The need for sleep is universal, and the ability to meet this need impacts the quality of life for patients, families, and caregivers. Although substantial progress has been made in treating rare diseases, many patients have unmet medical sleep needs, and current regulatory policy makes it prohibitively difficult to address those needs medically. This opinion reviews the rare disease experience with sleep disorders and explores potential solutions. First, we provide case profiles for the rare diseases Wilson's Disease, Angelman Syndrome, and Prader-Willi Syndrome. These profiles highlight challenges in rare disease diagnosis and barriers to pinpointing disease pathophysiology, including biomarkers that intersect with sleep disorders. Second, we transition to a bird's eye view of sleep disorders and rare diseases by reporting input from a stakeholder discussion with the U.S. Food and Drug Administration regarding abnormal sleep patterns in various rare diseases. Last, in response to the profound unmet medical needs of patients with rare diseases and sleep disorders, we propose adapting and using the clinical trial design known as a "basket trial". In this case, a basket trial would include patients with different rare diseases but the same debilitating symptoms. This research approach has the potential to benefit many rare disease patients who are otherwise left with profound unmet medical needs.

Insurance companies and the Centers for Medicaid and Medicare Services are shifting from reimbursing health providers a fixed amount for a service to reimbursement based in part on patients' outcomes. This approach is called value-based care (VBC) and includes a wide range of programs. Although the behavioral health providers that have been impacted by VBC to date are primarily those in larger health systems, use of VBC is expanding as payors seek to combat rising health care costs and increase transparency and accountability for health services. Thus, behavioral health providers need to know about VBC models and their impact as well as steps they can take to be better prepared for this shift.

Boswell et al. (2022) persuasively make the case for and propose professional practice guidelines (PPG) for measurement-based care (MBC). Although the evidence for MBC is robust, implementing MBC effectively in practice requires skills and processes not discussed in the PPG. We discuss five problems with the PPG for MBC: The "what's in a name?" problem, lack of actionable actions problem, the stopwatch problem, the stock market problem, and looking for the keys under the light problem. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Emotion recognition skills and the ability to understand the mental states of others are crucial for normal social functioning. Conversely, delays and impairments in these processes can have a profound impact on capability to engage in, maintain, and effectively regulate social interactions. Therefore, this study aimed to compare the performance of 42 autistic children (Mage = 8.25 years, SD = 2.22), 45 unaffected siblings (Mage = 8.65 years, SD = 2.40), and 41 typically developing (TD) controls (Mage = 8.56 years, SD = 2.35) on the Affect Recognition (AR) and Theory of Mind (TOM) subtests of the Developmental Neuropsychological Assessment Battery. There were no significant differences between siblings and TD controls. Autistic children showed significantly poorer performance on AR when compared to TD controls and on TOM when compared to both TD controls and unaffected siblings. An additional comparison of ASD, unaffected sibling and TD control subsamples, matched on full-scale IQ, revealed no group differences for either AR or TOM. AR and TOM processes have received less research attention in siblings of autistic children and remain less well characterized. Therefore, despite limitations, findings reported here contribute to our growing understanding of AR and TOM abilities in siblings of autistic children and highlight important future research directions.

In the current healthcare climate, reimbursement for services is increasingly linked to the ability to demonstrate beneficial patient outcomes. Neuropsychology faces some unique challenges in outcomes research, namely, that neuropsychologists often do not follow patients over time and the effect of neuropsychological services on patient outcomes may not be fully realized until under another provider’s care. Yet there is an urgent need for empirical evidence linking neuropsychological practice to positive patient outcomes. To provide a framework for this research, we define a core set of patient-centered outcomes and neuropsychological processes that apply across practice settings and patient populations. Within each area, we review the available existing literature on neuropsychological outcomes, identifying substantial gaps in the literature for future research. This work will be critical for the field to demonstrate the benefit of neuropsychological services, to continue to advocate effectively for reimbursement, and to ensure high-quality patient care.

Background In the United States, more than 6 million adults live with Alzheimer disease (AD) that affects 1 out of every 3 older adults. Although there is no cure for AD currently, lifestyle-based interventions aimed at slowing the rate of cognitive decline or delaying the onset of AD have shown promising results. However, most studies primarily focus on older adults (>55 years) and use in-person interventions. Objective The aim of this study is to determine the effects of a 2-year digital lifestyle intervention on AD risk among at-risk middle-aged and older adults (45-75 years) compared with a health education control. Methods The lifestyle intervention consists of a digitally delivered, personalized health coaching program that directly targets the modifiable risk factors for AD. The primary outcome measure is AD risk as determined by the Australian National University-Alzheimer Disease Risk Index; secondary outcome measures are functional fitness, blood biomarkers (inflammation, glucose, cholesterol, and triglycerides), and cognitive function (Repeatable Battery for the Assessment of Neuropsychological Status and Neurotrack Cognitive Battery). Screening commenced in January 2021 and was completed in June 2021. Results Baseline characteristics indicate no difference between the intervention and control groups for AD risk (mean −1.68, SD 7.31; P=.90). Conclusions The intervention in the Digital, Cognitive, Multi-domain Alzheimer Risk Velocity is uniquely designed to reduce the risk of AD through a web-based health coaching experience that addresses the modifiable lifestyle-based risk factors. Trial Registration ClinicalTrials.gov NCT04559789; https://clinicaltrials.gov/show/NCT04559789 International Registered Report Identifier (IRRID) DERR1-10.2196/31841

BACKGROUND:More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. OBJECTIVE:This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. METHODS:The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. RESULTS:Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. CONCLUSIONS:This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/35442.

Symptoms of psychological distress and disorder have been widely reported in people under quarantine during the COVID-19 pandemic; in addition to severe disruption of peoples' daily activity and sleep patterns. This study investigates the association between physical-activity levels and sleep patterns in quarantined individuals. An international Google online survey was launched in April 6th, 2020 for 12-weeks. Forty-one research organizations from Europe, North-Africa, Western-Asia, and the Americas promoted the survey through their networks to the general society, which was made available in 14 languages. The survey was presented in a differential format with questions related to responses "before" and "during" the confinement period. Participants responded to the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the short form of the International Physical Activity Questionnaire. 5056 replies (59.4% female), from Europe (46.4%), Western-Asia (25.4%), America (14.8%) and North-Africa (13.3%) were analysed. The COVID-19 home confinement led to impaired sleep quality, as evidenced by the increase in the global PSQI score (4.37 ± 2.71 before home confinement vs. 5.32 ± 3.23 during home confinement) (p < 0.001). The frequency of individuals experiencing a good sleep decreased from 61% (n = 3063) before home confinement to 48% (n = 2405) during home confinement with highly active individuals experienced better sleep quality (p < 0.001) in both conditions. Time spent engaged in all physical-activity and the metabolic equivalent of task in each physical-activity category (i.e., vigorous, moderate, walking) decreased significantly during COVID-19 home confinement (p < 0.001). The number of hours of daily-sitting increased by ~2 hours/days during home confinement (p < 0.001). COVID-19 home confinement resulted in significantly negative alterations in sleep patterns and physical-activity levels. To maintain health during home confinement, physical-activity promotion and sleep hygiene education and support are strongly warranted.

Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted. Objective: We conducted an exploratory, cross-sectional study to assess feasibility of several novel digital technologies in subjects with major depressive disorder (MDD) and normal healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for MDD, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression. Methods: A cross-sectional, non-interventional study of 20 subjects with MDD and 20 normal healthy volunteers was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and novel digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, eight digital technologies were evaluated in this study. Results: Our data analysis was organized by technology – to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression. Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof of-concept clinical trials in depression and possibly other indications.

Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted.Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression.Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception.Results: Our data analysis was organized by technology – to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression.Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications.

BACKGROUND In the US, there are more than 6 million adults living with Alzheimer’s disease (AD), affecting one out of every three older adults. Currently, there is no cure for AD, though lifestyle-based interventions aimed at slowing the rate of cognitive decline and/or delaying onset of AD have shown promising results. However, most studies primarily focus on older adults (>55years) and utilize in-person interventions. OBJECTIVE Thus, the purpose of the present investigation is to determine the effects of a 2-year digital lifestyle intervention on AD risk among at-risk The lifestyle intervention consists of a digitally delivered, personalized health coaching program directly focused on targeting modifiable risk factors for AD. METHODS The lifestyle intervention consists of a digitally delivered, personalized health coaching program directly focused on targeting modifiable risk factors for AD. The primary outcome measure is AD risk as determined by the ANU-Alzheimer's Disease Risk Index (ANU-ADRI); secondary outcome measures are functional fitness, blood biomarkers (inflammation, glucose, cholesterol, triglycerides), and cognitive function (RBANS and Neurotrack Cognitive Battery). Screening began in January 2021 and ended June 2021. RESULTS Baseline characteristics indicate no difference between the intervention and control groups for AD risk (mean = -1.68 + 7.31; p = .90). CONCLUSIONS The intervention in the Digital Cognitive Multi-domain Alzheimer’s Risk Velocity (DCMARVel) is uniquely designed to reduce the risk of AD through a virtual health coaching experience that addresses modifiable lifestyle-based risk factors. CLINICALTRIAL NCT04559789

Background. The COVID-19 lockdown could engender disruption to lifestyle behaviors, thus impairing mental wellbeing in the general population. This study investigated whether sociodemographic variables, changes in physical activity, and sleep quality from pre- to during lockdown were predictors of change in mental wellbeing in quarantined older adults. Methods. A 12-week international online survey was launched in 14 languages on 6 April 2020. Forty-one research institutions from Europe, Western-Asia, North-Africa, and the Americas, promoted the survey. The survey was presented in a differential format with questions related to responses “pre” and “during” the lockdown period. Participants responded to the Short Warwick–Edinburgh Mental Wellbeing Scale, the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and the short form of the International Physical Activity Questionnaire. Results. Replies from older adults (aged >55 years, n = 517), mainly from Europe (50.1%), Western-Asia (6.8%), America (30%), and North-Africa (9.3%) were analyzed. The COVID-19 lockdown led to significantly decreased mental wellbeing, sleep quality, and total physical activity energy expenditure levels (all p < 0.001). Regression analysis showed that the change in total PSQI score and total physical activity energy expenditure (F(2, 514) = 66.41 p < 0.001) were significant predictors of the decrease in mental wellbeing from pre- to during lockdown (p < 0.001, R2: 0.20). Conclusion. COVID-19 lockdown deleteriously affected physical activity and sleep patterns. Furthermore, change in the total PSQI score and total physical activity energy expenditure were significant predictors for the decrease in mental wellbeing.

Objective: To compare the prevalence of cognitive symptoms and their functional impact by age group accounting for depression and number of other health conditions. Methods: We analyzed data from the 2011 Behavioral Risk Factor Surveillance System, a population-based, crosssectional telephone survey of US adults. Twenty-one US states asked participants (n = 131, 273) about cognitive symptoms (worsening confusion or memory loss in the past year) and their functional impact (interference with activities and need for assistance). We analyzed the association between age, depression history and cognitive symptoms and their functional impact using logistic regression and adjusted for demographic characteristics and other health condition count. Results: There was a significant interaction between age and depression (p < 0.0001). In adults reporting depression, the adjusted odds of cognitive symptoms in younger age groups ( 75 years) were comparable or greater to those in the oldest age group ( 75 years had a significantly lower adjusted odds of cognitive symptoms compared to the oldest age group with the exception of the middle-aged group where the difference was not statistically significant. Over half of adults under age 65 with depression reported that cognitive symptoms interfered with life activities compared to 35.7% of adults 65 years. Conclusions: Cognitive symptoms are not universally higher in older adults; middle-aged adults are also particularly vulnerable. Given the adverse functional impact associated with cognitive symptoms in younger adults, clinicians should assess cognitive symptoms and their functional impact in adults of all ages and consider treatments that impact both cognition and functional domains.

Researchers at Stanford University have developed a three-pronged Caring for Caregivers model that includes peer support, an integrated caregiver workflow, and virtual assistants to address unmet s...

Psychiatric symptomatology, including anxiety, partially comprise the clinical prodrome of dementia. Moreover, increased anxiety may represent a risk factor associated with neurodegenerative disease. Efficient, longitudinal measurement of anxiety remains difficult with traditional paper-pencil measures. As few digital measures of anxiety symptomatology exist, we aimed to develop and validate a digitally native, efficient and repeatable, anxiety survey to measure self-reported anxiety in adults: the Digital Choice Anxiety Survey (DCAS). Development of the DCAS included three studies: Study one included adult participants (n=407) who completed a larger set of anxiety questions, alongside the Penn State Worry Questionnaire (PSWQ) and General Anxiety Disorder 7-item (GAD-7) survey. Factor analysis then reduced the larger set of DCAS questions and investigated convergent validity and accuracy of the DCAS. Study two recruited a sub-sample of the original cohort (n=70) who completed the reduced DCAS survey to investigate convergent validity with the Geriatric Depression Scale (GDS). Study three recruited a separate sample of adults (n =58), who were administered the DCAS at baseline and again approximately two weeks after initial administration to examine test-retest reliability. Study one: Mean participant age was 42.92±12.86 years. After removing questions with a Spearman’s correlation greater than or equal to 0.6, DCAS was shortened from 20 to 7 items. The 7 items showed strong internal reliability (Cronbach’s α=0.86), with a one factor solution found utilizing factor analysis (all factors r>0.56). There were positive associations with the PSWQ and GAD-7 (r=0.82 & r=0.85), with overall accuracy of 0.93 for moderate anxiety on both PSWQ & GAD-7. Study two: Mean participant age was 48.94±14.63 years. A positive association was found between the 7-item DCAS and the GDS-15 (r=0.58, p<0.01). Study three: Mean participant age was 54.79±12.53 years. Participants completed the DCAS an average of 11.7 days apart (SD=1.2) and showed robust test-retest reliability (Pearson’s r=0.81). This study provides evidence for psychometric validity and reliability of the DCAS. Follow-up studies will investigate performance of the DCAS on clinically characterized populations and examine participant-associated meta-data.

Many older adults report difficulty performing one or more activities of daily living. These difficulties may be attributed to cognitive decline and as a result, measuring cognitive status among aging adults may help provide an understanding of current functional status. The purpose of the present investigation was to determine the association between cognitive status and measures of physical functioning. Seventy-six older adults participated in this study; 41 were categorized as normal memory function (NM) and 35 were poor memory function (PM). NM participants had significantly higher physical function as measured by Short Physical Performance Battery (SPPB; 9.4 ± 2.2 vs. 8.4 ± 2.0; p = .03) and peak velocity (0.67 ± 0.16 vs. 0.56 ± 0.19; p = .04) during a quick sit-to-stand task. Dual-task walking velocities were 22% and 126% slower between cognitive groups for the fast and habitual trials, respectively when compared to the single-task walking condition. Significant correlations existed between measures of memory and physical function. The largest correlations with memory were for peak (r = 0.42) and average (r = 0.38) velocity. The results suggest a positive relationship between physical function and cognitive status. However, further research is needed to determine the mechanism of the underlying relationships between physical and cognitive function.

To evaluate the effects of Ramadan observance on dietary intake, body mass and body composition of adolescent athletes (design: systematic review and meta-analysis; data sources: PubMed and Web of Science; eligibility criteria for selecting studies: single-group, pre-post, with or without control-group studies, conducted in athletes aged <19 years, training at least 3 times/week, and published in any language before 12 February 2020). Studies assessing body mass and/or body composition and/or dietary intake were deemed eligible. The methodological quality was assessed using ‘QualSyst’. Of the twelve selected articles evaluating body mass and/or body composition, one was of strong quality and eleven were rated as moderate. Ten articles evaluated dietary intake; four were rated as strong and the remaining moderate in quality. Continuation of training during Ramadan did not change body mass from before to the first week (trivial effect size (ES) = −0.011, p = 0.899) or from before to the fourth week of Ramadan (trivial ES = 0.069, p = 0.277). Additionally, Ramadan observance did not change body fat content from before to the first week (trivial ES = −0.005, p = 0.947) and from before to the fourth week of Ramadan (trivial ES = -0.057, p = 0.947). Lean body mass remained unchanged from before to the fourth week of Ramadan (trivial ES = −0.025, p = 0.876). Dietary data showed the intake of energy (small ES = -0.272, p = 0.182), fat (trivial ES = 0.044, p = 0.842), protein (trivial ES = 0.069, p = 0.720), carbohydrate (trivial ES = 0.075, p = 0.606) and water (trivial ES = −0.115, p = 0.624) remained essentially unchanged during as compared to before Ramadan. Continued training of adolescent athletes at least three times/week during Ramadan observance has no effect on body mass, body composition or dietary intake.

AbstractBackgroundThe rate of Alzheimer’s disease (AD) is anticipated to triple by 2050, affecting 131 million people globally. To combat this dramatic increase, it is imperative to detect early cognitive decline in order to provide timely interventions. As a result, the ability to predict cognitive status through ubiquitous functional fitness assessment would provide a cost‐effective method for identifying cognitively at‐risk older adults. This study sought to determine whether functional fitness measures could accurately predict cognitive outcomes.Method85 older adults (age: 80.93 ± 5.4) participated in the current study. Each participant completed demographic questionnaires; completed three cognitive tasks: Montreal Cognitive Assessment (MoCA), digit coding symbol test (DCS), and visual paired comparison target foil accuracy (VPCTFA) assessment; and completed six functional fitness assessments : 10‐meter maximal speed walk, dual‐task maximal speed (DTMS), dual‐task habitual speed (DTHS), sit‐to‐stand power, timed up‐and‐go (TUG), and the short physical performance battery (SPPB). Results were analyzed through three multiple linear regressions with MoCA, DCS and VPCTFA test each as the dependent variables, and age, sex, education, DTMS, DTHS, sit‐to‐stand power, TUG, and SPPB as predictor variables.ResultThe first model explained 55% of the variance of the MoCA (p < .001) with DTMS (45%; p < .001) representing the only significant predictor. The second model explained 13% of the variance of the DCS (p = .13) with age (28%; p = .01) and DTMS (23%; p = .04), representing significant predictors. The last model explained 18% of the variance of the VPCTFA (p = .007) with DTMS (21%; p = .05), TUG (21%; p = .05), 10‐meter maximal walking speed (21%; p = .05) and 4‐meter walk (SPPB variable; 22%; p = .04) representing significant predictors.ConclusionThese results suggest functional fitness assessments may predict cognitive outcomes. Functional fitness assessments accounted for more variance of MOCA scores than DCS and VPCTFA outcomes. This suggests functional fitness assessments may be better predictors of global cognition performance than performance on assessments of processing speed or working memory. Future research will investigate whether functional fitness parameters may be cost‐effective evaluation tools for predicting global cognitive performance over time.

Background Public health recommendations and government measures during the COVID-19 pandemic have enforced restrictions on daily-living. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on mental health and emotional wellbeing is undefined. Therefore, an international online survey (ECLB-COVID19) was launched on April 6, 2020 in seven languages to elucidate the impact of COVID-19 restrictions on mental health and emotional wellbeing. Methods The ECLB-COVID19 electronic survey was designed by a steering group of multidisciplinary scientists, following a structured review of the literature. The survey was uploaded and shared on the Google online-survey-platform and was promoted by thirty-five research organizations from Europe, North-Africa, Western-Asia and the Americas. All participants were asked for their mental wellbeing (SWEMWS) and depressive symptoms (SMFQ) with regard to “during” and “before” home confinement. Results Analysis was conducted on the first 1047 replies (54% women) from Asia (36%), Africa (40%), Europe (21%) and other (3%). The COVID-19 home confinement had a negative effect on both mental-wellbeing and on mood and feelings. Specifically, a significant decrease (p < .001 and Δ% = 9.4%) in total score of the SWEMWS questionnaire was noted. More individuals (+12.89%) reported a low mental wellbeing “during” compared to “before” home confinement. Furthermore, results from the mood and feelings questionnaire showed a significant increase by 44.9% (p < .001) in SMFQ total score with more people (+10%) showing depressive symptoms “during” compared to “before” home confinement. Conclusion The ECLB-COVID19 survey revealed an increased psychosocial strain triggered by the home confinement. To mitigate this high risk of mental disorders and to foster an Active and Healthy Confinement Lifestyle (AHCL), a crisis-oriented interdisciplinary intervention is urgently needed.