Sleep reactivity predicts insomnia in patients diagnosed with breast cancer.

STUDY OBJECTIVES: To examine the role of sleep reactivity as a predictor of insomnia in patients diagnosed with breast cancer. METHODS: A total of 173 women with breast cancer participated and were followed up over a period of 9 months. At baseline, participants were assigned to a high (n = 114) or low (n = 59) sleep reactivity group, based on their responses to the Ford Insomnia Response to Stress Test (FIRST). We assessed whether these FIRST groupings (high/low sleep reactivity) predicted changes in insomnia over time using the Insomnia Severity Index. We also tested if these FIRST groupings predicted insomnia disorder (using Insomnia Severity Index cutoffs) at 3 different time points (T3, T6, and T9). RESULTS: Individuals with high sleep reactivity were more likely to experience a worsening of insomnia. Using logistic regression, we also found that FIRST grouping predicted insomnia disorder. Results remained significant after controlling for estimated premorbid sleep, age, and whether someone had chemotherapy. CONCLUSIONS: Our study shows that sleep reactivity may be a robust predictor of insomnia within breast cancer populations. Sleep reactivity should be considered in routine clinical assessments as a reliable way to identify patients at risk of developing insomnia. This would facilitate early sleep intervention for those patients who are considered high risk. CITATION: Rehman A, Drake CL, Shiramizu V, Fleming L. Sleep reactivity predicts insomnia in patients diagnosed with breast cancer. J Clin Sleep Med. 2022;18(11):2597-2604.

Sleep quality and paranoia: The role of alexithymia, negative emotions and perceptual anomalies.

Recent evidence suggests that sleep problems are associated with psychotic like experiences including paranoia. However, the mechanisms underpinning this association are not well understood and thus studies modelling hypothesised mediating factors are required. Alexithymia, the inability to recognise and describe emotions within the self may be an important candidate. In two separate studies we sought to investigate factors mediating the relationship between sleep quality and paranoia using a cross-sectional design. Healthy volunteers without a mental health diagnosis were recruited (study 1, N = 401, study 2, N = 402). Participants completed a series of measures assessing paranoia, negative emotions, alexithymia and perceptual anomalies in an online survey. In study 1, regression and mediation analyses showed that the relationship between sleep quality and paranoia was partially mediated by alexithymia, perceptual anomalies and negative affect. In contrast, study 2 found that the relationship between sleep quality and paranoia was fully mediated by negative affect, alexithymia and perceptual anomalies. The link between sleep quality and paranoia is unclear and reasons for discrepant results are discussed. Novel findings in this study include the link between alexithymia and paranoia.

Clinician perceptions of sleep problems, and their treatment, in patients with non-affective psychosis.

Aims and method: To assess clinicians' views about their understanding and treatment of sleep problems in people with non-affective psychosis. An online survey was emailed to adult mental health teams in two NHS trusts. Results: One hundred and eleven clinicians completed the survey. All clinicians reported disrupted sleep in their patients, and endorsed the view that sleep and psychotic experiences each exacerbate the other. However, most clinicians (n = 92, 82%) assessed sleep problems informally, rather than using standard assessment measures. There was infrequent use of the recommended cognitive-behavioural treatments for sleep problems such as persistent insomnia, with the approaches typically used being sleep hygiene and medications instead. Clinical implications: Clinicians recognise the importance of sleep in psychosis, but the use of formal assessments and recommended treatments is limited. Barriers to treatment implementation identified by the clinicians related to services (e.g. lack of time), patients (e.g. their lifestyle) and environmental features of inpatient settings.