Preterm birth poses a risk to cognition during childhood. The resulting cognitive problems may persist into young adulthood. The early motor repertoire in infancy is predictive of neurocognitive development in childhood. Our present aim was to investigate whether it also predicts neurocognitive status in young adulthood.

We conducted an explorative observational follow-up study in 37 young adults born at a gestational age of less than 35 weeks and/or with a birth weight below 1200 g. Between 1992 and 1997, these individuals were videotaped up until 3 months’ corrected age to assess the quality of their early motor repertoire according to Prechtl. The assessment includes general movements, fidgety movements (FMs), and a motor optimality score (MOS). In young adulthood, the following cognitive domains were assessed: memory, speed of information processing, language, attention, and executive function.

Participants in whom FMs were absent in infancy obtained lower scores on memory, speed of information processing, and attention than those with normal FMs. Participants with aberrant FMs, that is, absent or abnormal, obtained poorer scores on memory, speed of information processing speed, attention, and executive function compared to peers who had normal FMs. A higher MOS was associated with better executive function.

The quality of the early motor repertoire is associated with performance in various cognitive domains in young adulthood. This knowledge may be applied to enable the timely recognition of preterm-born individuals at risk of cognitive dysfunctions.

Predicting future states of psychopathology such as depressive episodes has been a hallmark initiative in mental health research. Dynamical systems theory has proposed that rises in certain ‘early warning signals’ (EWSs) in time-series data (e.g. auto-correlation, temporal variance, network connectivity) may precede impending changes in disorder severity. The current study investigates whether rises in these EWSs over time are associated with future changes in disorder severity among a group of patients with major depressive disorder (MDD).

Thirty-one patients with MDD completed the study, which consisted of daily smartphone-delivered surveys over 8 weeks. Daily positive and negative affect were collected for the time-series analyses. A rolling window approach was used to determine whether rises in auto-correlation of total affect, temporal standard deviation of total affect, and overall network connectivity in individual affect items were predictive of increases in depression symptoms.

Results suggested that rises in auto-correlation were significantly associated with worsening in depression symptoms (r = 0.41, p = 0.02). Results indicated that neither rises in temporal standard deviation (r = −0.23, p = 0.23) nor in network connectivity (r = −0.12, p = 0.59) were associated with changes in depression symptoms.

This study more rigorously examines whether rises in EWSs were associated with future depression symptoms in a larger group of patients with MDD. Results indicated that rises in auto-correlation were the only EWS that was associated with worsening future changes in depression.

Does the genetic aptitude for educational attainment (GAEA) moderate the genetic risk for alcohol use disorder (AUD) and drug use disorder (DUD)?

In the native Swedish population, born 1960–1980 and followed through 2017 (n = 1 862 435), the family genetic risk score (FGRS) for AUD and DUD and GAEA were calculated from, respectively, the educational attainment and risk for AUD and DUD, of 1st through 5th degree relatives from Swedish national registers. Analyses utilized Aalen's linear hazards models.

Risk for AUD was robustly predicted by the main effects of FGRSAUD [b = 6.32 (95% CI 6.21–6.43), z = 64.9, p < 0.001) and GAEA [b = −2.90 (2.83–2.97), z = 44.1, p < 0.001] and their interaction [b = −1.93 (1.83–2.03), z = 32.9, p < 0.001]. Results were similar for the prediction of DUD by the main effects of FGRSDUD [b = 4.65 (CI 4.56–4.74), z = 59.4, p < 0.001] and GAEA [−2.08 (2.03–2.13), z = 46.4, p < 0.001] and their interaction [b = −1.58 (1.50–1.66)), z = 30.2, p < 0.001]. The magnitude of the interactions between GAEA and FGRSAUD and FGRSDUD in the prediction of, respectively, AUD and DUD was attenuated only slightly by the addition of educational attainment to the model.

The genetic propensity to high educational attainment robustly moderates the genetic risk for both AUD and DUD such that the impact of the genetic liability to AUD and DUD on the risk of illness is substantially attenuated in those with high v. low GAEA. This effect is not appreciably mediated by the actual level of educational attainment. These naturalistic findings could form the basis of prevention efforts in high-risk youth.

Emerging evidence suggests low vision may be a modifiable risk factor for cognitive decline. We examined effects of baseline visual acuity (VA) on level of, and change in, cognitive test performance over 9 years.

A population-based sample of 1,621 participants (average age 77 years) completed a comprehensive neuropsychological evaluation and VA testing at baseline and reassessed at nine subsequent annual visits. Linear regression modeled the association between baseline VA and concurrent cognitive test performance. Joint modeling of a longitudinal sub-model and a survival sub-model to adjust for attrition were used to examine associations between baseline VA and repeated cognitive test performance over time.

Better baseline VA was associated cross-sectionally with younger age, male sex, greater than high school education, and higher baseline neuropsychological test scores on both vision-dependent (B coefficient range −0.163 to −0.375, p = .006 to <.001) and vision-independent tests (−0.187 to −0.215, p = .003 to .002). In longitudinal modeling, better baseline VA was associated with slower decline in vision-dependent tests (B coefficient range −0.092 to 0.111, p = .005 to <.001) and vision-independent tests (−0.107 to 0.067, p = .007 to <.001).

Higher VA is associated with higher concurrent cognitive abilities and slower rates of decline over 9 years in both vision-dependent and vision-independent tests of memory, language, and executive functioning. Findings are consistent with emerging literature supporting vision impairment in aging as a potentially modifiable risk factor for cognitive decline. Clinicians should encourage patient utilization of vision assessment and correction with the added aim of protecting cognition.

Lack of knowledge and discriminatory attitudes and behaviours towards individuals with mental disorders is a worldwide problem but may be particularly damaging for young people. This pilot study examined knowledge, attitudes and behaviours towards schizophrenia, bipolar disorder and autism within a large sample of adults in Ireland, a country with the youngest population in Europe, in order to better understand public views on these groups.

In a correlational, cross-sectional design, 307 adults in Ireland over the age of 18 completed a questionnaire over Google Forms examining knowledge, attitudes and behaviours towards schizophrenia, bipolar disorder and autism. Responses to questions specifically relating to each diagnosis were compared using trimmed mean ANOVA to examine whether responses to questions differed depending on diagnosis.

Results indicate varied knowledge, attitudes and behaviours towards these groups, but a majority believe it should be a research priority. ANOVA and post hoc tests revealed significant differences in knowledge, attitudes and behaviours towards each of schizophrenia, bipolar disorder, and autism (p < 0.005), and reported attitudes and behaviours towards schizophrenia were more negative than either bipolar disorder or autism. A majority of participants (54.8%) felt not informed enough about mental health by the media.

In our Irish sample, type and level of stigma varies according to mental health diagnosis. Our sample also report feeling inadequately informed about mental health by the media. Thus future policy and campaigns could consider targeting individual mental health diagnoses, with a focus on increasing familiarity and knowledge.

Rates of suicide in older adults may be higher than reported due to poor understandings of presentation of suicide ideation in this group. The objectives of this paper were to (i) review current measurement tools designed for older adults to detect suicide ideation and (ii) assess their psychometric properties.

We used a systematic review approach to identify measurement tools developed specifically for older adults without cognitive decline or impairment.

Ten articles that reported on a total of seven different measurement tools were identified. These included tools that focused on resiliency to suicide and those that measured risk of suicide behavior. There was wide variation across the articles: some were adaptations of existing scales to suit older populations, others were developed by authors; they varied in length from four to 69 items; a range of settings was used, and there was a mix of self-report and clinician-administered measures. Most displayed good psychometric properties, with both approaches showing similar quality. Limitations in terms of samples, settings, and measurement design are discussed.

The case for specific measures for older adults is clear from this review. There appear to be unique factors that should be considered in understanding suicide ideation and behavior among older adults that may not be directly assessed in non-specific measurements. However, there is a need to expand the diversity of individuals included in measurement development to ensure they are appropriate across gender, culture and minority status, and for the views of professionals to be considered.

Exposure to parental suicide has been associated with increased risk for suicide and suicide attempts, although the strength of this association is unclear as evidence remains inconsistent.

To quantify this risk using meta-analysis and identify potential effect modifiers.

A systematic search in PubMed, PsycInfo and Embase databases to 2020 netted 3614 articles. Inclusion criteria were: observation of history of parental death by suicide, comparison with non-exposed populations and definition of suicide and suicide attempt according to standardised criteria. We focused on population-based studies. The primary outcome was the pooled relative risk (RR) for incidence of suicide attempt and suicide in offspring of a parent who died by suicide compared with offspring of two living parents. Additionally, we compared the RR for attempted and completed suicide after parental suicide with the RR for attempted and completed suicide after parental death by other causes.

Twenty studies met our inclusion criteria. Offspring exposed to parental suicide were more likely to die by suicide (RR = 2.97, 95% CI 2.50–3.53) and attempt suicide (RR = 1.76, 95% CI 1.58–1.96) than offspring of two living parents. Furthermore, their risk of dying by or attempting suicide was significantly higher compared with offspring bereaved by other causes of death.

The experience of losing a parent to suicide is a strong and independent risk factor for suicidal behaviour in offspring. Our findings highlight the need for prevention strategies, outreach programmes and support interventions that target suicide-related outcomes in the exposed population.

Major depressive disorder (MDD) is closely related to obesity, inflammation, and insulin resistance, all together being etiologically linked to metabolic syndrome (MetS) development. The depressive disorder has a neuroendocrinological component, co-influencing the MetS, while MetS is characterised by increased cytokine levels, which are known to cause a depressed mood. This study aimed to establish biological subtypes of the depressive disorder based on researched clinical, laboratory, and anthropometric variables.

We performed a cross-sectional study on a sample of 293 subjects (145 suffering from a depressive disorder and 148 healthy controls). Results were analysed with multivariate statistical methods as well as with cluster and discriminant analysis. In order to classify depressive disorder on the grounds of laboratory, anthropometric, and clinical parameters, we performed cluster analysis, which resulted in three clusters.

The first cluster is characterised by low platelet serotonin, high cortisol levels, high blood glucose levels, high triglycerides levels, high Hamilton Depression Rating Scale score, high waist circumference, high C-Reactive Protein values, and a high number of previous depressive episodes, was named Combined (Metabolic) depression. The inflammatory depression cluster is defined with average platelet serotonin values, normal cortisol, and all other parameter levels, except for increased IL-6 levels. The serotoninergic depression cluster is characterised by markedly low platelet serotonin, and all other parameters are within the normal range.

From a biological point of view, depressive disorder is not uniform, and as such, these findings suggest potential clinically useful and generalisable biological subtypes of depressive disorder.