The Sleep Impact on Activity Diary (SIAD): A Novel Assessment of Daytime Functioning in Insomnia

Insomnia is associated with conspiracy mentality, psychological distress, and psychological well-being

RATIONALE

Conspiracy theories are frequently encountered as they exist across all domains of life, from interpersonal issues in the workplace to global events. Research has primarily focused on uncovering the antecedents of conspiracy beliefs; meanwhile, little research has examined the impacts of possessing a conspiracy mentality.

OBJECTIVE

In the current research, we examined the relationships of conspiracy mentality with perceived control, insomnia, psychological well-being (i.e., positive emotions, engagement, relationships, meaning, and achievement), and psychological distress (i.e., anxiety and depression).

METHODS

Participants (N = 388) reported their conspiracy mentality at Time 1 and then completed measures assessing perceived control, insomnia, psychological well-being, and psychological distress 1 month later at Time 2. We conducted regression analyses, structural equation modeling, and bootstrapping analyses to test our predictions that conspiracy mentality predicts insomnia through thwarted perceived control and that this relationship carries direct implications for psychological well-being and distress.

RESULTS

As predicted, regression analyses showed that conspiracy mentality is negatively associated with perceived control and indicators of psychological well-being, and positively associated with insomnia and indicators of psychological distress 1 month later. The results of structural equation modeling and bootstrapping analyses provided empirical support to our theoretical model that perceived control and insomnia serially mediate the relationship between conspiracy mentality and both psychological well-being and psychological distress.

CONCLUSIONS

These findings offer important contributions to the literature on conspiracy beliefs. Practically, they offer potential routes of intervention to weaken insomnia and psychological distress and enhance psychological well-being.

Meaningful Within-Patient Change on the Insomnia Daytime Symptoms and Impacts Questionnaire (IDSIQ): Analysis of Phase III Clinical Trial Data of Daridorexant

BACKGROUND

The Insomnia Daytime Symptoms and Impacts Questionnaire (IDSIQ) is a new validated 14-item patient-reported outcome (PRO) instrument for evaluating daytime functioning in people with insomnia. It comprises three domains: Alert/Cognition, Mood, and Sleepiness.

OBJECTIVE

The aim of this analysis was to estimate the minimum within-patient change for IDSIQ scores that an adult patient with insomnia would consider meaningful.

METHODS

Data were from a randomized, double-blind, placebo-controlled, phase III clinical trial of daridorexant in adults with insomnia. Subjects completed the IDSIQ daily in the evening, with a recall period of 'today', throughout the 3-month double-blind treatment period. Scores were calculated as a weekly average. Each IDSIQ item was scored on an 11-point numeric rating scale ranging from 0 (not at all/none at all) to 10 (very/a lot), with a higher score indicating a greater severity or impact. PRO measures with correlation coefficients ≥0.30 were included in a subsequent anchor-based analysis. For the IDSIQ total score and each IDSIQ domain, meaningful within-patient change was estimated as the minimum score change patients would consider meaningful in an anchor-based analysis using data from PRO instruments capturing daytime and night-time insomnia symptoms (the Insomnia Severity Index [four items, each scored 0-4, with a higher score indicating greater symptom severity; assessed at screening, baseline, month 1 and month 3], Patient Global Assessment of Disease Severity [6-point scale from 'none' to 'very severe'; assessed weekly], Patient Global Impression of Severity [4-point scale from 'none' to 'severe'; assessed weekly], and Patient Global Impression of Change [7-point scale from 'very much better' to 'very much worse'; assessed weekly for night-time and daytime symptoms separately]). A supplemental distribution-based analysis was also conducted to support the anchor-based analysis.

RESULTS

The analysis included 930 subjects aged 18-88 years. Spearman correlation coefficients for the relationships between score changes/ratings for anchors and the IDSIQ (0.36-0.44 at month 1, 0.45-0.57 at month 3) were all above the prespecified threshold of 0.30. Mean IDSIQ score changes at months 1 and 3 based on the different anchors supported meaningful within-patient change estimates starting at 17 points for the IDSIQ total score, 9 points for the Alert/Cognition domain, and 4 points for the Mood and Sleepiness domains.

CONCLUSION

This analysis demonstrates the meaningful within-patient change for the IDSIQ total score and domain scores, that the instrument is sensitive to changes in the patient experience of insomnia, and that it can be used in clinical trials to evaluate changes in daytime functioning.

CLINICAL TRIALS REGISTRATION

NCT03545191 (4 June 2018).

Emerging applications of objective sleep assessments towards the improved management of insomnia

Self-reported sleep difficulties are the primary concern associated with diagnosis and treatment of chronic insomnia. This said, in-home sleep monitoring technology in combination with self-reported sleep outcomes may usefully assist with the management of insomnia. The rapid acceleration in consumer sleep technology capabilities together with their growing use by consumers means that the implementation of clinically useful techniques to more precisely diagnose and better treat insomnia are now possible. This review describes emerging techniques which may facilitate better identification and management of insomnia through objective sleep monitoring. Diagnostic techniques covered include insomnia phenotyping, better detection of comorbid sleep disorders, and identification of patients potentially at greatest risk of adverse outcomes. Treatment techniques reviewed include the administration of therapies (e.g., Intensive Sleep Retraining, digital treatment programs), methods to assess and improve treatment adherence, and sleep feedback to address concerns about sleep and sleep loss. Gaps in sleep device capabilities are also discussed, such as the practical assessment of circadian rhythms. Proof-of-concept studies remain needed to test these sleep monitoring-supported techniques in insomnia patient populations, with the goal to progress towards more precise diagnoses and efficacious treatments for individuals with insomnia.