Gender and sexual identity-based inequalities in adolescent wellbeing: findings from the #BeeWell Study

This research addresses the significant gap in understanding wellbeing disparities between gender/sexual minority adolescents and their peers, particularly during early adolescence (ages 10-15), a crucial period for identity development. The study employs a multi-faceted approach to wellbeing, encompassing hedonic (affect and life satisfaction), eudaimonic (autonomy, self-esteem, etc.), and complete state (mental wellbeing and distress) frameworks. This comprehensive approach aims to move beyond the existing literature’s predominant focus on mental health difficulties, offering a more nuanced understanding of the broader wellbeing landscape for LGBTQ+ youth. The lack of a universally accepted definition of wellbeing necessitates clarification of the theoretical frameworks used in this study and its importance to adolescent development and long-term outcomes.

Existing research demonstrates that LGBTQ+ adolescents experience higher rates of psychological distress than their heterosexual and cisgender peers. Minority stress theory posits that this is due to the added stress from prejudice, discrimination, and internalized stigma. Studies show elevated risks of depression, anxiety, suicide attempts, and self-harm among sexual minority youth. Research also highlights significant wellbeing disparities between boys and girls, with girls consistently reporting worse outcomes across various indicators. Sociocultural, psychological, and biological factors contribute to this gender gap. However, existing research often lacks granular analyses of gender identity and focuses primarily on later stages of adolescence, mostly from a US perspective, leaving early adolescence relatively understudied.

The #BeeWell study utilized a large dataset comprising 37,978 adolescents (ages 12-15) from 165 secondary schools in Greater Manchester. Data collection involved surveys measuring wellbeing across the hedonic, eudaimonic, and complete state frameworks. The survey items were selected through an extensive consultation process involving adolescents, academics, and mental health professionals. Structural correlated factor models were used to assess wellbeing inequalities related to gender and sexual identity, controlling for covariates such as age, free school meal eligibility, special educational needs, and ethnicity. The analysis compared three measurement structures (unidimensional, bifactor, correlated factors) before adopting the correlated factors structure. Two models were estimated for each framework: Model A used gender identity and sexual identity variables, while Model B used gender modality (transgender/cisgender). Multi-categorical variables were dummy coded, and analyses accounted for the clustered nature of the data using the 'Type = complex' function in MPlus 8.7. Maximum likelihood with robust standard errors (MLR) was used; sensitivity analyses using WLSMV and multiple imputation confirmed the results.

The study reveals that wellbeing inequalities related to gender and sexual identity were consistently and substantially larger than those associated with other covariates (age, socioeconomic status, special educational needs, ethnicity). For gender identity, the most significant disparities were found between gender-diverse adolescents (non-binary, other) and boys. Similarly, for sexual identity, the largest inequalities were between sexual minority youth (gay/lesbian, bi/pansexual) and heterosexual peers. These patterns were consistent across all three wellbeing frameworks (hedonic, eudaimonic, and complete state). However, the magnitude of inequalities varied across different wellbeing domains; the largest disparities were observed for negative affect and symptoms of distress, while the smallest were seen for positive relationships. Replacing gender identity with gender modality in the models did not significantly alter the observed sexual identity inequalities. The size of inequalities for sexual minority youth were remarkably similar for gay/lesbian and bi/pansexual adolescents across all domains.

The findings underscore the substantial impact of gender and sexual identity on adolescent wellbeing. The magnitude of these inequalities significantly exceeds those associated with other well-established risk factors, highlighting their critical importance. The results are consistent with minority stress theory, suggesting that experiences of prejudice, discrimination, and internalized stigma contribute significantly to these disparities. Early adolescence may represent a particularly vulnerable period for exposure to these stressors. The study also found consistent wellbeing inequalities for girls compared to boys, although the magnitude of these differences varied across different wellbeing domains, being most pronounced for negative affect and distress. The eudaimonic framework showed the least significant boy-girl disparities. This highlights the importance of considering multiple aspects of wellbeing when assessing inequalities.

This study demonstrates significant wellbeing inequalities for gender-diverse and sexual minority adolescents. Future research should employ more nuanced measurements of gender and sexual identity and adopt an intersectional approach to examine how these inequalities intersect with other socio-demographic factors. Longitudinal studies are needed to understand the development of these inequalities and the underlying mechanisms. The findings strongly advocate for prioritizing preventative and interventional efforts tailored to the unique needs of LGBTQ+ youth.

The study's reliance on self-report measures raises concerns about common method variance. While the study comprehensively modeled domains of the hedonic and complete state frameworks, limitations in the available dataset restricted the inclusion of all eudaimonic domains. The cross-sectional design limits causal inference, and the unbalanced sample size reduces the precision of estimates for minority groups. Generalizability may be limited due to societal variations in factors affecting LGBTQ+ youth. The dataset’s lack of information on gender and sexuality expression is a further limitation, as expression can mediate the relationship between identity and wellbeing.