Adolescent mental health profiles through a latent dual-factor approach

Uncovering heterogeneity in mental health changes among first-year medical students

INTRODUCTION

The initial year of medical school is linked to a decline in mental health. To assess mental health comprehensively, the dual-factor model posits the consideration of both psychopathology (e.g., depression) and positive mental health (e.g., well-being). Previous mental health research among medical students has primarily examined these two factors independently. This study uses the dual-factor approach for a deeper understanding of mental health changes during the first year of medical school.

METHODS

Students from eight German medical schools (N = 450) were surveyed three times (T0 = entering medical school, T1 = end of the first semester, T2 = end of the second semester) regarding depression (PHQ-9), well-being (subscale of FAHW-12), and general life satisfaction (German Single-Item Scale L1). Latent profile analysis was used to identify distinct mental health groups based on their combinations of psychopathology and positive mental health. We then analysed trajectories descriptively by examining the longitudinal stability and dynamics of mental health group membership during the first year of medical school.

RESULTS

We identified five mental health groups: (1) complete mental health, (2) moderately mentally healthy, (3) symptomatic but content, (4) vulnerable, and (5) troubled. The examination of change trajectories unveiled diverse paths pointing towards both recovery and deterioration. In comparison to the other groups, students belonging to the complete mental health group exhibited greater stability and a higher potential to recover after initial deteriorations in the first semester.

CONCLUSIONS

Our study uncovers distinct mental health trajectories in the first year of medical school, emphasizing the crucial role of initial mental health status. Our findings stress the diverse nature of mental health changes in medical students, underscoring the need for tailored prevention strategies. The implications for research and practice are discussed.

Dual-factor mental health in adolescence: Comparing classification methods

Addressing adolescent mental health difficulties often begins by first correctly identifying students who are at risk when using universal mental health screeners in the school setting. A comprehensive conceptualization of mental health may enhance school psychologists' ability to effectively understand the mental health of students they serve. The dual-factor model of mental health posits a more holistic approach to mental health by capturing subjective-wellbeing scores alongside psychopathology. When employing the dual-factor model, practitioners have various ways to classify students as at risk for mental health difficulties, including locally normed cut scores and latent profile analysis (LPA); without an empirical comparison between the two approaches, practitioners may be uninformed in their decision making. The present study surveyed 404 adolescents on subjective wellbeing and psychopathology and examined how mental health classification varied when two common dual-factor approaches were employed (i.e., locally normed cut scores and LPA). Results indicated that 71.2% of the sample were classified in the same dual-factor mental health group across the two approaches, whereas 28.8% of adolescents' mental health classifications changed. The lack of agreement between the two approaches for a sizable proportion of the present sample presents an area for future research to ensure the correct identification of at-risk students and appropriately allocate services in schools.

Mental health and meaning in life in Chinese military personnel: a cross-lagged analysis

BACKGROUND

The burgeoning field of research on the dual-factor model of mental health (DFM) has highlighted its significance, yet the applicability of the DFM in military personnel and its longitudinal relationships with different dimensions of meaning in life remains unclear. This study aimed to clarify the applicability of the DFM for military personnel and to investigate longitudinal relationships between the dual factors of mental health (negative factor, positive factor) and the two dimensions of meaning in life (presence of meaning, search for meaning) in military personnel.

METHODS

In this study, data were collected in two waves (April and August 2023) from 227 Chinese military personnel. We constructed a dual-factor model with depression as the negative factor and subjective well-being as the positive factor, and we compared it with a single-factor model to determine if DFM could be applied to military personnel. We also constructed a cross-lagged model to investigate longitudinal relationships between depression, subjective well-being, presence of meaning, and search for meaning.

RESULTS

According to the findings, military personnel fit better with the DFM than with the single-factor model. Cross-lagged analysis results revealed that both the presence of meaning and the search for meaning negatively predicted depression and positively predicted subjective well-being.

CONCLUSIONS

The DFM had good applicability among military personnel. Both the presence of meaning and the search for meaning could improve military mental health, suggesting that both dimensions of meaning in life may be potential targets for improving military mental health.

Developmental Trajectories of Mental Health in Chinese Early Adolescents: School Climate and Future Orientation as Predictors

There is growing support for the dual-continua model of mental health, which emphasizes psychopathology and well-being as related but distinct dimensions. Yet, little is known about how these dimensions co-develop from childhood to early adolescence and what factors predict their different trajectories. The current study aimed to identify distinct patterns of mental health in Chinese early adolescents, focusing on both psychopathological symptoms (i.e., depressive symptoms and self-harm behaviors) and subjective well-being (i.e., life satisfaction and affect balance). This study also examined the contributions of school climate and future orientation to these trajectories. A total of 1,057 students (Mage = 11.88, SDage = 1.67; 62.1% boys) completed four assessments over two years, with six-month intervals. Using parallel-process latent class growth modeling, we identified four groups: Flourishing (32.5%), Languishing (43.8%), Troubled with Stable Depressive Symptoms (16.1%), and Troubled with Increasing Self-Harm Risk (7.6%). Furthermore, school climate and future orientation contributed to adolescents' membership in these trajectories, either independently or jointly. Specifically, higher levels of future orientation combined with higher school climate were associated with a lower likelihood of belonging to the Troubled with Increasing Self-Harm Risk trajectory, compared to the Flourishing group. Our findings identified four distinct mental health trajectories consistent with the dual-continua model, and demonstrated that the development of psychopathology and well-being were not always inversely related (e.g., the Languishing group). Adolescents with unique developmental profiles may benefit from tailored intervention strategies that build on the personal and environmental assets of the adolescent.

Psychological distress, wellbeing and resilience: modelling adolescent mental health profiles during the COVID-19 pandemic

There has been concern about adolescent mental health during the pandemic. The current study examined adolescent mental health during the initial phase of the COVID-19 pandemic in the UK. Using indicator of psychological distress, wellbeing and resilience, latent profile analysis was used to identify homogeneous mental health groups among young people aged 13-24 (N = 1971). Multinomial logistic regression was then used to examine which sociodemographic and psychosocial variables predicted latent class membership. Four classes were found. The largest class (Class 1, 37.2%) was characterised by moderate symptomology and moderate wellbeing. Class 2 (34.2%) was characterised by low symptomology and high wellbeing, while Class 3 (25.4%) was characterised by moderate symptomology and high wellbeing. Finally, Class 4 was the smallest (3.2%) and was characterised by high symptomology and low wellbeing. Compared to the low symptomology, high wellbeing class, all other classes were associated with less social engagement with friends, poorer family functioning, greater somatic symptoms, and a less positive model of self. A number of unique associations between the classes and predictor variables were identified. Although around two-thirds of adolescents reported moderate-to-high symptomology, most of these individuals also reported concurrent moderate-to-high levels of wellbeing, reflecting resilience. Furthermore, these findings demonstrate how a more comprehensive picture of mental health can be gained through adopting a dual-continua conceptualisation of mental health that incorporates both pathology and well-being. In this way, at-risk youth can be identified and interventions and resources targeted appropriately.

Dual-factor Models of Mental Health: A Systematic Review of Empirical Evidence

Objective: Dual-factor models of mental health propose that mental health includes two interrelated yet distinct dimensions - psychopathology and well-being. However, there is no systematization of the evidence following these models. This review aims to address the following research question: what evidence exists using dual-factor models? Method: The current systematic review was conducted using PRISMA guidelines on the following databases: Web-of-science, Scopus, Academic Search Complete, APA PsycArticles, APA PsycInfo, Psychology and Behavioral Sciences Collection, ERIC, and MEDLINE. The screening process resulted in 85 manuscripts that tested the assumptions of dual-factor models. Results: Evidence revealed psychometric substantiation on the two-dimensionality of the dual-factor model, and 85% of the manuscripts provided evidence related to classifying participants into different mental health groups. Most studies showed that the Complete Mental Health or Positive Mental Health group is the most prevalent status group, and longitudinal evidence suggests that most participants (around 50%-64%) remain in the same group across time. Regarding the factors associated with mental health status groups, studies reviewed in this manuscript focus mainly on school-related outcomes, followed by supportive relationships, sociodemographic characteristics, psychological assets, individual attributes, physical health, and stressful events. Conclusions: This review highlights the importance of considering the two dimensions of mental health when conceptualizing, operationalizing, and measuring mental health. Fostering mental health must go beyond reducing symptoms, and practitioners would be able to include well-being-related interventions in their regular practice to improve individuals' mental health outcomes.

Mental health profiles and academic achievement in Australian school students

This study explored mental health profiles in Australian school students using indicators of well-being (i.e., optimism, life satisfaction, and happiness) and psychological distress (i.e., sadness and worries). The sample included 75,757 students (ages 8-18 years) who completed the 2019 South Australian Wellbeing and Engagement Collection. Latent profile analysis identified five mental health profiles consisting of (a) complete mental health (23%), (b) good mental health (33%), (c) moderate mental health (27%), (d) symptomatic but content (9%), and (e) troubled (8%). Findings provide partial support for the dual-factor model of mental health. Distal outcomes analysis on a sub-set of students (n = 24,466) found students with a symptomatic but content, moderate mental health, or troubled profile had poorer academic achievement than students with complete mental health. Implications for schools and education systems are discussed, including the need to pair clinical supports for students with psychological distress with population-level preventative health approaches to build psychological well-being.

Factor structure and measurement invariance of the 8-item CES-D: a national longitudinal sample of Chinese adolescents

BACKGROUND

The 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8) has been widely used to measure depressive symptoms in many large-scale surveys. Due to its brevity, it can lower costs, relieve respondent burdens, and ensure data quality. However, its factor structure and measurement invariance across gender and time among adolescents have not been adequately evaluated. This study investigated its factor structure and measurement invariance across gender and time among adolescents.

METHODS

The data was drawn from the China Family Panel Studies (CFPS) conducted in 2018 and 2020, with 3099 participants (46.82% girls) aged 11 to 18 in 2018. First, exploratory and confirmatory factor analyses were used to examine the factor structure of the CES-D 8. Next, multi-group confirmatory factor analysis was conducted to test its measurement invariance across gender and time. Finally, a longitudinal cross-gender test was conducted to further confirm the stability of the scale.

RESULTS

A two-factor structure was identified among the adolescents, including Negative Symptoms and Diminished Happiness Feeling. Measurement invariance across gender and time, as well as the longitudinal cross-gender invariance, was supported, with configural, factor loadings, thresholds and residual invariance.

CONCLUSIONS

The factor structure of the CES-D 8 remains stable across gender and time among adolescents, indicating that it is a promising instrument for measuring depressive symptoms, especially in large-scale and longitudinal surveys.

Mental health latent profiles and emotion regulation in women with polycystic ovary syndrome: A cross-sectional study

This cross-sectional study aimed to identify latent mental health subgroups of reproductive-aged women with polycystic ovary syndrome (PCOS) and examine differences in emotion regulation and social support. A total of 477 samples (age = 27.22 ± 5.37) diagnosed with PCOS were included in this study, all of whom were of the same ethnicity. Latent profile analysis (LPA) was conducted in Mplus version 8.3 to identify mental health latent profiles in women with PCOS based on the dual-factor approach. The current study identified three distinct mental health profiles within women with PCOS: High-Symptom and High-Well-being Profile, Low-Symptom and High-Well-being Profile, and High-Symptom and Low-Well-being Profile, with group proportions of 52.3%, 35.7%, and 11.1%, respectively. This study revealed that cognitive reappraisal and social support are important protective factors for the mental health of women with PCOS, whereas expressive suppression is a negative factor for their mental health.

The Influence of Growth Mindset on the Mental Health and Life Events of College Students

Growth mindset refers to our core belief that our talents can be developed through practice, which may influence our thoughts and behaviors. Growth mindset has been studied in a variety of fields, including education, sports, and management. However, few studies have explored whether differences in individuals' growth mindsets influence college students' self-reported mental health. Using the Growth Mindset Scale, Adolescent Self-rating Life Events Checklist, and SCL-90 Scale, data was collected from 2,505 freshmen in a University in China. Findings revealed that the students within the growth mindset group scored significantly lower on "mental health issues" and "stress due to life events" than the students in the fixed mindset group. Our findings suggest that individuals with a growth mindset are less prone to mental health problems than individuals with a fixed mindset.