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Individuals with diminished social connections are at higher risk of mental disorders, dementia, circulatory conditions and musculoskeletal conditions. However, evidence is limited by a disease-specific focus and no systematic examination of sex differences or the role of pre-existing mental disorders.
Methods
We conducted a cohort study using data on social disconnectedness (loneliness, social isolation, low social support and a composite measure) from the 2013 and 2017 Danish National Health Survey linked with register data on 11 broad categories of medical conditions through 2021. Poisson regression was applied to estimate incidence rate ratios (IRRs), incidence rate differences (IRDs), and explore sex differences and interaction with pre-existing mental disorders.
Results
Among 162,497 survey participants, 7.6%, 3.5% and 14.8% were classified as lonely, socially isolated and with low social support, respectively. Individuals who were lonely and with low social support had a higher incidence rate in all 11 categories of medical conditions (interquartile range [IQR] of IRRs, respectively 1.26–1.49 and 1.10–1.14), whereas this was the case in nine categories among individuals who were socially isolated (IQR of IRRs, 1.01–1.31). Applying the composite measure, the highest IRR was 2.63 for a mental disorder (95% confidence interval [CI], 2.38–2.91), corresponding to an IRD of 54 (95% CI, 47–61) cases per 10,000 person-years. We found sex and age differences in some relative and absolute estimates, but no substantial deviations from additive interaction with pre-existing mental disorders.
Conclusions
This study advances our knowledge of the risk of medical conditions faced by individuals who are socially disconnected. In addition to the existing evidence, we found higher incidence rates for a broad range of medical condition categories. Contrary to previous evidence, our findings suggest that loneliness is a stronger determinant for subsequent medical conditions than social isolation and low social support.
A preregistered analysis plan and statistical code are available at Open Science Framework (https://osf.io/pycrq).
Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways.
Methods
We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators.
Results
Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: −1.99%, 110.38%) of the ADHD–T2D association.
Conclusions
These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.
The COVID-19 pandemic negatively impacted healthcare worker well-being, leading to increased burnout and decreased workplace engagement. To combat expected stressors from the pandemic, our mid-sized academic health center implemented numerous institutional support, such as town halls, and virtual support groups. This study aimed to evaluate faculty utilization of institutional support, its association with perceived organizational support, received organizational support, and burnout.
Methods:
A retrospective, cross-sectional survey was distributed to 630 faculty employed at our institution in September 2020, assessing participant demographics, institutional support utilized, perceived organizational support, and burnout, through a combination of self-report measures and qualitative responses.
Results:
A total of 79 (12.5%) faculty provided complete responses and were included in the analysis. Qualitative analysis identified 4 primary themes: (1) flexibility and adjusted expectations, (2) direct communication, (3) sense of community, and (4) no support felt, with additional subthemes within each larger theme. Increased utilization of institutional support was associated with decreased odds of experiencing burnout.
Conclusion:
Flexibility, communication, and sense of community emerged as important strategies for maintaining faculty well-being and engagement during the early stages of the COVID-19 pandemic. This study suggests that utilization of workplace support is protective against burnout. Perceived support was not beneficial.
The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients.
Methods:
Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub’s EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis.
Results:
One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%–98%: Ethnicity, Race; < 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation.
Conclusion:
Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy.
Scientists are becoming increasingly aware that disparities in opportunities for conducting and publishing research among scientists living under different socio-economic contexts have created pervasive biases and long-lasting impacts on our views of the natural world. These disparities are challenging the establishment of a global research agenda for a variety of disciplines, including seed ecology. Seed ecology has progressed enormously recently, but multiple barriers have hindered progress in the Global South where biodiversity and environmental complexity are highest. Here, we identify ten major challenges that seed ecologists from developing countries face in relation to planning, designing, conducting and publishing their research. We also propose several measures to overcome these challenges: (1) closing biodiversity knowledge shortfalls, (2) enhancing and creating long-term seed ecological networks, (3) supporting better infrastructure, (4) making fieldwork easier and safer, (5) unlocking funding opportunities, (6) promoting inclusive scientific meetings, (7) alleviating language barriers, (8) improving education, (9) shifting the notion of novelty and relevance and (10) supporting native seed markets. The authors recommend that the proposed solutions can be implemented by seed ecologists and the broader scientific community including funding agencies, research directors, journal editors and the academic publishing industry. Solutions can help mitigate multiple challenges simultaneously, thus offering a relatively inexpensive, fast and productive pathway for the development of seed ecology into a truly global research discipline that benefits scientists irrespective of their geographic location and background.
Undergraduate students encounter developmental challenges during their transition into adulthood. Previous studies have claimed that adults with later chronotypes usually manifest negative psychological effects: poor sleep quality, greater stress, depression, and cognitive dysfunction. However, knowledge about the relationship between chronotype, stress, and sleep quality among young adults is lacking.
Objectives
The present study investigated the relationship between undergraduates’ chronotypes and perceived stress on sleep quality.
Methods
An online survey with a descriptive, cross-sectional design was conducted with a convenience sample of undergraduate students at a university in southern Taiwan. Those who were 20-25 years old and enrolled as a student were included; but who had been suspended or had deferred graduation were excluded. Students’ chronotype, stress, and sleep quality were assessed with three self-reported instruments: Munich Chronotype Questionnaire (MCTQ), Perceived Stress Scale (PSS), and Pittsburgh Sleep Quality Index (PSQI).
Results
Of 161 undergraduates who completed the questionnaires, 51 reported using an alarm clock to wake and were removed from data analysis. One hundred and ten students’ mean age is 20.3 and perceived moderate stress. Sixty-one percent were poor-quality sleepers. The mean chronotype score was 5.7, and 85.5% had an intermediate chronotype, while 13.6% had an evening chronotype. Chronotype and perceived stress were positively correlated with sleep quality (p < .001). Social jetlag was positively correlated with chronotype (p =.036). Undergraduate’s later chronotype and higher stress perception predicted 30% of poorer sleep quality (p < .001).
Conclusions
Undergraduate students’ chronotype and perceived stress were positively correlated and acted as predictors of the sleep quality. The findings could help to develop health-promotion interventions for these emerging adults to adjust their daily routines; and reduce their social jetlag, stress levels, and sleep disturbance.
Background: The late-onset cerebellar ataxias (LOCAs) have until recently resisted molecular diagnosis. Contributing to this diagnostic gap is that non-coding structural variations, such as repeat expansions, are not fully accessible to standard short-read sequencing analysis. Methods: We combined bioinformatics analysis of whole-genome sequencing and long-read sequencing to search for repeat expansions in patients with LOCA. We enrolled 66 French-Canadian, 228 German, 20 Australian and 31 Indian patients. Pathogenic mechanisms were studied in post-mortem cerebellum and induced pluripotent stem cell (iPSC)-derived motor neurons from 2 patients. Results: We identified 128 patients who carried an autosomal dominant GAA repeat expansion in the first intron of the FGF14 gene. The expansion was present in 61%, 18%, 15% and 10% of patients in the French-Canadian, German, Australian and Indian cohorts, respectively. The pathogenic threshold was determined to be (GAA)≥250, although incomplete penetrance was observed in the (GAA)250-300 range. Patients developed a slowly progressive cerebellar syndrome at an average age of 59 years. Patient-derived post-mortem cerebellum and induced motor neurons both showed reduction in FGF14 RNA and protein expression compared to controls. Conclusions: This intronic, dominantly inherited GAA repeat expansion in FGF14 represents one of the most common genetic causes of LOCA uncovered to date.
Recent findings on the Reynolds-number-dependent behaviour of near-wall turbulence in terms of the ‘foot-printing’ of outer large-scale structures call for a new modelling development. A two-scale framework was proposed to couple a local fine-mesh solution with a global coarse-mesh solution by He (Intl J. Numer. Meth. Fluids, vol. 86, 2018, pp. 655–677). The methodology was implemented and demonstrated by Chen & He (J. Fluid Mech, vol. 933, 2022, p. A47) for a canonical turbulent channel flow, where the mesh-count scaling with Reynolds number is potentially reduced from $O(R{e^2})$ for a conventional wall-resolved large-eddy simulation (WRLES) to $O(R{e^1})$. The present work extends the two-scale method to turbulent boundary layers. A two-dimensional roughness element is used to trip a turbulent boundary layer. It is observed that large-scale disturbances originating at the trip have a much shorter lifetime and weaker foot-printing signatures on near-wall flow compared to those long streaky coherent structures in well-developed wall-bounded turbulent flows. Modal analyses show that the impact of trip-induced large scales can be adequately captured by a locally embedded fine-mesh block. For the tripped turbulent boundary layer, a Chebyshev block-spectral mapping is adopted to propagate source terms from the local fine-mesh blocks to the global coarse-mesh domain, driving to a target solution for the upscaled equations. The computed mean statistics and energy spectra are in good agreement with corresponding experimental data, WRLES and direct numerical simulation (DNS) results. The overall mesh count–$Re$ scaling is estimated to reduce from $O(R{e^{1.8}})$ for the full wall-resolved LES to $O(R{e^{0.9}})$ for the present two-scale solution.
Consumption of unpasteurised milk in the United States has presented a public health challenge for decades because of the increased risk of pathogen transmission causing illness outbreaks. We analysed Foodborne Disease Outbreak Surveillance System data to characterise unpasteurised milk outbreaks. Using Poisson and negative binomial regression, we compared the number of outbreaks and outbreak-associated illnesses between jurisdictions grouped by legal status of unpasteurised milk sale based on a May 2019 survey of state laws. During 2013–2018, 75 outbreaks with 675 illnesses occurred that were linked to unpasteurised milk; of these, 325 illnesses (48%) were among people aged 0–19 years. Of 74 single-state outbreaks, 58 (78%) occurred in states where the sale of unpasteurised milk was expressly allowed. Compared with jurisdictions where retail sales were prohibited (n = 24), those where sales were expressly allowed (n = 27) were estimated to have 3.2 (95% CI 1.4–7.6) times greater number of outbreaks; of these, jurisdictions where sale was allowed in retail stores (n = 14) had 3.6 (95% CI 1.3–9.6) times greater number of outbreaks compared with those where sale was allowed on-farm only (n = 13). This study supports findings of previously published reports indicating that state laws resulting in increased availability of unpasteurised milk are associated with more outbreak-associated illnesses and outbreaks.
The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.
Exposure to maternal hyperglycemia in utero has been associated with adverse metabolic outcomes in offspring. However, few studies have investigated the relationship between maternal hyperglycemia and offspring cortisol levels. We assessed associations of gestational diabetes mellitus (GDM) with cortisol biomarkers in two longitudinal prebirth cohorts: Project Viva included 928 mother–child pairs and Gen3G included 313 mother–child pairs. In Project Viva, GDM was diagnosed in N = 48 (5.2%) women using a two-step procedure (50 g glucose challenge test, if abnormal followed by 100 g oral glucose tolerance test [OGTT]), and in N = 29 (9.3%) women participating in Gen3G using one-step 75 g OGTT. In Project Viva, we measured cord blood glucocorticoids and child hair cortisol levels during mid-childhood (mean (SD) age: 7.8 (0.8) years) and early adolescence (mean (SD) age: 13.2 (0.9) years). In Gen3G, we measured hair cortisol at 5.4 (0.3) years. We used multivariable linear regression to examine associations of GDM with offspring cortisol, adjusting for child age and sex, maternal prepregnancy body mass index, education, and socioeconomic status. We additionally adjusted for child race/ethnicity in the cord blood analyses. In both Project Viva and Gen3G, we observed null associations of GDM and maternal glucose markers in pregnancy with cortisol biomarkers in cord blood at birth (β = 16.6 nmol/L, 95% CI −60.7, 94.0 in Project Viva) and in hair samples during childhood (β = −0.56 pg/mg, 95% CI −1.16, 0.04 in Project Viva; β = 0.09 pg/mg, 95% CI −0.38, 0.57 in Gen3G). Our findings do not support the hypothesis that maternal hyperglycemia is related to hypothalamic–pituitary–adrenal axis activity.
Young people are most vulnerable to suicidal behaviours but least likely to seek help. A more elaborate study of the intrinsic and extrinsic correlates of suicidal ideation and behaviours particularly amid ongoing population-level stressors and the identification of less stigmatising markers in representative youth populations is essential.
Methods
Participants (n = 2540, aged 15–25) were consecutively recruited from an ongoing large-scale household-based epidemiological youth mental health study in Hong Kong between September 2019 and 2021. Lifetime and 12-month prevalence of suicidal ideation, plan, and attempt were assessed, alongside suicide-related rumination, hopelessness and neuroticism, personal and population-level stressors, family functioning, cognitive ability, lifetime non-suicidal self-harm, 12-month major depressive disorder (MDD), and alcohol use.
Results
The 12-month prevalence of suicidal ideation, ideation-only (no plan or attempt), plan, and attempt was 20.0, 15.4, 4.6, and 1.3%, respectively. Importantly, multivariable logistic regression findings revealed that suicide-related rumination was the only factor associated with all four suicidal outcomes (all p < 0.01). Among those with suicidal ideation (two-stage approach), intrinsic factors, including suicide-related rumination, poorer cognitive ability, and 12-month MDE, were specifically associated with suicide plan, while extrinsic factors, including coronavirus disease 2019 (COVID-19) stressors, poorer family functioning, and personal life stressors, as well as non-suicidal self-harm, were specifically associated with suicide attempt.
Conclusions
Suicide-related rumination, population-level COVID-19 stressors, and poorer family functioning may be important less-stigmatising markers for youth suicidal risks. The respective roles played by not only intrinsic but also extrinsic factors in suicide plan and attempt using a two-stage approach should be considered in future preventative intervention work.
The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.
Recent findings on wall-bounded turbulence have prompted a new impetus for modelling development to capture and resolve the Reynolds-number-dependent influence of outer flow on near-wall turbulence in terms of the ‘foot-printing’ of the large-scale coherent structures and the scale-interaction associated ‘modulation’. We develop a two-scale method to couple a locally embedded near-wall fine-mesh direct numerical simulation (DNS) block with a global coarser mesh domain. The influence of the large-scale structures on the local fine-mesh block is captured by a scale-dependent coarse–fine domain interface treatment. The coarse-mesh resolved disturbances are directly exchanged across the interface, while only the fine-mesh resolved fluctuations around the coarse-mesh resolved variables are subject to periodic conditions in the streamwise and spanwise directions. The global near-wall coarse-mesh region outside the local fine-mesh block is governed by the augmented flow governing equations with forcing source terms generated by upscaling the space–time-averaged fine-mesh solution. The validity and effectiveness of the method are examined for canonical incompressible channel flows at several Reynolds numbers. The mean statistics and energy spectra are in good agreement with the corresponding full DNS data. The results clearly illustrate the ‘foot-printing’ and ‘modulation’ in the local fine-mesh block. Noteworthy also is that neither spectral-gap nor scale-separation is assumed, and a smooth overlap between the global-domain and the local-domain energy spectra is observed. It is shown that the mesh-count scaling with Reynolds number is potentially reduced from $O(R{e^2})$ for the conventional fully wall-resolved large-eddy simulation (LES) to $O(Re)$ for the present locally embedded two-scale LES.
This study investigated the audiometric and sound localisation results in patients with conductive hearing loss after bilateral Bonebridge implantation.
Method
Eight patients with congenital microtia and atresia supplied with bilateral Bonebridge devices were enrolled in this study. Hearing tests and sound localisation were tested under unaided, unilateral and bilateral aided conditions.
Results
Mean functional gain was higher with a bilateral fitting than with a unilateral fitting, especially at 1.0–4.0 kHz (p < 0.05, both). The improvement in speech reception threshold in noise with a bilateral fitting was a 2.3 dB higher signal-to-noise ratio compared with unilateral fitting (p < 0.05). Bilateral fitting had better sound localisation than unilateral fitting (p <0.001). Four participants who attended follow up showed improved sound localisation ability after one year.
Conclusion
Patients demonstrated better hearing threshold, speech reception thresholds in noise and directional hearing with bilateral Bonebridge devices than with a unilateral Bonebridge device. Sound localisation ability with bilateral Bonebridge devices can be improved through long-term training.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, with its impact on our way of life, is affecting our experiences and mental health. Notably, individuals with mental disorders have been reported to have a higher risk of contracting SARS-CoV-2. Personality traits could represent an important determinant of preventative health behaviour and, therefore, the risk of contracting the virus.
Aims
We examined overlapping genetic underpinnings between major psychiatric disorders, personality traits and susceptibility to SARS-CoV-2 infection.
Method
Linkage disequilibrium score regression was used to explore the genetic correlations of coronavirus disease 2019 (COVID-19) susceptibility with psychiatric disorders and personality traits based on data from the largest available respective genome-wide association studies (GWAS). In two cohorts (the PsyCourse (n = 1346) and the HeiDE (n = 3266) study), polygenic risk scores were used to analyse if a genetic association between, psychiatric disorders, personality traits and COVID-19 susceptibility exists in individual-level data.
Results
We observed no significant genetic correlations of COVID-19 susceptibility with psychiatric disorders. For personality traits, there was a significant genetic correlation for COVID-19 susceptibility with extraversion (P = 1.47 × 10−5; genetic correlation 0.284). Yet, this was not reflected in individual-level data from the PsyCourse and HeiDE studies.
Conclusions
We identified no significant correlation between genetic risk factors for severe psychiatric disorders and genetic risk for COVID-19 susceptibility. Among the personality traits, extraversion showed evidence for a positive genetic association with COVID-19 susceptibility, in one but not in another setting. Overall, these findings highlight a complex contribution of genetic and non-genetic components in the interaction between COVID-19 susceptibility and personality traits or mental disorders.
Brief measurements of the subjective experience of stress with good predictive capability are important in a range of community mental health and research settings. The potential for large-scale implementation of such a measure for screening may facilitate early risk detection and intervention opportunities. Few such measures however have been developed and validated in epidemiological and longitudinal community samples. We designed a new single-item measure of the subjective level of stress (SLS-1) and tested its validity and ability to predict long-term mental health outcomes of up to 12 months through two separate studies.
Methods
We first examined the content and face validity of the SLS-1 with a panel consisting of mental health experts and laypersons. Two studies were conducted to examine its validity and predictive utility. In study 1, we tested the convergent and divergent validity as well as incremental validity of the SLS-1 in a large epidemiological sample of young people in Hong Kong (n = 1445). In study 2, in a consecutively recruited longitudinal community sample of young people (n = 258), we first performed the same procedures as in study 1 to ensure replicability of the findings. We then examined in this longitudinal sample the utility of the SLS-1 in predicting long-term depressive, anxiety and stress outcomes assessed at 3 months and 6 months (n = 182) and at 12 months (n = 84).
Results
The SLS-1 demonstrated good content and face validity. Findings from the two studies showed that SLS-1 was moderately to strongly correlated with a range of mental health outcomes, including depressive, anxiety, stress and distress symptoms. We also demonstrated its ability to explain the variance explained in symptoms beyond other known personal and psychological factors. Using the longitudinal sample in study 2, we further showed the significant predictive capability of the SLS-1 for long-term symptom outcomes for up to 12 months even when accounting for demographic characteristics.
Conclusions
The findings altogether support the validity and predictive utility of the SLS-1 as a brief measure of stress with strong indications of both concurrent and long-term mental health outcomes. Given the value of brief measures of mental health risks at a population level, the SLS-1 may have potential for use as an early screening tool to inform early preventative intervention work.