Positive psychological well-being and psychological distress in higher education students

Abstract

Background:

Positive psychology well-being constructs like flourishing are important predictors of health and quality of life. However, few studies have examined the association between flourishing and psychological distress (i.e., depression and anxiety). We investigated the association between flourishing and psychological distress symptoms among higher education students.

Methods:

We analyzed cross-sectional survey data from 60,386 students aged 18–34 in the United States (Healthy Minds Study 2022–2023). Flourishing was measured using the Flourishing Scale, while symptoms of depression and anxiety were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales, respectively. Associations between flourishing and psychological distress were examined using multiple logistic regression models, adjusting for age, gender identity, race/ethnicity, financial stress, and self-reported mental health treatment.

Results:

Of the 60,386 participants included the mean age was 21.7 (SD = 3.6). Most participants were female (68.3 %) and White (55.6 %). Among individuals with significant symptoms of depression or anxiety, 13.7 % and 17.7 % were classified as flourishing (Flourishing Scale ≥48), respectively. Participants with significant symptoms of depression (OR: 0.23; CI: 0.22–0.25) or anxiety (OR: 0.56; CI: 0.54–0.59) were less likely to be classified as flourishing than those without significant symptoms.

Conclusion:

Flourishing is possible within psychological distress. These results suggest the importance of assessing both positive psychological well-being and psychological distress to understand student mental health. While reducing symptoms of psychological distress is crucial, enhancing positive psychological well-being should also be prioritized as part of mental health treatment.

1. Introduction

The predominant focus of mental healthcare systems has traditionally been the alleviation of psychological distress (i.e., symptoms of depression and anxiety), rather than the cultivation of positive psychological well-being (PPWB) (Jeste et al., 2015). PPWB can be defined as optimal functioning across multiple domains of a person’s life (Park et al., 2023; VanderWeele and Lomas, 2023). However, the World Health Organization’s 2022 World Mental Health Report called for a more whole-person approach, urging mental healthcare systems to prioritize overall well-being rather than merely the absence of symptoms of mental illness (Freeman, 2022). This shift aligns with a broader trend in research and clinical practice to consider and incorporate PPWB measures. PPWB is associated with improved physical health outcomes (Amonoo et al., 2022; Levine et al., 2021), better quality of life, and reduced all-cause mortality (Boylan et al., 2022; Guven and Saloumidis, 2009; Liu et al., 2016), likely due to a myriad of biological, psychological, and behavioral mechanisms that mediate its impact on health-related outcomes (Boylan et al., 2022). However, while PPWB has garnered increasing attention in the medical and overall population health literature, there remains a lack of research on the relationship between PPWB and mental illness (Jeste et al., 2015).

A budding body of work has highlighted that PPWB and symptoms of illness are distinct but interrelated constructs (Iasiello and Van Agteren, 2020), with the presence of mental illness not necessarily precluding the experience of well-being, and vice versa. In this “dual continua” model of mental health, individuals can be classified into four states: A) high PPWB without mental illness, B) high PPWB with mental illness, C) low PPWB without mental illness, and D) low PPWB with mental illness (Iasiello and Van Agteren, 2020). Emerging evidence demonstrates high levels of PPWB may be protective against future onset of mental illness (Burns et al., 2022; Marques et al., 2011; Wasserman et al., 2023; Westerhof and Keyes, 2010; Wood and Joseph, 2010). However, limitations of this literature include limited exploration of diverse samples and inconsistent operationalization of PPWB constructs.

The rapidly evolving PPWB literature has shifted from assessing single constructs to exploring more multidimensional, holistic constructs, such as flourishing (Brandel et al., 2017; VanderWeele et al., 2019). Flourishing is broadly understood as an evolving state of optimal well-being and functioning across multiple domains of an individual’s life, including emotional, psychological, and social functioning (Freeman, 2022; VanderWeele, 2017; VanderWeele and Lomas, 2023; VanderWeele et al., 2019). Flourishing has been linked to positive physical health outcomes, though much of the research is cross-sectional and focuses on populations without mental illness (Chen et al., 2022). Given multiple conceptualizations and cross-cultural definitions of flourishing, researchers are still working toward a consensus definition of flourishing in the research community (Rule et al., 2024).

Students in higher education (i.e., beyond high school) are in a critical period of identity development and social connection formation and are at high-risk for mental illness. Large survey data suggests 40 % of college students experience significant symptoms of depression and over one third experience significant symptoms of anxiety, a rate that has doubled within the past decade (Lipson et al., 2022). This high burden of psychological distress among higher education students underscores the need for comprehensive approaches to enhance psychological health in this population (Gaiotto et al., 2022; Worsley et al., 2022). Despite the numerous potential benefits of promoting PPWB, relatively few studies have examined the relationship between PPWB and psychological distress in higher education students (Eklund et al., 2010; Galsky, 2019; Renshaw and Cohen, 2014). Secondly, this study aims to highlight differences in flourishing among minority groups and participants with mental illness using a large, nationally representative sample of higher education students.

2. Material and methods

2.1. Data

We used data from the 2022–2023 Healthy Minds Study (HMS), a cross-sectional survey of undergraduate and graduate students in the United States. The survey is administered online to institutions that elect to participate, and students are invited and reminded to complete the survey via emails. The response rate for the 2022–2023 cohort was 9 %, yielding a total of 76,635 observations (Healthy Minds Network, 2022–2023). We followed STROBE reporting guidelines for cross-sectional studies (Cuschieri, 2019).

Consistent with previous use of the Healthy Minds Study, we restricted our analysis participants aged 18–34 to focus on young adult students (Oh, 2023). HMS was approved by the Advarra Institutional Review Boards at each participating campus (Healthy Minds Network, 2022–2023). The HMS dataset is available upon request at https://healthymindsnetwork.org/hms/.

2.2. Participant characteristics used as covariates

Sociodemographic variables included self-reported age, race/ethnicity, gender, financial stress, and history of mental health treatment. Age was coded continuously, in line with previous publications using the Healthy Minds dataset (Oh, 2023). Race/ethnicity categories included White, Black, Asian, Latinx/Hispanic, Native Hawaiian/Pacific Islander, Middle Eastern, American Indian/Alaska Native. Individuals who selected “other,” more than one racial category, or did not respond were classified as “Other/Multiple.” Gender was categorized as cisgender man, cisgender woman, and gender diverse (including “Trans male/Trans man,” “Trans female/Trans woman,” “Genderqueer/Gender non-conforming,” “Gender non-binary,” or “Self-identify [please specify]”). Non-respondents and those selecting “Prefer not to respond” were classified as “Missing.” Financial stress was measured using a 5-point Likert scale ranging from “Always” to “Never,” reflecting respondents’ perceived financial situation at the time of the survey. Students also reported whether they had engaged in mental health treatment within the past year, including therapy and/or psychiatric prescription medications (psychostimulants, antidepressants, antipsychotics, anxiolytics, and sleep medications).

2.3. Measures of flourishing, depression, and anxiety

2.3.1. Flourishing

Flourishing was assessed using the eight-item Flourishing Scale, a multidimensional PPWB scale with scores ranging from 8 to 56 (Diener et al., 2010). This scale assesses dimensions of well-being, including purpose, social relationships, engagement, contribution, competence, self-esteem, optimism, and respect. We used the standardized flourishing cut-off of ≥48 to dichotomize flourishing scores into individuals classified as flourishing (Diener et al., 2010).

2.3.2. Psychological distress

Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) (Löwe et al., 2004). We used the standardized cut-off of ≥10 to dichotomize PHQ-9 scores to identify individuals likely to have moderate to severe symptoms of depression (Beard et al., 2016). Anxiety symptoms were assessed using the Generalized Anxiety Disorder 7-item scale (GAD-7) (Spitzer et al., 2006). We used the standardized GAD-7 cut-off of ≥10 to identify individuals likely to have moderate to severe symptoms of anxiety (Spitzer et al., 2006).

2.4. Statistical analysis

All analyses were conducted using Stata version 18.5 (StataCorp, College Station, TX). We first summarized participant characteristics with descriptive statistics (i.e., mean for continuous variables and proportions for categorical variables). We then summarized rates of flourishing by group for all participant characteristics, including gender, race/ethnicity, history of mental health treatment, financial stress, symptoms of depression and/or anxiety, and self-reported prior diagnosis of depression and/or anxiety. To assess relationships between sociodemographic variables and flourishing as well as depression/anxiety, we calculated summary statistics and conducted chi squared tests of flourishing.

In our primary analysis, we used three multiple logistic regression models to examine the association between flourishing and self-reported mental health, adjusting for additional individual characteristics. In Model 1, we assessed the relationship between flourishing and all sociodemographic variables, including age, gender, race/ethnicity, and financial stress given well-established links between these sociodemographic variables and mental health. In Model 2, we assessed the relationship between flourishing and current symptoms of depression (PHQ-9 ≥ 10) and anxiety (GAD-7 ≥ 10), controlling for the sociodemographic variables included in Model 1. In Model 3, we controlled for any reported mental health treatment within the previous year including therapy and medications, given the potential influence of treatment on mental health outcomes.

In our secondary analysis in Models 4 and 5, we assessed the relationship between flourishing and self-reported prior diagnoses of depression or anxiety instead of self-reported symptoms. Lastly, we graphed a heat plot illustrating the association between symptoms of mental illness and flourishing, based on established cut-offs for the Flourishing Scale, PHQ-9, and GAD-7, with rectangle sizes denoting relative frequency (Fig. 1).

Fig. 1.

Flourishing, depression, and anxiety heatmap by frequency.

Lastly, we conducted exploratory analyses to test whether the relationship between depression and flourishing differed by key sociodemographic factors by adding interaction terms to our models. Specifically, we evaluated interaction terms for depression * race/ethnicity (Black, Hispanic/Latin(x), Asian/Asian-American), gender (women, transgender) and financial stress.

2.5. Missing data

Out of the 76,406 initial observations, we excluded 5771 individuals ≥35 years old. We sequentially excluded all observations with incomplete or missing main outcome or predictor variable data, including the Flourishing Scale (n = 5761; 8.2 %), PHQ-9 (n = 2370; 3.7 %), and GAD-7 (n = 1582; 2.5 %). Observations from covariates with <1 % missing responses were dropped, including gender (n = 400), race/ethnicity (n = 98), and financial stress (n = 38). For covariates with ≥1 % missing data (i.e., mental health treatment), we included ‘Missing’ as a separate category to retain respondents in the analysis. Appendix A displays the differences in flourishing rates between dropped and retained observations.

3. Results

Our final analytic sample included 60,386 participants, with a mean age of 21.7 (SD = 3.6). Most participants were female (n = 41,234; 68.3 %) and White (n = 33,545; 55.6 %). A minority of the sample reported psychiatric medication use within the past year (n = 16,641; 27.6 %) or being engaged in therapy within the past year (n = 22,616; 37.5 %). The mean flourishing score was 43.0 (SD = 8.9), while the mean scores for PHQ-9 score and GAD-7 were 9.1 (SD = 6.4) and 8.3 (SD = 5.9), respectively. Approximately one-third (n = 21,366, 35.4 %) were classified as flourishing (Flourishing Scale ≥48), 41.0 % (n = 24,677) had clinically significant symptoms of depression (PHQ-9 ≥ 10), and 37.7 % (n = 22,760) had clinically significant symptoms of anxiety (GAD-7 ≥ 10; Table 1 summarizes descriptive statistics). Of the participants who reported significant symptoms of depression on the PHQ-9, 13.7 % were flourishing (5.6 %, n = 3379 of total sample). Of the individuals with significant symptoms of anxiety on GAD-7, 17.7 % were flourishing (6.7 %, n = 4026 of total sample; Fig. 1).

Table 1.

Sociodemographic characteristics, flourishing, and mental illness of the study participants.

	n	% flourishing	% depression	% anxiety	% medication	% therapy	% flourishing within psychological distress
Total sample	60.386	35.4	40.9	37.7	27.6	37.5	8.8
Gender
Male	15,262	38.2	31.6	24.9	17.1	23.8	5.9
Female	41,234	36.1	41.7	40.6	29.1	40.1	10.0
Gender diverse	3890	16.4	68.1	56.9	52.2	62.8	7.0
Race/ethnicity
White	33,545	37.2	39.4	38.6	34.7	41.7	9.1
Black	5298	38.9	42.1	35.0	15.4	33.2	10.2
Hispanic/Latin(x)	5689	32.1	45.2	40.2	17.5	31.8	9.1
Asian/Asian American	7677	30.5	37.6	30.6	12.6	24.3	6.0
AI/NA	122	35.3	48.4	38.5	27.9	24.6	7.4
Pacific Islander	85	38.8	58.8	40.0	15.3	27.1	17.7
Middle East	936	34.0	42.5	38.0	18.6	28.1	8.5
Other/multiple	7041	32.4	46.6	41.2	28.6	40.8	8.8
Current financial stress
Always	9298	22.4	66.5	62.2	35.5	42.7	11.3
Often	14,777	28.2	50.3	44.9	30.6	39.8	9.7
Sometimes	20,548	38.0	34.6	31.6	24.8	35.6	8.3
Rarely	11,535	44.6	26.1	25.4	23.9	34.9	7.0
Never	4228	51.7	22.3	21.5	22.8	33.6	7.2
Mental illness symptoms
PHQ-9 < 10	35,709	50.4	–	15.0	20.0	30.8	5.4
PHQ-9 ≥ 10	24,677	13.7	100	70.5	38.4	47.1	13.6
GAD-7 < 10	37,789	46.1	19.4	–	20.4	30.5	3.4
GAD-7 ≥ 10	22,925	17.7	76.4	100	39.4	49.0	17.6
Self-reported diagnoses
No depression	43,954	40.9	32.1	30.0	12.3	25.3	8.5
Depression	16,760	20.8	63.9	57.9	67.7	69.5	9.6
No anxiety	39,087	40.1	32.7	27.6	8.1	21.3	7.3
Anxiety	21,299	26.7	55.8	56.3	63.2	67.2	11.5
Past year mental health treatment
No psychiatric medication	40,666	39.3	33.9	30.8	–	25.4	7.8
Psychiatric medication	16,641	26.4	57.0	54.0	100	70.3	11.0
Missing	3079	32.8	46.0	41.7	–	19.6	8.9
No therapy	35,972	39.3	34.2	30.5	13.6	–	7.7
Therapy	22,616	29.1	51.3	49.3	51.7	100	10.5
Missing	1798	36.2	41.6	36.4	3.7	–	8.4

Notes: Healthy Minds Study 2022–23 Dataset; Data and analyses are observed at the individual-level.

p < 0.0001 for the Chi-square tests examining the relationship between sociodemographic factors and mental health variables (flourishing, depression, anxiety, medications, and therapy).

AI/NA = American Indian/Native American; PHQ-9 = Patient Health Questionnaire-9; GAD-7 = Generalized Anxiety Disorder-7; Psychological Distress represents significant symptoms of depression (PHQ-9 ≥ 10) or anxiety (GAD-7 ≥ 10).

We first examined the relationship between flourishing and sociodemographic variables, including age, gender, race/ethnicity, and financial stress. Notably, those who identified as gender diverse, Hispanic/Latinx, Asian/Asian American, Middle Eastern, and Other/Multiple race/ethnicities were less likely to flourish. Those who identified as Black and under less financial stress were more likely to flourish (Table 2, Model 1).

Table 2.

Association between mental illness symptoms and flourishing.

	Model 1		Model 2		Model 3
	OR	95 % CI	OR	95 % CI	OR	95 % CI
Agea	1.04	[1.04–1.05]	1.02	[1.02–1.03]	1.03	[1.02–1.03]
Gender
Male (ref)	1.00		1.00		1.00
Female	0.99	[0.95–1.03]	1.18*	[1.13–1.23]	1.22*	[1.17–1.27]
Gender diverse	0.35*	[0.32–0.39]	0.58*	[0.53–0.64]	0.64*	[0.58–0.70]
Race/ethnicity
White (ref)	1.00		1.00		1.00
Black	1.24*	[1.17–1.32]	1.18*	[1.11–1.26]	1.13*	[1.06–1.21]
Hispanic/Latin(x)	0.89*	[0.84–0.95]	0.89*	[0.83–0.95]	0.85*	[0.79–0.91]
Asian/Asian American	0.66*	[0.63–0.70]	0.63*	[0.59–0.66]	0.59*	[0.56–0.63]
American Indian/Native American	0.93	[0.63–1.36]	1.06	[0.70–1.59]	1.02	[0.68–1.53]
Pacific Islander	1.28	[0.82–2.00]	1.60	[0.98–2.61]	1.51	[0.93–2.46]
Middle East	0.85*	[0.73–0.97]	0.87	[0.75–1.01]	0.83*	[0.72–0.97]
Other/multiple	0.87*	[0.82–0.92]	0.91*	[0.86–0.97]	0.90*	[0.85–0.96]
Current financial stress
Always (ref)	1.00		1.00		1.00
Often*	1.40*	[1.31–1.49]	1.01	[0.95–1.08]	1.01	[0.95–1.08]
Sometimes*	2.23*	[2.11–2.36]	1.28*	[1.20–1.36]	1.27*	[1.19–1.35]
Rarely*	3.07*	[2.88–3.27]	1.56*	[1.45–1.67]	1.55*	[1.45–1.66]
Never*	4.19*	[3.87–4.53]	2.06*	[1.89–2.24]	2.06*	[1.89–2.25]
Mental illness symptoms
PHQ-9 < 10 (ref)			1.00		1.00
PHQ-9 ≥ 10			0.23*	[0.22–0.25]	0.24*	[0.23–0.25]
GAD-7 < 10 (ref)			1.00		1.00
GAD-7 ≥ 10			0.56*	[0.54–0.59]	0.58*	[0.55–0.61]
Past year mental health treatment
No psychiatric medication (ref)					1.00
Psychiatric medication					0.84*	[0.80–0.88]
Missing					0.90	[0.80–1.01]
No therapy (ref)					1.00
Therapy					0.87*	[0.83–0.91]
Missing					1.08	[0.94–1.25]

Notes: Healthy Minds Study 2022–23 Dataset; data and analyses are observed at the individual-level.

OR = odds ratio; CI = confidence interval; Ref = reference group; PHQ-9 = Patient Health Questionnaire-9; GAD-7 = Generalized Anxiety Disorder-7.

^aOdds ratio for 1 unit increase.

^*Statistically significant at a p < 0.05 level.

Model 2 added symptoms of depression and anxiety as predictors into Model 1. Symptoms of depression (OR: 0.23; 95 % CI: 0.22–0.25) and symptoms of anxiety (OR: 0.56; 95 % CI: 0.54–0.59) were associated with a lower likelihood of flourishing (Table 2, Model 2).

Model 3 added self-reported past-year mental health treatment (medication or therapy) into Model 2, resulting in modest changes to the overall results. Individuals who utilized psychiatric medication or therapy were less likely to be classified as flourishing compared to those who did not report past-year medication or therapy (Table 2, Model 3).

In secondary analyses, we added self-reported diagnoses of depression and anxiety instead of self-reported symptoms of depression and anxiety, controlling for the same covariates. Of individuals with significant symptoms of depression, 64.0 % (n = 10,727) also reported a diagnostic history of depression. In the adjusted model, a self-reported diagnosis of depression (OR: 0.45; 95 % CI: 0.42–0.47) and anxiety (OR: 0.88; 95 % CI: 0.84–0.92) was associated with a lower likelihood of flourishing (Table 3, Model 4). For Model 5, we added treatment variables to Model 4, a self-reported depression diagnosis remained significant (OR: 0.47; 95 % CI: 0.45–0.50), but a self-reported anxiety diagnosis was no longer significant (OR: 0.95; 95 % CI: 0.84–1.00). Individuals who utilized psychiatric medication or therapy were less likely to flourish than those not using medication or therapy (Table 3, Model 5).

Table 3.

Association between mental illness diagnosis and flourishing.

	Model 4		Model 5
	OR	95 % CI	OR	95 % CI
Agea	1.05*	[1.04–1.05]	1.05*	[1.05–1.06]
Gender
Male (ref)	1.00		1.00
Female	1.11*	[1.06–1.15]	1.12*	[1.06–1.15]
Gender diverse	0.48*	[0.44–0.53]	0.50*	[0.44–0.53]
Race/ethnicity
White (ref)	1.00		1.00
Black	1.10	[1.03–1.17]	1.09	[1.03–1.16]
Hispanic/Latin(x)	0.81	[0.76–0.86]	0.80	[0.75–0.85]
Asian/Asian American	0.57*	[0.54–0.61]	0.56*	[0.53–0.60]
American Indian/Native American	0.87	[0.59–1.28]	0.85	[0.58–1.26]
Pacific Islander	1.09	[0.70–1.72]	1.09	[0.69–1.70]
Middle East	0.74*	[0.64–0.86]	0.74*	[0.64–0.85]
Other/multiple	0.85*	[0.80–0.90]	0.85*	[0.80–0.90]
Current financial stress
Always (ref)	1.00		1.00
Often*	1.32*	[1.25–1.41]	1.32*	[1.25–1.41]
Sometimes*	2.01*	[1.89–2.13]	2.01*	[1.90–2.13]
Rarely*	2.71*	[2.54–2.89]	2.70*	[2.54–2.89]
Never*	3.67*	[3.38–3.98]	3.69*	[3.40–4.00]
Self-reported diagnoses
No self-reported depression	1.00		1.00
Self-reported depression	0.45*	[0.42–0.47]	0.47*	[0.45–0.50]
No self-reported anxiety	1.00		1.00
Self-reported anxiety	0.88*	[0.84–0.92]	0.95	[0.84–1.00]
Past year mental health treatment
No psychiatric medication (ref)			1.00
Psychiatric medication			0.91*	[0.86–0.96]
Missing			0.81*	[0.73–0.91]
No therapy (ref)			1.00
Therapy			0.86*	[0.82–0.90]
Missing			1.05	[0.91–1.20]

Notes: Healthy Minds Study 2022–23 Dataset; Data and analyses are observed at the individual-level.

OR = odds ratio; CI = confidence interval; Ref = reference group; PHQ-9 = Patient Health Questionnaire-9; GAD-7 = Generalized Anxiety Disorder-7.

^aOdds ratio for 1 unit increase.

^*Statistically significant at a p < 0.05 level.

In exploratory analyses examining the relationship between key sociodemographic variables and the effect of depression on flourishing, we added key interaction terms to the base model (Model #3). The interaction terms improved the fit for models when including Hispanic/Latin(x) * depression (OR: 1.21; 95 % CI 1.05–1.40) and Asian/Asian-American * depression (OR 1.16; 95 % CI 1.01–1.33), as indicated by significant changes in the likelihood ratio compared to the base model (p < 0.05). Compared to White students, the negative association between depressive symptoms and flourishing was found to be weaker for Asian and Hispanic groups. The interaction terms between depression and Black race/ethnicity, women, transgender, or moderate financial stress did not significantly improve overall model fit, as indicated by non-significant changes in the likelihood ratios compared to the base model.

4. Discussion

In this cross-sectional study of higher education students, we found that flourishing was strongly associated with the absence of mental illness; however, a non-trivial proportion of individuals with mental illness were flourishing. Moreover, flourishing rates varied significantly across sociodemographic groups. These findings underscore the complex relationship between flourishing and psychological distress in diverse populations. When considered alongside prior research showing that individuals with mental illness often prioritize goals related to PPWB (Cummergen et al., 2022; Zimmerman et al., 2006), these results reinforce the importance of incorporating PPWB assessments when evaluating the overall mental health of higher education students. More work is needed to establish whether college mental health services could consider routine PPWB assessment at initial intake or even repeated measures over time to better assess overall mental well-being.

We found that self-reported symptoms of depression and anxiety were associated with lower flourishing rates. The inverse relationship may, in part, reflect the presence of inversely worded items on both the Flourishing Scale and the PHQ-9. For instance, the Flourishing Scale includes an item asking whether individuals feel, “engaged and interested in daily activities,” which contrasts with the PHQ-9’s item on anhedonia. Similarly, individuals experiencing hopelessness or negative self-perceptions may rate items related to competence, optimism, or personal worth more negatively. For example, individuals experiencing sleep disturbances, concentration difficulties, or low energy may still highly rate items on the Flourishing Scale such as having purpose, social relationships, and contributing to the happiness of others. Interestingly, 8.8 % of individuals in our sample with significant symptoms of depression or anxiety were classified as flourishing, suggesting that PPWB and psychological distress are distinct but interrelated domains, as suggested by previous research (Galsky, 2019; Iasiello and Van Agteren, 2020; Magalhães, 2024). Moreover, the rates of flourishing within psychological distress were descriptively higher among females, Blacks, and Pacific Islanders.

Self-reported past year mental health treatment was also associated with lower flourishing rates, which may reflect clinical factors not controlled for in this study, such illness severity or comorbid psychiatric illness, both of which have been found to impact likelihood of engaging in mental health treatment (Chen et al., 2013; Doll et al., 2021; Mojtabai et al., 2002, 2011). An alternative possibility is that individuals engaged in mental health treatment may cause people to rate their self-reported levels of flourishing as lower. Although the rates of flourishing within psychological distress were higher within those who were in past year mental health treatment, the underlying causal direction of this relationship remains unclear.

Flourishing also varied significantly across sociodemographic variables. While much of the existing PPWB literature focuses on White, college-educated, Western populations (Hendriks et al., 2019), our study contributes to the literature by highlighting and assessing differences in flourishing among minority sociodemographic groups and individuals with varying levels of mental health symptoms. Notably, low financial stress was strongly associated with flourishing, having the largest effect size of any predictor in this study, underscoring the crucial role of financial well-being in flourishing (VanderWeele, 2017). Although the importance of financial stability, material conditions, and structural inequities to facilitate flourishing remains a topic of debate (Willen et al., 2022), some definitions of flourishing have incorporated social determinants of health (VanderWeele, 2017). When considering the development of mental health services, higher education should account for financial stress and social determinants of health when considering the overall mental health of students.

We found significant differences in rates of flourishing by self-reported race/ethnicity. Asian Americans had the lowest rates of flourishing, mental illness, and mental healthcare utilization among all racial/ethnic groups. This could reflect cultural stigma around help-seeking or underreporting of symptoms in Asian/Asian American communities (Chu and Sue, 2011; Sue et al., 2012; Yang et al., 2020). Notably, after adjusting for psychological distress and mental healthcare utilization, the flourishing gap for Asian Americans widened, possibly due to lower rates of psychological distress and treatment utilization. Hispanic/Latinx participants exhibited lower flourishing, higher mental illness rates, and lower mental health treatment utilization – patterns that may relate to structural inequities and cultural stressors (Cook et al., 2019). Our results suggested that Asian/Asian-American and Latino identity buffered the negative association between depression and flourishing, a relationship we could not identify elsewhere in the literature. Black participants had higher flourishing rates in adjusted models; however, these odds decreased after accounting for psychological distress and mental health treatment utilization, potentially reflecting differences in access to care or help-seeking behavior (Cook et al., 2019; Meyer et al., 2015). More research is needed to explore the relationship between race/ethnicity and PPWB, particularly in relation to factors like belonging, discrimination, loneliness, and bicultural identity, which other studies have identified as potential mediators or confounders (Iturbide et al., 2009; Schmitt et al., 2014; Thornhill et al., 2023). Because flourishing focuses on holistic well-being, it may represent a less stigmatizing and more culturally acceptable outcome for individuals facing barriers to traditional mental healthcare in the student mental health settings. These findings highlight the importance of promoting flourishing—not just the alleviation of symptoms—as a pathway to improving mental health across diverse racial and ethnic groups.

Gender differences in flourishing were also significant. After adjusting for psychological distress and mental health treatment utilization, female participants were more likely to flourish than males. This may reflect higher baseline rates of depression, anxiety, and treatment use among females, which could increase flourishing odds after controlling for these factors (American Psychiatric Association, 2017). In contrast, gender diverse participants exhibited some of the most pronounced disparities, with high levels of psychological distress and low flourishing rates, possibly due to systemic discrimination, stigma, social isolation, and limited access to affirming mental healthcare (Drabish and Theeke, 2022; Pinna et al., 2022). Research highlights the challenges for gender diverse populations due to the COVID-19 pandemic and evolving sociopolitical and legal landscape in the United States (Jarrett et al., 2021; Mallory and Redfield, 2023). In a recent systematic review of transgender mental health, nearly all of the 165 included studies examined the prevalence of psychiatric illness (Pinna et al., 2022), while only a handful of studies have focused on PPWB (Barr et al., 2016; Gothard, 2023; Hajo et al., 2024). Further research should explore the relationships among mental illness, PPWB, access to general and gender-affirming healthcare, and interventions aimed at improving overall well-being in gender diverse young adults.

There are several limitations to this study worthy of discussion. Although we analyzed a large cohort of higher education students, the response rate was 9 %. The relationship between flourishing and mental health symptoms for students who chose not to participate in the survey may be different than for those who participated. Although this low response rate may have led to sampling bias and lower generalizability to all college students, this rate is consistent with other national survey data and prior years of the Healthy Minds Study (Lipson et al., 2022). We excluded approximately 14.5 % of the sample because of missing/incomplete data; however, differences in the primary outcome measure, flourishing, between the data included and excluded were marginal (Appendix A). The Flourishing Scale was first studied in samples in only the United States and Singapore, which limits the generalizability of these findings across different ethnic and cultural groups (Diener et al., 2010). Efforts to confirm a gold standard consensus measure of PPWB, validated cross-culturally, would go a long way to facilitating direct comparisons across studies in the future. While this study elucidates important new findings about the relationship between flourishing and symptoms of mental illness in college-enrolled young adults, we were unable to study the relationship between mental health symptoms and other types of commonly used PPWB measures. Future qualitative research studies may aim to understand the acceptability and appropriateness of PPWB assessment within mental healthcare. Furthermore, understanding the underlying mechanisms and longitudinal relationship between PPWB and mental illness will be a key area for future research.

5. Conclusions

This cross-sectional study contributes to the growing body of evidence suggesting that PPWB is an important consideration for mental health in higher education. Future work should establish the need to integrate PPWB measures into longitudinal and interventional studies to more comprehensively assess mental health. While the treatment of mental illness symptoms remains essential, describing and potentially intervening on PPWB should also be considered.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jad.2025.120550.