Abstract
Meaning and purpose in life are related to a reduced risk of mortality and cardiovascular events, and meaning has been established as a correlate of physical activity. However, it is not clear what mechanisms account for the relationship between meaning and physical activity. A cross-sectional analysis (N = 94) indicated that self-efficacy in improving physical fitness is a statistically significant mediator of the relationship between meaning and physical activity.
Introduction
Physical activity (PA) is an important predictor of health outcomes, yet, only about one in five Americans maintain a desirable level of PA (Clarke et al., 2018). Presence of meaning in life (MIL) reflects individuals’ perceptions of the level of meaning and purpose in their lives (Steger et al., 2006). MIL is related to reduced risk of mortality and cardiovascular events (Cohen et al., 2016; Kim et al., 2013) and has been established as a correlate of PA (Holahan et al., 2008, 2011; Hooker and Masters, 2016, 2018; Roepke et al., 2014; Takkinen et al., 2001). However, it is not clear what mechanisms account for the relationships between MIL and PA and physical health (Hooker et al., 2018; Hooker and Masters, 2016, 2018).
Self-efficacy is the belief in one’s capabilities to carry out designated actions in pursuit of a target goal (Bandura, 1982). Cross-sectional and longitudinal studies demonstrate that those with greater MIL display enhanced self-efficacy to cope with stressful life events and recovery after a medical procedure (Miao et al., 2017; Sherman and Simonton, 2012; Shrira et al., 2015; Skrabski et al., 2005; Smith and Zautra, 2000). It is plausible that MIL fosters self-efficacy in the face of a wide array of challenges, including pursuing PA. Having MIL appears to enhance the perception that one’s life has an organized, controllable narrative (McCullough and Willoughby, 2009), which may then instill self-efficacy to pursue goals, especially if those goals are congruent with one’s sense of meaning. Stated differently, a belief in one’s own meaning and purpose may provide a stable, affirming foundation for pursuing desired goals that would otherwise seem insurmountable or overwhelming.
Bandura (1982) asserts that self-efficacy fosters effort as well as persistence during challenging tasks. Indeed, greater self-efficacy is linked to greater PA levels (Bauman et al., 2012; Blanchard et al., 2007; Darker et al., 2010; Teixeira et al., 2015). In other research, meaning predicted self-efficacy as well as self-esteem and optimism among breast and colorectal cancer populations (Lee et al., 2006). Furthermore, there is a link between meaning and self-control to predict self-rated health among older adults (Krause and Shaw, 2003). However, to date, no studies have explored the relationship between meaning and self-efficacy to predict PA. In this study, we hypothesize that meaning may be linked to PA, an important health behavior, through self-efficacy. The goal of this research was to evaluate whether self-efficacy statistically mediated the relationship between MIL and PA.
Method
Design
A cross-sectional design was employed.
Participants
Participants (N = 94; M age = 49, SD = 14.15; 72% female; 78% white, non-Hispanic) were selected from a larger sample (N = 427; M age = 49; 67% female; 78% white, non-Hispanic) of individuals recruited from an online Qualtrics survey research panel. Individuals were included in the larger sample if they were between 18 and 89 years of age and able to read English. For this study, only those participants who identified improving general physical fitness as their most important well-being goal, from a list of 13 well-being goals, were included.
Materials and procedure
The appropriate Institutional Review Board approved the study procedures. Data were collected using the Qualtrics online survey platform. Participants provided consent and completed a battery of questionnaires, which included demographics as well as the measures listed below.
MIL
The MIL presence scale includes four items from the Meaning in Life Questionnaire (Steger et al., 2006). Responses are captured on a Likert-type scale ranging from 1 (absolutely untrue) to 7 (absolutely true). The presence scale measures the sense that one’s life is meaningful (e.g. “My life has a clear sense of purpose”). Designated items are reverse scored, and responses are summed with scores ranging from 4 to 28, with higher scores indicating greater presence of meaning. The original scale includes five items; however, the fifth item was unintentionally omitted from the questionnaire. Nevertheless, the four-item MIL presence scale demonstrated good internal consistency in this sample (α = 0.89).
Self-efficacy in improving physical fitness
Self-efficacy was assessed with one item, “How confident are you in your ability to improve general physical fitness?” Responses range from 0 (no self-efficacy) to 10 (total self-efficacy).
International Physical Activity Questionnaire–Short Form
The International Physical Activity Questionnaire–Short Form (IPAQ-SF; Craig et al., 2003) is a seven-item self-report assessment of time spent in days or hours or minutes being physically active in the last 7 days and includes items such as “During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, digging, aerobics, or fast bicycling?” For this study, we calculated metabolic equivalent of task (MET) minutes of PA for each participant by assessing MET level × minutes of activity × events per week (Craig et al., 2003). The IPAQ-SF has been shown to correlate with accelerometer assessments of PA over a 7-day period (r = 0.26–0.47; Craig et al., 2003).
Statistical analysis
Descriptive statistics were calculated in SPSS version 24 and mediation analyses were conducted using Mplus 7.3 software controlling for gender, age, body mass index (BMI), race, ethnicity, education, income, and marital status. PA data were positively skewed and were transformed for analysis using a square root transformation. When necessary, variables were dummy coded so they could be used in linear analyses (gender: 0 = female, 1 = male; body mass index: 0 = BMI < 25, 1 = BMI ⩾ 25; race: 0 = non-White, 1 = White; ethnicity: 0 = non-Hispanic or Latino, 1 = Hispanic or Latino; education: 0 = less than a bachelor’s degree, 1 = bachelor’s degree or higher; annual income: 0 ⩽ US$60,000, 1 = US$60,000 and up; and marital status: 0 = other, 1 = married). Bivariate correlations examined the associations between MIL, self-efficacy, and PA. Path analyses using maximum likelihood estimation evaluated MIL as a predictor of self-efficacy and PA and self-efficacy as a mediator of the MIL-PA relationship. Hypotheses were tested using the product of coefficients approach to testing mediation (Figure 1). The product of coefficients approach to establishing mediation includes these steps: (1) derive a and b from regression analyses, (2) derive the standard error of a and b, (3) multiply a and b to compute ab (the indirect effect), (4) compute the standard error of ab, (5) divide ab by the standard error of ab, and (6) apply the resulting number to a z-distribution, with a ratio of greater than 1.96 or less than −1.96, indicating a significant indirect effect (MacKinnon et al., 2002). Unstandardized beta (b) coefficients, indirect effect size, and percent mediated are reported.
Model of purpose as a predictor of PA, mediated by self-efficacy.
Results
Mean scores, SDs, and range for MIL, self-efficacy, and transformed PA (total METS over 7 days) were, 4.44 (SD = 0.99, range = 1–7), 6.91 (SD = 2.3, range = 0–10), and 39.31 (SD = 27.18, range = 0–109), respectively. MIL was positively associated with self-efficacy (r = 0.35, p = 0.001) and PA (r = 0.29, p = 0.005). Self-efficacy was also positively associated with PA (r = 0.40, p = 0.01).
Mediation model: MIL
Fit statistics indicated the model fit the data well (χ2(8) = 9.70, p = 0.29; comparative fit index (CFI) = 0.95; root mean square error of approximation (RMSEA) = 0.05; standardized root mean square residual (SRMR) = 0.04). There was a significant indirect effect of MIL on PA through self-efficacy, b = 0.54, p = 0.014, which explained 42 percent of the variance in PA. The direct effect of MIL on PA, when controlling for self-efficacy as well as gender, age, BMI, race, ethnicity, education, income, and marital status, was b = 0.75, p = 0.11, indicating significant mediation.
Discussion
The results of this study extend prior work by identifying self-efficacy as one mechanism that accounts for variability in the relationship between MIL and PA. The results of this study are consistent with previous studies that identify a relationship between MIL and PA (Holahan et al., 2008, 2011; Hooker and Masters, 2016, 2018; Roepke et al., 2014; Takkinen et al., 2001).
Although it is possible to target self-efficacy alone as a well-established correlate of PA, this study suggests that one’s sense of MIL predicts favorable self-efficacy for PA behavior. Accounting for MIL as an organizing framework for fostering self-efficacy could potentially enhance one’s ability to sustain self-efficacy even in the face of difficulty when pursuing PA. MIL offers a reason for believing in one’s ability to persist through challenge as well a self-identified narrative pathway to follow for setting intentions and goals and following through to fulfill desired outcomes (McCullough and Willoughby, 2009). Results of this work suggest that rather than evaluating self-efficacy or MIL alone to increase PA, it may be wise to explore MIL as a resource for supporting physical fitness self-efficacy in future studies of PA behavior.
This study is limited by its cross-sectional design and self-report of PA. Furthermore, the sample was small and strongly represented by white, middle-aged, physically active women; therefore, the generalizability of results may be limited among those for whom PA is not a top well-being goal. It is also possible that participants were already engaging in PA, which could then promote greater sense of meaning. Future work can address limitations of this study by assessing alternative models of the relationships among the variables, collecting data from larger, more diverse samples, and exploring moderators of the relationships among MIL and self-efficacy to predict increased PA as well as utilizing longitudinal and randomized controlled trial (RCT) methodologies comparing meaning-based interventions to target physical fitness self-efficacy and PA with current practice. In addition, future research could explore whether MIL and physical fitness self-efficacy as predictors of PA may partially explain the link between MIL and cardiovascular events and mortality findings in other studies (Cohen et al., 2016; Kim et al., 2013). The results of this work suggest that MIL may be a target to increase physical fitness self-efficacy and PA.
Footnotes
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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funded by the Anschutz Health and Wellness Center at the University of Colorado Anschutz Medical Campus.
