Sleep disorders (e.g., insomnia) are extremely prevalent in our population and are intimately associated with distress and productivity impairment. It is estimated that between 40 to 60% of people suffering from a sleep disorder have an underlying psychiatric diagnosis.

Mindfulness, which is described as the quality or state of being self-conscious or aware of something, has shown to be a potential helpful therapy in insomnia.

Therefore, and due to the lack of new and effective treatment approaches, we did a non-systematic review of the positive impact of mindfulness in quality of sleep.

Bibliographic research through PubMed, Web of Science and Springer Link.

The mindfulness tools that may be linked to its therapeutic effects include the awareness state and conscious posture to respond when perceiving insomnia symptoms, as well as the modulation of sleep-related arousal courses. These can be primary when directly related to the inability to sleep, or secondary if considering the relationship with thoughts about sleep (such as the tendency to create bias in the attention and perception of sleep related thoughts).

Formerly, mindfulness-based cognitive therapy (MTPC) was designed for the treatment of chronic depression and has shown to be efficacious. It was hypothesized that interoceptive dysfunction in the insula, commonly observed in anxiety and depression, may respond to MTPC by the gained interoceptive awareness, which provides advantage to adapt to life challenges and ongoing adjustments.

Based on the currently available literature, mindfulness-based strategies may be a valuable treatment option in sleep disorders, especially for patients with concomitant mental illness. Therefore, it is necessary further research to standardize in terms of type of approach, duration, and outcome measures since it seems promising as an intervention for insomnia.

None Declared

Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD.

Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age).

Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD.

Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

To evaluate the construct validity of the NIH Toolbox Cognitive Battery (NIH TB-CB) in the healthy oldest-old (85+ years old).

Our sample from the McKnight Brain Aging Registry consists of 179 individuals, 85 to 99 years of age, screened for memory, neurological, and psychiatric disorders. Using previous research methods on a sample of 85 + y/o adults, we conducted confirmatory factor analyses on models of NIH TB-CB and same domain standard neuropsychological measures. We hypothesized the five-factor model (Reading, Vocabulary, Memory, Working Memory, and Executive/Speed) would have the best fit, consistent with younger populations. We assessed confirmatory and discriminant validity. We also evaluated demographic and computer use predictors of NIH TB-CB composite scores.

Findings suggest the six-factor model (Vocabulary, Reading, Memory, Working Memory, Executive, and Speed) had a better fit than alternative models. NIH TB-CB tests had good convergent and discriminant validity, though tests in the executive functioning domain had high inter-correlations with other cognitive domains. Computer use was strongly associated with higher NIH TB-CB overall and fluid cognition composite scores.

The NIH TB-CB is a valid assessment for the oldest-old samples, with relatively weak validity in the domain of executive functioning. Computer use’s impact on composite scores could be due to the executive demands of learning to use a tablet. Strong relationships of executive function with other cognitive domains could be due to cognitive dedifferentiation. Overall, the NIH TB-CB could be useful for testing cognition in the oldest-old and the impact of aging on cognition in older populations.

To determine whether age, gender and marital status are associated with prognosis for adults with depression who sought treatment in primary care.

Medline, Embase, PsycINFO and Cochrane Central were searched from inception to 1st December 2020 for randomised controlled trials (RCTs) of adults seeking treatment for depression from their general practitioners, that used the Revised Clinical Interview Schedule so that there was uniformity in the measurement of clinical prognostic factors, and that reported on age, gender and marital status. Individual participant data were gathered from all nine eligible RCTs (N = 4864). Two-stage random-effects meta-analyses were conducted to ascertain the independent association between: (i) age, (ii) gender and (iii) marital status, and depressive symptoms at 3–4, 6–8,<Vinod: Please carry out the deletion of serial commas throughout the article> and 9–12 months post-baseline and remission at 3–4 months. Risk of bias was evaluated using QUIPS and quality was assessed using GRADE. PROSPERO registration: CRD42019129512. Pre-registered protocol https://osf.io/e5zup/.

There was no evidence of an association between age and prognosis before or after adjusting for depressive ‘disorder characteristics’ that are associated with prognosis (symptom severity, durations of depression and anxiety, comorbid panic disorderand a history of antidepressant treatment). Difference in mean depressive symptom score at 3–4 months post-baseline per-5-year increase in age = 0(95% CI: −0.02 to 0.02). There was no evidence for a difference in prognoses for men and women at 3–4 months or 9–12 months post-baseline, but men had worse prognoses at 6–8 months (percentage difference in depressive symptoms for men compared to women: 15.08% (95% CI: 4.82 to 26.35)). However, this was largely driven by a single study that contributed data at 6–8 months and not the other time points. Further, there was little evidence for an association after adjusting for depressive ‘disorder characteristics’ and employment status (12.23% (−1.69 to 28.12)). Participants that were either single (percentage difference in depressive symptoms for single participants: 9.25% (95% CI: 2.78 to 16.13) or no longer married (8.02% (95% CI: 1.31 to 15.18)) had worse prognoses than those that were married, even after adjusting for depressive ‘disorder characteristics’ and all available confounders.

Clinicians and researchers will continue to routinely record age and gender, but despite their importance for incidence and prevalence of depression, they appear to offer little information regarding prognosis. Patients that are single or no longer married may be expected to have slightly worse prognoses than those that are married. Ensuring this is recorded routinely alongside depressive ‘disorder characteristics’ in clinic may be important.

COVID-19 altered research in Clinical and Translational Science Award (CTSA) hubs in an unprecedented manner, leading to adjustments for COVID-19 research.

CTSA members volunteered to conduct a review on the impact of CTSA network on COVID-19 pandemic with the assistance from NIH survey team in October 2020. The survey questions included the involvement of CTSAs in decision-making concerning the prioritization of COVID-19 studies. Descriptive and statistical analyses were conducted to analyze the survey data.

60 of the 64 CTSAs completed the survey. Most CTSAs lacked preparedness but promptly responded to the pandemic. Early disruption of research triggered, enhanced CTSA engagement, creation of dedicated research areas and triage for prioritization of COVID-19 studies. CTSAs involvement in decision-making were 16.75 times more likely to create dedicated diagnostic laboratories (95% confidence interval [CI] = 2.17–129.39; P < 0.01). Likewise, institutions with internal funding were 3.88 times more likely to establish COVID-19 dedicated research (95% CI = 1.12–13.40; P < 0.05). CTSAs were instrumental in securing funds and facilitating establishment of laboratory/clinical spaces for COVID-19 research. Workflow was modified to support contracting and IRB review at most institutions with CTSAs. To mitigate chaos generated by competing clinical trials, central feasibility committees were often formed for orderly review/prioritization.

The lessons learned from the COVID-19 pandemic emphasize the pivotal role of CTSAs in prioritizing studies and establishing the necessary research infrastructure, and the importance of prompt and flexible research leadership with decision-making capacity to manage future pandemics.

The heterogeneity in the manifestation of PSTD symptomatology has never been described in a developmental period spanning from middle childhood through adolescence. The examination of developmental influences on PTSD symptomatic expression is a high priority for DSM-V and could inform research on the etiology and treatment of PTSD.

To examine the symptom structure of PTSD across different age, gender, and exposure groups, and in association with impairment and other disorders.

To identify homogeneous latent classes of PTSD symptoms in children and adolescents.

Latent class analysis (LCA) was applied to 6,733 New York City students (4th–12th grades) exposed to 9/11-related potentially traumatic events. LCA was first applied to PTSD symptoms only, stratified by age, gender and empirically defined exposure groups, and then in combination with impairment indicators. The resultant classes were studied in association with other disorders.

LCA identified 4 classes that vary in severity and symptom configuration. Only the most severe profile, qualitatively characterized by the presence of traumatic memories in combination with avoidance and sleep-related problems, showed high levels of impairment and high rates of other disorders. Girls after puberty and subjects indirectly exposed to 9/11 are at increased risk of severe disturbance.

The 4-class model describes quantitative and qualitative differences in the structure of PTSD across age, gender and exposure. These findings support the inclusion of developmental considerations into DSM-V PTSD diagnostic criteria and suggest that also gender and the nature of traumatic exposure inflence PTSD phenomenology in children and adolescents.

The capacity to accumulate information over time is crucial to our functioning in an ever-changing world. Recently, in healthy subjects, we showed that brain uses a distributed and hierarchical network of brain areas to process information over time. Specifically, we revealed hierarchy of information processing over time from early sensory areas toward high order perceptual and cognitive areas. Here, we investigate this issue in first-episode schizophrenia patients.

Previous studies posited that schizophrenia is the result of impairment of hierarchical temporal processing by the brain, claiming for impairment in use of context while being processing information. The hierarchical temporal deficit is a fundamental trait that may be a better target for the study of etiology and pathophysiology of the disease.

We intended to map, in schizophrenia patients, the topographical organization of temporal scales using an ecologically relevant auditory stimulus - a real-life story. In addition, we assumed that studying healthy siblings, who are at high-risk for cognitive dysfunctions, will enable to determine functional neuromarkers of predisposition to disorder.

The fMRI data were analyzed using inter-subject correlation approach. The time-courses within each brain area in schizophrenia patients were estimated against healthy controls and unaffected siblings of the patients.

Among patients, we observed impaired hierarchy with processing intact in low level but disturbed in high level. The sibling group showed an intermediate effect.

Better understanding of the underlying neural circuit involved in information processing in schizophrenia patients may assist in early identification of functional neuromarkers for the disease.

Some techniques of psychotherapy are now widely evidence-based and very cost effective, especially cognitive and behavioral therapies. Most of the studies are indirectly based on patient reported outcomes or problematic behaviors evaluated before and after the psychotherapy. Unfortunately, studies struggle to control for what is actually happening during psychotherapy, especially the non-specific aspects, like the interaction between the patient and the therapist, that is a known predictor of psychotherapeutic efficacy. Consequently, it is difficult to make precise links between theory and practice, control its application and understand which of its ingredients are the most important.

Here, we suggest a research framework to extract automatically social signals from psychotherapy videos. We focused on the extraction of synchrony of the motor signal since it was considered to be a predictor of psychotherapeutic outcome in an earlier study and a relevant signal for the study of mother-child interactions.

We developed open source python and R scripts to compute this synchrony of motion history on a database of interaction between a parent and a child http://bit.ly/syncpsy

We confirmed that synchrony, was a relevant signal for studying social interactions since the scores are completely different from synchrony scores computed on shuffle motion history data. However, these scores alone are unable to distinguish the two periods of the videos (with and without disagreement).

Synchrony of motion history is a promising marker of social interactions.

The authors have not supplied their declaration of competing interest.

Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.

Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.

Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).

A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

This paper examines whether a relationship exists between paternal psychological stability and daughters' symptomatology following the death of a wife/mother from breast cancer. Specifically, is there a relationship between paternal parenting style and the daughters' subsequent capacity to form committed relationships later in life?

We assessed 68 adult daughters (average age = 23.5 years) since the mother's breast cancer diagnosis by means of a semistructured clinical interview and psychological testing.

The daughters were subdivided into three psychiatric risk groups. Those in the highest risk group were most likely to be single and to have high CES–Depression and STAI–Anxiety scores. Daughters in the highest risk group were also most likely to have fathers who abused substances, fathers who had experienced a serious psychiatric event, and families with the most closed communication about the mother's cancer.

Psychopathology in fathers correlated with increasing anxiety and depression in adult daughters. Daughters at the highest level of risk had the most severe affective states, the most disturbed father–daughter bonding, and the least ability to create successful interpersonal relationships as adults. We suggest specific interventions for these daughters of the lowest-functioning fathers.