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Cognitive dysfunction is a well-documented feature of schizophrenia (SZ) and bipolar (BD) disorder. The person's subjective experience of cognitive difficulties is less investigated. Here we investigated subjective cognition in SZ and BD compared to healthy controls (HC).Subjective and objective cognition were assessed in 91 SZ participants, 55 BD participants and 55 HC, applying a novel measure of subjective cognition, the self-assessed cognitive complaints scale (SACCS) and a clinically relevant neuropsychological test battery. The psychometric properties of SACCS were investigated. The relationship between subjective and objective cognition, and subjective cognition and clinical variables were explored in SZ and BD.The SACCS showed adequate psychometric properties. Clinical groups reported significantly more cognitive complaints than HCs, without differences between SZ and BD. There were no significant associations between subjective and objective cognitive measures. There was a small trend association between subjective cognition and insight in SZ participants, and moderate sized associations between subjective cognition and general psychopathology and functioning in BD participants.Although SZ participants are more cognitively impaired than BD participants, the two groups report similar levels of subjective cognitive complaints, with no association between subjective and objective cognition. Our results suggest that the expression of subjective cognition is associated with different clinical factors in SZ and BD.

Abstract Background Affective lability is elevated and associated with increased clinical burden in psychosis spectrum disorders. The extent to which the level, structure and dispersion of affective lability varies between the specific disorders included in the psychosis spectrum is however unclear. To have potential value as a treatment target, further characterization of affective lability in these populations is necessary. The main aim of our study was to investigate differences in the architecture of affective lability in different psychosis spectrum disorders, and if putative differences remained when we controlled for current symptom status. Methods Affective lability was measured with The Affective Lability Scale Short Form (ALS-SF) in participants with schizophrenia (SZ, n = 76), bipolar I disorder (BD-I, n = 105), bipolar II disorder (BD-II, n = 68) and a mixed psychosis-affective group (MP, n = 48). Multiple analyses of covariance were conducted to compare the ALS-SF total and subdimension scores of the diagnostic groups, correcting for current psychotic, affective and anxiety symptoms, substance use and sex. Double generalized linear models were performed to compare the dispersion of affective lability in the different groups. Results Overall group differences in affective lability remained significant after adjusting for covariates (p = .001). BD-II had higher affective lability compared to SZ and BD-I (p = .004), with no significant differences between SZ and BD-I. There were no significant differences in the contributions of ALS-SF dimensions to the total affective lability or in dispersion of affective lability between the groups. Conclusions This study provides the construct of affective lability in psychosis spectrum disorders with more granular details that may have implications for research and clinical care. It demonstrates that despite overlap in core symptom profiles, BD-I is more similar to SZ than it is to BD-II concerning affective lability and the BD groups should consequently be studied apart. Further, affective lability appears to be characterized by fluctuations between depressive- and other affective states across different psychosis spectrum disorders, indicating that affective lability may be related to internalizing problems in these disorders. Finally, although the level varies between groups, affective lability is evenly spread and not driven by extremes across psychosis spectrum disorders and should be assessed irrespective of diagnosis.

IntroductionThe illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors.MethodsAn app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability.ResultsThe final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway.DiscussionWe believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.

Substance misuse is highly prevalent in bipolar disorder even in the early illness phases. However, the trajectories of misuse of different substances after treatment initiation is not well-studied. Also, knowledge on how substance misuse trajectories influence the early course of bipolar disorder is limited. We recruited 220 individuals in first treatment of bipolar disorder of which 112 participated in a 1-year follow-up study at the NORMENT center in Oslo, Norway. Misuse was defined as having scores above cut-off for harmful use on the Alcohol or Drug Use Disorders Identification Tests (AUDIT or DUDIT). We investigated rates of stopping and continuing misuse of alcohol, cannabis and other illicit substances and daily nicotine use over the follow-up period, and whether such misuse trajectories predicted the risk for affective relapse. The prevalence of cannabis misuse was reduced from 29 to 15% and alcohol misuse was reduced from 39 to 21% during follow-up. Continuing alcohol misuse significantly and independently predicted affective relapse, whereas there was no difference in relapse risk between individuals stopping alcohol misuse and never misusing alcohol. Cannabis misuse trajectories did not significantly predict relapse risk although we cannot exclude interactions with alcohol misuse. In conclusion, substance misuse decreased in the early phase of bipolar disorder treatment but should be further reduced with interventions specifically addressing substance misuse. Stopping alcohol misuse is likely to yield substantial benefit on the clinical course of bipolar disorder.