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STUDY OBJECTIVES: Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network (SN), and central executive network (CEN). METHODS: We selected 320 subjects from the ADNI database and divided by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores. RESULTS: Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterised by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were non-significant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD. CONCLUSIONS: We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.
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BACKGROUND: A critical gap in our knowledge about social media is whether we can alleviate accessibility barriers and challenges for individuals with traumatic brain injury (TBI), to improve their social participation and health. To do this, we need real-time information about these barriers and challenges, to design appropriate aids. OBJECTIVE: The aim of this study was to characterize the ways people with TBI accessed and used social media websites and understand unique challenges they faced. METHODS: We invited 8 adults with moderate to severe TBI to log onto their own Facebook page and use it as they regularly would while thinking aloud. Their comments were recorded and transcribed for qualitative analysis. We first analyzed participants' utterances using a priori coding based on a framework proposed by Meshi et al to classify adults' motives for accessing social media. We next used an open coding method to understand the challenges that people with TBI faced while using Facebook. In other words, we analyzed participants' needs for using Facebook and then identified Facebook features that made it challenging for them to meet those needs. RESULTS: Participants used all categories of codes in the framework by Meshi et al and provided detailed feedback about the Facebook user interface. A priori coding revealed 2 dimensions that characterized participants' Facebook use: whether they were active or passive about posting and self-disclosure on Facebook and their familiarity and fluency in using Facebook. The open coding analysis revealed 6 types of challenges reported by participants with TBI, including difficulty with language production and interpretation, attention and information overload, perceptions of negativity and emotional contagion, insufficient guidance to use Facebook, concerns about web-based scams and frauds, and general accessibility concerns. CONCLUSIONS: Results showed that individuals with TBI used Facebook for the same reasons typical adults do, suggesting that it can help increase social communication and reduce isolation and loneliness. Participants also identified barriers, and we propose modifications that could improve access for individuals with brain injury. On the basis of identified functions and challenges, we conclude by proposing design ideas for social media support tools that can promote more active use of social media sites by adults with TBI.
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Posttraumatic stress disorder (PTSD) is a common mental disorder, which is strongly associated with insomnia, yet their epidemiological overlap is poorly understood. To determine the convergent quantitative magnitude of their relationship, PubMed, EMBASE, Scopus, Web of Science, PubPsych, and PsycINFO were searched to identify studies that either reported the correlation or frequency of insomnia symptoms in PTSD and posttraumatic stress symptoms (PTSS), or both. Out of 3714 records, 75 studies met selection criteria and aggregate effect size (ES) estimates were generated for the correlations (K=44, comprising 57,618 subjects) and frequencies (K=33, comprising 573,665 subjects with PTSD/PTSS) of insomnia symptoms in PTSD/PTSS. A medium-size significant correlation was found [ES: 0.52 (CI: 0.47-0.57)] with moderating effects of the COVID-19 pandemic and military service as causes of trauma. The prevalence of insomnia in PTSD/PTSS was 63% [CI: 45%-78%] and was moderated by the cause of trauma as well as the PTSD/PTSS assessment scale. The findings from this meta-analysis highlight the importance of screening and managing insomnia in PTSD patients.