Sleep and circadian rhythm actigraphy measures, mood instability and impulsivity: A systematic review.

The normal spectrum trait measures of mood instability and impulsivity are implicated in and comprise core symptoms of several psychiatric disorders. A bidirectional relationship between these traits and sleep disturbance and circadian rhythm dysfunction has been hypothesised, although has not been systematically assessed using objective measures in naturalistic settings. We systematically reviewed the literature following PRISMA guidelines, according to a pre-registered protocol (PROSPERO: CRD 42018108213). Peer-reviewed quantitative studies assessing an association between actigraphic variables and any measure of mood instability or impulsivity in participants aged 12-65 years old were included. Studies were critically appraised using the AXIS tool. Twenty-three articles were retained for inclusion. There was significant heterogeneity in the selection and reporting of actigraphic variables and metrics of mood instability and impulsivity. We identified emerging evidence of a positive association between circadian rest-activity pattern disturbance and delayed sleep timing with both mood instability and impulsivity. Evidence for an association with sleep duration, sleep efficiency or sleep quality was inconsistent. Future research should focus on longitudinal intra-individual associations to establish the directionality between these measures and may lead to the development of chronotherapeutic interventions for a number of psychiatric disorders.

Have I argued with my family this week?": What questions do those with lived experience choose to monitor their bipolar disorder?

BACKGROUND: Electronic self-report mood monitoring tools for individuals with bipolar disorder (BD) are rapidly emerging and predominately employ predefined symptom-based questions. Allowing individuals to additionally choose what they monitor in relation to their BD offers the unique opportunity to capture and gain a deeper insight into patient priorities in this context. METHODS: In addition to monitoring mood symptoms with two standardised self-rated questionnaires, 308 individuals with BD participating in the Bipolar Disorder Research Network True Colours electronic mood-monitoring tool for research chose to create and complete additional personalised questions. A content analysis approach was used to analyse the content of these questions. RESULTS: 35 categories were created based on the personalised questions with the most common being physical activity and exercise, anxiety and panic, sleep and coping/stress levels. The categories were grouped into six overarching themes 1) mental health; 2) behaviour and level of functioning; 3) physical wellbeing; 4) health behaviours; 5) active self-management; and, 6) interpersonal. LIMITATIONS: The average age of the sample was around 50 years meaning our findings may not be generalisable to younger individuals with BD. CONCLUSIONS: Aspects of BD important to patients in relation to longitudinal monitoring extend well beyond mood symptoms, highlighting the limitations of solely relying on standardised questions/mood rating scales based on symptoms primarily used for diagnosis. Additional symptoms and aspects of life not necessarily useful diagnostically for BD may be more important for individuals themselves to monitor and have more meaning in capturing their own experience of changes in BD severity.

Apps and wearables in the monitoring of mental health disorders.

Recent advances in smartphone technology have revealed new opportunities for the diagnosis, monitoring and provision of mental health care. Such digital approaches have the potential to enhance our understanding of the course of mental disorder, enable early diagnosis and generate new treatment targets. However, issues relating to mobile phone ownership, misuse of clinical data, commercial devices and the ethics of such approaches need to be overcome if smartphones are to be routinely used in mental health care. This article reviews the potential as well as the challenges posed by the use of such technologies in mental health settings.

Lamotrigine Therapy for Bipolar Depression: Analysis of Self-Reported Patient Data.

BACKGROUND: Depression in people with bipolar disorder is a major cause of long-term disability, possibly leading to early mortality and currently, limited safe and effective therapies exist. Although existing monotherapies such as quetiapine have limited proven efficacy and practical tolerability, treatment combinations may lead to improved outcomes. Lamotrigine is an anticonvulsant currently licensed for the prevention of depressive relapses in individuals with bipolar disorder. A double-blinded randomized placebo-controlled trial (comparative evaluation of Quetiapine-Lamotrigine [CEQUEL] study) was conducted to evaluate the efficacy of lamotrigine plus quetiapine versus quetiapine monotherapy in patients with bipolar type I or type II disorders. OBJECTIVE: Because the original CEQUEL study found significant depressive symptom improvements, the objective of this study was to reanalyze CEQUEL data and determine an unbiased classification accuracy for active lamotrigine versus placebo. We also wanted to establish the time it took for the drug to provide statistically significant outcomes. METHODS: Between October 21, 2008 and April 27, 2012, 202 participants from 27 sites in United Kingdom were randomly assigned to two treatments; 101: lamotrigine, 101: placebo. The primary variable used for estimating depressive symptoms was based on the Quick Inventory of Depressive Symptomatology-self report version 16 (QIDS-SR16). The original CEQUEL study findings were confirmed by performing t test and linear regression. Multiple features were computed from the QIDS-SR16 time series; different linear and nonlinear binary classifiers were trained to distinguish between the two groups. Various feature-selection techniques were used to select a feature set with the greatest explanatory power; a 10-fold cross-validation was used. RESULTS: From weeks 10 to 14, the mean difference in QIDS-SR16 ratings between the groups was -1.6317 (P=.09; sample size=81, 77; 95% CI -0.2403 to 3.5036). From weeks 48 to 52, the mean difference was -2.0032 (P=.09; sample size=54, 48; 95% CI -0.3433 to 4.3497). The coefficient of variation (σ/µ) and detrended fluctuation analysis (DFA) exponent alpha had the greatest explanatory power. The out-of-sample classification accuracy for the 138 participants who reported more than 10 times after week 12 was 62%. A consistent classification accuracy higher than the no-information benchmark was obtained in week 44. CONCLUSIONS: Adding lamotrigine to quetiapine treatment decreased depressive symptoms in patients with bipolar disorder. Our classification model suggested that lamotrigine increased the coefficient of variation in the QIDS-SR16 scores. The lamotrigine group also tended to have a lower DFA exponent, implying a substantial temporal instability in the time series. The performance of the model over time suggested that a trial of at least 44 weeks was required to achieve consistent results. The selected model confirmed the original CEQUEL study findings and helped in understanding the temporal dynamics of bipolar depression during treatment. TRIAL REGISTRATION: EudraCT Number 2007-004513-33; https://www.clinicaltrialsregister.eu/ctr-search/trial/2007-004513-33/GB (Archived by WebCite at http://www.webcitation.org/73sNaI29O).

Sleep problems and suicide associated with mood instability in the Adult Psychiatric Morbidity Survey, 2007.

OBJECTIVE: Mood instability is common in the general population. Mood instability is a precursor to mental illness and associated with a range of negative health outcomes. Sleep disturbance appears to be closely linked with mood instability. This study assesses the association between mood instability and sleep disturbance and the link with suicidal ideation and behaviour in a general population sample in England. METHOD: The Adult Psychiatric Morbidity Survey, 2007 collected detailed information about mental health symptoms and correlates in a representative sample of adult household residents living in England ( n = 7303). Mood instability was assessed using the Structured Clinical Interview for DSM-IV Axis-II. Sleep problems were defined as sleeping more than usual or less than usual during the past month. Other dependent variables included medication use and suicidal ideation and behaviour (response rate 57%). Generalized linear modelling was used to estimate the prevalence of mood instability and sleep problems. Logistic regression was used to estimate odds ratios. All estimates were weighted. RESULTS: The prevalence of mood instability was 14.7% (95% confidence interval [13.6%, 15.7%]). Sleep problems occurred in 69.8% (95% confidence interval: [66.6%, 73.1%]) of those with mood instability versus 37.6% (95% confidence interval: [36.2%, 39.1%]) of those without mood instability. The use of sedating and non-sedating medications did not influence the association. Sleep problems were significantly associated with suicidal ideation and behaviour even after adjusting for mood instability. CONCLUSION: Sleep problems are highly prevalent in the general population, particularly among those with mood instability. Sleep problems are strongly associated with suicidal ideation and behaviour. Treatments that target risk and maintenance factors that transcend diagnostic boundaries, such as therapies that target sleep disturbance, may be particularly valuable for preventing and addressing complications related to mood instability such as suicide.