BackgroundMobile health (mHealth) apps demonstrate promise for improving sleep at scale. End-user engagement is a prerequisite for sustained use and effectiveness.ObjectiveWe assessed the needs and preferences of those with poor sleep and insomnia to inform the development of an engaging sleep app.MethodsWe triangulated results from qualitative (focus groups and app reviews) and quantitative (online survey) approaches. A total of 2 focus groups were conducted (N=9). An online survey tested themes identified from the focus groups against a larger population (N=167). In addition, we analyzed 434 user reviews of 6 mobile apps available on app stores.ResultsCommon focus group themes included the need to account for diverse sleep phenotypes with an adaptive and tailored program, key app features (alarms and sleep diaries), the complex yet condescending nature of existing resources, providing rationale for information requested, and cost as a motivator. Most survey participants (156/167, 93%) would try an evidence-based sleep app. The most important app features reported were sleep diaries (148/167, 88%), sharing sleep data with a doctor (116/167, 70%), and lifestyle tracking (107/167, 64%). App reviews highlighted the alarm as the most salient app feature (43/122, 35%) and data synchronization with a wearable device (WD) as the most commonly mentioned functionality (40/135, 30%).ConclusionsThis co-design process involving end users through 3 methods consistently highlighted sleep tracking (through a diary and WD), alarms, and personalization as vital for engagement, although their implementation was commonly criticized in review. Engagement is negatively affected by poorly designed features, bugs, and didactic information which must be addressed. Other needs depend upon the type of user, for example, those with severe insomnia.
Objectives: Evaluate whether insomnia symptoms and short or long sleep duration, alone or in combination, are robustly associated with subsequent trajectory of mental health symptoms. Methods: Participants were 2,598 individuals (15-to-94 years of age) with elevated mental health symptoms at baseline (2013-14). Associations of baseline insomnia symptoms and sleep duration with two-year trajectory of mental health were estimated and adjusted for multiple potential confounders. Outcomes included recovery (well at both follow-up timepoints), intermittent symptoms (unwell at one follow-up timepoint), and chronic symptoms (unwell at each follow-up timepoint). Results: Adjusted for age and sex, baseline insomnia symptoms predicted intermittent (OR 1.43, 95% CI 1.15-1.80) and chronic (OR 2.16, 95% CI 1.77-2.68) trajectories of mental health symptoms. Short sleep duration (<6h and ≥6 to <7h) only predicted a chronic trajectory (ORs 1.70-2.06). Associations were attenuated but significant after confounder adjustment. Those who experienced both insomnia and short (<7h) sleep duration had the greatest risk of chronic mental health symptoms (OR 2.35, 95% CI 1.60-3.45). Conclusion: A focus on just sleep duration or insomnia symptoms in those with elevated mental health symptoms will not be adequate to address chronicity. Both components of sleep disturbance, and in particular their co-occurrence, should be addressed.
there is a strong case for further investigation of the Task Cohesion construct under sleep loss. These findings may reflect a (top-down) shift in the behavioral economic framework of cooperation/parochial altruism, or a (bottom-up) load-shedding due to reduced attentional resources. Additional analysis of task performance and subjective ratings of individual and team perceived motivation for cooperation may help explain these findings. Introduction: Accurate assessment of sleep can be fundamental for monitoring, managing, and evaluating treatment outcomes within diseases. Proliferation of consumer activity trackers gives easy access to objective sleep. We evaluated the performance of a commercial device (Fitbit Alta HR, FBA) relative to a research-grade actigraph (Actiwatch Spectrum Pro, AWS) in measuring sleep before and after a cognitive behavioural intervention in Insomnia Disorder. Methods: Twenty five individuals with DSM-5 insomnia disorder (M = 50.6 ± 15.9 years) wore FBA and AWS and completed a sleep diary during an in-lab polysomnogram, and for one week preceding and following 7 weekly sessions of cognitive-behavioural intervention for insomnia. Device performance was compared for sleep outcomes (total sleep time, sleep latency, sleep efficiency, and
Background Mobile health (mHealth) apps offer a scalable option for treating sleep disturbances at a population level. However, there is a lack of clarity about the development and evaluation of evidence-based mHealth apps. Objective The aim of this systematic review was to provide evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. Methods A systematic search of studies published from the inception of databases through February 2020 was conducted using 5 databases (MEDLINE, Embase, Cochrane Library, PsycINFO, and CINAHL). Results A total of 6015 papers were identified using the search strategy. After screening, 15 papers were identified that examined the design engineering and clinical implementation and evaluation of 8 different mHealth apps for sleep disturbance. Most of these apps delivered cognitive behavioral therapy for insomnia (CBT-I, n=4) or modified CBT-I (n=2). Half of the apps (n=4) identified adopting user-centered design or multidisciplinary teams in their design approach. Only 3 papers described user and data privacy. End-user acceptability and engagement were the most frequently assessed implementation metrics. Only 1 app had available evidence assessing all 4 implementation metrics (ie, acceptability, engagement, usability, and adherence). Most apps were prototype versions (n=5), with few matured apps. A total of 6 apps had supporting papers that provided a quantitative evaluation of clinical outcomes, but only 1 app had a supporting, adequately powered randomized controlled trial. Conclusions This is the first systematic review to synthesize and examine evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. The minimal number of apps with published evidence for design engineering and clinical implementation and evaluation contrasts starkly with the number of commercial sleep apps available. Moreover, there appears to be no standardization and consistency in the use of best practice design approaches and implementation assessments, along with very few rigorous efficacy evaluations. To facilitate the development of successful and evidence-based apps for sleep disturbance, we developed a high-level framework to guide researchers and app developers in the end-to-end process of app development and evaluation.
We report distributional analyses of response times (RT) in two variants of the color-word Stroop task using manual keypress responses. In the classic Stroop task, in which the color and word dimensions are integrated into a single stimulus, the Stroop congruence effect increased across the quantiles. In contrast, in the primed Stroop task, in which the distractor word is presented ahead of colored symbols, the Stroop congruence effect was manifested solely as a distributional shift, remaining constant across the quantiles. The distributional-shift pattern mirrors the semantic-priming effect that has been reported in semantic categorization tasks. The results are interpreted within the framework of evidence accumulation, and implications for the roles of task conflict and informational conflict are discussed.
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