Mental Health Indicators Research Articles

Exposure to firearm injury and suicide in a rural Pennsylvania county: implications for mental and behavioral health.

To evaluate the association between self-reported gun violence exposures and mental health and behavioral health indicators in a rural population. Using cross-sectional survey responses from 630 residents of a rural county in Pennsylvania, logistic regression models estimate the likelihood of residents indicating moderate or severe levels of health outcomes as a function of gun violence exposure. We control for a series of variables related to gun ownership, behavior, history with firearms and demographic characteristics. Personal firearm victimization was associated with self-reported depressive symptoms and interrupted sleep. Secondary exposure to firearm violence, particularly exposure to friends attempting or completing a suicide, was associated with higher odds of reporting severe levels (14days or more in the past month) of depressive symptoms, anxiety, and poor sleep. For firearm suicide involving a friend or family member, the odds of reporting severe levels of all three outcomes are 3 times greater (OR 2.984, 95% CI 1.457-6.108). For each additional firearm exposure, the odds of experiencing severe levels of mental health and sleep difficulties are 1.4 times greater (OR 1.384, 95% CI 1.115-1.720). Cumulative exposures also increase the odds of reporting binge drinking and drug use. Firearm violence exposure was associated with adverse health indicators in this rural population. Approaches to counter the effects of cumulative firearm exposure and firearm suicide exposure, including reinvigorating community spaces and strengthening social supports, may help to reduce mental health burden in rural communities.

Automated digital counselling promotes therapeutic change in mental health in patients with chronic heart failure or chronic kidney disease: ODYSSEE-vCHAT study

Abstract Background The efficacy of digital programs to improve the management of chronic heart failure (CHF) and chronic kidney disease (CKD) is not established. Building on related studies in digital health, behavioural counselling, and social support, we evaluated whether an automated digital counselling program with social network support (ODYSSEE-vCHAT) could improve mental health and health-related quality of life in patients with CHF or CKD. Purpose The primary objective was to examine whether engagement with ODYSSEE-vCHAT was associated with a minimal clinically important difference for improvement in the Mental Component Summary (MCS) of the SF-36 at end-of-study. Secondary outcomes included: ENRICHD Social Support Index (ESSI), Patient Health Questionnaire for Depression (PHQ-9) Godin-Shephard Leisure Time Physical Activity Scale (GSLTPAQ), and an index of the frequency to which patients engaged in goal-directed activities for living well (EUROIA). Methods ODYSSEE-vCHAT was a multi-centre, single group, open label study with assessments at baseline and end-of-study (approximately 11 months). Inclusion criteria were: ≥18 years of age, diagnosis of CHF (reduced ejection fraction (EF) ≤ 40%, mid-range EF, 41-49%, or preserved EF ≥ 50%); or CKD diagnosis (>10% risk for dialysis using the 4-variable, 2-year Kidney Failure Risk Equation, or on dialysis). Exclusion was based on inability to participate due to co-morbidities. The digital counselling protocol taught self-care skills to improve mental health, quality of life, and adherence to medications, exercise, diet, and smoke-free living (Figure 1). Patient engagement with ODYSSEE-vCHAT was defined as Not Engaged (0 logon minutes) vs. Engaged (> 0 logon minutes). The primary outcome was a minimal clinically important difference for MCS change: ΔMCS ≥ 3.8 or MCS ≥ 65 at baseline and study endpoint. It was assessed using multivariable binary logistic regression, controlling for exposure to COVID-19 and health literacy. Secondary outcomes were assessed using multivariable linear regression analyses with the same covariates. Results 215 patients were enrolled. There were 7 deaths and 34 withdrew. In our sample of 174 patients, mean age = 54.4 years (95% Confidence Interval, CI, 25, 81), gender identity as women, n = 68 (39%), ethno-racial group other than White, n = 83, (48%), primary diagnosis, CHF, n = 68 (39%), and CKD, n = 106 (61%). Duration of enrolment to end-of-study: median = 352 days, (95% CI, 159, 496). Engagement with ODYSSEE was associated with therapeutic change on the MCS (for both CHF and CKD patients, and CHF patients alone), GSLTPAQ, and EUROIA, but not the PHQ9 or ESSI (Figure 2). Conclusions Automated digital counselling with social network support promotes improvement in indices of mental health for patients with CHF and CKD. These findings support a follow-up randomized controlled trial.Figure 1.ODYSSEE-vCHAT Study ProtocolFiFigure 2.ODYSSEE-vCHAT Study Outcomes

Multiple behavioural risk factors and mental health complaints among adults in Estonia

Abstract Background Behavioural risk factors are inter-related and often coincide, resulting in potentially worse mental health outcomes. This study explores the association between multiple behavioural risk factors and mental health among adults in Estonia. Methods We used nationally representative survey data from 2020 (n = 6404) to study the co-occurrence of lifestyle risk factors (smoking, alcohol consumption, physical inactivity, unhealthy diet, drug use, and high screen time) in relation to mental health indicators. Latent class analysis (LCA) was used to identify lifestyle risk profiles, while regression analysis was used to examine associations. Results Mental health outcomes were more frequent among females and younger respondents, but 54.4% of respondents reported having at least one mental health problem. Using LCA, three lifestyle classes were identified: multiple risk factors (17.9% of respondents), healthy lifestyle (76.1%), and drug use lifestyle (5.9%). Compared to individuals in healthy lifestyle class, respondents in multiple risk factors had higher odds for experiencing depressiveness (OR 1.46; CI 1.24-1.72), stress (OR 1.26; CI 1.06-1.49), and suicidal thoughts (OR 1.50; CI 1.26-1.80), as well as self-reported diagnoses of depression and insomnia, and using medications, such as antidepressants, hypnotics and sedatives. Respondents in drug use lifestyle had 1.5-2.5 times higher odds for all mental health items compared to healthy lifestyle class with largest difference found for suicidal thoughts (OR 2.46; CI 1.92-3.16) and medication use (OR 2.58; CI 1.91-3.47). Conclusions The current data highlights the importance of preventive measures targeting multiple behavioural risk factors, given that these factors often coincide. Moreover, the study showed a high proportion of individuals with at least one mental health problem, highlighting the necessity to continue efforts in preventive and interventive methods. Key messages • The study highlights the significant association between multiple behavioural risk factors and mental health outcomes. • The study also emphasizes the importance of focused interventions targeting multiple behavioural risk factors to address the increased risk of mental health problems.

Optimism mitigated impacts of pre-operative depression and anxiety on post-operative distress in cardiac patients

ABSTRACT Both anxiety and depression are comorbid mortality risks in middle-aged and older patients with heart diseases. Open-heart surgery (OHS), a life-altering procedure, can induce psychological distress that impedes postoperative recovery. Extensive research has shown the health benefit of optimism, an indicator of hope—a Character Strength in positive psychology. It predicts low mortality in cardiovascular disease—the number one killer of all Americans. Few studies, however, have explored whether that optimism mitigates the negative impact of preoperative depression and anxiety on postoperative general psychological distress. This interdisciplinary clinical study evaluated a hypothetical model of these relationships prior to and 1 month following OHS in 311 U.S. patients using a three-wave survey. Structural equation modeling (SEM) was performed to predict post-OHS general psychological distress. Optimism was indicated by two subscales in the Life Orientation Test (LOT). Based on the definition, general psychological distress was indicated by low symptom levels of somatization, depression, and anxiety as measured by the SCL-90 subscales. The final solution demonstrated a good fit. Optimism alleviates the negative effects of preoperative depression and anxiety, as indicators of poor mental health, on postoperative distress. Both older age and female gender were positively and directly associated with higher levels of post-OHS symptoms. The finding supports the beneficial role of optimism in mitigating the damage of poor mental health in the postoperative outcome of cardiac patients. The desirable function of character strength hope suggests that health providers should be attentive to and enhance inner strength for reducing the distress of cardiac patients in the postoperative recovery month.

Explainable Multi-Layer Dynamic Ensemble Framework Optimized for Depression Detection and Severity Assessment.

Depression is a pervasive mental health condition, particularly affecting older adults, where early detection and intervention are essential to mitigate its impact. This study presents an explainable multi-layer dynamic ensemble framework designed to detect depression and assess its severity, aiming to improve diagnostic precision and provide insights into contributing health factors. Using data from the National Social Life, Health, and Aging Project (NSHAP), this framework combines classical machine learning models, static ensemble methods, and dynamic ensemble selection (DES) approaches across two stages: detection and severity prediction. The depression detection stage classifies individuals as normal or depressed, while the severity prediction stage further classifies depressed cases as mild or moderate-severe. Finally, a confirmation depression scale prediction model estimates depression severity scores to support the two stages. Explainable AI (XAI) techniques are applied to improve model interpretability, making the framework more suitable for clinical applications. The framework's FIRE-KNOP DES algorithm demonstrated high efficacy, achieving 88.33% accuracy in depression detection and 83.68% in severity prediction. XAI analysis identified mental and non-mental health indicators as significant factors in the framework's performance, emphasizing the value of these features for accurate depression assessment. This study emphasizes the potential of dynamic ensemble learning in mental health assessments, particularly in detecting and evaluating depression severity. The findings provide a strong foundation for future use of dynamic ensemble frameworks in mental health assessments, demonstrating their potential for practical clinical applications.

The mental health toll of the Russian-Ukraine war across 11 countries: Cross-sectional data on war-related stressors, PTSD and CPTSD symptoms

Exposure to war is a severe traumatic experience with disastrous mental health effects. This study examined the mental health among 5,560 residents in 11 countries worldwide at different geographic distances from the epicenter of the Russian-Ukrainian War (RUW). An online questionnaire assessed war-related variables (e.g., personal experiences with RUW, perceived concern and threat), previous life stress experiences, and mental health (i.e., resilience, anxiety, depression, perceived stress, ICD-11 PTSD, and CPTSD). Results showed regional differences. Ukrainians had the worst mental health indices, followed by participants in the bordering countries, and then by those in the distal ones. War-related variables were associated with worse mental health. The common predictors for PTSD and CPTSD were previous mental disorder, anxiety, and perceived stress, whereas unique predictors were also found (PTSD: female gender and impact of news on mental health; CPTSD: being single, overall impact of war on mental health, sum of lifetime traumatic experiences, resilience (inversely), and depression). Given the continuing uncertainty about the threat of war for many of the nations in this study, findings suggest the need for practitioners to support concerned populations.

Association between Jewish religious observance and mental health among Israeli adults: Findings from the Global Flourishing Study.

This study investigates the association between Jewish religious observance and several indicators of mental health and psychological well-being among Jewish Israeli adults. Data are from adult (18+) Jewish respondents in the Israeli sample (N = 2958) of the first wave of the Global Flourishing Study (GFS), a 22-nation population survey which will eventually consist of five annual waves of panel data. The GFS Israeli data were collected via a randomized, stratified, probability-based sampling design, and contained dozens of indicators of sociodemographic, socioeconomic, political, religious, health-related, and other constructs. Measures of Jewish religious observance, including religious service attendance, prayer, scripture reading, belief in God, and importance of Judaism, are statistically significant predictors of several single-item indicators of mental health (overall mental health, depression, anxiety) and psychological well-being (suffering, happiness, life satisfaction). Greater religious observance is associated with a higher self-rating of overall mental health, less depression and anxiety, less suffering, and greater happiness and life satisfaction. Nearly all results withstood adjusting for effects of several sociodemographic covariates. These results offer confirmation of prior studies using smaller samples or non-population-based designs and with fewer mental health and religious indicators. They suggest that evidence for a salutary association between religious observance and mental health or psychological well-being among Israeli Jewish adults is consistent with findings in this literature for adherents to other faith traditions throughout the world.

Urbanization, loneliness and mental health model - A cross-sectional network analysis with a representative sample

With increasing urbanization, more people are exposed to mental health risk factors stemming from the urban social or physical environment. However, research on the relationship between urbanization and mental health is lacking. This cross-sectional study aimed to explore the relationships of the physical environment (spatial cohesion and urban environment) and social factors (neighborhood cohesion) with mental health (stress, anxiety and depression symptoms) and physical health and the mediating role of loneliness based on the proposed theoretical model. The study was conducted in Metropolis GZM (Silesia, Poland) in a representative sample of 3296 residents (48% women). The measurements used were the PSS-10, GAD-7, PHQ-9, R-UCLA3 and neighborhood cohesion scale. ANOVA results showed that city residents had better mental health indices than residents of villages and small towns. The network approach revealed that urbanization was one of the most influential nodes and played the role of a bridge between all other nodes. The model was confirmed and showed that the relationships between the physical environment and mental health were consecutively mediated by neighborhood cohesion and loneliness. Spatial cohesion related to factors of the physical environment and physical health, while physical health was directly connected to sociodemographic factors and weakly to stress. Anxiety was the strongest risk factor. Mental health can be improved by social and architectural factors, such as strengthening neighborhood cohesion and improving neglected buildings.

01 Vaping, mental and physical health in adolescents in a COMPASS-Quebec cohort

Abstract Background Better knowledge of the association between vaping and youth’s health would help raise awareness among adolescents, parents, professionals and decision-makers on the likely threat it represents. Objectives Our objective is to examine the association between vaping, its frequency, and adolescent health. Design/Methods This observational study is based on data from the 2022-23 survey round of COMPASS-Quebec school cohorts through self-reported measures. It includes 45,203 respondents aged from 12 to 18 years old from 99 schools of Eastern Quebec. A four-modality variable depicts the vaping frequency in the last twelve months (abstinence, < once/month, ≥ once/month, ≥ once/week, daily). The measurement of health states is based on 5 dichotomous indicators: (i) good vs poor physical health (excellent, very good, good, vs fair, poor), (ii) maximum oxygen consumption considered at risk for health vs not (estimated VO2max, calculated using Léger’s equation); (iii) good vs poor mental health (excellent, very good, good, vs fair, poor); (iv) the presence vs absence of moderate to severe anxiety (GAD7, score ≥10/30) and; (v) the presence vs absence of significant depressive symptoms (CESD-R, score ≥10/21). Sex, age and family material deprivation level are taken into account as confounding factors. Results The proportion of adolescents who have vaped in the last 12 months is 26.8%. After adjustment, daily vaping is associated with poor physical health, a VO2max considered at risk for health, poor mental health, moderate to severe anxiety and significant depressive symptoms, compared to abstinence (adjusted relative risk [aRR] 2,46 [95%CI: 2,05-2,88]; 1,66 [95%CI: 1,44-1,89]; 1,88 [95%CI: 1,66-2,11]; 1,75 [95%CI: 1,53-1,97]; 1,55 [95%CI: 1,40-1,70]). A gradient in the associations between vaping frequency and lower mental health indicators has been observed. Adolescents who have vaped <once/month, ≥once/month, ≥once/week and daily have more risk of presenting moderate to severe anxiety (aRR 1,21 [95%CI: 1,09-1,33]; 1,44 [95%CI: 1,27-1,61]; 1,54 [95%CI: 1,37-1,72]; 1,75 [95%CI: 1,53-1,97]). Regarding significant depressive symptoms, aRR are 1,23 [95%CI: 1,14-1,32], 1,39 [95%CI: 1,27-1,51], 1,49 [95%CI: 1,36-1,62], 1,55 [95%CI: 1,40-1,70]. Regarding poor mental health, aRR are 1,29 [95%CI: 1,17-1,42], 1,61 [95%CI : 1,43-1,79], 1,63 [95%CI : 1,45-1,81], 1,88 [95%CI: 1,66-2,11]. Conclusion This study suggests a consistent association between health, both physical and mental, and use of electronic cigarettes in adolescents. Longitudinal studies would help clarify possible causal influence of vaping on youth's health.

Mental health and support for rigorous tobacco control strategies in South Australia

IntroductionTobacco endgame strategy includes policies to end the tobacco epidemic. As tobacco smoking prevalence is higher among people with mental health conditions (MHC), understanding the impact of rigorous tobacco control...

Impact of healthy lifestyles on mental health indicators in adolescents after the COVID-19 pandemic

ObjectiveHealthy lifestyles are extremely important since they are one of the main protective factors in adolescence, especially after the COVID-19 pandemic. However, no explanatory models have been found that study the impact of healthy lifestyles on levels of anxiety, depression, and psychological well-being. The study's objective was to test a model that allows determining the impact of healthy lifestyles on mental health indicators in adolescents in a post-COVID-19 pandemic period. MethodNon-probabilistic sampling was used to collect the participants. The sample included 1515 Peruvian adolescents of both sexes (53.4% men and 46.6% women) from 12 to 18 years of age (M = 14.5; SD = 1.5). The WMS Healthy Lifestyle Scale, the Generalized Anxiety Disorder Scale, the Patient Health Questionnaire, and the General Well-being Index were used to measure the variables. ResultsThe study results show that the proposed explanatory model presents adequate fit indices (χ2 = 4280.30; df = 1113; P < 0.001; RMSEA = 0.043 [IC90% 0.042 – 0.045]; CFI = 0.94; TLI = 0.94; SRMR = 0.064). Specifically, it was found that the practice of healthy lifestyles negatively predicts the level of anxiety (-0.37; P < 0.001) and depression (-0.47; P < 0.001). On the other hand, it positively predicts the level of psychological well-being (0.74; P < 0.001) experienced by adolescents. The study also found that an important group of adolescents present anxiety symptoms (38.6%) and depression (38.3%). ConclusionHealthy lifestyles are important for the mental health of adolescents since they manage to predict the level of anxiety, depression, and, above all, the level of psychological well-being of adolescents after the COVID-19 pandemic.

Adolescents’ mental health is associated with food parenting practices among British Columbian families

BackgroundAdolescence is a developmental period marked by significant changes related to the body and food parenting practices. However, few studies have explored child-level psychological correlates of these practices during adolescence. Our study examined whether adolescents’ weight status, weight concerns, self-esteem, and anxiety were associated with food parenting practices, and whether these associations significantly differed by adolescents’ gender among 297 families in British Columbia, Canada. MethodsParents (47 years, 76% mothers) completed a food parenting practice item bank. Adolescents (14 years, 52% girls) self-reported their height and weight, weight concerns, self-esteem, and anxiety. Covariate-adjusted regression models evaluated the association of adolescents’ weight and mental health with nine practices (main effects). Interactions were used to evaluate the moderating role of gender, and further decomposed in all models to examine simple effects within each gender group. ResultsMain-effect models showed positive associations between: (1) weight concerns and child involvement, (2) weight concerns and accommodating practices, (3) self-esteem and healthy eating opportunities, and (4) self-esteem with meal routines, as well as negative associations between: (5) self-esteem and accommodating practices, (6) self-esteem and coercive control, and (7) anxiety and rules and limits. In these 7 models interactions with gender were not significant; however, in all cases (except in model 5) the decomposed effects showed only significant associations among girls. A significant gender interaction emerged in (8) the association between anxiety and coercive control, but the decomposed effects were not significant for either gender. Adolescents’ weight status was not associated with food parenting practices in any model. ConclusionsFood parenting practices are associated with mental health indicators among British Columbian families; however, future studies should examine multidirectional relationships between these practices, adolescents’ mental health, and eating habits.

Descriptive study of mental health care users 12 months pre- and post-COVID-19 lockdown.

Coronavirus disease 2019 (COVID-19) has impacted on a range of physical, mental and societal health indices. Increased levels of psychological stress are often reported following pandemics. To describe and compare the presentations of mental health care users pre- and post-initiation of the lockdown, with an emphasis on demographic profiles and final diagnoses. The study was conducted as a retrospective record review over the predetermined period at a large public hospital in Johannesburg and included all mental health care users requiring psychiatry consultation during the study period. Clinical records were traced via the emergency department registration desk, and information pertaining to demographics, presenting complaints, date of presentation and diagnosis was extracted. A significant increase was seen in patients with psychotic disorders from pre-COVID-19 to post-COVID-19. There was a reduction in presentations of mood disorders and substance-related disorders. Patients presenting in the post-COVID-19 time period were significantly younger than in the pre-COVID-19 time period. Pandemics result in notable negative mental health sequelae. Policies aimed at mitigating the spread of infective agents should be implemented with consideration of the burden of psychological distress following the pandemic. This study provides insights into clinical and demographic variables in a mental health care population serviced at a government hospital pre- and post-COVID-19 lockdown regulations.

Climate emotions, thoughts, and plans among US adolescents and young adults: a cross-sectional descriptive survey and analysis by political party identification and self-reported exposure to severe weather events

Climate change has adverse effects on youth mental health and wellbeing, but limited large-scale data exist globally or in the USA. Understanding the patterns and consequences of climate-related distress among US youth can inform necessary responses at the individual, community, and policy level. A cross-sectional descriptive online survey was done of US youth aged 16-25 years from all 50 states and Washington, DC, between July 20 and Nov 7, 2023, via the Cint digital survey marketplace. The survey assessed: climate-related emotions and thoughts, including indicators of mental health; relational aspects of climate-related emotions; beliefs about who or what has responsibility for causing and responding to climate change; desired and planned actions in response to climate change; and emotions and thoughts about the US Government response to climate change. Respondents were asked whether they had been affected by various severe weather events linked to climate change and for their political party identification. Sample percentages were weighted according to 2022 US census age, sex, and race estimates. To test the effects of political party identification and self-reported exposure to severe weather events on climate-related thoughts and beliefs we used linear and logistic regression models, which included terms for political party identification, the number of self-reported severe weather event types in respondents' area of residence in the past year, and demographic control variables. We evaluated survey responses from 15 793 individuals (weighted proportions: 80·5% aged 18-25 years and 19·5% aged 16-17 years; 48·8% female and 51·2% male). Overall, 85·0% of respondents endorsed being at least moderately worried, and 57·9% very or extremely worried, about climate change and its impacts on people and the planet. 42·8% indicated an impact of climate change on self-reported mental health, and 38·3% indicated that their feelings about climate change negatively affect their daily life. Respondents reported negative thoughts about the future due to climate change and actions planned in response, including being likely to vote for political candidates who support aggressive climate policy (72·8%). In regression models, self-reported exposure to more types of severe weather events was significantly associated with stronger endorsement of climate-related distress and desire and plans for action. Political party identification as Democrat or as Independent or Other (vs Republican) was also significantly associated with stronger endorsement of distress and desire and plans for action, although a majority of self-identified Republicans reported at least moderate distress. For all survey outcomes assessed in the models, the effect of experiencing more types of severe weather events did not significantly differ by political party identification. Climate change is causing widespread distress among US youth and affecting their beliefs and plans for the future. These effects may intensify, across the political spectrum, as exposure to climate-related severe weather events increases. Avaaz Foundation.

Glycemic indicators and mental health symptoms: results from the greater Beirut area cardiovascular cohort.

Depression and anxiety present high and complex comorbidity with diabetes. One proposed explanation is that glycemic dysregulations and diabetes-related processes can influence mental health risk. We examined the associations of concurrent and prior glycemic indicators (Hemoglobin A1c (HbA1c) and fasting blood glucose (FBG) levels) with depression and anxiety symptoms in a community-based sample of middle-aged Lebanese adults. Data come from the Greater Beirut Area Cardiovascular Cohort (GBACC), with baseline and 5-year assessments of sociodemographic, lifestyle, and biological factors (n=198). Depression (Patient Health Questionnaire-9) and anxiety (General Anxiety Disorder-7) symptoms were assessed at follow-up. We investigated associations between glycemic indicators and continuous mental health scores using first linear and then piecewise regression models. Adjusted piecewise regression models showed different associations with mental outcomes across glycemic indicators in the diabetic/clinical compared to the non-diabetic range: Among participants with <126 mg/dl baseline FBG, higher FBG levels in this range were significantly associated with lower depressive (beta=-0.12, 95%CI= [-0.207, -0.032]) and anxiety symptoms (beta=-0.099, 95%CI= [-0.186, -0.012]). In contrast, among participants with baseline FBG levels ≥126 mg/dl, higher FBG levels were significantly associated with higher anxiety symptoms (beta=0.055; 95%CI= 0.008, 0.102). Higher baseline FBG levels in the ≥126 mg/dl range showed a not statistically significant trend for higher depressive symptoms. Although not significant, baseline HbA1c levels showed similar patterns with negative associations with mental health symptoms in the <6.5% range. Results show that FBG levels were associated with poorer mental health symptoms only in the clinical/diabetic range, and not in the normal range. Associations were observed with baseline glycemic indicators, highlighting potentially early and prolonged associations with mental health. Findings highlight the importance of clinical changes in glycemic indicators for mental health and motivate further research into the transition toward adverse associations between diabetes and mental health.

Weight-control compensatory behaviors patterns and correlates: a scoping review.

Weight-control compensatory behaviors appear to be a commonly utilized strategy for health management. Individuals engaging in such behaviors believe that the negative consequences from unhealthy behaviors will be neutralized by the positive consequences of healthy behaviors. Existing research has not reached a consensus on whether such behaviors are beneficial to health. This review aims to (1) summarize the patterns of weight-control compensatory health behaviors in different populations, (2) highlight correlates, predictors, and consequences of compensatory health behaviors, and (3) identify gaps for future research. This review identified existing literature using online databases, CINAHL and PubMed. Primary research articles published after 2000 with non-clinical participants of 12 years or older who engaged in compensatory behaviors for weight control purposes were selected. Descriptive statistics were extracted from 35 studies. Different patterns for weight-control compensatory behaviors emerged between the female and male sexes. Meanwhile, no clear association of such behaviors was found across weight status. Studies reviewed also highlighted three main areas of compensatory behaviors for weight management, namely dietary behaviors, physical activity, and alcohol consumption. Weight-control compensatory behaviors had significant negative correlations with mental health indicators, such as psychosocial functioning, emotional differentiation ability, and body esteem. Weight-control compensatory behaviors may be a widely used weight management strategy and can be presented in diverse ways. Although believed to be promoting health, such behaviors appear to be associated with poor psychological well-being. This emerging topic warrants more in-depth investigation to establish the direction of causation. Future research may investigate the relationship between weight-control compensatory behaviors and various aspects of health over longer time periods, examine the engagement of multiple weight-control compensatory behaviors, and focus on high-risk populations.

Linking housing, socio-demographic, environmental and mental health data at scale

Mental disorders are a growing problem worldwide, putting pressure on healthcare systems and wider society. Anxiety and depression are estimated to cost the global economy US$1 trillion per year, yet only 2% of global median government healthcare expenditure goes towards mental health. There is growing evidence linking housing, socio-economic status and local environmental conditions with mental health inequalities. The aim of this paper is to link several open-access datasets at the local area level (N = 32,844) for England to clinical mental health metrics and describe initial statistical findings. Two mental health metrics were used: Small Area Mental Health Index (SAMHI) and diagnosed depression prevalence. To demonstrate the utility of the longitudinal mental health data, changes in depression prevalence were investigated over two study periods (2011–19, i.e. austerity; and 2019–22, i.e. COVID-19). These data were linked to housing data (energy efficiency, floor area, year built, type and tenure) from Energy Performance Certificates (EPCs); socio-demographic data (age, sex, income and education deprivation, household size) from administrative records; and local environment data (winter temperature, air pollution and access to green space). The linked dataset provides a useful resource with which to investigate the social and environmental determinants of mental health. Practice relevance Initial observations of the data revealed a non-linear relationship between home energy efficiency (EPC band) and the mental health metrics, with depression prevalence higher in local areas where the mode EPC bands were C and D, compared with B and E. Researchers can further investigate this relationship using the dataset through robust statistical analysis, adjusting for confounding variables. National and local governments may use the dataset to help allocate resources to prevent and treat mental health conditions. Practitioners can map and interrogate the data to describe their local areas and make preliminary conclusions about the relationships between the built environment and mental health. This preliminary analysis of the data demonstrated a gradient in SAMHI and depression prevalence with income and employment deprivation at the local area level.

Experiences of Racism in School and Associations with Mental Health, Suicide Risk, and Substance Use Among High School Students - Youth Risk Behavior Survey, United States, 2023.

Racism is a fundamental determinant of health inequities among racial and ethnic groups and is understudied among adolescents. In 2023, the national Youth Risk Behavior Survey questionnaire included an item assessing experiences of racism in the school setting among students in grades 9-12 in the United States. This report estimates the prevalence of students who reported ever having experienced racism in school and compares prevalence by racial and ethnic groups. For each racial and ethnic group, prevalence differences and prevalence ratios were estimated comparing the prevalence of indicators of poor mental health, suicide risk, and substance use among students who reported that they have ever versus never experienced racism in school. In 2023, approximately one in three high school students (31.5%) said that they had ever experienced racism in school. Reported experiences of racism were most prevalent among Asian (56.9%), multiracial (48.8%), and Black or African American (Black) (45.9%) students and least prevalent among White students (17.3%). Black and Hispanic or Latino (Hispanic) students who reported experiencing racism had a higher prevalence of all health risk behaviors and experiences investigated, including indicators of poor mental health, suicide risk, and substance use compared with students of their racial and ethnic group who reported never experiencing racism. Many of these associations were also found among multiracial and White students. Student reports of racism were associated with indicators of mental health and suicide risk among American Indian or Alaska Native (AI/AN) and Asian students. Among students of color, including AI/AN, Asian, Black, Hispanic, and multiracial students, the prevalence of seriously considering and attempting suicide was more than two times higher among students who ever compared with never experienced racism. These findings demonstrate that racism in the school setting is experienced by high school students attending public and private schools and continues to disproportionately affect students of color. Students who reported experiencing racism had a higher prevalence of indicators of poor mental health, suicide risk, and substance use. Schools can incorporate policies and practices to prevent unfair treatment on the basis of race and ethnicity and offer resources to help students cope with these experiences.

Mental Health and Suicide Risk Among High School Students and Protective Factors - Youth Risk Behavior Survey, United States, 2023.

Adolescent mental health and suicide risk remain substantial public health concerns. High pre-COVID rates of poor mental health and suicide-related behaviors have continued to rise, highlighting the need to identify factors that might foster positive mental health outcomes and reduce suicide-related behaviors at population levels. Using CDC's 2023 Youth Risk Behavior Survey, CDC analyzed the prevalence of mental health and suicide risk indicators and their associations with individual-, family-, and school- or community-level protective factors. Prevalence estimates were calculated for each of the mental health and suicide risk indicators by demographic characteristic. Prevalence ratios adjusted for sex, sexual identity, grade, and race and ethnicity were calculated to examine the association between protective factors and mental health and suicide risk indicators. Overall, 39.7% of students experienced persistent feelings of sadness and hopelessness, 28.5% experienced poor mental health, 20.4% seriously considered attempting suicide, and 9.5% had attempted suicide. Mental health and suicide risk indicators differed by sex, sexual identity, grade, and race and ethnicity. All protective factors were associated with lower prevalence of one or more risk indicators. Findings from this report can serve as a foundation for the advancement of research on protective factors and for the development and implementation of programs, practices, and policies that protect and promote mental health and emotional well-being among youth.

A mental health monitoring system based on intelligent algorithms and biosensors: Algorithm behaviour analysis and intervention strategies

Introduction: Mental health monitoring encompasses the systematic observation and assessment of an individual’s psychological well-being, aiming to detect, understand and manage mental health conditions. It involves various techniques and interventions tailored to support individuals in achieving and maintaining optimal mental wellness. Recent advancements include the use of biosensors and biomechanics to analyze physiological signals that correlate with mental states, providing a more comprehensive understanding of psychological well-being. Aim: The aim of this research is to construct an innovative mental health monitoring system established on intelligent algorithms and biomechanical data through behaviour analysis and intervention strategies. Methodology: We propose a novel Snow Ablation-driven Bi-directional Fine-tuned Recurrent Neural Network (SA-BFRNN) to identify the state of mental health. In addition to behavioural data, biosensors are employed to collect real-time physiological signals such as heart rate variability, skin conductance, and muscle tension, offering objective markers of mental stress and anxiety. These biomechanical inputs are integrated into the system for multi-modal analysis. We employ the SA algorithm, iteratively removing less influential connections and nodes based on their impact on model performance. This process enhances network efficiency and generalization capabilities, refining the BFRNN for mental health state identification. Utilizing a questionnaire with 25 questions, administered to a selected group of 756 individuals, we validate our proposed model. Biosensor data is synchronized with questionnaire responses to improve the precision of mental state identification. Clustering-derived labels are validated with mean opinion score. These labels inform classifiers for individual mental health prediction, aligning with our objective of robust mental health assessment through data-driven approaches. SA-BFRNN integrates both forward and backward temporal information, enhancing its ability to discern subtle patterns in behaviour. Through iterative fine-tuning, our network learns to adapt to diverse datasets, enabling precise identification of mental health states. Research findings: In the result evaluation phase, we thoroughly examine how well our proposed SA-BFRNN model recognizes various states of mental health across different parameters. Our findings also highlight the significance of incorporating biomechanics, where biosensor data showed a strong correlation with mental health indicators, thereby augmenting the accuracy of the system. Our findings emphasize the efficacy of the SA-BFRNN technique, as demonstrated by its overall performance in terms of recall (92.56%), accuracy (90.13%), F1-score (88.16%) and precision (89.23%). Our experimental results unequivocally demonstrate that our proposed model performed better than other traditional approaches in classifying contents from multimodal data, showing notable enhancements in accuracy and robustness, particularly under dynamic conditions.