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Current Issues in Personality Psychology
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Original paper

Examining the impact of mindfulness and self-compassion on the relationship between mental health and resiliency

Fajar Rizal
1
,
Helen Egan
1
,
Amy Cook
1
,
Rebecca Keyte
1
,
Michail Mantzios
1

1.
Birmingham City University, Birmingham, United Kingdom
Current Issues in Personality Psychology, 8(4), 279–288
Online publish date: 2020/11/09
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BACKGROUND

Research has shown that stressful environments can increase the chances of individuals developing de-creased job satisfaction, depression and other problems including physical injury, anxiety or other mood dis-orders (Greenberg, Jones, Jones, Fear, & Wessely, 2011). This can harm an individual’s cognitive functioning and may contribute to poorer behaviours (e.g., substance abuse, family dysfunction, marital problems, social isolation, and in extreme cases, suicide or suicide attempts; Iversen et al., 2008). Indeed, in such cases being resilient is key to overcoming barriers to ill mental health and improving overall wellbeing. Early definitions for resilience first arise in physics and engineering, where it defines the ability for a material to “bounce back” to its original form when unloading the application of extensive energy without creating a permanent distor-tion (Wied, Oehmen, & Welo, 2019). This definition also has application to psychology regarding to the abil-ity to “bounce back” when individuals are faced with disappointments, defeats, and failures, and instead of wallowing or letting things keep them down, individuals tend to get back up and continue on with their lives (Smith, Tooley, Christopher, & Kay, 2010). Some research exists between ill mental health and resiliency, but has focused on specific populations such as spinal injury, health professionals and students (e.g., Hayter & Dorstyn, 2014; Kemper, Mo, & Khayat, 2015; McArthur et al., 2017; Pidgeon & Keye, 2014). Both self-compassion and mindfulness are important concepts for resiliency, with little being known about these rela-tionships through general population studies in the United Kingdom.
According to Ruiz-Casares, Guzder, Rousseau, and Kirmayer (2014), resilience can be described both as a trait and a dynamic process of development, involving social interactions and compensatory behaviours over the lifespan. Eggerman and Panter-Brick (2010) carried out a study on health-related issues and resilien-cy in war-affected areas. Their research aimed to identify how an individual makes sense of adversity and why they show resilience in a high-risk environment. They reported that these individuals possess resilience through the belief that adversity can be overcome by adhering to cultural values (e.g., religion, family unity, morals, and daily perseverance). Research by Shrivastava, De Sousa, Sonavane, and Shah (2016) led to hy-pothesising and verifying that an individual’s resilience may be linked between positive cognition and the outcome of mental wellbeing.
There is a general consensus that mental health illnesses such as depression, anxiety, and stress im-pact upon individuals (e.g., Bolton, 2009). Understanding mental health issues efficiently can enable an indi-vidual to cope with adversity, reach their full potential and achieve optimal levels of wellbeing. Research has consistently demonstrated that individuals with mental health issues experience an increase of occupational absenteeism, with a resulting negative impact on productivity and profits (Bender & Farvolden, 2008; Rajgopal, 2010). Depression is a common and debilitating mental health disorder that negatively affects how individuals feel, think and behave. This can further cause feelings of sadness and/or a loss of interest in activ-ities that were once enjoyed, leading to a variety of emotional and physical problems and a decrease in an individuals’ ability to function at work and/or at home (APA, 2013; McLaughlin, 2011).
According to Bittner et al. (2004), anxiety is an emotion characterized by feelings of tension, worried thoughts and physical changes (such as increased blood pressure). People with anxiety disorders often have recurring intrusive thoughts or concerns that can result in avoiding certain situations out of worry and may have physical symptoms (e.g., sweating, trembling, dizziness or rapid heartbeat) (APA, 2013; Bystritsky, Khalsa, Cameron, & Schiffman, 2013). Research has also identified that anxiety can result in behaviours such as worry and impulsivity. Characteristics such as impulse control (i.e., gambling, self-harming), mood disor-ders and anxiety disorders can be the resulting effects of altering an individual’s behaviour (Schaefer, Esposi-to-Smythers, & Riskind, 2012; Mantzios, 2014; Jakuszkowiak-Wojten, Landowski, Wiglusz, & Cubała, 2015).
Similarly, stress is another significant contributor that can negatively affect an individual’s well-being. People have different coping abilities to deal with demands and experiences, which may be deemed to be more stressful to some. For instance, deadlines, work-related pressure (such as upholding good service) and complex problem solving can cause higher levels of anxiety and stress amongst individuals (Brand, Nakkas, & Annen, 2016). Overall, the literature indictates that mental health issues can contribute negatively in sever-al ways throughout the lifespan, and public health incentives are a long way from influencing the current way mental health is identified and treated (see Mantzios, 2020; Mantzios, Egan, & Cook, 2019a, b). Problems such as increased absenteeism, impulsive behaviours, emotional and physical issues at work and home, as out-comes of mental illness, highlight the need for interventions to provide resolutions for poor mental health, and often interventions are proposed though increasing resiliency.
Research has considered such possible tools to enhance mental health through resiliency to be mind-fulness and self-compassion. The trait of mindfulness has been described as fostering greater attention to and awareness of present-moment experiences (Creswell, 2017). Mindfulness assists in improving mental health, where research showed that higher levels of mindfulness assist with mental illness (Baer, Lykins, & Peters, 2012). Kabat-Zinn (2003) described the practice of mindfulness as being attentive to the present moment and non-judgemental with oneself. Past research, indeed, demonstrated that individuals with higher scores in mindfulness are more likely to experience lower levels of depression and anxiety, further suggesting that in-dividuals can successfully regulate emotions and positive cognition, as mindfulness can be a proactive tool for fostering health and subjective wellbeing for individuals (Allen, Henderson, Mancini, & French, 2017; Dutt, Keyte, Egan, Hussain, & Mantzios, 2019; Gu, Strauss, Bond, & Cavanagh, 2015; Ilies, Egan, & Mantzios, 2019; Mantzios, Wilson, Linnell, & Morris, 2014). Conversely, being less mindful can induce behavioural symptoms such as low motivation, which in turn may lead to depression or anxiety (Keng, Smoski, & Robins, 2011). Stress and anxiety may make an individual move away from the present moment and result in repeti-tive patterns of negative thinking, which may develop to a more severe form of mental illness (Mantzios & Wilson, 2013). The nature of an individual’s day-to-day life can be typically overwhelming, thus extinguish-ing any ability to be mindful, but reinstating mindful living through practice may form a method of optimal wellbeing.
Similarly, Neff (2003) defines self-compassion as an experience of one’s own suffering such as per-ceived inadequacy, failures or general suffering, through three main components including: self-kindness (be-ing sympathetic to oneself when experiencing pain and personal failings, rather than ignoring them or hurting oneself with self-criticism), common humanity (recognising that failures and sufferings are part of a shared common human experience) and mindfulness (observing negative thoughts and emotions as they are without trying to suppress or deny them). Moreover, self-compassion associates negatively with self-criticism, which has been found to positively relate to symptoms such as depression and anxiety, and impact life satisfaction and social connectedness (e.g., LoParo, Mack, Patterson, Negi, & Kaslow, 2018). To enhance mental health and resiliency, individuals need to identify failures and realise that poor mental health may need a compassionate reflection that is balanced between physical and mental expressions of self-care (Ali, Wong, Egan, Cook, & Mantzios, 2017; Egan et al., 2019; Egan & Mantzios, 2018; Mantzios & Egan, 2017; Mantzios & Giannou, 2018). Leary, Tate, Adams, Batts-Allen, and Hancock (2007) stated that self-compassion is the ability to be compassionate to oneself, and without this ability, individuals will lack the skills to tolerate stressful envi-ronments (such as work or family stressors). On the other hand, mindfulness can be a tool to help individuals with and without personal self-reflections of suffering to understand, tolerate, and deal with their emotions in a healthy way (Donald, Atkins, Parker, Christie, & Ryan, 2016).
Recent research indicated that higher scores of self-compassion reduce the association of depressive symptoms (Zhang et al., 2019) and strong positive relationships to an individual’s cognitive and psychologi-cal well-being (Zessin, Dickhäuser, & Garbade, 2015). Along with an improved quality of life for individuals, self-compassion has a direct effect on health-related factors, as well as an indirect relationship through resili-ence (Roulston, Montgomery, Campbell, & Davidson, 2017; Nery-Hurwit, Yun, & Ebbeck, 2018). Therefore, self-compassion is a vital aspect when exploring the benefits of mindfulness for mental health and resiliency by motivating individuals to physically, mentally or emotionally support themselves (Limebury & Shea, 2015). These findings appear to explain how an individual can better deal with stressors, where self-compassion can help to identify and accept negative aspects of one’s life, and improve an individual’s self-esteem (Kim & Ko, 2018; Mongrain, Chin, & Shapira, 2010).
The ever-changing environment experienced by individuals during everyday tasks is frequentlhy ad-verse and stressful, and the importance of placing interventions at the forefront to enhance resiliency and im-prove wellbeing is imperative. Being mindful and compassionate with oneself can have a positive impact on an individual’s wellbeing, physically and mentally (Horan & Taylor, 2018). Thus, incorporating mindfulness and compassion-based interventions may mitigate long-term mental health issues by understanding the indi-vidual’s ability to adapt to the environment (Wamsler, 2018). There is, however, a need for further evidence before suggesting interventions.
This work builds on the need to identify the intangible nature of resiliency. The purpose of this study was to examine whether mindfulness and self-compassion are mechanisms through which mental health (i.e., depression, anxiety and stress) influences resiliency. Hence, using mindfulness and self-compassion as po-tential mediating factors to mediate the relationship between resiliency and mental health was explored in the present research. The present study hypothesised that depression, anxiety and stress relate negatively to re-silience, and such a relationship is mediated through self-compassion and mindfulness.

PARTICIPANTS AND PROCEDURE

PARTICIPANTS

Five-hundred and fifty-one people responded to the call to take part in this research from the general commu-nity of West and East Midlands in England. Prior to analysis, the data were screened for outliers, normality and missing data. After deleting a sample with no or excessively missing data, 367 participants remained (121 males, 246 females) with a mean age of 24.32 (SD = 7.01). Participants were recruited through snowball sam-pling (Faugier & Sargeant, 1997) via online forums and social media group pages. Recruitment of participants was voluntary and did not involve any incentives. Cohen’s (1992) guidelines suggested that to achieve a medium effect size a minimum of 300 participants was required (Cohen, 1992).

MEASURES

Demographics questionnaire. Participants’ background information such as gender, age, and ethnicity, as well as previous and current diagnoses of ill mental health, was explored as a method of analysing the results on the basis of recruiting a healthy community population.
Depression, Anxiety, and Stress Scale (DASS; Lovibond & Lovibond, 1995). DASS consists of 21 items, designed to measure related negative emotional states. The depression scale assesses devaluation of life, self-deprecation and lack of interest or involvement. The anxiety scale assesses situational anxiety and subjective experience of anxious effects. The stress scale assesses difficulty in relaxing, nervous arousal, being easily upset or agitated, and impatient behaviours. Example items include the following: “I found it hard to wind down” measured stress; “I was aware of dryness of my mouth” measured anxiety and items such as “I couldn’t seem to experience any positive feeling at all” measured depression. The calculation scores were measured on a 4-point Likert scale which ranged from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time). The present study produced a Cronbach’s α of .86.
Self-Compassion Scale (SCS; Neff’s, 2003). SCS consists of 26 items designed to measure 6 bidirection-al elements of self-compassion including self-kindness (five items) vs. self-judgment (five items); common humanity (four items) vs. isolation (four items); mindfulness (four items) vs. over-identification (four items). Example items include the following: “I try to be loving towards myself when I’m feeling emotional pain” measures self-kindness; “I’m disapproving and judgmental about my own flaws and inadequacies” measures self-judgment; “When things are going badly for me, I see the difficulties as part of life that everyone goes through” measures common humanity. The calculation scores were measured on a 5-point Likert scale which ranged from 1 (almost never) to 5 (almost always). Negative subscale items including self-judgment, isolation, and over-identification were reverse scored (i.e., 1 = 5, 2 = 4, 3 = 3, 4 = 2, and 5 = 1). The present study produced a Cronbach’s α of .77.
Five Facet Mindful Questionnaire (FFMQ; Bohlmeijer, ten Klooster, Fledderus, Veehof, & Baer, 2011). The questionnaire tested five facets including non-reactivity to inner experiences, observing, act awareness, describing and non-judging of inner experiences. Example items include: “I’m good at finding the words to describe my feeling” and “I watch my feelings without getting carried away by them”, which measured non-reactivity and describe mindfulness, while items such as “I find myself doing things without paying attention” and “I disapprove of myself for illogical ideas” measured act awareness and non-judgemental components of mindfulness. The calculation scores consisted of responses measured on a 5-point Likert scale which ranged from 1 (never or very rarely true) to 5 (very often or always true). The present study produced a Cronbach’s α of .70.
10-item Connor-Davidson Resilience Scale (CD-RISC-10; Campbell-Sills & Stein, 2007). CD-RISC-10 il-lustrated Connor and Davidson’s (2003) 25-item CD-RISC that was based on Connor and Davidson’s opera-tional definition of resilience, which is the ability to thrive in the face of adversity. However, the original scale was rejected due to the extensive administration timescale. Example items include: “Able to adapt to change” and “Can deal with whatever comes”. The calculation scores consisted of responses measured on a 5-point Likert scale which ranged from 0 (never) to 4 (almost always). The present study produced a Cronbach’s α of .87.

PROCEDURE

Ethical approval was obtained from the ethical board within the university and this study followed ethical practices following the British Psychological Society. Participants were recruited using a hyperlink posted in forums and social media group pages. The general information sheet, consent form, and demographics were administered concurrently to all participants through Qualtrics. The participant signed the consent form by creating a unique candidate number which indicated anonymity and their voluntary participation. Participants began the research by answering the DASS, followed by FFMQ, and then SCS questionnaire, concluding with the CD-RISC-10. The debrief form indicated the end of the research.

STATISTICAL ANALYSIS

This study used a Pearson’s bivariate correlation to explore the relationships. Next, the relationship between wellbeing (through the overall score of the DASS) and resilience was explored by investigating the potential mediation of this relationship through mindfulness and self-compassion. The results were followed up by exploring mediations to examine the relationship between depression, anxiety and stress to resilience, and the potential mediation of this relationship through mindfulness and self-compassion. Mediation analyses were carried out using the PROCESS macro (Hayes, 2015) in SPSS version 24, with 5,000 bootstrapped samples and bias corrected 95% confidence intervals. Mediation analyses were run to assess the impact of mindfulness and self-compassion as mediators.
Following previous research further analysis on gender and age was conducted to identify statistically significant differences in emotion (e.g., Brummer, Stopa, & Bucks, 2013; Soysa & Wilcomb, 2015), self-compassion (e.g., Neff & Pommier, 2013; Yarnell et al., 2015), mindfulness (e.g., Lilja et al., 2011; Mahoney, Segal, & Coolidge, 2015), and resilience (e.g., Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003), but the results did not yield any significance.

RESULTS

Initially, a bivariate correlation was conducted, and the findings suggested a positive correlation between mindfulness, self-compassion and resiliency traits. These traits were negatively associated with stress, anxie-ty and depression (see Table 1).
The first mediational model predicted resiliency. The model analysed resiliency as the dependant var-iable, DASS as the independent variable, and mindfulness and self-compassion as potential mediators. Firstly, DASS predicting resiliency showed a significant direct effect (F(1, 365) = 65.18, p < .001, R2 = .20). Second, DASS predicting mindfulness showed a significant direct effect (F(1, 365) = 37.80, p < .001, R2 = .10) as well as self-compassion (F(1, 365) = 144.02, p < .001, R2 = .30). When DASS total, mindfulness and self-compassion were analysed to predict resiliency, the results indicated a significant direct effect (F(1, 365) = 70.98, p < .001, R2 = .38) (see Table 2).
The second mediation model predicted resiliency when controlling for depression. Firstly, depression predicting resiliency showed a significant direct effect (F(1, 365) = 62.04, p < .001, R2 = .18). Second, depres-sion predicting mindfulness showed a significant direct effect (F(1, 365) = 26.09, p < .001, R2 = .07) as well as self-compassion (F(1, 365) = 136.81, p < .001, R2 = .29). When depression, mindfulness and self-compassion were analysed to predict resiliency, the results indicated a significant direct effect (F(1, 365) = 66.23, p < .001, R2 = .37) (see Table 3).
The third mediation model predicts resiliency when controlling for stress. Firstly, stress predicting resiliency showed a significant direct effect (F(1, 365) = 44.00, p < .001, R2 = .14). Second, stress predicting mindfulness showed a significant direct effect (F(1, 365) = 32.07, p < .001, R2 = .08) as well as self-compassion (F(1, 365) = 134.48, p < .001, R2 = .30). When stress, mindfulness and self-compassion were ana-lysed to predict resiliency, the results indicated a significant direct effect (F(1, 365) = 60.88, p < .001, R2 = .34) (see Table 4).
The final mediation model predicts resiliency when controlling for anxiety. Firstly, stress predicting resiliency showed a significant direct effect (F(1, 365) = 57.35, p < .001, R2 = .17). Second, anxiety predicting mindfulness showed a significant direct effect (F(1, 365) = 34.78, p < .001, R2 = .09) as well as self-compassion (F(1, 365) = 82.62, p < .001, R2 = .17). When stress, mindfulness and self-compassion were ana-lysed to predict resiliency, the results indicated a significant direct effect (F(1, 365) = 78.87, p < .001, R2 = .40) (see Table 5).

DISCUSSION

The present study aimed to identify the relationship between mental health and resiliency and investigated whether or not mindfulness and self-compassion could mediate such relationships by controlling for their influence. Firstly, correlation analysis indicated that mental health correlated negatively with resiliency. This suggests that as mental health issues decreased, resiliency increased and vice versa. When the total DASS score was used, self-compassion and mindfulness mediated the relationship between mental health and resil-iency. Subscales also proposed that mindfulness and self-compassion were equally effective in mediating the relationship. The findings were consistent with previous research (see Mantzios, 2014; Färber & Rosendahl, 2018) suggesting that poor mental health can affect resiliency, and therefore overall wellbeing.
The present findings build on existing evidence of other research that looked into the benefit of mind-fulness and self-compassion (e.g., Baer et al., 2012; Brewer, 2014; Meland et al., 2015). It is fair to assume that identifying these psychological traits (i.e., mindfulness and self-compassion) as potentially enhancing mental health and resiliency may mediate further health behaviours (e.g., smoking, addiction and eating impulsively) (Egan, Mantzios, & Jackson, 2017; Egan & Mantzios, 2018). In addition, the findings supported research such as that by Mantzios (2014), who reported that mindfulness and self-compassion are useful strategies in deal-ing with behaviours such as worry and impulsivity, which are associated with anxiety and stress.
As discussed earlier, when the DASS subscale and total scores were analysed, self-compassion was a better mediator when compared to mindfulness. Such a finding could be explained in light of an individual’s experience to pay attention to themselves and have the cognitive ability to consider emotions focused on care-giving, kindness and loving oneself and to one’s well-being (Neff, 2003; Mantzios & Egan, 2017). This research further supports studies on the benefits of self-compassion and well-being. It has been identified that self-compassion can provide emotional benefits including a shift in perspectives, creativity and better overall health (Graham, 2016), which directly affect the outcome of resiliency in individuals in any given situation. Therefore, it is fair to assume that the perspective shift can improve resilience (even in adverse environ-ments) and improve productivity (e.g., Mantzios & Wilson, 2015).
There were a few notable limitations in the present research. First, the design of the research was cross-sectional; therefore, no firm conclusion could be drawn on the relational design between constructs. Findings for the use of mindfulness and compassion-based interventions need to be investigated further in experimental settings and/or longitudinal designs, to demonstrate credible changes in practice. Second, miss-ing data may be another limitation. Missing data may suggest that only motivated participants filled in the questionnaire, which may have implications for generalising the findings further. Despite these limitations, the results of this study may provide an initial insight into the relative relationships between mindfulness and self-compassion among an individual’s well-being and resilience and inform future research and practic-es. Third, the questionnaire was not randomised when presented to each participant so there was a potential exposure to order effect. Fourth, using the CD-RISC-10 scale suggests that the majority of the sample were re-silient, which may limit the generalisability of the data. Fifth, the attrition rate of the sample was high com-pared to other research, though normative data did not indicate any significant differences.
In conclusion, the current study suggests that mindfulness and self-compassion can positively influ-ence the relationship between mental health and resiliency. These findings also provide evidence that mind-fulness and self-compassion may be a useful intervention in supporting mental health. Further research is needed to corroborate these results and build controlled empirical studies that test the efficacy of mindful-ness and compassion-based intervention for shifting an individual’s perspective to be better equipped to an-ticipate and cope with everyday stressors.
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