16 research outputs found

    Sensitive periods, but not critical periods, evolve in a fluctuating environment:: a model of incremental development

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    Sensitive periods, during which the impact of experience on phenotype is larger than in other periods, exist in all classes of organisms, yet little is known about their evolution. Recent mathematical modelling has explored the conditions in which natural selection favours sensitive periods. These models have assumed that the environment is stable across ontogeny or that organisms can develop phenotypes instantaneously at any age. Neither assumption generally holds. Here, we present a model in which organisms gradually tailor their phenotypes to an environment that fluctuates across ontogeny, while receiving cost-free, imperfect cues to the current environmental state. We vary the rate of environmental change, the reliability of cues and the duration of adulthood relative to ontogeny. We use stochastic dynamic programming to compute optimal policies. From these policies, we simulate levels of plasticity across ontogeny and obtain mature phenotypes. Our results show that sensitive periods can occur at the onset, midway through and even towards the end of ontogeny. In contrast with models assuming stable environments, organisms always retain residual plasticity late in ontogeny. We conclude that critical periods, after which plasticity is zero, are unlikely to be favoured in environments that fluctuate across ontogeny

    Digital cognitive behavioural therapy intervention in the workplace:study protocol for a feasibility randomised waitlist-controlled trial to improve employee mental well-being, engagement and productivity

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    INTRODUCTION: One in six workers experience some form of mental health problems at work costing the UK economy an estimated £70 billion/year. Digital interventions provide low cost and easily scalable delivery methods to implement psychological interventions in the workplace. This trial tests the feasibility of implementing a self-guided 8-week digital cognitive behavioural therapy intervention for subthreshold to clinical depression and/or anxiety versus waitlist control (ie, life as usual) in the workplace. METHODS AND ANALYSIS: Feasibility of implementation will be tested using a mixed-methods evaluation of the two-arm randomised waitlist-control trial. Evaluation will include examination of organisational buy-in, and the engagement of employees through the trial indicated by the completion of outcome measures. In addition, we also explore how participants use the platform, the appropriateness of the analysis both with reference to the outcome measures and linear modelling. Finally, we examine the acceptability of the intervention based on participants experiences using qualitative interviews. Assessments take place at baseline (T0), at 8 weeks post-treatment (T1), at short-term follow-up 4 weeks post-treatment (T2) and long-term follow-ups (6 and 12 months after-end of treatment). We will recruit from 1 July 2021 to 31 December 2021 for employees and self-employed workers with depression and anxiety symptoms (subclinical and clinical levels) who are not seeking or engaged in treatment at the time of the trial. ETHICS AND DISSEMINATION: Full approval was given by the University of Warwick Biomedical and Research Ethics Committee (BSREC 45/20–21). The current protocol version is 2.8 (August 2021). Publication of results in peer-reviewed journals will inform the scientific, clinical and business communities. We will disseminate results through webinars, conferences, newsletter as well as a lay summary of results on the study website (mhpp.me). TRIAL REGISTRATION NUMBER: ISRCTN31161020

    Can a 'rewards-for-exercise app' increase physical activity, subjective well-being and sleep quality? An open-label single-arm trial among university staff with low to moderate physical activity levels.

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    Funder: Universität Bielefeld (3146)BACKGROUND: This study examined the impact of a 'rewards-for-exercise' mobile application on physical activity, subjective well-being and sleep quality among 148 employees in a UK university with low to moderate physical activity levels. METHODS: A three-month open-label single-arm trial with a one-year follow-up after the end of the trial. Participants used the Sweatcoin application which converted their outdoor steps into a virtual currency used for the purchase of products available at the university campus' outlets, using an in-app marketplace. The primary outcome measure was self-reported physical activity. Secondary measures included device-measured physical activity, subjective well-being (i.e., life satisfaction, positive affect, negative affect), and self-reported sleep quality. RESULTS: The findings show an increase in self-reported physical activity (d = 0.34), life satisfaction (d = 0.31), positive affect (d = 0.29), and sleep quality (d = 0.22) during the three-month trial period. CONCLUSION: The study suggests that mobile incentives-for-exercise applications might increase physical activity levels, positive affect, and sleep quality, at least in the short term. The observed changes were not sustained 12 months after the end of the trial

    Improving university students’ mental health using multi-component and single-component sleep interventions: A systematic review and meta-analysis

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    University is a time of significant transitions during a young adult's life, with delayed and shortened sleep and poor mental health a common occurrence. This systematic review and meta-analysis examined the effect of both multi-component and single-component sleep interventions on improving university students' sleep and mental health. Five databases (MEDLINE, PsycINFO, Embase, CINAHL and Cochrane Library) were searched for relevant literature published until April 2022. Treatment studies including university students aged 18–24 years, participating in a sleep intervention (multi-component, e.g., CBT-I, or single-component, e.g., sleep hygiene) were eligible. Comparator groups were either active, i.e., alternative intervention, or passive, i.e., waitlist control or treatment-as-usual, with study outcomes to include measures of sleep and mental health. Of 3435 references screened, 11 studies involving 5267 participants, with and without insomnia symptoms, were included for a narrative synthesis on intervention designs and methodology. Six studies eligible for meta-analyses showed a moderate effect of sleep interventions in reducing sleep disturbance (SMD = −0.548 [CI: −0.837, −0.258]) at post-treatment, alongside a small effect in improving anxiety (SMD = −0.226 [CI: −0.421, −0.031]) and depression (SMD = −0.295 [CI: −0.513, −0.077]). Meta-regression examining study and intervention characteristics identified subpopulation (experiencing insomnia or not) as a significant moderator for effects on sleep (p = 0.0003) and depression (p = 0.0063), with larger effects in studies with participants experiencing insomnia. Comparison group type (active or passive) was also a significant moderator (p = 0.0474), with larger effects on sleep in studies using passive comparison groups. Study type, delivery format, and intervention duration were not identified as significant moderators. At follow-ups, small but significant effects were sustained for anxiety and depression. Protecting and promoting sleep amongst university students may help safeguard and advance mental health

    Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

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    Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set. In LUNA16, participants develop their algorithm and upload their predictions on 888 CT scans in one of the two tracks: 1) the complete nodule detection track where a complete CAD system should be developed, or 2) the false positive reduction track where a provided set of nodule candidates should be classified. This paper describes the setup of LUNA16 and presents the results of the challenge so far. Moreover, the impact of combining individual systems on the detection performance was also investigated. It was observed that the leading solutions employed convolutional networks and used the provided set of nodule candidates. The combination of these solutions achieved an excellent sensitivity of over 95% at fewer than 1.0 false positives per scan. This highlights the potential of combining algorithms to improve the detection performance. Our observer study with four expert readers has shown that the best system detects nodules that were missed by expert readers who originally annotated the LIDC-IDRI data. We released this set of additional nodules for further development of CAD systems

    Sensitive periods, but not critical periods, evolve in a fluctuating environment:: a model of incremental development

    No full text
    Sensitive periods, during which the impact of experience on phenotype is larger than in other periods, exist in all classes of organisms, yet little is known about their evolution. Recent mathematical modelling has explored the conditions in which natural selection favours sensitive periods. These models have assumed that the environment is stable across ontogeny or that organisms can develop phenotypes instantaneously at any age. Neither assumption generally holds. Here, we present a model in which organisms gradually tailor their phenotypes to an environment that fluctuates across ontogeny, while receiving cost-free, imperfect cues to the current environmental state. We vary the rate of environmental change, the reliability of cues and the duration of adulthood relative to ontogeny. We use stochastic dynamic programming to compute optimal policies. From these policies, we simulate levels of plasticity across ontogeny and obtain mature phenotypes. Our results show that sensitive periods can occur at the onset, midway through and even towards the end of ontogeny. In contrast with models assuming stable environments, organisms always retain residual plasticity late in ontogeny. We conclude that critical periods, after which plasticity is zero, are unlikely to be favoured in environments that fluctuate across ontogeny

    The relationship between online vigilance and affective well-being in everyday life : Combining smartphone logging with experience sampling

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    Through communication technology, users find themselves constantly connected to others to such an extent that they routinely develop a mind-set of connectedness. This mind-set has been defined as online vigilance. Although there is a large body of research on media use and well-being, the question of how online vigilance impacts well-being remains unanswered. In this preregistered study, we combine experience sampling and smartphone logging to address the relation of online vigilance and affective well-being in everyday life. Seventy-five Android users answered eight daily surveys over five days (N = 1,615) whilst having their smartphone use logged. Thinking about smartphone-mediated social interactions (i.e., the salience dimension of online vigilance) was negatively related to affective well-being. However, it was far more important whether those thoughts were positive or negative. No other dimension of online vigilance was robustly related to affective well-being. Taken together, our results suggest that online vigilance does not pose a serious threat to affective well-being in everyday life
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