Testing a Mediation Model of Dispositional Optimism,Mindful Self-Care,and Subjective Well-Being

Abstract

Research consistently demonstrates a positive association between dispositional optimism (DO) and subjective well-being (SWB). This study takes a step forward by exploring potential mechanisms underlying this relationship, with a specific focus on the mediating role of mindful self-care (MSC). We conducted a cross-sectional online survey involving 312 Singaporean adults. Participants completed questionnaires assessing their DO, MSC practices, and overall SWB. Our findings confirmed a significant link between DO and SWB, with individuals exhibiting higher optimism reporting greater well-being. Importantly, the relationship was mediated by MSC, suggesting that optimism motivates individuals to engage in MSC practices, which in turn, enhances SWB. Moreover, DO was linked to all SWB subcomponents, even after controlling for MSC as a mediator. Among the six MSC facets, self-compassion and purpose, supportive relationships, and mindful awareness emerged as significant mediators. This study adds to the growing body of evidence recognizing the positive role of DO and MSC in improving well-being outcomes. It highlights the potential of interventions aimed at cultivating optimism as a promising approach for enhancing mindful self-care practices and ultimately promoting well-being in adults.

Keywords

Subcomponents facets mediator mindful self-care optimism subjective well-being

Introduction

The concept of well-being has captivated philosophers for centuries (Stoll, 2014) and has recently emerged as a prominent area of scientific inquiry, particularly within psychology and public health (Das et al., 2020). Well-being is widely understood as a multidimensional construct encompassing optimal experience and functioning. Two primary traditions frame its study: the hedonic and eudaimonic approaches (Joshanloo et al., 2021; Ryan & Deci, 2001). The hedonic perspective emphasizes pleasure and happiness, focusing on the balance between positive and negative emotions. In contrast, the eudaimonic perspective explores different dimensions of psychological and social well-being, broadening the concept beyond the simple pursuit of pleasure emphasized by the hedonic view. Conversely, the eudaimonic approach delves into various aspects of psychological and social functioning, extending well-being beyond the mere experience of “feeling good” as prioritized by the hedonic perspective (Joshanloo et al., 2021; Ryan & Deci, 2001).

As well-being is rooted in individual experiences, research has predominantly focused on subjective well-being (SWB) for decades (Diener et al., 1999). SWB reflects the degree to which an individual perceives their life as positive, fulfilling expectations, and desirable (Diener et al., 1999). Traditionally, assessments of SWB encompass both affective (presence of positive emotions and absence of negative emotions) and cognitive components (evaluations of life satisfaction) (Diener et al., 2018). While these elements are crucial to understanding SWB, they offer an incomplete picture. Personal and social factors, such as health and relationships, also significantly impact well-being and are frequently employed as indicators (Kinderman et al., 2011). Recognizing this need for a broader measure, the BBC Subjective Well-being Scale (BBC-SWB; Pontin et al., 2013) was developed. This scale incorporates individuals’ subjective experiences across a wider spectrum of domains commonly associated with well-being: physical health, psychological well-being, and relationships will be used in this study to measure SWB.

Personality and Well-Being

The positive consequences of high SWB are well-documented, ranging from enhanced cognitive function and decision-making to stronger relationships and increased civic engagement (Das et al., 2020; Diener et al., 2018). This widespread impact has garnered significant interest, influencing policy decisions in countries like Australia, Canada, New Zealand, the UK, and parts of Europe (Salameh et al., 2022). As a result, researchers are actively exploring factors that contribute to SWB. While demographics like age, gender, and socioeconomic status were initially thought to be key determinants, their impact appears modest, accounting for only 2%–15% of the variance in SWB (Diener et al., 1999; Salameh et al., 2022). Given these limitations, researchers have increasingly focused on personality traits—often referred to as “top-down factors”—due to their significant influence on human behavior and emotions, ultimately impacting SWB (Anglim et al., 2020; Das et al., 2020; Diener et al., 1999, 2018).

DeNeve and Cooper (1998) were among the first to highlight personality as a significant predictor of SWB in the late 1990s. Their meta-analysis of 148 studies identified 137 personality traits linked to SWB components, such as emotional control, trust, locus of control, and resilience. Notably, neuroticism emerged as the strongest predictor when traits were grouped according to the Big Five model. However, despite the recognition DeNeve and Cooper’s work received, the established associations between personality and SWB appeared weaker than expected. Overall correlations were modest (around 0.19), suggesting personality explained only 4% of the variance in SWB. These counterintuitive findings challenged initial assumptions and spurred further exploration.

Steel et al. (2008) re-examined the personality-SWB relationship, offering a contrasting perspective. Their review revealed a considerably stronger association than previously reported, particularly for traits like Extraversion and Neuroticism. These correlations were often double, triple, or even quadruple those found earlier. For instance, DeNeve and Cooper (1998) reported a 4% explanation for positive affect by Extraversion, while Steel et al. (2008) found it to be as high as 19%. Similarly, Neuroticism accounted for 29% of the variance in negative affect compared to DeNeve and Cooper’s 5%. This suggests that the earlier study likely underestimated the SWB-personality link. Another key area of follow-up work addressed the exclusion of positive personality traits in DeNeve and Cooper’s (1998) study. Notably, optimism, self-esteem, and social support were excluded due to potential overlap with SWB itself. However, subsequent research demonstrated that these traits share a low variance (less than 25%) with SWB, suggesting that the constructs are not redundant (Quevedo & Abella, 2010). Building upon this, Quevedo and Abella (2011) conducted a study examining the influence of both the Big Five and previously excluded traits on SWB. Their findings revealed that these excluded traits accounted for twice the variance compared to the Big Five alone. Additionally, their results suggested a somewhat stronger influence of the Big Five on SWB than originally reported by DeNeve and Cooper (1998), aligning with Steel et al. (2008). These studies underscore the importance of considering personality, particularly traits linked to positive outlooks when examining SWB.

Dispositional Optimism and SWB

Fueled by the growing interest in positive psychology (Malouff & Schutte, 2017; Peterson & Seligman, 2004), research has increasingly focused on the potent role of optimism in fostering SWB. Carver and Scheier (2014) theorized “dispositional optimism (DO)” as a personality trait reflecting a balanced perspective across time and situations. DO influences how individuals interpret events in their present, past, and future (Carver & Scheier, 2014). It represents a generalized, relatively stable tendency to expect positive outcomes in various life domains (Scheier & Carver, 2018). Correspondingly, DO is associated with a range of adaptive psychological qualities (Carver & Scheier, 2014; Scheier & Carver, 2018; Scheier et al., 1994). Individuals high in DO tend to exhibit more protective attitudes and greater resilience in the face of stress. They appear to employ more effective problem-focused coping strategies and emotional regulation techniques, both contributing to improved functioning and well-being (Daukantaitė & Zukauskiene, 2012).

Consistent with these findings, DO is also linked to indicators of better physical health (Carver & Scheier, 2014; Rozanski et al., 2019; Scheier & Carver, 2018) and mental health outcomes (Gallagher & Lopez, 2009; Uribe et al., 2021). Studies suggest that individuals high in DO experience higher physical fitness and lower rates of depression and anxiety symptoms. Emerging research further underscores the critical role of DO in the social domain (Carver & Scheier, 2014). Studies have linked optimism to decreased loneliness (Cecen, 2008). Optimists also tend to invest greater effort (or effectiveness) in close relationships, leading to stronger social support and reduced interpersonal conflict (Carver et al., 2005; Feeney & Collins, 2015). In essence, the positive outlook inherent in DO translates into a more positive and fulfilling life experience across various well-being domains of SWB.

Mindful Self-Care as a Potential Mechanism

While DO’s protective role in fostering SWB is well-established (Scheier et al., 1994), a key question remains: what mechanism explains DO’s influence on SWB? Theoretically, DO connects to motivational theories known as expectancy-value models (Scheier & Carver, 2018). These models posit that the combination of outcome expectancy (belief in achieving goals) and goal value determines goal-directed behavior (Carver & Scheier, 2014). Optimists’ confidence in future success acts as a motivational force, driving them to maintain effort toward desired goals even in challenging situations. Conversely, pessimists’ doubt about future outcomes leads to reduced effort and goal disengagement. Consistent with this framework, optimists are typically described as approach or engagement copers.

Given DO’s roots in motivation theory, research has investigated its role in influencing motivation-related outcomes across various life domains. Studies consistently demonstrate that healthy lifestyles mediate the positive associations between DO and different well-being outcomes (Boehm et al., 2018; Carver et al., 2005; Rozanski et al., 2019; Yue et al., 2022). Optimists tend to engage in more health-promoting behaviors, such as physical activity, healthier diets, and reduced smoking compared to less optimistic individuals. All these behaviors are, in turn, linked to lower risks of chronic diseases, particularly heart disease, and better psychosocial functioning, ultimately contributing to enhanced well-being. These findings are not surprising as optimists’ belief in positive future outcomes motivates them to engage in adaptive behaviors because they believe desired outcomes are attainable (Carver & Scheier, 2014; Scheier & Carver, 2018).

Building upon this logic, we propose that mindful self-care (MSC) might be a particularly relevant, yet unexplored, mechanism linking DO and SWB. The concept of self-care has expanded beyond its initial focus on managing chronic illness (Martínez et al., 2021). Today, self-care encompasses proactive strategies to promote and maintain overall well-being, encompassing both physical and mental health (Butler et al., 2019). This shift reflects the growing recognition of self-care’s potential benefits for the general population (Luciani et al., 2022).

Mindfulness, a construct with multiple elements, cultivates present-moment awareness and attention (Hotchkiss & Cook-Cottone, 2019; Lee & Ang, 2023). Comprised of attitude, attention, and intention, mindfulness fosters a non-judgmental and accepting approach to experiences (Shapiro et al., 2006). The attentional component involves the ability to focus on different stimuli while maintaining a broader awareness. Intention refers to the deliberate effort to sustain attention and manage responses. Through mindfulness practice, individuals cultivate a less self-centered perspective, becoming more objective observers of their thoughts, emotions, and bodily sensations. This shift allows for a more reflective and less reactive approach to experiences. Mindfulness practice enhances awareness not only of present experiences but also of bodily sensations and associated emotions (Gibson, 2019). This heightened awareness is believed to improve cognitive flexibility, allowing individuals to engage with present experiences in a more insightful manner. Research suggests that mindfulness fosters serenity and self-patience, strengthening the connection between thoughts, emotions, and bodily sensations, ultimately leading to improved executive functioning and positive affect (Garland et al., 2015). Mindfulness has also been shown to promote psychological well-being and act as a buffer against psychopathological symptoms (Gibson, 2019; Lee & Ang, 2023). Given these benefits, mindfulness can be considered a core component of self-care, enabling individuals to engage with their experiences non-judgmentally and respond in ways that promote positive change.

The growing recognition of mindfulness and self-care benefits has spurred exploration into their combined impact, resulting in the concept of mindful self-care (MSC) (Cook-Cottone, 2015; Cook-Cottone & Guyker, 2018). This recently developed approach merges mindfulness practices with traditional self-care to promote optimal well-being and functioning. Cook-Cottone (2015) defines MSC as an iterative process. It begins with mindful awareness, where individuals assess their internal needs (e.g., emotions, physical sensations) and external demands (e.g., work deadlines, social obligations). This awareness is then followed by intentional actions – engaging in specific self-care practices that address those needs and demands in a way that promotes well-being and personal effectiveness. Cook-Cottone and Guyker’s (2018) multifaceted model of MSC outlines six key facets that contribute to positive embodiment and overall well-being: mindful relaxation (activities promoting relaxation and stress reduction while staying present), physical care (prioritizing healthy habits like nutrition, hydration, and exercise), self-compassion and purpose (cultivating kindness and direction in life), supportive relationships (building positive connections with others), supportive structure (creating a fostering environment), and mindful awareness (non-judgmental observation of thoughts, feelings, and bodily sensations). These six facets can be further categorized into three core domains: nurturing the internal self (physical care and self-compassion and purpose), nurturing the external self (supportive relationships and structure), and integrating practices (mindful awareness and relaxation techniques)—all working together to allow individuals to comprehensively assess their needs and regulate their responses in a balanced and self-directed manner.

Drawing on existing research, it is reasonable to assume that individuals with higher DO are likely to take a more proactive approach to promoting their well-being due to their hopeful and confident attitude in success and a positive future (Carver & Scheier, 2014). In this context, MSC practices may be particularly well-suited for optimists seeking to enhance their overall well-being (Chatterjee & Jethwani, 2020). While no prior studies have directly examined the combined effects of DO and MSC (or mindfulness and self-care) on SWB, research provides support for the independent positive associations between both DO and MSC (or mindfulness and self-care) with SWB. Studies have demonstrated positive correlations between measures of mindfulness and self-care with optimism (Fournier et al., 2002; Vos et al., 2021), and both mindfulness and self-care practices have been identified as significant predictors of SWB (Aldahadha, 2023; Chatterjee & Jethwani, 2020; Torres-Soto, 2022). Similar to mindfulness and self-care, MSC could be considered a fundamental component for promoting physical, mental, and social well-being (Cook-Cottone & Guyker, 2018). This emerging body of research sheds light a potential link between DO and engagement in MSC practices, ultimately impacting SWB. As individuals experience positive outcomes (e.g., improved mood, and reduced stress) from engaging in MSC practices, their belief in their ability to influence SWB strengthens. This positive reinforcement loop further enhances their optimistic outlook and overall well-being (Scheier & Carver, 2018).

Specific Aims and Hypotheses

This study aimed to investigate the relationship between Dispositional Optimism (DO), Mindful Self-Care (MSC), and Subjective Well-Being (SWB). The primary aim was to examine the direct association between DO and SWB. An exploratory aim was to assess whether MSC potentially mediates the relationship between DO and SWB. Based on these aims, the following specific hypotheses were formulated: DO will be positively associated with SWB (c path), DO will be positively associated with MSC (a path), and MSC will be positively associated with SWB after controlling for DO (b path). Figure 1 provides a visual representation of the hypothesized model, where c’ denotes the indirect effect of DO on SWB mediated by MSC.

Methods

Sample Size, Recruitment, and Procedure

A power analysis conducted with G*Power 3.1 software (Faul et al., 2007) indicated a minimum sample size of 210 participants to achieve a moderate effect size (f² = .25) with a significance level of .05 and a power of .95. Participants were recruited through social media platforms (Facebook and Instagram) and the messaging app WhatsApp. All participants were 21 years of age or older and residing in Singapore.

The study received ethical approval from the Institutional Ethics Committee (No: TM18-10011). A standardized information sheet outlining the study’s objectives, potential risks, and the confidential nature of their responses was included in the social media posts and WhatsApp messages used for recruitment. Participants provided implied consent by accessing the web-based questionnaire hosted on the JISC Survey platform. The questionnaire comprised demographic questions and validated measures of DO, MSC, and SWB. To address potential biases, the survey was designed anonymously, and participants were reassured about data confidentiality and the importance of honest responses for accurate scientific findings.

Measures

Subjective Well-Being (SWB)

The Modified BBC-Subjective Well-Being Scale (BBC-SWB; Pontin et al., 2013) is a 24-item scale that assesses SWB across three subscales: Physical Health (seven items; e.g., “Are you happy with the quality of your sleep”), Psychological Well-Being (12 items; e.g., “Do you feel you have a purpose in life”), and Relationships (five items; “Are you happy with your personal and family life”). Participants rated their responses on a 5-point Likert scale (1 = not at all, 5 = extremely). Subscale scores were averaged to create a total SWB score, with higher scores indicating greater well-being.

Mindful Self-Care (MSC)

The 24-item Brief Mindful Self-Care Scale (B-MSCS; Hotchkiss & Cook-Cottone, 2019) assessed participants’ engagement in six MSC facets: Mindful Relaxation (four items; e.g., “I sought out smells to relax”), Physical Care (five items; e.g., “I exercised at least 30–60 minutes”), Self-Compassion and Purpose (four items; e.g., “I gave myself permission to feel my feelings”), Supportive Relationships (four items; e.g., “I spent time with people who are good to me”), Supportive Structure (four items; e.g., “I maintained a manageable schedule”), and Mindful Awareness (three items; e.g., “I had a calm awareness of my thought”). Participants rated the frequency of each statement on a 5-point Likert scale (1 = never, 5 = regularly). Subscale scores were averaged to create a total MSC score, with higher scores indicating greater engagement in MSC practices.

Dispositional Optimism (DO)

The Revised Life Orientation Test (LOT-R; Scheier et al., 1994) is a 10-item scale that measures optimism. Three items are positively worded, three are negatively worded, and four are filler items. Participants rated their responses on a 5-point Likert scale (1 = agree a lot, 5 = disagree a lot). The score for DO was calculated by averaging the remaining six items after excluding the filler items, with higher scores indicating greater optimism.

Data Analysis

The IBM Statistical Package for the Social Sciences (SPSS) software was used to analyze the study’s data. The analysis process involved the following steps. First, descriptive statistics, including means, standard deviations, and frequencies, were calculated for all study variables, followed by bivariate Pearson correlation to evaluate the associations between the variables. Second, Mediation analyses were conducted using the PROCESS macro for SPSS (Igartua & Hayes, 2021) with bootstrapping to investigate whether MSC mediates the relationship between DO and SWB using Model 4. Three mediation models were examined: (1) simple mediation for total MSC as a mediator in the DO-SWB association, (2) simple mediation for total MSC as a mediator in the associations between DO and the three SWB subcomponents (physical health, psychological well-being, and relationships), and (3) parallel mediation for the six facets of MSC (mindful relaxation, physical care, self-compassion and purpose, supportive relationships, supportive structure, and mindful awareness). For each model, 5000 bootstrapped samples were drawn to estimate the indirect effects and their CIs at a 95% confidence level (CIs). Significant mediation was established if the CI for the indirect effect did not include zero at the .05 alpha level. While acknowledging the limitations of cross-sectional designs in establishing causal relationships, this study adopted this approach based on previous research in behavioral science that has successfully utilized cross-sectional mediation analysis (Shrout & Bolger, 2002). Given the mixed findings in the literature regarding the influence of sociodemographic variables on the study variables (Camfield et al., 2009; Igarashi, 2015), these variables were not initially included in the mediation analysis. However, based on their statistical significance, specific sociodemographic variables may be incorporated as covariates in the analysis, and their influence on the results will be addressed in the Results section.

Results

Sample Characteristics

The study recruited a sample of 312 participants, with a majority identifying as female, Singaporean, Chinese, unmarried, religious, and employed. The mean age of participants was 36.07 years (SD = 7.65), ranging from 23 to 62 years old. Table 1 provides a more detailed breakdown of the sample demographics.

Table 1.

Sociodemographic Characteristics of Participants (n = 312).

Variable	f¹ (%)
Age^a	36.07 ± 7.65
Gender
Male	84 (26.9)
Female	228 (73.1)
Nationality
Singaporean	249 (79.8)
Permanent resident	63 (20.2)
Ethnicity
Chinese	258 (82.7)
Non-Chinese	54 (17.3)
Marital status
Not married	165 (52.9)
Married	147 (47.1)
Religion
Atheist	90 (28.8)
Religious	222 (71.2)
Occupation status
Not working	54 (17.3)
Working	258 (82.7)

f¹= = absolute and percentage frequency.

^aThe values are expressed in mean ± standard deviation.

Descriptive Statistics and Bivariate Associations

Descriptive statistics, internal consistency estimates (Cronbach’s alpha), and correlations between the study variables are presented in Table 2. Cronbach’s alpha coefficients indicated good internal consistency for all scales. Univariate normality tests revealed that skewness and kurtosis values for all variables fell within an acceptable range (±2), suggesting adherence to a normal distribution. Bivariate correlations generally reflected the expected patterns of association. Positive correlations of moderate to strong strength were observed between DO, MSC, and SWB. Additionally, all MSC subscales displayed positive correlations with each other, as well as with DO and SWB and its subcomponents (weak to strong strength). Moderate to strong correlations were also found among the three SWB subscales and their association with DO.

Table 2.

Descriptive Statistics and Bivariate Associations Among Study Variables.

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19
1. DO		.000	.001	.000	.000	.000	.000	.000	.000	.000	.000	.000	.781	.666	.953	.074	.094	.000	.606
2. Mindful relaxation	.30		.000	.000	.001	.000	.000	.000	.000	.004	.035	.000	.680	.012	.785	.927	.046	.074	.927
3. Physical care	.19	.34		.000	.035	.000	.000	.000	.000	.000	.004	.000	.332	.009	.007	.753	.062	.129	.618
4. Self-compassion and purpose	.38	.35	.32		.000	.000	.000	.000	.000	.000	.000	.000	.945	.121	.360	.873	.179	.281	.682
5. Supportive relationships	.30	.20	.12	.54		.000	.000	.000	.000	.000	.000	.000	.639	.963	.092	.885	.116	.000	.266
6. Supportive structure	.37	.26	.38	.65	.73		.000	.000	.000	.000	.000	.000	.842	.911	.950	.049	.116	.000	.086
7. Mindful awareness	.46	.32	.33	.52	.59	.72		.000	.000	.000	.000	.000	.636	.135	.002	.088	.815	.036	.713
8. MSC	.46	.56	.57	.79	.73	.87	.81		.000	.000	.000	.000	.900	.994	.797	.400	.917	.007	.460
9. Physical health	.47	.32	.47	.58	.58	.68	.69	.77		.000	.000	.000	.398	.056	.096	.771	.195	.004	.502
10. Psychological well-being	.59	.16	.25	.63	.63	.66	.65	.70	.77		.000	.000	.574	.063	.128	.037	.407	.000	.173
11. Relationships	.46	.12	.16	.54	.71	.62	.58	.61	.65	.78		.000	.980	.835	.058	.002	.082	.000	.942
12. SWB	.56	.20	.29	.64	.71	.62	.70	.76	.88	.94	.91		.635	.122	.052	.034	.558	.000	.450
13. Age	−.02	.02	−.06	−.01	.03	.01	−.03	−.01	−.05	−.03	.00	−.03		.445	.551	.818	.263	.179	.587
14. Gender^a	.03	.14	−.15	.09	.00	.01	−.09	.00	−.07	−.06	.02	−.09	.04		.115	.244	.000	.948	.062
15. Nationality^b	−.01	.02	.15	.05	−.10	−.01	−.17	−.02	−.09	−.09	−.08	−.11	−.03	.09		.000	.000	.325	.008
16. Ethnicity^c	−.10	−.01	.02	−.01	.01	−.11	−.10	−.05	−.02	−.12	−.18	−.12	−.01	−.01	.40		.023	.001	.295
17. Marital status^d	.10	−.11	−.11	.08	.09	.09	−.01	.01	−.07	.05	.10	.03	.06	.27	.25	.13		.920	.184
18. Religion^e	−.23	.10	−.09	−.06	−.24	−.27	−.12	−.15	−.16	−.22	−.32	−.26	.08	−.01	.06	.18	.01		.239
19. Occupation status^f	.03	.01	.03	−.02	.06	.10	.02	.04	0.04	.08	.01	.04	.03	−.11	−.15	−.06	.08	−.07
Mean	2.28	3.01	2.42	3.34	3.99	3.66	3.49	3.32	3.26	3.34	3.45	3.35	36.07	0.73	0.20	0.17	0.47	0.71	0.83
Standard deviation	0.65	0.85	0.88	0.98	0.80	0.89	1.01	0.65	0.67	0.77	0.83	0.69	7.65	0.44	0.40	0.38	0.50	0.45	0.38
Range	0.67–4	1–5	1–4.6	1–5	1–5	1–5	1–5	1.22–4.61	1.57–5	1–5	1–5	1.46–5	23–62	0–1	0–1	0–1	0–1	0–1	0–1
Skewness	0.15	0.22	0.48	−0.28	−1.07	−1.08	−0.62	−0.71	0.05	−0.58	−0.64	−0.42	0.79	−1.05	1.49	1.74	0.12	−0.94	−1.74
Kurtosis	0.45	0.02	−0.76	−0.56	1.94	1.13	0.16	0.68	−0.09	0.55	0.51	0.50	0.52	−0.91	0.23	1.02	−1.99	−1.13	1.02
α	.73	.70	.73	.84	.85	.88	.94	.90	.80	.94	.87	.95

The values present below the diagonal are Pearson’s correlations and the values present above the diagonal are p-value (two-tailed).

Bolded values are significant.

DO = Dispositional optimism, MSC = Mindful self-care, SWB = Subjective well-being.

α= Cronbach’s alpha for the study variables.

^aGender was coded as 0 = Male, 1= Female.

^bNationality was coded as 0 = Singaporean, 1= Permanent resident.

^cEthnicity was coded as 0= Chinese, 1 = Non-Chinese.

^dMarital status was coded as 0= Not married, 1 = Married.

^eReligion was coded as 0 = Atheist, 1= Religious.

^fOccupational status was coded as 0 = Not working, 1 = Working.

Analyses of correlations between sociodemographic variables and the study variables yielded the following findings. Females reported lower levels of physical care, but higher levels of mindful relaxation compared to males. Singaporean participants reported lower physical care, but higher mindful awareness compared to permanent residents. Chinese participants reported higher supportive structure, psychological well-being, relationship well-being, and overall SWB compared to non-Chinese participants. Married participants reported lower mindful relaxation compared to unmarried counterparts. Religious participants reported lower levels of DO, MSC, and SWB, along with their subscales (supportive relationships, supportive structure, mindful awareness, physical health, psychological well-being, and relationship well-being) compared to atheists. Age and occupation status did not exhibit significant correlations with any of the main study variables. Based on the observed correlations, only sociodemographic variables that displayed statistically significant associations with the main study variables were included as covariates in the subsequent mediation models.

Mediation Analysis

Simple Mediation Model (SWB as an Outcome Variable)

A simple mediation model was first tested (see Table 3) to examine whether MSC mediates the relationship between DO (independent variable) and SWB (dependent variable). Ethnicity and religion were included as covariates in the analysis due to their significant correlations with the study variables in the bivariate analyses. Multicollinearity was assessed to ensure the independence of predictor variables. Variance inflation factor (VIF) values were all below 1.27, and tolerance values were all above 0.79, indicating no significant multicollinearity according to Myers (1990). Additionally, standardized residuals fell within an acceptable range (−2.99 to 2.39).

Table 3.

Mediation by Mindful Self-Care in the Dispositional Optimism-Subjective Well-Being Association.

Predictor	SWB (total effect)					MSC (direct effect)					SWB (direct effect)
Predictor	B	SE	t	p	95% CI	B	SE	t	p	95% CI	B	SE	t	p	95% CI
DO	.56	.05	10.83	.000	.45, .66	.46	.05	8.72	.000	.35, .56	.25	.04	5.97	.000	.17, .33
Ethnicity	−.08	.09	−0.89	.372	−.25, .09	.01	.09	0.14	.888	−.16, .19	−.09	.06	−1.35	.178	−.21, .04
Religion	−.21	.07	−2.87	.004	−.36, −.07	−.07	.08	−0.98	.330	−.22, .08	−.16	.05	−2.99	.003	−.27, −.06
	F (3, 308) = 50.59, p = .000; R² = .33					F (3, 308) = 28.43, p = .000; R² = .22
MSC											.66	.04	16.27	.000	.58, .75
											F (4, 307) = 136.65, p = .000; R² = .64

DO = Dispositional optimism, MSC = Mindful self-care, SWB = Subjective well-being.

The total effect of DO on SWB (path c) was significant (B = .56, 95% CI [.45, .66]). After controlling for the mediating effect of MSC, the direct effect of DO on SWB (path c’) became partially attenuated (B = .25, 95% CI [.17, .33]). The path coefficient for the effect of DO on MSC (path a) was significant (B = .46, 95% CI [.35, .56]). The path coefficient for the effect of MSC on SWB (path b) was also significant (B = .66, 95% CI [.58, .75]). Bootstrapping analysis confirmed a significant indirect effect of DO on SWB through MSC (indirect effect = .30, BootSE = .04, 95% CI [.23, .39]). This indirect effect accounted for 53.6% of the total effect of DO on SWB, highlighting the mediating role of MSC.

Simple Mediation Model (Individual SWB Subcomponents as the Outcome Variables)

Given that SWB is comprised of three subcomponents (physical health, psychological well-being, and relationships), separate mediation analyses were conducted using each subcomponent as the outcome variable. The results for each SWB subcomponent mirrored the findings for total SWB. All path coefficients and indirect effects were significant, suggesting that MSC significantly mediates the association between DO and all three SWB subcomponents (Physical Health: indirect effect = .33, BootSE = .04, 95% CI [.26, .41]; Psychological Well-Being: indirect effect = .29, BootSE = .04, 95% CI [.21, .38]; Relationships: indirect effect = .29, BootSE = .05, 95% CI [ .20, .39]). Overall, these mediation analyses provide strong evidence that MSC plays a significant mediating role in the relationship between DO and SWB. Results can be found in Table 4.

Table 4.

Mediation by Mindful Self-Care in the Dispositional Optimism -Subjective Well-Being Subcomponents Association.

Predictor	Physical health (total effect)					MSC (direct effect)					Physical health (direct effect)
Predictor	B	SE	t	p	95% CI	B	SE	t	p	95% CI	B	SE	t	p	95% CI
DO	.48	.05	8.89	.000	.37, .58	.46	.05	8.72	.000	.35, .56	.15	.04	3.45	.001	.06, .23
Ethnicity	.07	.09	0.82	.414	−.10, .25	.01	.09	0.14	.888	−.16, .19	.07	.06	1.01	.311	−.06, .19
Religion	−.10	.08	−1.26	.209	−.25, .06	−.07	.08	−0.98	.330	−.22, .08	−.04	.06	−0.80	.422	−.15, .06
	F (3, 308) = 29.84, p = .000; R² = .23					F (3, 308) = 28.43, p = .000; R² = .22
MSC											.72	.04	17.51	.000	.64, .81
											F (4, 307) = 121.25, p = .000; R² = .61

Predictor	Psychological well-being (total effect)					MSC (direct effect)					Psychological well-being (direct effect)
Predictor	B	SE	t	p	95% CI	B	SE	t	p	95% CI	B	SE	t	p	95% CI
DO	.67	.06	11.97	.000	.56, .79	.46	.05	8.72	.000	.35, .56	.39	.05	7.56	.000	.29, .49
Ethnicity	−.09	.10	−0.97	.331	−.28, .10	.01	.09	0.14	.888	−.16, .19	−.10	.08	−1.31	.192	−.25, .05
Religion	−.15	.08	−1.87	.063	−.31, .01	−.07	.08	−0.98	.330	−.22, .08	−.11	.07	−1.60	.112	−.23, .02
	F (3, 308) = 56.80, p = .000; R² = .36					F (3, 308) = 28.43, p = .000; R² = .22
MSC											.63	.05	12.79	.000	.54, .73
											F (4, 307) = 106.01, p = .000; R² = .58

Predictor	Relationships (total effect)					MSC (direct effect)					Relationships (direct effect)
Predictor	B	SE	t	p	95% CI	B	SE	t	p	95% CI	B	SE	t	p	95% CI
DO	.51	0.07	7.92	.000	.39, .64	.46	.05	8.72	.000	.35, .56	.22	.06	3.56	.000	.10, .34
Ethnicity	−.21	0.11	−1.95	.052	−.43, .01	.01	.09	0.14	.888	−.16, .19	−.22	.09	−2.36	.019	−.41, −.04
Religion	−.39	0.09	−4.14	.000	−.57, −.20	−.07	.08	−0.98	.330	−.22, .08	−.34	.08	−4.23	.000	−.50, −.18
	F (3, 308) = 36.99, p = .000; R² = .27					F (3, 308) = 28.43, p = .000; R² = .22
MSC											.64	.06	10.57	.000	.52, .76
											F (4, 307) = 65.61, p = .000; R² = .46

DO = Dispositional optimism, MSC = Mindful self-care.

Specificity of MSC Facets as Mediators

To explore the specific mediating roles of the six MSC facets (mindful relaxation, physical care, self-compassion & purpose, supportive relationships, supportive structure, and mindful awareness), a parallel multiple mediation analysis was conducted as a post-hoc analysis. All six facets were included simultaneously as mediators in the model, while controlling for gender, nationality, ethnicity, marital status, and religion. The total effect of DO on SWB was significant (B = .56, 95% CI [.46, .66]), and remained significant when the mediators were present (B = .27, 95% CI [.20, .35]). The total indirect effect of DO on SWB through all six MSC facets was also significant, with a point estimate of .29 (BootSE = .04, 95% CI [ .21, .36]. This suggests an overall mediation effect for facets of MSC within the association between DO and SWB. A closer look at the specific indirect effect for each mediator revealed that self-compassion and purpose (indirect effect = .09, BootSE = .02, 95% CI [.06, .13]), supportive relationship (indirect effect = .10, BootSE = .02, 95% CI [.05, .15]), and mindful awareness (indirect effect = .11, BootSE = .03, 95% CI [.05, .16]) emerged as significant individual mediators. However, mindful relaxation (indirect effect = −.04, BootSE = .02, 95% CI [-.08, .02]), physical care (indirect effect = .01, BootSE = .01, 95% CI [-.01, .04]), and supportive structure (indirect effect = .02, BootSE = .02, 95% CI [-.02, .05]) did not exhibit indirect effects on SWB. These findings suggest that specific facets of MSC, particularly self-compassion and purpose, supportive relationships, and mindful awareness, partially mediate the positive association between DO and SWB. In contrast, mindful relaxation, physical care, and supportive structure appear to play a less prominent role in this mediation process. Detailed results are presented in Table 5.

Table 5.

Mediation Effect of Six Mindful Self-Care Facets.

Predictor	SWB (total effect)					MR (direct effect)					SWB (direct effect)
Predictor	B	SE	t	p	95% CI	B	SE	t	p	95% CI	B	SE	t	p	95% CI
DO	.56	.05	10.89	.000	.46, .66	.47	.07	6.63	.000	.33, .61	.27	.04	7.22	.000	.20, .35
Gender	−.16	.08	−2.14	.033	−.31, −.01	.36	.10	3.46	.001	.16, .56	−.11	.05	−2.17	.031	−.21, −.01
Nationality	−.16	.09	−1.82	.070	−.33, .01	.06	.12	0.53	.599	−.18, .31	−.04	.06	−0.64	.524	−.16, .08
Ethnicity	−.03	.09	−0.31	.757	−.22, .16	.06	.13	0.45	.654	−.20, .32	−.10	.06	−1.67	.096	−.22, .02
MS	.05	.07	0.76	.448	−.08, .19	−.36	.09	−3.75	.000	−.54, −.17	−.02	.05	−0.49	.623	−.11, .07
Religion	−0.21	0.07	−2.89	.004	−.36, −.07	.33	.10	3.28	.001	.13, .53	−.07	.05	−1.32	.188	−.16, .03
	F (6, 305) = 27.18, p = .000; R² = .35					F (6, 305) = 10.80, p = .000; R² = .18

						PC (direct effect)
DO						.26	.08	3.41	.001	.11, .41
Gender						−.27	.11	−2.43	.016	−.49, −.05
Nationality						.47	.13	3.51	.001	.20, .73
Ethnicity						−.07	.14	−0.52	.604	−.35, .20
MS						−.24	.10	−2.32	.021	−.44, −.04
Religion						−.09	.11	−0.87	.386	−.31, .12
						F (6, 305) = 6.06, p = .000; R² = .11

						SCP (direct effect)
DO						.58	.08	7.01	.000	.42, .75
Gender						.16	.12	1.34	.181	−.08, .40
Nationality						.09	.15	0.63	.528	−.19, .38
Ethnicity						.04	.15	0.25	.804	−.26, .34
MS						.02	.11	0.16	.874	−.20, .23
Religion						.05	.12	0.38	.706	−.19, .28
						F (6, 305) = 9.15, p = .000; R² = .15

						SR (direct effect)
DO						.32	.07	4.74	.000	.19, .46
Gender						−.01	.10	−0.13	.898	−.21, .18
Nationality						−.31	.12	−2.59	.010	−.53, −.07
Ethnicity						.25	.13	1.99	.047	.01, .50
MS						.14	.09	1.58	.115	−.04, .32
Religion						−.34	.10	−3.48	.001	−.53, −.15
						F (6, 305) = 8.74, p = .000; R² = .15

						SS (direct effect)
DO						.43	.07	5.79	.000	.28, .57
Gender						−.05	.11	−0.50	.616	−.27, .16
Nationality						.04	.13	0.33	.743	−.21, .30
Ethnicity						−.15	.14	−1.12	.263	−.42, .12
MS						.13	.10	1.28	.200	−.07, .32
Religion						−.37	.11	−3.45	.001	−.57, −.16
						F (6, 305) = 10.94, p = .000; R² = .18

						MA (direct effect)
DO						.71	.08	8.91	.000	.56, .87
Gender						−.18	.12	−1.56	.119	−.42, .05
Nationality						−.43	.14	−3.08	.002	−.70, −.15
Ethnicity						.04	.15	0.26	.796	−.25, .33
MS						.01	.11	0.10	.921	−.20, .22
Religion						−.02	.11	−0.16	.870	−.24, .20
						F (6, 305) = 16.59, p = .000; R² = .25

MR											−.09	.03	−1.88	.070	−.15, .04
PC											.04	.03	1.73	.086	−.01, .10
SCP											.16	.03	5.69	.000	.10, .22
SR											.30	.04	7.50	.000	.22, .38
SS											.04	.05	0.79	.432	−.05, .13
MA											.15	.03	4.61	.000	.09, .22
											F (12, 299) = 74.05, p = .000; R² = .75

MS = Marital status, DO = Dispositional optimism, SWB = Subjective well-being, MR = Mindful Relaxation, PC = Physical Care, SCP = Self-Compassion and Purpose, SR = Supportive Relationships, SS = Supportive Structure, MA = Mindful awareness.

Discussion

The growing field of positive psychology focuses on identifying factors that contribute to optimal functioning and well-being (Diener et al., 2018; Malouff & Schutte, 2017; Peterson & Seligman, 2004). Dispositional optimism (DO), a core positive personality trait, has received significant research attention. Numerous studies have established a positive association between DO and subjective well-being (SWB) (Carver et al., 2005; Gallagher & Lopez, 2009; Rozanski et al., 2019). However, the underlying mechanisms explaining how DO influences SWB remain less explored. This study investigated whether mindful self-care (MSC) mediates the relationship between DO and SWB in adults. As hypothesized, a simple mediation model revealed partial mediation by MSC. Individuals with higher DO reported higher levels of MSC, which in turn, were associated with greater SWB. Examining three SWB subcomponents (i.e., physical health, psychological well-being, and relationships) as outcome variables separately revealed that DO remained a significant predictor and MSC remained a significant mediator for each SWB subcomponent. As a post-hoc analysis, a parallel mediation analysis was performed to explore the specific mediating roles of the six MSC facets. The results indicated that three facets—self-compassion & purpose, supportive relationships, and mindful awareness—emerged as significant mediators in the DO-SWB association. In contrast, mindful relaxation, physical care, and supportive structure did not exhibit significant mediating effects.

The positive association between DO and SWB can be explained by the optimistic characteristics of individuals with high DO. Optimists tend to hold more positive appraisals, focus on future positive information, manage stress more effectively, and exhibit higher goal orientation, ultimately increasing their likelihood of success (Malouff & Schutte, 2017; Scheier et al., 1994). This aligns with existing literature, including longitudinal evidence supporting the predictive role of DO in promoting SWB (Daukantaitė & Zukauskiene, 2012; Scheier & Carver, 2018). The observed positive association between DO and MSC aligns with findings demonstrating a positive correlation between these variables in both patient and general population (Butler et al., 2019; Fournier et al., 2002; Luciani et al., 2022; Martínez et al., 2021; Vos et al., 2021).

Developing an optimistic perspective serves as a strong motivator for individuals to adopt a proactive approach to life (Carver & Scheier, 2014). This notion is further supported by research highlighting the positive association between DO and health-promoting behaviors (Boehm et al., 2018; Carver et al., 2005; Rozanski et al., 2019; Yue et al., 2022), behaviors that conceptually align with facets of MSC like mindful relaxation and physical care. Finally, the positive association between MSC and SWB is consistent with prior research documenting the positive effects of mindfulness and self-care on well-being (Aldahadha, 2023; Torres-Soto, 2022). High MSC may enhance SWB by increasing cognitive reactivity to widen the individual’s behavioural repertoire of responses to a variety of situations (Shapiro et al., 2006). The success of mindfulness and self-care interventions in promoting greater SWB further supports this explanation (Chatterjee & Jethwani, 2020). Taken together, all the significant pathways confirmed a significant positive indirect effect from DO to SWB through high MSC. Over half of the total effect of DO on SWB was transmitted through this indirect pathway. Individuals with higher DO reported higher levels of MSC, which in turn, were associated with greater SWB. The findings from another three simple mediation models suggested that association between DO and the three subcomponents of SWB were consistent, even after controlling MSC as a mediator, reinforcing the protective role of DO and MSC on SWB (Shrout & Bolger, 2002).

A parallel mediation model examining all six facets of MSC as simultaneous mediators revealed that self-compassion & purpose, supportive relationships, and mindful awareness emerged as significant in the relationship between DO and SWB. These findings align with prior research demonstrating stronger associations between these specific facets and measures of well-being (Chew & Ang, 2023; Feeney & Collins, 2015; Garland et al., 2015). Our findings may shed light that self-compassion and purpose, supportive relationships, and mindful awareness may be more frequently employed well-being enhancement strategies. While the non-significant results for the remaining three facets (physical care, mindful relaxation, and supportive structure) were unexpected, two explanations are possible for this null result. As previously described, the six MSC facets can be categorized into three higher-order domains: nurturing the internal self (including physical care and self-compassion & purpose), nurturing the external self (including supportive relationships and supportive structure), and integrating practices (including mindful awareness and mindful relaxation) (Cook-Cottone & Guyker, 2018). It is interesting to observe that the facets emerging as significant mediators (self-compassion & purpose, supportive relationships, and mindful awareness) exhibited stronger bivariate correlations with SWB compared to the non-significant mediators (physical care, mindful relaxation, and supportive structure) within their respective domains (see Table 2). Stronger bivariate correlations between a mediator and SWB may translate into higher path coefficients (Myers, 1990), indicating a more substantial influence on well-being. This could explain why some facets emerged as significant, potentially “overtaking” the influence of other facets within the same domain that had weaker correlations with SWB. Additionally, Second, including all six MSC facets in the mediation model might have inflated the risk of biased results. When multiple mediators are considered within a single model, the influence of any one mediator can become obscured, even if it has a genuine association with the outcome variable. This is particularly true when the mediators themselves affect one another (VanderWeele & Vansteelandt, 2014).

Although facet-level analysis offers practical appeal for researchers and healthcare professionals, analyzing highly correlated facets (see Table 2) can compromise statistical robustness due to violations of statistical assumptions (Myers, 1990). Therefore, the current findings suggest that considering MSC and SWB as umbrella terms encompassing various dimensions or types might be more statistically appropriate. Future research could explore treating MSC and SWB as latent variables in Structural Equation Modeling, with subcomponents or facets serving as indicators (VanderWeele & Vansteelandt, 2014). Nevertheless, the parallel mediation model’s findings partially concur with previous research, supporting MSC as a potent mediator. This is evident as all three underlying MSC domains still functioned as partial mediators (Cook-Cottone & Guyker, 2018), despite not all individual facets achieving significance.

While the primary focus was on the mediating role of MSC in the relationship between DO and SWB, our analysis revealed statistically significant, albeit minor, effects of select sociodemographic variables. This aligns with previous research suggesting demographics have a marginal influence on well-being (Diener et al., 1999; Salameh et al., 2022). Religion emerged as the most impactful demographic factor. Our study found a surprising result: religiosity was associated with lower scores on DO, MSC, and SWB. This contradicts previous findings, although the research by González-Rivera et al. (2019) might offer a potential explanation. According to González-Rivera et al. (2019), it’s important to emphasize that religion is just one path to a meaningful and fulfilling life. Atheists, for example, may find meaning through other avenues such as living in the present, cherishing loved ones, pursuing goals, or contributing to a worthy cause – all without relying on divine intervention. Furthermore, our study measured religion with a single survey item, simply asking participants if they identified with a religion. This limited scope doesn’t capture the nuances of religious engagement. Research by Michaels et al. (2022) demonstrated that a sense of belonging to a community, religious or otherwise, is a significant factor in subjective happiness. In other words, it appears that social connection and shared values, rather than religious belief alone, may contribute more to well-being. Future research should explore religion using a more comprehensive measure that captures not only belief but also the depth of participants’ religious engagement and practices. This would provide a richer picture of the relationship between religion and well-being. Ethnicity also influenced SWB. Notably, Chinese participants reported higher SWB compared to non-Chinese counterparts. This is particularly interesting considering Singapore’s demographics, where the Chinese ethnicity is the overwhelming majority (∼75%). Prior studies often report lower well-being in racial/ethnic minorities (Stopforth et al., 2023), likely due to structural racism and inequalities (e.g., economic disparities, limited opportunities). Our findings highlight the importance of considering ethnicity in well-being research. Future investigations could delve deeper by examining how ethnicity interacts with other variables, such as religion, to influence SWB.

In a similar vein, our analysis revealed significant correlations between mindful self-care or its facets and five out of seven demographic variables: gender, nationality, ethnicity, marital status, and religion. This suggests a potential influence of sociodemographic factors on mindful self-care levels. Investigating these variables as moderators could be highly valuable. Identifying how sociodemographic characteristics moderate the relationship between mindful self-care and well-being would allow for the development of more targeted mindfulness or self-care interventions for the general population. This, in turn, could significantly enhance the effectiveness of future interventions.

As with any scientific endeavor, this study has limitations that we acknowledge and detail below. The cross-sectional design inherently limits the ability to establish causal relationships due to its observational nature and potential for reverse causality (e.g., increased MSC leading to higher DO). Prospective studies are necessary to clarify causal direction. Convenience sampling may introduce selection bias, limiting generalizability. While attempts were made to mitigate this by using diverse recruitment channels, future studies could benefit from employing more robust sampling strategies. Additionally, other potentially influential sociodemographic factors (e.g., education, income, and living arrangements) were not considered in the current investigation. While some explored sociodemographic variables (e.g., religion, ethnicity) might emerge as potential mediators based on variable correlations, prior research to support a moderated mediation model was lacking, and their influence was not explored. Future research could utilize more complex models incorporating these variables. Finally, self-reported measures introduce potential bias. Future studies could explore alternative data collection methods, such as text analysis for optimism assessment and digital sensing for objective self-care measurement.

Nevertheless, this study is novel in its joint examination of DO and MSC in relation to SWB. By exploring them together, we bridge separate bodies of literature on these individual relationships. Our findings suggest that the link between personality and well-being might not be entirely direct but mediated by MSC, which aims to elevate well-being in adults. These findings contribute to the broader SWB literature by offering insights into “why” or “how” personality, specifically DO, influences SWB, as opposed to simply understanding “what” personality explains about SWB. Some theoretical and practical implications can be derived from our results. While DO is a relatively stable construct, it is considered more malleable than basic personality dispositions (Uribe et al., 2021). A meta-analysis by Malouff and Schutte (2017) reviewed 29 studies and concluded that psychological interventions can increase DO, with the strongest effect achieved through the Best Possible Self method. Therefore, DO should be a focus of interventions given its potential for enhancement. This emphasis is relevant in two ways. First, if optimistic beliefs about the future feed into broader personality traits and can be changed, they contribute to personality malleability. Second, this possibility increases the potential for improving SWB levels associated with the personality profile through well-being enhancing strategies like MSC.

Conclusion

This study expands on existing knowledge by demonstrating a positive association between DO and SWB and critically, by elucidating the potential mechanism of MSC. Notably, MSC has been largely overlooked in previous research exploring the mediating processes between personality traits and well-being. Our mediation analysis supports the hypothesis that specific MSC facets, particularly self-compassion & purpose, supportive relationships, and mindful awareness, partially explain the beneficial effects of DO on SWB. Future research employing longitudinal designs is recommended to establish causal relationships between the study variables and their impact on SWB over time.

Footnotes

Author Contributions

The author contributed to the design and implementation of the research, to the analysis of the results, and the writing of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

ORCID iD

Chin-Siang Ang

Data Availability Statement

The data supporting this study's findings are available from the corresponding author upon reasonable request.

Author Biography

Chin-Siang Ang is a senior research fellow at the Centre of Population Health Sciences, LKC School of Medicine, Nanyang Technological University, Singapore. His research interests include psychology of well-being and cyberpsychology.

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