Quality of life is decreased in bipolar disorders (BD) and contributes to poor prognosis. However, little is known about the causal pathways that may affect it. This study aimed to explore health-related QoL (HRQoL) in BD and investigate its relationship with cognition and psychosocial functioning.

This multicenter cross-sectional study used a neuropsychological battery to assess five cognition domains. Functioning was evaluated using global and domain-based tools, and health-related HRQoL was assessed using the EQ-5D-3L. Structural equation modeling was used to test whether the association between cognition and HRQoL would be mediated by functioning in BD while controlling for covariates such as residual depression, anxiety, antipsychotic medication, and psychotic features.

We included 1 190 adults with euthymic BD. The model provided a good fit for the data. In this model, the direct effect of cognition on HRQoL was not significant (β = − 0.03, z = −0.78, p = 0.433). The total effect of cognition on HRQoL was weak, albeit significant (β = 0.05, z = 3.6, p < 0.001), thus suggesting that cognition affected HRQoL only indirectly through functioning. Anxiety was associated with decreased functioning (β = −0.27, z = −7.4, p < 0.001) and QoL (β = −0.39, z = −11.8, p < 0.001).

These findings suggest that improving cognition may not directly lead to a higher HRQoL. Cognitive remediation is expected to improve HRQoL only through functioning enhancement. They also reveal the potential importance of functional remediation and reduction of comorbid anxiety symptoms in improving HRQoL in BD.

Most patients (70%) discontinuing tobacco smoking will relapse within 6 months. A major challenge is the understanding of the processes involved in relapse. High cigarette craving has been proposed as a predictor of relapse. A recent study suggests that low inhibitory control capacities (low ability to inhibit prepotent responses) were correlated with high nicotine dependence. In this study, we focused on the link between inhibition capacity, craving, tobacco dependence and relapse.

134 smokers willing to quit smoking were consecutively included and followed prospectively. Tobacco dependence was assessed with the Fagerstorm test. We used the Hayling task to measure their inhibitory capacity and a specific questionnaire to measure tobacco craving (TCQ 12). Assessments were performed at baseline, 1, 3 and 6 months after smoking cessation. Any relapse in smoking during the follow-up was evaluated.

There was an association between lower inhibition capacities and higher dependance level at baseline. Low inhibition capacities were an independent predictor of relapse at 6 months (logit R 2 = .08, F (2,134) = 10.851, p <. 004). In contrast, although level of tobacco dependence and craving predicted relapse in the short term (first month), they did not predict relapse at 6 months.

These results suggest that inhibition capacities may predict smoking relapse in the long term (6 months) better than usual measures of craving. In clinical practice, an inhibition test, which is short and feasible, could be of interest to identify smokers at higher risk of relapse.

A recent meta-analysis showed that lack of early improvement is able to predict absence of later treatment response in Major Depressive Disorder. Whilst the majority of studies are based on depressive symptoms reduction, early variability of negative and positive emotions could be even more informative.

2938 adult outpatients with MDD were included in this observational study to receive agomelatine. QIDS-C, CGI, and MATHYS scales were completed at inclusion, W2 and W6 for 1565 subjects. The MATHYS rates tonalities of emotions during the previous week, including sadness and happiness, on a Likert Scale with 5 frequencies: from’never’ to’constantly’.

Responders were 25.72% at W2 (N=402) and 58.02% (N=908) at W6. QIDS-C score decreased from 18.78 at inclusion to 9.28 at W6. At W6, 26.00% patients were remitters (QIDS-C<6). At W2, 67.72% of patients (577/852) with decreased negative emotions, and 72.30% of patients (261/361) with increased positive emotions, were treatment responders. The increase of positive emotions is more specific (84.78% versus 58.14%), with a better positive predictive value (72.30% versus 67.72%) than the decrease of negative emotions. The global predictive value for positive emotions increase (Yule Q=38.40%, 95%CI[35.99%–40.81%] was overlapping with the one derived from the decrease of negative emotions (Q=41.55, 95%CI[39.10%–43.99%]).

Beside depressive symptoms, considering early changes in positive and negative emotions could be a relevant choice, as the more specific value for symptoms reduction (QIDS-C) was 72.5% in the same study and the specificity detected for the increase of positive emotions is 84.8% in this analysis.