Sleep and emotion are closely linked, however the effects of sleep on socio-emotional task performance have only recently been investigated. Sleep loss and insomnia have been found to affect emotional reactivity and social functioning, although results, taken together, are somewhat contradictory. Here we review this advancing literature, aiming to 1) systematically review the relevant literature on sleep and socio-emotional functioning, with reference to the extant literature on emotion and social interactions, 2) summarize results and outline ways in which emotion, social interactions, and sleep may interact, and 3) suggest key limitations and future directions for this field. From the reviewed literature, sleep deprivation is associated with diminished emotional expressivity and impaired emotion recognition, and this has particular relevance for social interactions. Sleep deprivation also increases emotional reactivity; results which are most apparent with neuro-imaging studies investigating amygdala activity and its prefrontal regulation. Evidence of emotional dysregulation in insomnia and poor sleep has also been reported. In general, limitations of this literature include how performance measures are linked to self-reports, and how results are linked to socio-emotional functioning. We conclude by suggesting some possible future directions for this field.

For the first time we show that chronic insomnia is associated with reduced ratings of emotion intensity for face expressions displaying sadness and fear. Further work is required to elucidate possible mechanisms and pathways underlying insomnia-related emotional impairment.

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Background Relapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions. Objective This study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial. Methods We will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support. Results Recruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation. Conclusions The knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 99559262; http://isrctn.com/ISRCTN99559262 International Registered Report Identifier (IRRID) DERR1-10.2196/15058

There appears to be some inconsistency in how normal sleepers (controls) are selected and screened for participation in research studies for comparison with insomnia patients. The purpose of the current study is to assess and compare methods of identifying normal sleepers in insomnia studies, with reference to published standards. We systematically reviewed the literature on insomnia patients, which included control subjects. The resulting 37 articles were systematically reviewed with reference to the five criteria for normal sleep specified by Edinger et al. In summary, these criteria are as follows: evidence of sleep disruption, sleep scheduling, general health, substance/medication use, and other sleep disorders. We found sleep diaries, polysomnography (PSG), and clinical screening examinations to be widely used with both control subjects and insomnia participants. However, there are differences between research groups in the precise definitions applied to the components of normal sleep. We found that none of the reviewed studies applied all of the Edinger et al. criteria, and 16% met four criteria. In general, screening is applied most rigorously at the level of a clinical disorder, whether physical, psychiatric, or sleep. While the Edinger et al. criteria seem to be applied in some form by most researchers, there is scope to improve standards and definitions in this area. Ideally, different methods such as sleep diaries and questionnaires would be used concurrently with objective measures to ensure normal sleepers are identified, and descriptive information for control subjects would be reported. Here, we have devised working criteria and methods to be used for the assessment of normal sleepers. This would help clarify the nature of the control group, in contrast to insomnia subjects and other patient groups.

Attention biases to sleep-related stimuli are held to play a key role in the development and maintenance of insomnia, but such biases have only been shown with controlled visual displays. This study investigated whether observers with insomnia symptoms allocate attention to sleep-related items in natural scenes, by recording eye movements during free-viewing of bedrooms. Participants with insomnia symptoms and normal sleepers were matched in their visual exploration of these scenes, and there was no evidence that the attention of those with insomnia symptoms was captured more quickly by sleep-related stimuli than that of normal sleepers. However, the insomnia group fixated bed regions on more trials and, once fixated on a bed, also remained there for longer. These findings indicate that sleep stimuli are particularly effective in retaining visual attention in complex natural scenes.

Previous studies have shown impaired memory for faces following restricted sleep. However, it is not known whether lack of sleep impairs performance on face identification tasks that do not rely on recognition memory, despite these tasks being more prevalent in security and forensic professions—for example, in photo-ID checks at national borders. Here we tested whether poor sleep affects accuracy on a standard test of face-matching ability that does not place demands on memory: the Glasgow Face-Matching Task (GFMT). In Experiment 1, participants who reported sleep disturbance consistent with insomnia disorder show impaired accuracy on the GFMT when compared with participants reporting normal sleep behaviour. In Experiment 2, we then used a sleep diary method to compare GFMT accuracy in a control group to participants reporting poor sleep on three consecutive nights—and again found lower accuracy scores in the short sleep group. In both experiments, reduced face-matching accuracy in those with poorer sleep was not associated with lower confidence in their decisions, carrying implications for occupational settings where identification errors made with high confidence can have serious outcomes. These results suggest that sleep-related impairments in face memory reflect difficulties in perceptual encoding of identity, and point towards metacognitive impairment in face matching following poor sleep.