS prevalence estimates. Methods: ALS is not a notifiable disease in the USA, so the Registry uses a two-pronged approach to identify cases. The first approach uses existing national administrative databases (Medicare, Veterans Health Administration, and Veterans Benefits Administration). The second method uses a secure web portal to gather voluntary participant data and identify cases not included in the national administrative databases. Results: State-level age-adjusted average prevalence from 2011-2018 ranged from 2.6 per 100,000 persons (Hawaii) to 7.8 per 100,000 persons (Vermont), with an average of 4.4 per 100,000 persons in the US. New England and Midwest regions had higher prevalence rates than the national average. Conclusions: These findings summarize the prevalence of ALS for all 50 states from 2011 to 2018. This is a continuing effort to identify ALS cases on a national population basis. The establishment of the National ALS Registry has allowed for epidemiological trends of this disease and the assessment of potential risk factors that could cause ALS.

The Stress of Advancement: A Nurse Practitioner's Exploration in Providing Culturally Competent Obesity Prevention Counseling in Black Women.

BACKGROUND: Black women are diagnosed, disabled, and die from obesity and associated chronic diseases at higher rates than any other sex or race. Advanced practice registered nurses (APRN) can potentially improve culturally relevant health education and counseling by using health literacy communication tools. OBJECTIVE: Explore individualized barriers and APRNs' role in providing obesity prevention education and counseling by assessing the efficacy of the Teach-Back Method (TBM) to understand health habits and attitudes. METHODS: Black women aged 18-45, previously diagnosed as overweight or obese, and identified with perceived barriers were recruited from a predominantly Black church in Atlanta. They engaged in weekly, 1-hour educational sessions via Zoom, addressing four common barriers identified in the literature. Sessions ended with a 5-10 minute Teach-Back session. Pre- and post-intervention Readiness to Change Questionnaire (RCQ) were completed. Descriptive statistics and quantitative data from surveys and pre- and post-RCQ were analyzed. RESULTS: Twenty women completed the intervention. Paired sample t-test revealed no statistical significance or correlation between pre- and post-RCQ scores after using TBM in educational sessions. However, Pearson's correlation showed positive associations between elevated body mass index levels as one advances their education and annual income, with a p-value of 0.05. DISCUSSION: Increased rates of obesity are experienced despite higher educational attainment or pay. Stress and high-coping mechanisms contributed to disordered eating, decreased physical activity engagement, and decreased motivation toward habit change. Clinicians should be held accountable for delivering culturally sensitive care using the TBM, addressing social determinants of health, performing routine stress assessments, and checking their implicit biases.

A brief report on juvenile amyotrophic lateral sclerosis cases in the United States National ALS Registry: 2010-2018.

Juvenile ALS (jALS) is a rare form of ALS, defined as symptom onset before age 25. This report describes the demographic characteristics of confirmed and likely jALS cases in a large cohort of ALS patients ascertained in the National ALS Registry (Registry) from 2010 to 2018. Patients in the Registry must be at least 18 years of age. Of the 44 identified patients, 37.8% were diagnosed at age 24, were more likely to be nonwhite (54.5%), male (79.5%), and live in the Midwest or Northeast regions (54.5%) of the US. Some 68.9% of the jALS cases were received from federal administrative databases, and 16% came from the web portal only. Demographic characteristics for jALS cases in the Registry differed from previous publications examining ALS cases for all adults. More research is needed to better understand risk factors contributing to jALS, which could lead to earlier diagnosis and therapeutic interventions.

Community-generated solutions to cancer inequity: recommendations from transgender, non-binary and intersex people on improving cancer screening and care.

Objective: Transgender, non-binary and intersex people are less likely to receive appropriate cancer screening for their bodies and have a higher incidence of certain cancers than cisgender people. We aimed to elicit community-generated solutions to improve cancer screening for these populations. Methods and analysis: We conducted six online, asynchronous focus groups in English and Spanish with transgender, non-binary, intersex and cisgender participants who were at least 15 years of age from across the USA. Participants shared their experiences with cancer screening and related conversations with healthcare providers and recommendations for making screening practices more inclusive of their bodies and experiences. Focus group data were exported into transcripts and analysed with thematic analysis. Results: The 23 participants represented a diversity of races, genders, sexualities, ages and geographical locations. Transgender, non-binary and intersex participants, particularly Black, Indigenous and/or people of colour, reported having to self-advocate to receive necessary care by initiating conversations about screening with their providers, requesting specific screenings and educating providers about the appropriate care for their body. Notably, no white or cisgender participants described having to request relevant screenings or initiate conversations with their providers. Participants recommended that forms ask about body parts and allow for self-identification. Conclusion: The ability to properly screen patients can have a direct impact on cancer outcomes. More inclusive intake forms may alleviate the need for transgender, non-binary and intersex patients to self-advocate to receive necessary care. More work should be done to educate providers on cancer risk for transgender, non-binary and intersex individuals.

Edge Computing in Nature: Minimal pre-processing of multi-muscle ensembles of spindle signals improves discriminability of limb movements.

Multiple proprioceptive signals, like those from muscle spindles, are thought to enable robust estimates of body configuration. Yet, it remains unknown whether spindle signals suffice to discriminate limb movements. Here, a simulated 4-musculotendon, 2-joint planar limb model produced repeated cycles of five end-point trajectories in forward and reverse directions, which generated spindle Ia and II afferent signals (proprioceptors for velocity and length, respectively) from each musculotendon. We find that cross-correlation of the 8D time series of raw firing rates (four Ia, four II) cannot discriminate among most movement pairs (∼ 29% accuracy). However, projecting these signals onto their 1st and 2nd principal components greatly improves discriminability of movement pairs (82% accuracy). We conclude that high-dimensional ensembles of muscle proprioceptors can discriminate among limb movements-but only after dimensionality reduction. This may explain the pre-processing of some afferent signals before arriving at the somatosensory cortex, such as processing of cutaneous signals at the cat's cuneate nucleus.

Reports of Negative Interactions with Healthcare Providers among Transgender, Nonbinary, and Gender-Expansive People assigned Female at Birth in the United States: Results from an Online, Cross-Sectional Survey.

Over one million people in the United States are transgender, nonbinary, or gender expansive (TGE). TGE individuals, particularly those who have pursued gender-affirming care, often need to disclose their identities in the process of seeking healthcare. Unfortunately, TGE individuals often report negative experiences with healthcare providers (HCPs). We conducted a cross-sectional online survey of 1684 TGE people assigned female or intersex at birth in the United States to evaluate the quality of their healthcare experiences. Most respondents (70.1%, n = 1180) reported at least one negative interaction with an HCP in the past year, ranging from an unsolicited harmful opinion about gender identity to physical attacks and abuse. In an adjusted logistic regression model, those who had pursued gender-affirming medical care (51.9% of the sample, n = 874) had 8.1 times the odds (95% CI: 4.1-17.1) of reporting any negative interaction with an HCP in the past year, compared to those who had not pursued gender-affirming care, and tended to report a higher number of such negative interactions. These findings suggest that HCPs are failing to create safe, high-quality care interactions for TGE populations. Improving care quality and reducing bias is crucial for improving the health and well-being of TGE people.

Trends in Passive IoT Biomarker Monitoring and Machine Learning for Cardiovascular Disease Management in the U.S. Elderly Population.

It is predicted that the growth in the U.S. elderly population alongside continued growth in chronic disease prevalence will further strain an already overburdened healthcare system and could compromise the delivery of equitable care. Current trends in technology are demonstrating successful application of artificial intelligence (AI) and machine learning (ML) to biomarkers of cardiovascular disease (CVD) using longitudinal data collected passively from internet-of-things (IoT) platforms deployed among the elderly population. These systems are growing in sophistication and deployed across evermore use-cases, presenting new opportunities and challenges for innovators and caregivers alike. IoT sensor development that incorporates greater levels of passivity will increase the likelihood of continued growth in device adoption among the geriatric population for longitudinal health data collection which will benefit a variety of CVD applications. This growth in IoT sensor development and longitudinal data acquisition is paralleled by the growth in ML approaches that continue to provide promising avenues for better geriatric care through higher personalization, more real-time feedback, and prognostic insights that may help prevent downstream complications and relieve strain on the healthcare system overall. However, findings that identify differences in longitudinal biomarker interpretations between elderly populations and relatively younger populations highlights the necessity that ML approaches that use data from newly developed passive IoT systems should collect more data on this target population and more clinical trials will help elucidate the extent of benefits and risks from these data driven approaches to remote care.

Automated Urinal-Based Specific Gravity Measurement Device for Real-Time Hydration Monitoring in Male Athletes.

Acute and chronic hydration status is important for athlete safety and performance and is frequently measured by sports scientists and performance staff in team environments via urinalysis. However, the time required for urine collection, staff testing, and reporting often delays immediate reporting and personalized nutrition insight in situations of acute hydration management before training or competition. Furthermore, the burdensome urine collection and testing process often renders chronic hydration monitoring sporadic or non-existent in real-world settings. An automated urinalysis device (InFlow) was developed to measure specific gravity, an index of hydration status, in real-time during urination. The device was strongly correlated to optical refractometry with a mean absolute error of 0.0029 (±0.0021). Our results show this device provides a novel and useful approach for real-time hydration status via urinalysis for male athletes in team environments with high testing frequency demands.

Impact of a brief behavioral treatment for insomnia (BBTi) on metacognition in older adults.

INTRODUCTION: Brief (≤4 sessions) behavioral treatment for insomnia (BBTi) improves insomnia symptoms in older adults. Findings for BBTi-related improvements in objective cognition are mixed, with our recent trial reporting no effects. Metacognition (appraisal of one's own performance) has not been examined. This study examined the effects of BBTi on metacognition in older adults with insomnia. METHODS: Older adults with insomnia [N = 62, Mage = 69.45 (SD = 7.71)] were randomized to 4-weeks of BBTi (n = 32; psychoeducation, sleep hygiene, stimulus control, sleep restriction, relaxation, review/maintenance) or self-monitoring control (SMC; n = 30; social conversations). Throughout the study (2 week baseline, 4 week treatment, 2 week post-treament, 2 week 3-month followup), participants completed daily paper/pencil cognitive tasks (measuring verbal memory, attention, processing speed and reasoning) and provided daily metacognition ratings of their performance in four areas: quality, satisfaction, compared to same age peers, compared to own ability. Two-week averages of metacognitive ratings were calculated for baseline, treatment-first half, treatment-second half, post-treatment, and 3-month follow-up. Multilevel Modeling examined treatment effects (BBTi/SMC) over time on metacognition, controlling for age and sex. RESULTS: A significant group by time interaction (p = 0.05) revealed consistent improvements over time in better metacognitive ratings relative to same age peers for BBTi. Specifically, baseline ratings [mean (M) = 51.21, standard error (SE) = 3.15] improved at first half of treatment (M = 56.65, SE = 3.15, p < 0.001), maintained improvement at second-half of treatment (p = 0.18), showed additional improvement at post-treatment (M = 60.79, SE = 3.15, p = 0.02), and maintained improvement at follow-up (M = 62.30, SE = 3.15; p = 0.02). SMC prompted inconsistent and smaller improvements between baseline (M = 53.24, SE = 3.29) and first-half of treatment (M = 56.62, SE = 3.28; p = 0.004), with additional improvement at second-half of treatment (M = 59.39, SE = 3.28; p = 0.02) that was maintained at post-treatment (p = 0.73) and returned to levels observed at first-half of treatment (M = 57.78, SE = 3.21; p = 0.55). Significant main effects of time (all ps < 0.001) for other metacognition variables (Quality, Satisfaction, Compared to own ability) indicated general improvements over time for both groups. DISCUSSION: Metacognition generally improved over time regardless of treatment. BBTi selectively improved ratings of performance relative to same age peers. Repeated objective testing alone may improve metacognition in older adults with insomnia. Better understanding of metacognition and how to improve it has important implications for older adults as metacognitive complaints have been associated with mild cognitive impairment.

Using Telehealth to Deliver Family-Based Cognitive Behavioral Treatment of Insomnia in a School-Aged Child With Autism Spectrum Disorder.

Chronic insomnia (>3 months) is common in children with autism. Cognitive behavioral treatment for insomnia in children (CBT-CI) holds promise for improving sleep and daytime functioning in school-aged children with autism and their parents, but typical delivery involving multiple in-person office visits limits accessibility. This case study describes telehealth delivery of CBT-CI (teleCBT-CI) with a 7-year 4-month-old biracial boy with autism spectrum disorder (ASD) and insomnia and his parents. He and his mother wore actigraphs and completed electronic sleep diaries for 2 weeks, and his mother completed the Aberrant Behavior Checklist at pre/post/1-month follow-up. He and both of his parents completed eight telehealth treatment sessions. TeleCBT-CI improved the boy's sleep (objective, subjective) and decreased irritability, lethargy, stereotypy, and hyperactivity. This case study shows that teleCBT-CI is feasible and can improve child sleep and functioning.

Children's evaluation of Everyday Social Encounters Questionnaire: Short form validation.

This study validated a short form of the Children's Evaluation of Everyday Social Encounters Questionnaire (ChEESE-Q). Fifth- to eighth-grade children (N = 241) completed a two-vignette version of the ChEESE-Q (i.e., ChEESE-Q SF), along with measures of adjustment and affect. The ChEESE-Q SF fit the same three-factor structure as the original ChEESE-Q, with each factor-based subscale being invariant across grade and gender. Results also indicated that the ChEESE-Q could not only be shortened at the vignette level, but at the item level as well, maintaining excellent model fit with the same three factor structure. ChEESE-Q SF subscale scores demonstrated acceptable internal consistency and correlated with related constructs in expected directions. Negative information processing was associated with higher anxious and depressive symptomology and negative affect. Positive information processing was associated with lower depressive symptomology, and higher positive affect. Analysis of a secondary sample of third- to sixth-grade youth (N = 252) also demonstrated adequate test-retest reliability. This study provided validation for a shortened version of the ChEESE-Q, and more support for specific styles of information processing. Validation of a short form enables researchers to assess social information processing in a multifaceted and comprehensive, yet resource-efficient way. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Effect of cognitive behavioural therapy on sleep and opioid medication use in adults with fibromyalgia and insomnia.

Sleep and opioid medications used to treat insomnia and chronic pain are associated with adverse side effects (falls and cognitive disturbance). Although behavioural treatments such as cognitive behavioral therapy for insomnia (CBT-I) and pain (CBT-P) improve sleep and clinical pain, their effects on sleep and opioid medication use are unclear. In this secondary analysis of published trial data, we investigated whether CBT-I and CBT-P reduced reliance on sleep/opioid medication in patients with fibromyalgia and insomnia (FMI). Patients with FMI (n = 113, Mage  = 53.0, SD = 10.9) completed 8 weeks of CBT-I (n = 39), CBT-P (n = 37) or waitlist control (WLC; n = 37). Participants completed 14 daily diaries at baseline, post-treatment and 6-month follow-up, assessing sleep and opioid medication usage. Multilevel modelling examined group by time effects on days of medication use. A significant interaction revealed CBT-P reduced the number of days of sleep medication use at post-treatment, but usage returned to baseline levels at follow-up. There were no other significant within- or between-group effects. CBT-P led to immediate reductions in sleep medication usage, despite lack of explicit content regarding sleep medication. CBT-I and CBT-P may be ineffective as stand-alone treatments for altering opioid use in FMI. Future work should explore CBT as an adjunct to other behavioural techniques for opioid reduction.

Preparedness and Community Resilience in Disaster-Prone Areas: Cross-Sectoral Collaborations in South Louisiana, 2018.

Objectives. To determine how community-based organizations (CBOs) define priorities for bolstering community resilience, challenges in addressing these priorities, and strategies to address challenges.Methods. The Community Resilience Learning Collaborative and Research Network (C-LEARN) is a multiphase study examining opportunities to improve community resilience to the threats of disaster and climate change in South Louisiana. Phase I of C-LEARN involved using the National Health Security Strategy and Implementation Plan for directed content analysis of key informant interviews with CBO representatives from 47 agencies within South Louisiana between February and May 2018.Results. CBO interviewees highlighted the importance of forging relationships and building trust through diverse cross-sector collaborations and partnerships before disasters. Such collaborations and partnerships were shown to tailor disaster response to the needs of particular communities and populations as well as address key challenges such as gaps in information, services, and resources.Conclusions. Our results encourage a culture of community resilience and community preparedness through partnerships and community-engaged strategies. C-LEARN will utilize the results of our interviews in the design of phase II of our agency-level coalition-building intervention.

An Analytical Approach to Posture-Dependent Muscle Force and Muscle Activation Patterns.

Personalized training by taking into account individual anatomy to improve performance is a research frontier. In this paper, we first introduce an analytical method to study the pattern of changes in muscle forces as a function of posture. Our method is also able to analyze variation of maximal muscle force and muscle activation values (in various postures) as a result of posture-dependent changes in moment arms. This method also helps us evaluate the utility of person specific training. It also provides us with model based approximations for activation and muscle force patterns during different motions without a need for subject recordings, which enables athletes to have a better understanding of how each muscle contributes during each posture, in a fast and efficient way. Second, we analyze the results of this method for a simple squat move. Our results show that both maximal muscle force and muscle activation values have variable sensitivity to the moment arm values for different postures and muscles. It suggests that individually modified training plans could likely improve performance for some sets of movements.