Background Social functioning is often impaired in schizophrenia (SZ) and Alzheimer’s disease (AD). However, commonalities and differences in social dysfunction among these patient groups remain elusive. Materials and methods Using data from the PRISM study, behavioral (all subscales and total score of the Social Functioning Scale) and affective (perceived social disability and loneliness) indicators of social functioning were measured in patients with SZ ( N = 56), probable AD ( N = 50) and age-matched healthy controls groups (HC, N = 29 and N = 28). We examined to what extent social functioning differed between disease and age-matched HC groups, as well as between patient groups. Furthermore, we examined how severity of disease and mood were correlated with social functioning, irrespective of diagnosis. Results As compared to HC, both behavioral and affective social functioning seemed impaired in SZ patients (Cohen’s d’s 0.81–1.69), whereas AD patients mainly showed impaired behavioral social function (Cohen’s d’s 0.65–1.14). While behavioral indices of social functioning were similar across patient groups, SZ patients reported more perceived social disability than AD patients (Cohen’s d’s 0.65). Across patient groups, positive mood, lower depression and anxiety levels were strong determinants of better social functioning (p’s <0.001), even more so than severity of disease. Conclusions AD and SZ patients both exhibit poor social functioning in comparison to age- and sex matched HC participants. Social dysfunction in SZ patients may be more severe than in AD patients, though this may be due to underreporting by AD patients. Across patients, social functioning appeared as more influenced by mood states than by severity of disease.
Variable mood is an important feature of psychiatric disorders. However, its measurement and relationship to objective measureas of physiology and behaviour have rarely been studied. Smart-phones facilitate continuous personalized prospective monitoring of subjective experience and behavioural and physiological signals can be measured through wearable devices. Such passive data streams allow novel estimates of diurnal variability. Phase and amplitude of diurnal rhythms were quantified using new techniques that fitted sinusoids to heart rate (HR) and acceleration signals. We investigated mood and diurnal variation for four days in 20 outpatients with bipolar disorder (BD), 14 with borderline personality disorder (BPD) and 20 healthy controls (HC) using a smart-phone app, portable electrocardiogram (ECG), and actigraphy. Variability in negative affect, positive affect, and irritability was elevated in patient groups compared with HC. The study demonstrated convincing associations between variability in subjective mood and objective variability in diurnal physiology. For BPD there was a pattern of positive correlations between mood variability and variation in activity, sleep and HR. The findings suggest BPD is linked more than currently believed with a disorder of diurnal rhythm; in both BPD and BD reducing the variability of sleep phase may be a way to reduce variability of subjective mood.