Few previous studies have established Snaith–Hamilton Pleasure Scale (SHAPS) cut-off values using receiver operating characteristic curve analysis and applied these values to compare predictors of anhedonia between clinical and nonclinical groups.

To determine the optimal cut-off values for the SHAPS and use them to identify predictors of anhedonia in clinical and nonclinical groups in Taiwan.

This cross-sectional and correlational study used convenience sampling to recruit 160 patients from three hospitals and 412 students from two universities in northern Taiwan. Data analysis included receiver operating characteristic curve, univariate and multivariate analyses.

The optimal SHAPS cut-off values were 29.5 and 23.5 for the clinical and nonclinical groups, respectively. Moreover, two-stage analysis revealed that participants in the clinical group who perceived themselves as nondepressed, and participants in the nonclinical group who did not skip classes and whose fathers exhibited higher levels of care and protection were less likely to attain the cut-off values. Conversely, participants in the nonclinical group who reported lower academic satisfaction and were unwilling to seek help from family or friends were more likely to attain the cut-off values.

Our findings highlight the importance of optimal cut-off values in screening for depression risk within clinical and nonclinical groups. Accordingly, the development of comprehensive, individualised programmes to monitor variation trends in SHAPS scores and relevant predictors of anhedonia across different target populations is crucial.

Approximately 6.5 million Americans ages 65 and older have Alzheimer’s disease and related dementias, a prevalence projected to triple by 2060. While subtle impairment in cognition and instrumental activities of daily living (IADLs) arises in the mild cognitive impairment (MCI) phase, early detection of these insidious changes is difficult to capture given limitations. Traditional IADL assessments administered infrequently are less sensitive to early MCI and not conducive to tracking subtle changes that precede significant declines. Continuous passive monitoring of IADLs using sensors and software in home environments is a promising alternative. The purpose of this study was to determine which remotely monitored IADLs best distinguish between MCI and normal cognition.

Participants were 65 years or older, independently community-dwelling, and had at least one daily medication and home internet access. Clinical assessments were performed at baseline. Electronic pillboxes (MedTracker) and computer software (Worktime) measured daily medication and computer habits using the Oregon Center for Aging and Technology (ORCATECH) platform. The Survey for Memory, Attention, and Reaction Time (SMART; Trail A, Trail B, and Stroop Tests) is a self-administered digital cognitive assessment that was deployed monthly. IADL data was aggregated for each participant at baseline (first 90 days) in each domain and various features developed for each. The receiver operating characteristic area under the curve (ROC-AUC) was calculated for each feature.

Traditional IADL Questionnaires.

At baseline, 103 participants (normal n = 59, Mage = 73.6±5.5; MCI n = 44, Mage = 76.0±6.1) completed three functional questionnaires (Functional Activities Questionnaire; Measurement of Everyday Cognition (ECog), both self-report and informant). The Informant ECog demonstrated the highest AUC (72% AUC, p = <.001).

Remotely monitored in-home IADLs and self-administered brief online cognitive test performance.

Eighty-four had medication data (normal n = 48, Mage = 73.2±5.4; MCI n = 36, Mage = 75.6±6.9). Four features related to pillbox-use frequency (73% AUC) and four features related to pillbox-use time (62% AUC) were developed. The discrepancy between self-reported frequency of use versus actual use was the most discriminating (67% AUC, p = .03).

Sixty-six had computer data (normal n = 38, Mage = 73.6±6.1; MCI n = 28, Mage = 76.6±6.8). Average usage time showed 64% AUC (p = .048) and usage variability showed 60% AUC (p = .18).

One hundred and two completed the SMART (normal n = 59, Mage = 73.6±5.5; MCI n = 43, Mage = 75.9±6.2). Eleven features related to survey completion time demonstrated 80% AUC in discriminating cognition. Eleven features related to the number of clicks during the survey demonstrated 70% AUC. Lastly, seven mouse movement features demonstrated 71% AUC.

Pillbox use frequency combined features and self-administered brief online cognitive test combined features (e.g., completion times, mouse cursor movements) have acceptable to excellent ability to discriminate between normal cognition and MCI and are relatively comparable to informant rated IADL questionnaires. General computer usage habits demonstrated lower discriminatory ability. Our approach has applied implications for detecting and tracking older adults’ declining cognition and function in real world contexts.

We aimed to investigate child mortality, perinatal morbidities and congenital anomalies born by women with substance misuse during or before pregnancy (DP or BP).

Taiwan Birth Registration from 2004 to 2014 linking Integrated Illicit Drug Databases used to include substance misuse participates. Children born by mothers convicted of substance misuse DP or BP were the substance-exposed cohort. Two substance-unexposed comparison cohorts were established: one comparison cohort selected newborns from the rest of the population on a ratio of 1:1 and exact matched by the child’s gender, child’s birth year, mother’s birth year and child’s first use of the health insurance card; another comparison cohort matched newborns from exposed and unexposed mothers by their propensity scores calculated from logistic regression.

The exposure group included 1776 DP, 1776 BP and 3552 unexposed individuals in exact-matched cohorts. A fourfold increased risk of deaths in children born by mothers exposed to substance during pregnancy was found compared to unexposed group (hazard ratio [HR] = 4.54, 95% confidence interval (CI): 2.07–9.97]. Further multivariate Cox regression models with adjustments and propensity matching substantially attenuated HRs on mortality in the substance-exposed cohort (aHR = 1.62, 95% CI: 1.10–2.39). Raised risks of perinatal morbidities and congenital anomalies were also found.

Increased risks of child mortality, perinatal morbidities or congenital anomalies were found in women with substance use during pregnancy. From estimates before and after adjustments, our results showed that having outpatient visits or medical utilizations during pregnancy were associated with substantially attenuated HRs on mortality in the substance-exposed cohort. Therefore, the excess mortality risk might be partially explained by the lack of relevant antenatal clinical care. Our finding may suggest that the importance of early identification, specific abstinence program and access to appropriate antenatal care might be helpful in reducing newborn mortality. Adequate prevention policies may be formulated.

The most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries.

Face-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents.

3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2–4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness.

ADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Prognostic heterogeneity in early psychosis patients yields significant difficulties in determining the degree and duration of early intervention; this heterogeneity highlights the need for prognostic biomarkers. Although mismatch negativity (MMN) has been widely studied across early phases of psychotic disorders, its potential as a common prognostic biomarker in early periods, such as clinical high risk (CHR) for psychosis and first-episode psychosis (FEP), has not been fully studied.

A total of 104 FEP patients, 102 CHR individuals, and 107 healthy controls (HCs) participated in baseline MMN recording. Clinical outcomes were assessed; 17 FEP patients were treatment resistant, 73 FEP patients were nonresistant, 56 CHR individuals were nonremitters (15 transitioned to a psychotic disorder), and 22 CHR subjects were remitters. Baseline MMN amplitudes were compared across clinical outcome groups and tested for utility prognostic biomarkers using binary logistic regression.

MMN amplitudes were greatest in HCs, intermediate in CHR subjects, and smallest in FEP patients. In the clinical outcome groups, MMN amplitudes were reduced from the baseline in both FEP and CHR patients with poor prognostic trajectories. Reduced baseline MMN amplitudes were a significant predictor of later treatment resistance in FEP patients [Exp(β) = 2.100, 95% confidence interval (CI) 1.104–3.993, p = 0.024] and nonremission in CHR individuals [Exp(β) = 1.898, 95% CI 1.065–3.374, p = 0.030].

These findings suggest that MMN could be used as a common prognostic biomarker across early psychosis periods, which will aid clinical decisions for early intervention.

To estimate the risks of depressive symptoms for developing frailty, accounting for baseline robust or pre-frailty status.

An incident cohort study design.

Community dwellers aged 55 years and above from urban and rural areas in seven regions in Taiwan.

A total of 2,717 participants from the Healthy Aging Longitudinal Study in Taiwan (HALST) were included. Subjects with frailty at baseline were excluded. The average follow-up period was 5.9 years.

Depressive symptoms were measured by the 20-item Center for Epidemiological Studies Depression (CES-D) Scale. Frailty was assessed using the Fried frailty measurement. Participants were stratified by baseline robust or pre-frailty status to reduce the confounding effects of the shared criteria between depressive symptoms and frailty. Overall and stratified survival analyses were conducted to assess risks of developing frailty as a result of baseline depressive symptoms.

One hundred individuals (3.7%) had depressive symptoms at baseline. Twenty-seven individuals (27.0%) with depressive symptoms developed frailty, whereas only 305 out of the 2,617 participants (11.7%) without depressive symptoms developed frailty during the follow-up period. After adjusting for covariates, depressive symptoms were associated with a 2.6-fold (95% CI 1.6, 4.2) increased hazard of incident frailty. The patterns of increased hazard were also observed when further stratified by baseline robust or pre-frailty status.

Depressive symptoms increased the risk of developing frailty among the older Asian population. The impact of late-life depressive symptoms on physical health was notable. These findings also replicated results from Western populations. Future policies on geriatric public health need to focus more on treatment and intervention against geriatric depressive symptoms to prevent incident frailty among older population.

Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years.

Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed k-means clustering and survival analysis to stratify the risk of psychosis.

The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's C-index of 0.78 and identified three subclusters with significantly different risk levels.

Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.

Suicide rate tends to peak in old age, and major depression is the most salient risk factor for late-life suicide. However, few studies have focused on the neuroscientific facet of suicide in the context of late-life depression (LLD).

We recruited 114 participants of LLD (28 with history of suicide attempt and 86 without) and 47 elderly controls. They received MRI scanning and behavioral assessment. White matter hyperintensity (WMH) was quantified by an automated segmentation algorithm and graph theoretical analysis was applied to resting-state fMRI. We used ANCOVA to compare group difference in WMH loading and multivariate generalized linear model to compare global and local topological parameters in fMRI signals, controlling for demographics. Partial correlation was conducted between imaging parameters and behavioral data in group of suicide attempters.

We found significant higher WMH in suicide attempters than those of LLD without suicide attempts and elderly controls (F =7.091; p = 0.001). Suicide attempters also had increased betweenness centrality (BC) in right superior occipital gyrus (SOG) (Bonferroni corrected), right precuneus (False positive corrected) and right superior temporal gyrus (uncorrected) and decreased BC in left hippocampus (uncorrected). In suicide attempters, higher BC in right SOG correlated with higher WMH, higher depression severity, higher illness awareness and insight, and lower cognitive function (digit backward), while higher BC in right precuneus correlated with higher decrease awareness and insight and higher cognitive function (digit backward).

Resonating with the vascular hypothesis in LLD, higher WMH was found in those having history of suicide attempts. However, the re-organized brain topology changes are related with divergent cognitive function and convergent heightened disease insight.

Major depressive disorder (MDD) is a leading cause of morbidity and mortality. Shortfalls in treatment quantity and quality are well-established, but the specific gaps in pharmacotherapy and psychotherapy are poorly understood. This paper analyzes the gap in treatment coverage for MDD and identifies critical bottlenecks.

Seventeen surveys were conducted across 15 countries by the World Health Organization-World Mental Health Surveys Initiative. Of 35 012 respondents, 3341 met DSM-IV criteria for 12-month MDD. The following components of effective treatment coverage were analyzed: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) adequate severity-specific combination of both.

MDD prevalence was 4.8% (s.e., 0.2). A total of 41.8% (s.e., 1.1) received any mental health services, 23.2% (s.e., 1.5) of which was deemed effective. This 90% gap in effective treatment is due to lack of utilization (58%) and inadequate quality or adherence (32%). Critical bottlenecks are underutilization of psychotherapy (26 percentage-points reduction in coverage), underutilization of psychopharmacology (13-point reduction), inadequate physician monitoring (13-point reduction), and inadequate drug-type (10-point reduction). High-income countries double low-income countries in any mental health service utilization, adequate pharmacotherapy, adequate psychotherapy, and adequate combination of both. Severe cases are more likely than mild-moderate cases to receive either adequate pharmacotherapy or psychotherapy, but less likely to receive an adequate combination.

Decision-makers need to increase the utilization and quality of pharmacotherapy and psychotherapy. Innovations such as telehealth for training and supervision plus non-specialist or community resources to deliver pharmacotherapy and psychotherapy could address these bottlenecks.