Intergenerational continuity of loneliness and potential mechanisms: Young Finns Multigenerational Study.

Evidence on the intergenerational continuity of loneliness and on potential mechanisms that connect loneliness across successive generations is limited. We examined the association between loneliness of (G0) parents (859 mothers and 570 fathers, mean age 74 years) and their children (G1) (433 sons and 558 daughters, mean age 47 years) producing 991 parent-offspring pairs and tested whether these associations were mediated through subjective socioeconomic position, temperament characteristics, cognitive performance, and depressive symptoms. Mean loneliness across parents had an independent effect on their adult children's experienced loneliness (OR = 1.72, 95% CI 1.23-2.42). We also found a robust effect of mothers' (OR = 1.64, 95% CI 1.17-2.29), but not of fathers' loneliness (OR = 1.47, 95% CI 0.96-2.25) on offspring's experienced loneliness in adulthood. The associations were partly mediated by offspring depressive (41-54%) and anxiety (29-31%) symptoms. The current findings emphasize the high interdependence of loneliness within families mediated partly by offspring's mental health problems.

School achievement in adolescence and the risk of mental disorders in early adulthood: a Finnish nationwide register study.

School grades in adolescence have been linked to later psychiatric outcomes, but large-scale nationwide studies across the spectrum of mental disorders are scarce. In the present study, we examined the risk of a wide array of mental disorders in adulthood, as well as the risk of comorbidity, associated with school achievement in adolescence. We used population-based cohort data comprising all individuals born in Finland over the period 1980-2000 (N = 1,070,880) who were followed from age 15 or 16 until a diagnosis of mental disorder, emigration, death, or December 2017, whichever came first. Final grade average from comprehensive school was the exposure, and the first diagnosed mental disorder in a secondary healthcare setting was the outcome. The risks were assessed with Cox proportional hazards models, stratified Cox proportional hazard models within strata of full-siblings, and multinomial regression models. The cumulative incidence of mental disorders was estimated using competing risks regression. Better school achievement was associated with a smaller risk of all subsequent mental disorders and comorbidity, except for eating disorders, where better school achievement was associated with a higher risk. The largest associations were observed between school achievement and substance use disorders. Overall, individuals with school achievement more than two standard deviations below average had an absolute risk of 39.6% of a later mental disorder diagnosis. By contrast, for individuals with school achievement more than two standard deviations above average, the absolute risk of a later mental disorder diagnosis was 15.7%. The results show that the largest mental health burden accumulates among those with the poorest school achievement in adolescence.

Socioeconomic position at the age of 30 and the later risk of a mental disorder: a nationwide population-based register study.

BACKGROUND: A study was undertaken to examine the association between multiple indicators of socioeconomic position (SEP) at the age of 30 and the subsequent risk of the most common mental disorders. METHODS: All persons born in Finland between 1966 and 1986 who were alive and living in Finland at the end of the year when they turned 30 were included. Educational attainment, employment status and personal total income were used as the alternative measures of SEP. Cox proportional hazards models were used to examine the association of SEP at the age of 30 with later risk of mental disorders. Additional analyses were conducted using a sibling design to account for otherwise unobserved shared family characteristics. Competing risks models were used to estimate absolute risks. RESULTS: The study population included 1 268 768 persons, 26% of whom were later diagnosed with a mental disorder. Lower SEP at age 30 was consistently associated with a higher risk of being later diagnosed with a mental disorder, even after accounting for shared family characteristics and prior history of a mental disorder. Diagnosis-specific analyses showed that the associations were considerably stronger when substance misuse or schizophrenia spectrum disorders were used as an outcome. Absolute risk analyses showed that, by the age of 52 years, 58% of persons who had low educational attainment at the age of 30 were later diagnosed with a mental disorder. CONCLUSIONS: Poor SEP at the age of 30 is associated with an increased risk of being later diagnosed with a mental disorder.

Association of social isolation and loneliness with risk of incident hospital-treated infections: an analysis of data from the UK Biobank and Finnish Health and Social Support studies.

BACKGROUND: Although loneliness and social isolation have been linked to an increased risk of non-communicable diseases such as cardiovascular disease and dementia, their association with the risk of severe infection is uncertain. We aimed to examine the associations between loneliness and social isolation and the risk of hospital-treated infections using data from two independent cohort studies. METHODS: We assessed the association between loneliness and social isolation and incident hospital-treated infections using data for participants from the UK Biobank study aged 38-73 years at baseline and participants from the nationwide population-based Finnish Health and Social Support (HeSSup) study aged 20-54 years at baseline. For inclusion in the study, participants had to be linked to national health registries, have no history of hospital-treated infections at or before baseline, and have complete data on loneliness or social isolation. Participants with missing data on hospital-treated infections, loneliness, and social isolation were excluded from both cohorts. The outcome was defined as a hospital admission with a primary diagnosis of infection, ascertained via linkage to electronic health records. FINDINGS: After exclusion of 8·6 million participants for not responding or not providing appropriate consent, the UK Biobank cohort consisted of 456 905 participants (249 586 women and 207 319 men). 26 860 (6·2%) of 436 001 participants with available data were reported as being lonely and 40 428 (9·0%) of 448 114 participants with available data were socially isolated. During a median 8·9 years (IQR 8·0-9·6) of follow-up, 51 361 participants were admitted to hospital due to an infectious disease. After adjustment for age, sex, demographic and lifestyle factors, and morbidities, loneliness was associated with an increased risk of a hospital-treated infection (hazard ratio [HR] 1·12 [95% CI 1·07-1·16]), whereas social isolation was not (HR 1·01 [95% CI 0·97-1·04]). Of 64 797 individuals in the HeSSup cohort, 18 468 (11 367 women and 7101 men) were eligible for inclusion. 4466 (24·4%) of 18 296 were lonely and 1776 (9·7%) of 18 376 socially isolated. During a median follow-up of 10·0 years (IQR 10·0-10·1), 814 (4·4%) participants were admitted to hospital for an infectious disease. The HRs for the HeSSup study replicated those in the UK Biobank (multivariable-adjusted HR for loneliness 1·32 [95% CI 1·06-1·64]; 1·08 [0·87-1·35] for social isolation). INTERPRETATION: Loneliness might increase susceptibility to severe infections, although the magnitude of this effect appears modest and residual confounding cannot be excluded. Interventional studies are required before policy recommendations can advance. FUNDING: Academy of Finland, the UK Medical Research Council, and Wellcome Trust UK.

The associations of childhood psychosocial factors with cognitive function in midlife-The young finns study.

OBJECTIVE: An adverse psychosocial environment in childhood may harm cognitive development, but the associations for adulthood cognitive function remain obscure. We tested the hypothesis that adverse childhood psychosocial factors associate with poor cognitive function in midlife by leveraging the prospective data from the Young Finns Study. METHOD: At the age of 3-18 years, the participants' psychosocial factors (socioeconomic and emotional environment, parental health behaviors, stressful events, child's self-regulatory behavior, and social adjustment) were collected. In addition to the separate psychosocial factors, a score indicating their clustering was created. Cognitive function was measured at the age of 34-49 years with a computerized test addressing learning and memory (N = 1,011), working memory (N = 1,091), sustained attention and information processing (N = 1,071), and reaction and movement time (N = 999). RESULTS: We observed an inverse association between the accumulation of unfavorable childhood psychosocial factors and poorer learning and memory in midlife (age, sex, education, adulthood smoking, alcohol drinking, and physical activity adjusted ß = -0.032, SE = 0.01, p = .009). This association corresponded approximately to the effect of 7 months aging. Specifically, poor self-regulatory behavior (ß = -0.074, SE = 0.03, p = .032) and social adjustment in childhood (ß = -0.111, SE = 0.03, p = .001) associated with poorer learning ability and memory 30 years later. No associations were found for other cognitive domains. CONCLUSIONS: The findings suggest an association of childhood psychosocial factors with midlife learning ability and memory. If these links are causal, the results highlight the importance of a child's self-regulation and social adjustment as plausible determinants for adulthood cognitive health. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Long-term residential sunlight exposure associated with cognitive function among adults residing in Finland.

While sunlight may influence cognitive function through several pathways, associations of residential sunlight exposure with cognitive function are not well known. We evaluated associations of long-term residential sunlight exposure with cognitive function among a representative cohort of 1838 Finnish adults residing in Finland who underwent comprehensive cognitive assessment in midlife. We linked daily recordings of global solar radiation to study participants using residential information and calculated the average daily residential exposure to sunlight for four exposure time intervals: 2 months, 1 year, 2 years and 5 years prior to the date of the cognition assessment. Associations of the residential sunlight exposure with cognitive function were assessed using linear regression analyses adjusting for season, sex, age, and individual- and neighborhood-level socioeconomic characteristics. Greater average residential sunlight exposure over 2 and 5 years prior to the cognitive function assessment was associated with better global cognitive function (b = 0.13, 95% CI = 0.01, 0.25; b = 0.17, 95% CI = 0.05, 0.29, per 1 MJ/m2 difference in sunlight exposure), while no associations with global cognitive function were observed at shorter exposure time intervals. In domain-specific analyses, greater residential exposure to sunlight over 1, 2 and 5 years prior to the cognitive function assessment was associated with better performance on new learning and visual memory (b = 0.10, 95% CI = 0.00, 0.20; b = 0.16, 95% CI = 0.04, 0.28; b = 0.19, 95% CI = 0.08, 0.31) and sustained attention (b = 0.15, 95% CI = 0.05, 0.25; b = 0.18, 95% CI = 0.06, 0.30; b = 0.17, 95% CI = 0.05, 0.29), but worse performance on reaction time (b = - 0.12, 95% CI = - 0.22, - 0.02; b = -0.15, 95% CI = - 0.28, - 0.02; b = - 0.18, 95% CI = - 0.30, - 0.05). Residential sunlight exposure was not associated with executive function. These findings suggest long-term residential sunlight exposure may be an environmental factor influencing cognitive function among a cognitively healthy cohort residing in Northern Europe. Further studies in populations residing in different geographical locations are needed.

Predictors of Dropout in a Digital Intervention for the Prevention and Treatment of Depression in Patients With Chronic Back Pain: Secondary Analysis of Two Randomized Controlled Trials.

BACKGROUND: Depression is a common comorbid condition in individuals with chronic back pain (CBP), leading to poorer treatment outcomes and increased medical complications. Digital interventions have demonstrated efficacy in the prevention and treatment of depression; however, high dropout rates are a major challenge, particularly in clinical settings. OBJECTIVE: This study aims to identify the predictors of dropout in a digital intervention for the treatment and prevention of depression in patients with comorbid CBP. We assessed which participant characteristics may be associated with dropout and whether intervention usage data could help improve the identification of individuals at risk of dropout early on in treatment. METHODS: Data were collected from 2 large-scale randomized controlled trials in which 253 patients with a diagnosis of CBP and major depressive disorder or subclinical depressive symptoms received a digital intervention for depression. In the first analysis, participants' baseline characteristics were examined as potential predictors of dropout. In the second analysis, we assessed the extent to which dropout could be predicted from a combination of participants' baseline characteristics and intervention usage variables following the completion of the first module. Dropout was defined as completing <6 modules. Analyses were conducted using logistic regression. RESULTS: From participants' baseline characteristics, lower level of education (odds ratio [OR] 3.33, 95% CI 1.51-7.32) and both lower and higher age (a quadratic effect; age: OR 0.62, 95% CI 0.47-0.82, and age2: OR 1.55, 95% CI 1.18-2.04) were significantly associated with a higher risk of dropout. In the analysis that aimed to predict dropout following completion of the first module, lower and higher age (age: OR 0.60, 95% CI 0.42-0.85; age2: OR 1.59, 95% CI 1.13-2.23), medium versus high social support (OR 3.03, 95% CI 1.25-7.33), and a higher number of days to module completion (OR 1.05, 95% CI 1.02-1.08) predicted a higher risk of dropout, whereas a self-reported negative event in the previous week was associated with a lower risk of dropout (OR 0.24, 95% CI 0.08-0.69). A model that combined baseline characteristics and intervention usage data generated the most accurate predictions (area under the receiver operating curve [AUC]=0.72) and was significantly more accurate than models based on baseline characteristics only (AUC=0.70) or intervention usage data only (AUC=0.61). We found no significant influence of pain, disability, or depression severity on dropout. CONCLUSIONS: Dropout can be predicted by participant baseline variables, and the inclusion of intervention usage variables may improve the prediction of dropout early on in treatment. Being able to identify individuals at high risk of dropout from digital health interventions could provide intervention developers and supporting clinicians with the ability to intervene early and prevent dropout from occurring.

Associations of long-term solar insolation with specific depressive symptoms: Evidence from a prospective cohort study.

Evidence suggests that sunlight counteracts depression, but the associations of long-term sunlight exposure with specific symptoms of depression are not well known. We evaluated symptom-specific associations of average 1-year solar insolation with DSM-5 depressive symptoms in a representative cohort of Finnish adults. The sample included 1,845 participants from the Cardiovascular Risk in Young Finns Study with data on DSM-5 depressive symptoms, place of residence and covariates. Daily recordings of global solar radiation were obtained from the Finnish Meteorological Institute. Each participant's residential zip code on each day one year prior to the assessment of depressive symptoms was linked to the solar radiation data, and 1-year average daily solar insolation was calculated. Associations of the average 1-year solar insolation with depressive symptoms were assessed with linear and logistic regression analyses adjusting for season, sex, age, as well as individual- and neighborhood-level socioeconomic characteristics. Average daily solar insolation over one year prior to the depressive symptom assessment was not associated with the total number of depressive symptoms reported by participants. In symptom-specific analyses, participants exposed to higher levels of solar insolation in their residential neighborhood were less likely to report suicidal thought (OR = 0.61, 95% CI, 0.39-0.94), and more likely to report changes in appetite (OR = 1.24, 95% CI, 1.00-1.54), changes in sleep (OR = 1.30, 95% CI, 1.06-1.59) and feelings of worthlessness/guilt (OR = 1.33, 95% CI = 1.07-1.65). These findings suggest that solar insolation may contribute to symptom-specific differences in depression. Studies in other populations residing in different geographical locations are needed.

Effectiveness of an Internet-Based and Telephone-Assisted Training for Parents of 4-Year-Old Children With Disruptive Behavior: Implementation Research.

BACKGROUND: There is a lack of effectiveness studies when digital parent training programs are implemented in real-world practice. The efficacy of the internet-based and telephone-assisted Finnish Strongest Families Smart Website (SFSW) parent training intervention on the disruptive behavior of 4-year-old children was studied in a randomized controlled trial setting in Southwest Finland between 2011 and 2013. After that, the intervention was implemented nationwide in child health clinics from 2015 onwards. OBJECTIVE: The main aim of this study was to compare the treatment characteristics and effectiveness of the SFSW parent training intervention between the families who received the intervention when it was implemented as a normal practice in child health clinics and the families who received the same intervention during the randomized controlled trial. METHODS: The implementation group comprised 600 families who were recruited in the SFSW intervention between January 2015 and May 2017 in real-world implementation. The RCT intervention group comprised 232 families who were recruited between October 2011 and November 2013. The same demographic and child and parent measures were collected from both study groups and were compared using linear mixed-effect models for repeated measurements. The child psychopathology and functioning level were measured using the Child Behavior Checklist (CBCL) version 1.5-5 for preschool children, the Inventory of Callous-Unemotional Traits (ICU), and a modified version of the Barkley Home Situations Questionnaire. Parenting skills were measured using the 31-item Parenting Scale and the shorter 21-item Depression, Anxiety and Stress Scale (DASS-21). The estimated child and parent outcomes were adjusted for CBCL externalizing scores at baseline, maternal education, duration of the behavior problems, and paternal age. The baseline measurements of each outcome were used as covariates. RESULTS: The implementation group was more likely to complete the intervention than the RCT intervention group (514/600, 85.7% vs 176/232, 75.9%, respectively; P<.001). There were no significant differences between the implementation and RCT intervention groups with regard to child measures, including CBCL externalizing score (-0.2, 95% CI -1.3 to 1.6; P=.83), total score (-0.7, 95% CI -3.0 to 4.5; P=.70), internalizing score (-0.3, 95% CI -1.0 to 1.6; P=.64), and ICU total score (-0.4, 95% Cl -1.9 to 1.2; P=.64). No significant difference was detected in the Parenting Scale total score (0.0, 95% Cl -0.1 to 0.1; P=.50), while DASS-21 total score differed nearly significantly (2.5, 95% Cl 0.0-5.1; P=.05), indicating better improvement in the implementation group. CONCLUSIONS: The internet-based and telephone-assisted SFSW parent training intervention was effectively implemented in real-world settings. These findings have implications for addressing the unmet needs of children with disruptive behavior problems. Our initiative could also provide a quick socially distanced solution for the considerable mental health impact of the COVID-19 pandemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT01750996; https://clinicaltrials.gov/ct2/show/NCT01750996. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/1471-2458-13-985.

Single-Session, Internet-Based Cognitive Behavioral Therapy to Improve Parenting Skills to Help Children Cope With Anxiety During the COVID-19 Pandemic: Feasibility Study.

BACKGROUND: The COVID-19 pandemic has had a major impact on families' daily routines and psychosocial well-being, and technology has played a key role in providing socially distanced health care services. OBJECTIVE: The first objective of this paper was to describe the content and delivery of a single-session, internet-based cognitive behavioral therapy (iCBT) intervention, which has been developed to help parents cope with children's anxiety and manage daily situations with their children. The second objective was to report user adherence and satisfaction among the first participants who completed the intervention. METHODS: The Let's Cope Together intervention has been developed by our research group. It combines evidence-based CBT elements, such as psychoeducation and skills to manage anxiety, with parent training programs that strengthen how parents interact with their child and handle daily situations. A pre-post design was used to examine user satisfaction and the skills the parents learned. Participants were recruited using advertisements, media activity, day care centers, and schools and asked about background characteristics, emotional symptoms, and parenting practices before they underwent the iCBT. After they completed the 7 themes, they were asked what new parenting skills they had learned from the iCBT and how satisfied they were with the program. RESULTS: Of the 602 participants who filled in the baseline survey, 196 (32.6%) completed the program's 7 themes, and 189 (31.4%) completed the postintervention survey. Most (138/189, 73.0%) of the participants who completed the postintervention survey were satisfied with the program and had learned skills that eased both their anxiety (141/189, 74.6%) and their children's anxiety (157/189, 83.1%). The majority (157/189, 83.1%) reported that they learned how to organize their daily routines better, and just over one-half (100/189, 53.0%) reported that the program improved how they planned each day with their children. CONCLUSIONS: The single-session iCBT helped parents to face the psychological demands of the COVID-19 pandemic. Future studies should determine how the participation rate and adherence can be optimized in digital, universal interventions. This will help to determine what kinds of programs should be developed, including their content and delivery.

Association of social isolation, loneliness and genetic risk with incidence of dementia: UK Biobank Cohort Study.

BACKGROUND: Social isolation and loneliness have been associated with increased risk of dementia, but it is not known whether this risk is modified or confounded by genetic risk of dementia. METHODS: We used the prospective UK Biobank study with 155 070 participants (mean age 64.1 years), including self-reported social isolation and loneliness. Genetic risk was indicated using the polygenic risk score for Alzheimer's disease and the incident dementia ascertained using electronic health records. RESULTS: Overall, 8.6% of participants reported that they were socially isolated and 5.5% were lonely. During a mean follow-up of 8.8 years (1.36 million person years), 1444 (0.9% of the total sample) were diagnosed with dementia. Social isolation, but not loneliness, was associated with increased risk of dementia (HR 1.62, 95% CI 1.38 to 1.90). There were no interaction effects between genetic risk and social isolation or between genetic risk and loneliness predicting incident dementia. Of the participants who were socially isolated and had high genetic risk, 4.4% (95% CI 3.4% to 5.5%) were estimated to developed dementia compared with 2.9% (95% CI 2.6% to 3.2%) of those who were not socially isolated but had high genetic risk. Comparable differences were also in those with intermediate and low genetic risk levels. CONCLUSIONS: Socially isolated individuals are at increased risk of dementia at all levels of genetic risk.

Parental psychological problems were associated with higher screen time and the use of mature-rated media in children.

AIM: Parents' psychological problems may affect children's screen time, but research has been scarce. We examined the association between parental psychological problems and children's screen media behaviours in a nationally representative sample. METHODS: The participants were from the Adolescent Brain Cognitive Development study, recruited by probability sampling from the USA population. Children reported their use of TV, videos, video games, social media and mature-rated media. The parents (85% mothers) reported psychological problems using the Adult Self-Report questionnaire. RESULTS: In 10,650 children (5112 girls, 5538 boys) aged 9.9 ± 0.6 years, the presence of parental psychological problems was associated with children spending more daily time on screen media and with meeting the recommendation of ≤2 daily hours less often than children whose parents did not have psychological problems. Parental psychological problems were associated with children's TV watching, video watching and gaming but not with using social media. Parental internalising problems were associated with children watching mature-rated movies (odds ratio [OR] = 1.14, 95% confidence interval [CI] = 1.00, 1.30) and playing mature-rated games (OR = 1.27, 95% CI = 1.11, 1.45). CONCLUSION: Presence of parental psychological problems is associated with higher screen time and use of mature-rated media in children. This cross-sectional study was not able to examine causal associations.

Long-term cumulative light exposure from the natural environment and sleep: A cohort study.

We analysed (A) the association of short-term as well as long-term cumulative exposure to natural light, and (B) the association of detailed temporal patterns of natural light exposure history with three indicators of sleep: sleep duration, sleep problems, and diurnal preference. Data (N = 1,962; 55% women; mean age 41.4 years) were from the prospective Young Finns Study, which we linked to daily meteorological data on each participant's neighbourhood natural light exposure using residential postal codes. Sleep outcomes were self-reported in 2011. We first examined associations of the sleep outcomes with cumulative light exposure of 5-year, 2-year, 1-year, and 2-month periods prior to the sleep assessment using linear and Poisson regression models adjusting for potential confounders. We then used a data-driven time series approach to detect clusters of participants with different light exposure histories and assessed the associations of these clusters with the sleep outcomes using linear and Poisson regression analyses. A greater cumulative light exposure over ≥1 year was associated with a shorter sleep duration (ß = -0.10, 95% confidence interval [CI] -0.15 to -0.04), more sleep problems (incident rate ratio [IRR] 1.04, 95% CI 1.0-1.07) and diurnal preference towards eveningness (ß = -0.09, 95% CI -0.14 to -0.03). The data-driven exposure pattern of "slowly increasing" light exposure was associated with fewer overall sleep problems (IRR 0.93, 95% CI 0.88-0.98) compared to a "recently declining" light exposure group representing the "average-exposure" group. These findings suggest that living in an area with relatively more intense light exposure for a longer period of time influences sleep.

Digital interventions for the treatment of depression: A meta-analytic review.

The high global prevalence of depression, together with the recent acceleration of remote care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of digital interventions for the treatment of depression. We provide a summary of the latest evidence base for digital interventions in the treatment of depression based on the largest study sample to date. A systematic literature search identified 83 studies (N = 15,530) that randomly allocated participants to a digital intervention for depression versus an active or inactive control condition. Overall heterogeneity was very high (I2 = 84%). Using a random-effects multilevel metaregression model, we found a significant medium overall effect size of digital interventions compared with all control conditions (g = .52). Subgroup analyses revealed significant differences between interventions and different control conditions (WLC: g = .70; attention: g = .36; TAU: g = .31), significantly higher effect sizes in interventions that involved human therapeutic guidance (g = .63) compared with self-help interventions (g = .34), and significantly lower effect sizes for effectiveness trials (g = .30) compared with efficacy trials (g = .59). We found no significant difference in outcomes between smartphone-based apps and computer- and Internet-based interventions and no significant difference between human-guided digital interventions and face-to-face psychotherapy for depression, although the number of studies in both comparisons was low. Findings from the current meta-analysis provide evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations. However, reported effect sizes may be exaggerated because of publication bias, and compliance with digital interventions outside of highly controlled settings remains a significant challenge. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Is symptom connectivity really the most important issue in depression? Depression as a dynamic system of interconnected symptoms revisited.

According to the network theory strong associations between symptoms drive the disease process. We compared those with and without diagnosed depressive disorders (DD+/DD-) and analysed the effects of differences in (a) network connectivity, (b) symptom thresholds, and (c) autoregressive loops (i.e. how strongly specific symptoms predict themselves) on the potential activation of symptoms over time using simulations developed by Cramer and others (2016). The parameters for the simulation (symptom connectivity and symptom threshold) were obtained from Ising models and cross-lagged panel network analyses. Data were from the nationally representative samples (Health 2000-2011 Study) of 4190 participants measured in 2011 (cross-sectional analyses) and 3201 participants measured in 2000 and 2011 (longitudinal analyses). DD diagnosis was based on the Composite International Diagnostic Interview and depressive symptoms were self-reported using the 13-item version of the Beck Depression Inventory (BDI). Differences in symptom connectivity between participants with and without DD were not observed, but the mean probability (threshold) of symptom existence in the DD + group was higher than in the DD-group (0.41 vs. 0.12). Simulation showed that there are more active symptoms in the DD + group after 10 000 time points (means 1.2 vs. 4.6) than in the DD-group. This difference largely disappeared when we used longitudinal networks, including autoregressive loops, in the connectivity matrix. Our results suggest that the differences in symptom thresholds and autoregressive loops may be more important features than symptom connectivity in differentiating people with and without DD.

Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data.

Background: Depression and anxiety are leading causes of disability worldwide but often remain undetected and untreated. Smartphone and wearable devices may offer a unique source of data to detect moment by moment changes in risk factors associated with mental disorders that overcome many of the limitations of traditional screening methods. Objective: The current study aimed to explore the extent to which data from smartphone and wearable devices could predict symptoms of depression and anxiety. Methods: A total of N = 60 adults (ages 24-68) who owned an Apple iPhone and Oura Ring were recruited online over a 2-week period. At the beginning of the study, participants installed the Delphi data acquisition app on their smartphone. The app continuously monitored participants' location (using GPS) and smartphone usage behavior (total usage time and frequency of use). The Oura Ring provided measures related to activity (step count and metabolic equivalent for task), sleep (total sleep time, sleep onset latency, wake after sleep onset and time in bed) and heart rate variability (HRV). In addition, participants were prompted to report their daily mood (valence and arousal). Participants completed self-reported assessments of depression, anxiety and stress (DASS-21) at baseline, midpoint and the end of the study. Results: Multilevel models demonstrated a significant negative association between the variability of locations visited and symptoms of depression (beta = -0.21, p = 0.037) and significant positive associations between total sleep time and depression (beta = 0.24, p = 0.023), time in bed and depression (beta = 0.26, p = 0.020), wake after sleep onset and anxiety (beta = 0.23, p = 0.035) and HRV and anxiety (beta = 0.26, p = 0.035). A combined model of smartphone and wearable features and self-reported mood provided the strongest prediction of depression. Conclusion: The current findings demonstrate that wearable devices may provide valuable sources of data in predicting symptoms of depression and anxiety, most notably data related to common measures of sleep.

Typologies of Family Functioning and 24-h Movement Behaviors.

Research on the importance of the family environment on children's health behaviors is ubiquitous, yet critical gaps in the literature exist. Many studies have focused on one family characteristic and have relied on variable-centered approaches as opposed to person-centered approaches (e.g., latent profile analysis). The purpose of the current study was to use latent profile analysis to identify family typologies characterized by parental acceptance, parental monitoring, and family conflict, and to examine whether such typologies are associated with the number of movement behavior recommendations (i.e., physical activity, screen time, and sleep) met by children. Data for this cross-sectional observational study were part of the baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data were collected across 21 study sites in the United States. Participants included 10,712 children (female = 5143, males = 5578) aged 9 and 10 years (M = 9.91, SD = 0.62). Results showed that children were meaningfully classified into one of five family typologies. Children from families with high acceptance, medium monitoring, and medium conflict (P2; OR = 0.54; 95% CI, 0.39-0.76); high acceptance, medium monitoring, and high conflict (P3; OR = 0.28; 95% CI, 0.20, 0.40); low acceptance, low monitoring, and medium conflict (P4; OR = 0.24; 95% CI, 0.16, 0.36); and medium acceptance, low monitoring, and high conflict (P5; OR = 0.19; 95% CI, 0.12-0.29) were less likely to meet all three movement behavior recommendations compared to children from families with high acceptance, high monitoring, and low conflict (P1). These findings highlight the importance of the family environment for promoting healthy movement behaviors among children.

Three genetic-environmental networks for human personality.

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

Employment and earnings trajectories before and after sickness absence due to major depressive disorder: a nationwide case-control study.

OBJECTIVES: To examine employment and earnings trajectories before and after the first sickness absence period due to major depressive disorder (MDD). METHODS: All individuals (n=158 813) in Finland who had a first sickness absence period (lasting longer than 9 days) due to MDD between 2005 and 2015 were matched with one randomly selected individual of the same age and gender with no history of MDD. Employment status and earnings were measured using register-based data annually from 2005 to 2015. Generalised estimating equations were used to examine the trajectories of employment and earnings before and after MDD diagnosis in men and women separately. RESULTS: Sickness absence due to MDD was associated with increased probability of non-employment during and after the year of the first sickness absence period. In men, but not in women, the probability of being employed was lower 5 years before the sickness absence period due to MDD. When compared with the individuals in the control group, men had around 34% and women 15% lower earnings 1 year, and 40% and 23%, respectively, 5 years, after the first sickness absence period due to MDD. More severe MDD and longer duration of sickness absence period were associated with lower probability of being employed. CONCLUSIONS: Sickness absence due to MDD was associated with considerable reduction in employment and earnings losses. For men and individuals with more severe MDD, this reduction was before the first sickness period. This supports a reciprocal association between employment and earnings with MDD.

General Health Questionnaire (GHQ-12), Beck Depression Inventory (BDI-6), and Mental Health Index (MHI-5): psychometric and predictive properties in a Finnish population-based sample.

The short versions of the General Health Questionnaire (GHQ-12), Beck's Depression Inventory (BDI-6), and Mental Health Index (MHI-5) are all valid and reliable measures of general psychological distress, depressive symptoms, and anxiety. We tested the psychometric properties of the scales, their overlap, and their ability to predict mental health service use using both regression and machine learning (ML, random forest) approaches. Data were from the population-based FinHealth-2017 Study of adults (N = 4270) with data on all of the evaluated instruments. Constructive validity, internal consistency, invariance, and optimal cut-off points in predicting mental health services were tested. Constructive validity was acceptable and all instruments measured their own distinct phenomenon. Some of the item scoring in BDI-6 was not optimal, and the sensitivity and specificity of all scales were relatively weak in predicting service use. Small gender differences emerged in optimal cut-off points. ML did not improve model predictions. GHQ-12, BDI-6, and MHI-5 may be interpreted to measure different constructs of psychological health symptoms, but are not particularly useful predictors of service use.