Readiness to change and commitment as predictors of therapy compliance in adolescents with Delayed Sleep-Wake Phase Disorder

© 2018 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ 12 month embargo from date of publication (Dec 2018) per publisher’s policyObjectives Recent evidence indicates that adolescents' motivation to change sleep-wake patterns is low, despite significant impact of adolescent sleep problems on many areas of daytime functioning. The aim of the present study is to evaluate components of adolescents' motivation, and subsequent changes in behaviour. Methods Fifty-six adolescents, aged 13–23 (M = 15.8 ± 2.3 y; 38% m) diagnosed with Delayed Sleep-Wake Phase Disorder (DSWPD) underwent three therapy sessions involving bright light therapy to phase advance sleep patterns. Adolescents were instructed to advance wake-up times by 30-min daily. Motivation ratings of desire, ability, reason, need and commitment to change sleep patterns were taken at baseline. Sleep diaries were taken at the end of treatment session 1, with sequentially earlier wake-up times in 30-min intervals indicating compliance. Results At the outset of therapy, adolescents indicated strong desire, reasons and need, yet moderate ability and commitment to advance their sleep-wake patterns. Following therapy, sleep-onset times were significantly advanced, total sleep time increased and sleep latency decreased (all p 0.05). Adolescents' desire to change (r = 0.30, p = 0.03) and commitment (r = 0.30, p = 0.03) were positively correlated with behaviour change, but their need, ability and reasons were not. A mediation analysis showed that ability and desire were important in predicting behaviour change, by total effects through commitment (ie, indirectly and directly). Conclusion Our findings suggest that the total effects of ability (ie, confidence) and desire to change are the best predictors of behavioural changes, thus clinicians should focus on these components of the readiness to change model when undertaking treatments with sleep-disordered adolescents

Differences in adolescent activity and dietary behaviors across home, school, and other locations warrant location-specific intervention approaches

Background Investigation of physical activity and dietary behaviors across locations can inform “setting-specific” health behavior interventions and improve understanding of contextual vulnerabilities to poor health. This study examined how physical activity, sedentary time, and dietary behaviors differed across home, school, and other locations in young adolescents. Methods Participants were adolescents aged 12–16 years from the Baltimore-Washington, DC and the Seattle areas from a larger cross-sectional study. Participants (n = 472) wore an accelerometer and Global Positioning Systems (GPS) tracker (Mean days = 5.12, SD = 1.62) to collect location-based physical activity and sedentary data. Participants (n = 789) completed 24-h dietary recalls to assess dietary behaviors and eating locations. Spatial analyses were performed to classify daily physical activity, sedentary time patterns, and dietary behaviors by location, categorized as home, school, and “other” locations. Results Adolescents were least physically active at home (2.5 min/hour of wear time) and school (2.9 min/hour of wear time) compared to “other” locations (5.9 min/hour of wear time). Participants spent a slightly greater proportion of wear time in sedentary time when at school (41 min/hour of wear time) than at home (39 min/hour of wear time), and time in bouts lasting ≥30 min (10 min/hour of wear time) and mean sedentary bout duration (5 min) were highest at school. About 61% of daily energy intake occurred at home, 25% at school, and 14% at “other” locations. Proportionately to energy intake, daily added sugar intake (5 g/100 kcal), fruits and vegetables (0.16 servings/100 kcal), high calorie beverages (0.09 beverages/100 kcal), whole grains (0.04 servings/100 kcal), grams of fiber (0.65 g/100 kcal), and calories of fat (33 kcal/100 kcal) and saturated fat (12 kcal/100 kcal) consumed were nutritionally least favorable at “other” locations. Daily sweet and savory snacks consumed was highest at school (0.14 snacks/100 kcal). Conclusions Adolescents’ health behaviors differed based on the location/environment they were in. Although dietary behaviors were generally more favorable in the home and school locations, physical activity was generally low and sedentary time was higher in these locations. Health behavior interventions that address the multiple locations in which adolescents spend time and use location-specific behavior change strategies should be explored to optimize health behaviors in each location

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Location-specific psychosocial and environmental correlates of physical activity and sedentary time in young adolescents: preliminary evidence for location-specific approaches from a cross-sectional observational study.

BackgroundA better understanding of the extent to which psychosocial and environmental correlates of physical activity are specific to locations would inform intervention optimization.PurposeTo investigate cross-sectional associations of location-general and location-specific variables with physical activity and sedentary time in three common locations adolescents spend time.MethodsAdolescents (N&nbsp;= 472,Mage&nbsp;= 14.1,SD = 1.5) wore an accelerometer and global positioning systems (GPS) tracker and self-reported on psychosocial (e.g., self-efficacy) and environmental (e.g., equipment) factors relevant to physical activity and sedentary time. We categorized each survey item based on whether it was specific to a location to generate psychosocial and environmental indices that were location-general or specific to either school, non-school, or home location. Physical activity (MVPA) and sedentary time were based on time/location match to home, school, or all "other" locations. Mixed-effects models investigated the relation of each index with location-specific activity.ResultsThe location-general and non-school physical activity psychosocial indices were related to greater MVPA at school and "other" locations. The school physical activity environment index was related to greater MVPA and less sedentary time at school. The home activity environment index was related to greater MVPA at home. The non-school sedentary psychosocial index was related to less sedentary time at home. Interactions among indices revealed adolescents with low support on one index benefited (i.e., exhibited more optimal behavior) from high support on another index (e.g., higher scores on the location-general PA psychosocial index moderated lower scores on the home PA environment index). Concurrent high support on two indices did not provide additional benefit.ConclusionsNo psychosocial or environment indices, including location-general indices, were related to activity in all locations. Most of the location-specific indices were associated with activity in the matching location(s). These findings provide preliminary evidence that psychosocial and environmental correlates of activity are location specific. Future studies should further develop location-specific measures and evaluate these constructs and whether interventions may be optimized by targeting location-specific psychosocial and environmental variables across multiple locations

Location-specific psychosocial and environmental correlates of physical activity and sedentary time in young adolescents: preliminary evidence for location-specific approaches from a cross-sectional observational study

Background A better understanding of the extent to which psychosocial and environmental correlates of physical activity are specific to locations would inform intervention optimization. Purpose To investigate cross-sectional associations of location-general and location-specific variables with physical activity and sedentary time in three common locations adolescents spend time. Methods Adolescents (N = 472,Mage = 14.1,SD = 1.5) wore an accelerometer and global positioning systems (GPS) tracker and self-reported on psychosocial (e.g., self-efficacy) and environmental (e.g., equipment) factors relevant to physical activity and sedentary time. We categorized each survey item based on whether it was specific to a location to generate psychosocial and environmental indices that were location-general or specific to either school, non-school, or home location. Physical activity (MVPA) and sedentary time were based on time/location match to home, school, or all “other” locations. Mixed-effects models investigated the relation of each index with location-specific activity. Results The location-general and non-school physical activity psychosocial indices were related to greater MVPA at school and “other” locations. The school physical activity environment index was related to greater MVPA and less sedentary time at school. The home activity environment index was related to greater MVPA at home. The non-school sedentary psychosocial index was related to less sedentary time at home. Interactions among indices revealed adolescents with low support on one index benefited (i.e., exhibited more optimal behavior) from high support on another index (e.g., higher scores on the location-general PA psychosocial index moderated lower scores on the home PA environment index). Concurrent high support on two indices did not provide additional benefit. Conclusions No psychosocial or environment indices, including location-general indices, were related to activity in all locations. Most of the location-specific indices were associated with activity in the matching location(s). These findings provide preliminary evidence that psychosocial and environmental correlates of activity are location specific. Future studies should further develop location-specific measures and evaluate these constructs and whether interventions may be optimized by targeting location-specific psychosocial and environmental variables across multiple locations.Applied Science, Faculty ofNon UBCCommunity and Regional Planning (SCARP), School ofReviewedFacultyResearche

Differences in adolescent activity and dietary behaviors across home, school, and other locations warrant location-specific intervention approaches

Background: Investigation of physical activity and dietary behaviors across locations can inform “setting-specific” health behavior interventions and improve understanding of contextual vulnerabilities to poor health. This study examined how physical activity, sedentary time, and dietary behaviors differed across home, school, and other locations in young adolescents. Methods: Participants were adolescents aged 12–16 years from the Baltimore-Washington, DC and the Seattle areas from a larger cross-sectional study. Participants (n = 472) wore an accelerometer and Global Positioning Systems (GPS) tracker (Mean days = 5.12, SD = 1.62) to collect location-based physical activity and sedentary data. Participants (n = 789) completed 24-h dietary recalls to assess dietary behaviors and eating locations. Spatial analyses were performed to classify daily physical activity, sedentary time patterns, and dietary behaviors by location, categorized as home, school, and “other” locations. Results: Adolescents were least physically active at home (2.5 min/hour of wear time) and school (2.9 min/hour of wear time) compared to “other” locations (5.9 min/hour of wear time). Participants spent a slightly greater proportion of wear time in sedentary time when at school (41 min/hour of wear time) than at home (39 min/hour of wear time), and time in bouts lasting ≥30 min (10 min/hour of wear time) and mean sedentary bout duration (5 min) were highest at school. About 61% of daily energy intake occurred at home, 25% at school, and 14% at “other” locations. Proportionately to energy intake, daily added sugar intake (5 g/100 kcal), fruits and vegetables (0.16 servings/100 kcal), high calorie beverages (0.09 beverages/100 kcal), whole grains (0.04 servings/100 kcal), grams of fiber (0.65 g/100 kcal), and calories of fat (33 kcal/100 kcal) and saturated fat (12 kcal/100 kcal) consumed were nutritionally least favorable at “other” locations. Daily sweet and savory snacks consumed was highest at school (0.14 snacks/100 kcal). Conclusions: Adolescents’ health behaviors differed based on the location/environment they were in. Although dietary behaviors were generally more favorable in the home and school locations, physical activity was generally low and sedentary time was higher in these locations. Health behavior interventions that address the multiple locations in which adolescents spend time and use location-specific behavior change strategies should be explored to optimize health behaviors in each location.Applied Science, Faculty ofNon UBCCommunity and Regional Planning (SCARP), School ofReviewedFacult