Grit, Illness-Related Distress, and Psychosocial Outcomes in College Students With a Chronic Medical Condition: A Path Analysis

Grit, Illness-Related Distress, and Psychosocial Outcomes in College Students With a Chronic... Abstract Objective Adolescents and young adults (AYAs) with chronic medical conditions are at increased risk for a host of negative psychosocial outcomes, including depressive and anxious symptoms. Although studies have shown that illness appraisals (e.g., illness intrusiveness [II] and illness uncertainty [IU]) demonstrate consistent associations with such outcomes, few studies have examined positive factors that may relate to better psychosocial outcomes and appraisals. The present study evaluated grit (i.e., perseverance and passion for long-term goals), a novel construct in pediatric psychology, as a positive factor that relates to reduced untoward effects of II and IU on psychosocial outcomes in AYAs with chronic medical conditions. Methods College students with a chronic medical condition (N = 120) completed questionnaires online, including measures of grit, II, IU, depression, anxiety, and emotional well-being (EWB). Results The overall path analysis demonstrated that increased grit is directly associated with decreased depressive and anxious symptoms and increased EWB (p < .05). Further, analyses indicated that the positive association between grit and psychosocial outcomes is partially mediated by illness appraisals (p < .05). Conclusions This study identified grit as a positive personal asset among AYAs with chronic medical conditions. By introducing a novel construct to the AYA literature, the study expands on the integration of positive psychology and pediatric psychology and underscores the need for greater research on the role of grit in chronic medical condition populations. anxiety, chronic illness, depression, quality of life, resilience The field of positive psychology provides a framework for understanding human flourishing that seeks to understand the positive attributes that contribute to optimal functioning (Duckworth, Steen, & Seligman, 2005). Positive health, a subdiscipline of inquiry proposed by Seligman (2008), seeks to determine relationships between mental and physical health to identify factors of resiliency, as well as factors that stimulate both physical and psychological well-being. This is of particular concern within populations where physiological functioning may not be completely within one’s control, such as among individuals with a chronic medical condition. Thus, the field of positive health merges the positive psychology ideology of promoting psychological strength and flourishing, with the overall goal of integrating both psychology and medicine to manage illness. Aspinwall and Pengchit (2013) put forth a succinct model for evaluating how positive psychology constructs may impact health outcomes within the positive health framework. They propose that the effect of positive phenomena (i.e., concepts based on positive psychology principles) on health is mediated by five pathways, including biological functioning, cognitive appraisals and emotions, coping styles, social development, and health behaviors. Pediatric and health psychologists have initiated investigations in this realm by connecting variables such as hope and mindfulness with positive outcomes (Grossman, Niemann, Schmidt, & Walach, 2004; Hullmann, Fedele, Molzon, Mayes, & Mullins, 2014). Research demonstrates that such positive psychological traits can reliably improve both physical and psychological outcomes (Berg, Rapoff, Snyder, & Belmont, 2007; Mannix, Feldman, & Moody, 2009). However, the extant literature exploring the various pathways proposed by Aspinwall and Pengchit (2013) is limited. Therefore, further investigation is necessary to fully understand the mechanisms by which positive outcomes are realized. Although the field of positive psychology has witnessed rapid growth, grit is a potentially overlooked construct, which has not been explored within the chronic medical condition context. Grit is an intrapersonal characteristic defined by “passion and perseverance for long-term goals” (Duckworth, Peterson, Matthews, & Kelly, 2007, p. 1087). It has been shown to predict success in academic endeavors, workplace retention, and personal pursuits (Eskreis-Winkler, Shulman, Beal, & Duckworth, 2014). Grit is also positively related to psychological well-being and protects against distressing symptomatology, such as suicidal ideation (Pennings, Law, Green, & Anestis, 2015; Vainio & Daukantaitė, 2016). However, grit encompasses much more than a simple drive to transcend obstacles; it includes the component of what has been referred to as passion, or a staunch interest in succeeding, regardless of the goal at hand (Duckworth, Peterson, Matthews, & Kelly, 2007). In the context of chronic medical conditions, success could be interpreted as the ability to manage one’s illness and to thrive throughout life, in the face of a burdensome life-threatening or chronic condition. Self-control, a similar concept related to aligning actions with one’s goal, such as completing a daily illness-related task, has been shown to be associated with improved quality of life in a pediatric sample (Monaghan, Clary, Stern, Hilliard, & Streisand, 2015). However, the concept of grit in a pediatric population would suggest a longer-term commitment to a superordinate goal, such as maintaining or improving one’s overall health status (Duckworth & Gross, 2014). To date, the only studies within the realm of positive health that have examined the relationship between grit and health outcomes linked grit with greater health-related quality of life (Sharkey et al., 2017), improved rates of exercise behavior in generally healthy populations (Reed, Pritschet, & Cutton, 2013), and lower body mass index in a population of adults with or without obesity (Graham et al., 2015). Thus, there is a need to explore the potential positive role of grit among youth with a chronic medical condition. Owing to the particular vulnerabilities of young adults with such conditions, an examination of grit appears particularly important for this population. In addition to the numerous stressors that many encounter during the transition to adulthood, including financial responsibilities, and increased academic loads, young adults with chronic medical conditions must also absorb responsibility for their health-care management (Brougham, Zail, Mendoza, & Miller, 2009; Devine, Monaghan, & Schwartz, 2017; Pai & Schwartz, 2011). In fact, research has shown that college students with chronic medical conditions miss more school days than peers without chronic medical conditions because of the intrusiveness of their conditions, and that the unpredictable nature of their illness may contribute to avoidance of valued activities and increased distressed (Carpentier, Mullins, & Van Pelt, 2007). Further, college students with health challenges are at risk for anxiety and depression, above and beyond their peers without chronic medical conditions, rendering it important to investigate potential factors that promote well-being in this population (Herts et al., 2014; Wodka & Barakat, 2007). Given these challenges, young adults, specifically college students, with chronic medical conditions are the ideal population to investigate the role of the positive health construct of grit in adjustment. Furthermore, the identification of potential mediating factors, which align with Aspinwall and Pengchit’s (2013) model, would add to the understanding of the mechanisms through which grit relates to adjustment outcomes in this population. Although the extant literature on factors that contribute to distress or well-being among college students with chronic medical conditions is limited, at least two clear predictors of negative psychological adjustment have been determined in this population: illness uncertainty (IU) and illness intrusiveness (II). IU has been defined as a cognitive experience within the circumstances of illness in which outcomes are unpredictable and the illness is characterized by ambiguity (Pai et al., 2006). Extensive research has shown consistent associations between IU and negative adjustment outcomes, including depression and anxiety within adolescent and young adult chronic medical condition populations (Szulczewski, Mullins, Bidwell, Eddington, & Pai, 2017). II is a cognitive appraisal mechanism that reflects the extent to which illness factors impede the ability to participate in daily valued activities (Devins, 2010; Mullins et al., 2001). II is associated with increased depressive and anxious symptoms, as well as reduced health-related quality of life (Carpentier et al., 2007; Mullins et al., 2001). Although these predictors have been identified as targets for psychosocial interventions to reduce risk, it is also important to ascertain factors that may promote resilient outcomes (Hilliard, McQuaid, Nabors, & Hood, 2015). In this vein, grit could be targeted as a positive factor that buffers against perceptions of uncertainty and intrusiveness, and in turn against the negative psychological effects of illness. Thus, the current study aimed to fill the gap in understanding grit, as it relates to physical and mental health by evaluating grit as a potential positive factor that inversely relates to depressive and anxious symptomatology, and thereby contributes to psychological well-being among young adults with a chronic medical condition. In addition, we sought to examine the possible mediating role of cognitive appraisals, namely, IU and II. Therefore, the overall goal of this initial examination within a chronic medical condition population was to evaluate the main effects of grit, and two potential mechanisms through which grit is associated with better adjustment and well-being. It was hypothesized that grit would have significant direct and indirect effects through IU and II on symptoms of depression and anxiety, as well as emotional well-being (EWB). Methods Participants College students with and without a self-reported chronic medical condition were recruited from a large Midwestern university via an online survey system in which students could choose to enroll in any number of several available studies throughout the entire academic year. Among a sample of 589 college students, 120 students (Mage = 21.13 years, SD = 5.45) reported having a chronic medical condition of some type (e.g., asthma, inflammatory bowel disease, type 1 diabetes). Students consented to the study and filled out all questionnaires online. All participants who completed measures were compensated with course credit, a requirement of many undergraduate courses. The study was approved by the institutional review board, and all procedures adhered to the American Psychological Association’s ethical guidelines. Measures Demographic Characteristics Demographic information, including age, gender, ethnicity, education level, and medical condition, was collected. Participants are asked to report if they have a chronic medical condition. They are then asked to specify their condition in a multiple-choice question, which includes options of medical conditions commonly present in this population, along with a text box to include any additional conditions. Owing to sample size considerations, ethnicity was collapsed into a dichotomized variable (i.e., White and non-White), and education was collapsed into a dichotomized variable (i.e., underclassmen, which refers to freshmen and sophomores, and upperclassmen, which refers to juniors and seniors). Short Grit Scale The Short Grit scale is an eight-item self-report Likert-scale questionnaire that measures an individual’s ability to persevere and sustain passion for long-term goals (Duckworth & Quinn, 2009). The scale includes items such as “I finish whatever I begin.” An average of the items is calculated to form the grit score, with higher scores indicating higher levels of grittiness. Previous research has indicated the Grit scale has good reliability and validity (Duckworth & Quinn, 2009). In the present study, internal consistency of the measure was adequate and consistent with the literature (α = .77). Center for Epidemiological Studies Depression Scale The Center for Epidemiological Studies Depression (CES-D) is a 20-item self-report Likert-scale measure of depressive symptomatology (Radloff, 1977). A sum score of the items is calculated and higher scores represent higher levels of depressive symptomatology. Previous research has indicated the CES-D has strong reliability and validity (Hann, Winter, & Jacobsen, 1999; Radloff, 1977). The internal consistency of the measure was excellent in the present study, and was consistent with the literature (α = .93). Zung Self-Rating Anxiety Scale The Self-Rating Anxiety Scale (SAS) is a 20-item self-report Likert-scale measure of anxious symptomatology (Zung, 1971). The items are summed to create a raw score, which is then converted to an anxiety index. Higher scores on the questionnaire indicate higher levels of anxiety. Previous research has indicated the SAS has good reliability and validity (Zung, 1971). In the current study, the internal consistency of the measure was good, and was consistent with the literature (α = .86). Rand SF-36 Health Survey The SF-36 Health Survey (SF-36) is a 36-item self-report Likert-scale measure assessing health-related quality of life across eight domains (Hays, Sherbourne, & Mazel, 1993). The EWB subscale, calculated by a normed scoring method of five items, was used in this study as a measure of positive EWB. Previous research has indicated that overall the Rand SF-36 has good reliability and validity (Hays, Sherbourne, & Mazel, 1993). In the present study, internal consistency of the subscale was good (α = .87). Illness Intrusiveness Ratings Scale The II is a 13-item, self-report instrument, which assesses II, or the appraisal of the degree to which an illness interferes with valued life activities, on a seven-point Likert scale (Devins, 2010). Previous research has indicated that the II has excellent reliability and validity (Devins, 2010; Devins et al., 2001). The measure had excellent internal consistency (α = .93) in the current study, which was consistent with the literature. Mishel Uncertainty in Illness Scale, community form The IU is a 23-item self-report Likert-scale questionnaire, which assesses IU, the cognitive experience when the meaning of illness-related events is ambiguous (Mishel, 1981). Previous research has indicated the IU scale has strong reliability and validity (Mishel, 1981). In the present study, internal consistency was excellent and consistent with the literature (α = .91). Overview of Analyses First, bivariate correlations were conducted to assess the presence of significant relationships between all variables of interest. Next, to examine the interrelationships between the variables, we tested the multiple mediator pathways simultaneously using structural equation modeling. The path models were tested using Mplus version 7.4 with full information maximum likelihood to accommodate missing data at the scale level (Baraldi & Enders, 2010; Little, Jorgensen, Lang, & Moore, 2014). Each measure had one participant who either missed the entire scale or an item. Thus, even with the missing data, the path analyses were based on the complete sample of N = 120. Grit was entered as an independent variable, and depression, anxiety, and EWB were entered as outcome variables. IU and II were entered as mediators. The model also controlled for demographic characteristics (i.e., age, sex, race/ethnicity, and grade level). All direct and indirect effects of grit were estimated in the model (see Figure 1). This model was based on the a priori hypothesis that the direct effects of grit on the outcomes of interest would remain meaningful in the presence of the mediating variables, in accordance with the model suggested by Aspinwall and Pengchit (2013), which included additional mediated pathways that were not included in the current study. Thus, an additional model without the direct effects of grit (i.e., a model constraining the relations between grit and the outcomes to zero) was also estimated, to examine the importance of the direct effects in the presently estimated model. Figure 1. View largeDownload slide Path analysis model. Mediated effects are Grit → IU → CES-D = −0.08*, Grit → II → CES-D = −0.07*, Grit → IU → SAS = −0.08*, Grit → II → SAS = −0.07*, Grit → IU → EWB = 0.07*, Grit → II → EWB = 0.04. Note. Demographic variables (i.e., age, sex, race/ethnicity, education level) were controlled for in the model, but are not depicted. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. *p < .05; **p < .01; ***p < .001. Figure 1. View largeDownload slide Path analysis model. Mediated effects are Grit → IU → CES-D = −0.08*, Grit → II → CES-D = −0.07*, Grit → IU → SAS = −0.08*, Grit → II → SAS = −0.07*, Grit → IU → EWB = 0.07*, Grit → II → EWB = 0.04. Note. Demographic variables (i.e., age, sex, race/ethnicity, education level) were controlled for in the model, but are not depicted. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. *p < .05; **p < .01; ***p < .001. Results The present sample was primarily Caucasian (78.3%), female (73.3%), and in their freshman year of college (42.5%). Demographic characteristics of the current sample are present in Table I. The participants reported significant distress, with 62.18% of the sample indicating depressive symptomatology above the clinically concerning cutoff for the CES-D, 31.9% of the sample reporting anxious symptomatology above the screening cutoff for the SAS, and 66.4% of the sample reporting lower EWB than a normative sample (Hays, Sherbourne, & Mazel, 1993; Zung, 1971). There was significant overlap, such that 91.7% of those with clinically concerning CES-D scores also reported clinically concerning SAS scores. Owing to this high level of distress, independent t-tests were conducted to compare outcomes between those students with and without a self-reported chronic medical condition. The sample of controls was derived from a previous project conducted by Sharkey and colleagues (Sharkey et al., 2017), which consisted of 470 college students between the ages of 18 and 23 years. Owing to violations of the homogeneity of variance assumption, some tests are presented with a Welch F-test correction. Students with a chronic medical condition reported significantly higher depressive (t(162.18) = 6.38, p < .001, 95% confidence interval (CI) [5.53, 10.48]) and anxious (t(160.90) = 8.07, p < .001, 95% CI [6.18, 10.19]) symptomatology, and significantly lower EWB (t(165.18) = −6.44, p < .001, 95% CI [−19.04, −10.11]) and grit (t(587) = −3.40, p < .001, 95% CI [−0.35, −0.09]) than peers without chronic medical conditions. Ms and SDs for those with chronic medical conditions are reported in Table II. Table I. Demographic Characteristics (N = 120) Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Note. Of those who reported that they have allergies, 55% also reported that they have asthma. Table I. Demographic Characteristics (N = 120) Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Note. Of those who reported that they have allergies, 55% also reported that they have asthma. Table II. Measure Average Total Scores and SDs Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. a Below community M. b Above screening clinical cutoff. Table II. Measure Average Total Scores and SDs Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. a Below community M. b Above screening clinical cutoff. Preliminary Analyses Partial correlations, controlling for demographics (i.e., age, sex, race/ethnicity, and grade level), were conducted for the relationships between Grit, II, and IU, because of detectable sex differences in reporting. Specifically, student sex was significantly related to several outcomes, with females reporting higher grit (p < .05), anxiety (p < .01), IU (p < .01), and II (p < .05) than males. Grit was significantly (p < .05) correlated with all outcomes of interest (i.e., EWB, SAS, CES-D) and both mediators (i.e., II and IU). The correlation matrix can be found in Table III. Table III. Bivariate Correlations Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. * p < .05; **p < .01; ***p < .001. a Partial correlations are reported, controlling for demographic variables. Table III. Bivariate Correlations Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. * p < .05; **p < .01; ***p < .001. a Partial correlations are reported, controlling for demographic variables. Model Specification The a priori hypothesized model is shown in Figure 1. Although omitted from the diagram, demographic characteristics (i.e., age, gender, race/ethnicity, and grade level) were estimated on all endogenous variables (i.e., II, IU, EWB, depression, and anxiety). As depicted in the figure, we allowed the residuals of the two mediators to correlate (II and IU) and the residuals of the outcome variables (EWB, depression, and anxiety) to correlate. In total, 5,000 bias-corrected bootstrapped samples were used to test conditional and indirect effects, based on current methodological recommendations (Fritz & MacKinnon, 2007). Path Analysis A fully saturated model was estimated (χ2(4) = 6.698, p = .15; CFI = 0.993; TLI = 0.942; SRMR = 0.04; RMSEA = 0.08). Results of our analysis demonstrate that grit had a significant direct effect on depressive symptoms (β = −0.18, SE = 0.08, p < .01) and anxious symptoms (β = −0.18, SE = 0.06, p < .01) such that higher grit was associated with lower self-reported symptomatology. Grit also had a significant direct effect on EWB (β = 0.29, SE = 0.07, p < .001) such that higher levels of grit were related to higher levels of EWB. Grit also had a significant direct effect on II (β = −0.22, SE = .10, p < .05) and IU (β = −0.21, SE = 0.11, p < .05), such that higher grit was directly associated with lower II and IU. Mediated path results indicated that grit had an indirect effect on depressive symptoms through IU (β = −0.08, SE = 0.04, 95% BC [−0.18, −0.01]) and through II (β = −0.07, SE = 0.03, 95% BC [−0.15, −0.02]). Grit also had an indirect effect on anxious symptoms through IU (β = −0.08, SE = 0.04, 95% BC [−0.17, −0.01]) and II (β = −0.07, SE = 0.04, 95% BC [−0.16, −0.02]). Finally, grit had an indirect effect on EWB through IU (β = 0.07, SE = 0.04, 95% BC [0.01, 0.17]) and II (β = 0.04, SE = 0.03, 95% BC [0.01, 0.11]). These results suggest that the relationship between grit and psychological distress or well-being is partially accounted for by cognitive appraisal mechanisms, among college students with a chronic medical condition. The model without any direct effects showed adequate to poor fit (χ2(7) = 22.33, p < .01; CFI = 0.963; TLI = 0.814; SRMR = 0.05; RMSEA = 0.14). To fully assess whether the direct paths between grit and the outcomes (i.e., EWB, anxiety, and depression) should be included in the model, we compared the fit of the two nested models (one with and one without the direct paths) using the likelihood ratio test (the χ2 difference test; Bentler & Bonett, 1980). If statistically significant, the test would suggest that the constraints on the more restricted model, without the direct paths, may be too strict. Results suggested that the model with direct effects (i.e., the model in Figure 1) provides better fit to the data (χ2 (3) = 15.63, p < .01). This is consistent with our hypothesis that the direct effects would remain meaningful in the presence of the mediators. Discussion The current study evaluated the role of grit, a relatively novel construct, as a contributor to resilience among college students with a chronic medical condition, an understudied and uniquely challenged population. This study expands on previously limited literature linking grit and positive health outcomes (Reed, Pritschet, & Cutton, 2013; Sharkey et al., 2017; Graham et al., 2015), by finding that grit may indeed serve as a positive factor that is inversely related to depressive and anxious symptomatology. Higher grit was also directly associated with increased EWB, suggesting that grit may not only be related to reduced negative outcomes but is also associated with more positive adjustment outcomes. Importantly, this finding aligns with the primary tenet of positive health, which asserts that well-being, beyond the absence of negative symptoms, is a valued objective (Seligman, 2008). The overall path analysis demonstrated that the positive association between grit and psychological outcomes is partially a function of its relation with reduced negative illness appraisals (i.e., IU and II). Grit was associated with lower levels of both II and IU, and in turn, was related to decreased distress, which has been substantiated by previous studies (Szulczewski et al., 2017). Specifically, the negative effects of II and IU reported by Carpentier and colleagues (Carpentier et al., 2007) are particularly relevant to the current findings, as both studies examined samples that largely consisted of students with asthma and/or allergies. Although speculative, this suggests that having higher levels of grit may influence the manner in which individuals perceive illness-related events, which in turn may decrease the likelihood of illness-related distress. Thus, the findings foster a more nuanced understanding of the relationship between cognitive appraisals and psychological outcomes in college students with a chronic medical condition, and provide support for the cognitive pathway of Aspinwall and Pengchit’s (2013) model for the relationship between positive phenomena, such as grit, and health outcomes. The direct effects of grit on depressive/anxious symptomatology and EWB, which remained significant in the presence of the mediators, are consistent with the theoretical model and suggest the existence of additional mechanisms that might influence the relationship between grit and mental health outcomes. For instance, future research could evaluate the additive or interactive effect of social support or coping strategies on the existing model in an effort to better understand how grit operates. Furthermore, the present findings are consistent with research indicating that adolescents and young adults (AYAs) with a chronic medical condition are at risk for clinically concerning anxious and depressive symptomatology, as well as reduced well-being (Barakat & Wodka, 2006; Herts, Wallis, & Maslow, 2014). However, the current study adds to the literature, as previous studies assessed only limited demographic groups (e.g., freshman only, few illness groups, small samples), whereas the current findings are across multiple illness groups and education levels. Additionally, roughly one third to two third of the current sample reported symptomatology that exceeded screening cutoffs, with twice the rate of clinically significant depressive versus anxious symptoms and significant overlap between the two outcomes, again underscoring the heightened risk for this population. Such findings support the positive role of grit in the context of interventions aimed at fostering perseverance and passion among college students who struggle to cope with their illness (Kichler & Kaugars, 2015). Indeed, research shows that building positive states alleviates depression, and future research might reveal that building grit can reduce such negative symptomatology for young adults with a chronic medical condition (Seligman, Rashid, & Parks, 2006; Seligman, Steen, Park, & Peterson, 2005). Currently, an empirically supported grit-based intervention does not exist, but it has been theorized that cognitive-behavioral techniques, such as cognitive restructuring to address distorted expectancies for success, or values-based interventions, such as Acceptance and Commitment Therapy, might cultivate grit by helping individuals to align their actions and thoughts with the valued long-term goal of successfully managing a chronic medical condition (Eskreis-Winkler, Gross, & Duckworth, 2016; Sharkey et al., 2017). Additionally, because of the high rates of depressive symptoms in this population, universities may wish to offer general wellness programs that promote well-being among students with chronic illness. For example, a peer-mentoring model that has shown benefits for both mentors and mentees, or interventions that have targeted IU as a modifiable factor associated with distress could be implemented (Ahola Kohut, Stinson, Forgeron, Luca, & Harris, 2017; Szulczewski et al., 2017). Previous findings, from a related investigation of a sample of college students without a chronic medical condition, also demonstrated a connection between grit and health-care management skills among healthy youth, suggesting that grit may be targeted to improve self-management and medical outcomes (Sharkey et al., 2017). However, the relationship between grit and such outcomes must first be tested among pediatric illness populations to facilitate future intervention development. Alternatively, assessing grit may be more appropriately used as a screening process for identifying those at risk for negative outcomes, or to assist in determining the most advantageous treatment plans (Sharkey et al., 2017). For instance, a student with a chronic medical condition who has depressive symptoms, and a high grit score, may be likely to benefit from cognitive techniques that require a great deal of practice and determination, whereas a more behaviorally focused treatment might be of larger benefit to a student with lower levels of grit. Assessing grit may also be valuable for determining if a grit-focused component must be added to increase the efficacy of interventions that use goal-setting to improve outcomes for AYAs with chronic medical conditions (Rosenberg et al., 2015). Campus student health clinics, mental health centers, or student disability services could also use this measure to screen for students at risk or in need of specific supports. Certainly, greater research is needed to test these hypotheses and to better understand the clinical implications of grit. The findings of the current study must be considered in light of several limitations. First, causal conclusions cannot be assumed because of the study’s cross-sectional design. Longitudinal assessments within the health context are necessary to fully ascertain the role of grit. Alternative theoretical models should also be considered, as the current study did not test multiple path directions. Generalizability of the present findings are limited, as our sample was not ethnically diverse and was collected from a single university. As females reported higher levels of grit and greater psychological problems, generalizability to male college students may also be limited. Although the heterogeneity of the diagnoses in our sample could be considered to have bolstered the generalizability of our findings across illness groups, the role of grit should still be tested among specific diagnostic populations, as research has shown that the effect of certain variables may differ across illness groups (Mullins et al., 2017). In particular, as our study relied on self-report measures and lacked information regarding illness severity, findings may differ for clinic-based populations. Confirmation of diagnoses and medical chart reviews conducted with campus student health services could improve future study designs by providing objective medical data. Although the current study provides support for the role of grit among young adults with chronic medical conditions, the developmental trajectory of grit is not well-established, and investigations of grit in younger pediatric populations are needed. Further, the incremental validity of grit within the pediatric psychology literature could not be established by the current study. Comparisons between grit and other commonly tested positive personal assets, such as self-efficacy and self-control, are necessary to determine the added value of grit. Despite these limitations, the current examination broadens the understanding of the role of grit within the context of health and illness. Taken together, the findings suggest that grit is an understudied positive factor among college students with a chronic medical condition, and has the potential to be a target of intervention focused on aiding those who are struggling to manage their health. Future research is warranted to explore the role of grit in reducing distress and promoting well-being among pediatric illness populations. Acknowledgments The authors would like to thank the participants and research assistants for their time and contributions to this study. Funding This study was approved by the institutional review board, and all procedures were in compliance with APA ethical standards. Conflicts of interest: None declared. References Ahola Kohut S., Stinson J., Forgeron P., Luca S., Harris L. ( 2017). 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A rating instrument for anxiety disorders. Psychosomatics , 12, 371– 379. http://dx.doi.org/10.1016/S0033-3182(71)71479-0 Google Scholar CrossRef Search ADS PubMed  © The Author 2017. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Pediatric Psychology Oxford University Press

Grit, Illness-Related Distress, and Psychosocial Outcomes in College Students With a Chronic Medical Condition: A Path Analysis

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Abstract

Abstract Objective Adolescents and young adults (AYAs) with chronic medical conditions are at increased risk for a host of negative psychosocial outcomes, including depressive and anxious symptoms. Although studies have shown that illness appraisals (e.g., illness intrusiveness [II] and illness uncertainty [IU]) demonstrate consistent associations with such outcomes, few studies have examined positive factors that may relate to better psychosocial outcomes and appraisals. The present study evaluated grit (i.e., perseverance and passion for long-term goals), a novel construct in pediatric psychology, as a positive factor that relates to reduced untoward effects of II and IU on psychosocial outcomes in AYAs with chronic medical conditions. Methods College students with a chronic medical condition (N = 120) completed questionnaires online, including measures of grit, II, IU, depression, anxiety, and emotional well-being (EWB). Results The overall path analysis demonstrated that increased grit is directly associated with decreased depressive and anxious symptoms and increased EWB (p < .05). Further, analyses indicated that the positive association between grit and psychosocial outcomes is partially mediated by illness appraisals (p < .05). Conclusions This study identified grit as a positive personal asset among AYAs with chronic medical conditions. By introducing a novel construct to the AYA literature, the study expands on the integration of positive psychology and pediatric psychology and underscores the need for greater research on the role of grit in chronic medical condition populations. anxiety, chronic illness, depression, quality of life, resilience The field of positive psychology provides a framework for understanding human flourishing that seeks to understand the positive attributes that contribute to optimal functioning (Duckworth, Steen, & Seligman, 2005). Positive health, a subdiscipline of inquiry proposed by Seligman (2008), seeks to determine relationships between mental and physical health to identify factors of resiliency, as well as factors that stimulate both physical and psychological well-being. This is of particular concern within populations where physiological functioning may not be completely within one’s control, such as among individuals with a chronic medical condition. Thus, the field of positive health merges the positive psychology ideology of promoting psychological strength and flourishing, with the overall goal of integrating both psychology and medicine to manage illness. Aspinwall and Pengchit (2013) put forth a succinct model for evaluating how positive psychology constructs may impact health outcomes within the positive health framework. They propose that the effect of positive phenomena (i.e., concepts based on positive psychology principles) on health is mediated by five pathways, including biological functioning, cognitive appraisals and emotions, coping styles, social development, and health behaviors. Pediatric and health psychologists have initiated investigations in this realm by connecting variables such as hope and mindfulness with positive outcomes (Grossman, Niemann, Schmidt, & Walach, 2004; Hullmann, Fedele, Molzon, Mayes, & Mullins, 2014). Research demonstrates that such positive psychological traits can reliably improve both physical and psychological outcomes (Berg, Rapoff, Snyder, & Belmont, 2007; Mannix, Feldman, & Moody, 2009). However, the extant literature exploring the various pathways proposed by Aspinwall and Pengchit (2013) is limited. Therefore, further investigation is necessary to fully understand the mechanisms by which positive outcomes are realized. Although the field of positive psychology has witnessed rapid growth, grit is a potentially overlooked construct, which has not been explored within the chronic medical condition context. Grit is an intrapersonal characteristic defined by “passion and perseverance for long-term goals” (Duckworth, Peterson, Matthews, & Kelly, 2007, p. 1087). It has been shown to predict success in academic endeavors, workplace retention, and personal pursuits (Eskreis-Winkler, Shulman, Beal, & Duckworth, 2014). Grit is also positively related to psychological well-being and protects against distressing symptomatology, such as suicidal ideation (Pennings, Law, Green, & Anestis, 2015; Vainio & Daukantaitė, 2016). However, grit encompasses much more than a simple drive to transcend obstacles; it includes the component of what has been referred to as passion, or a staunch interest in succeeding, regardless of the goal at hand (Duckworth, Peterson, Matthews, & Kelly, 2007). In the context of chronic medical conditions, success could be interpreted as the ability to manage one’s illness and to thrive throughout life, in the face of a burdensome life-threatening or chronic condition. Self-control, a similar concept related to aligning actions with one’s goal, such as completing a daily illness-related task, has been shown to be associated with improved quality of life in a pediatric sample (Monaghan, Clary, Stern, Hilliard, & Streisand, 2015). However, the concept of grit in a pediatric population would suggest a longer-term commitment to a superordinate goal, such as maintaining or improving one’s overall health status (Duckworth & Gross, 2014). To date, the only studies within the realm of positive health that have examined the relationship between grit and health outcomes linked grit with greater health-related quality of life (Sharkey et al., 2017), improved rates of exercise behavior in generally healthy populations (Reed, Pritschet, & Cutton, 2013), and lower body mass index in a population of adults with or without obesity (Graham et al., 2015). Thus, there is a need to explore the potential positive role of grit among youth with a chronic medical condition. Owing to the particular vulnerabilities of young adults with such conditions, an examination of grit appears particularly important for this population. In addition to the numerous stressors that many encounter during the transition to adulthood, including financial responsibilities, and increased academic loads, young adults with chronic medical conditions must also absorb responsibility for their health-care management (Brougham, Zail, Mendoza, & Miller, 2009; Devine, Monaghan, & Schwartz, 2017; Pai & Schwartz, 2011). In fact, research has shown that college students with chronic medical conditions miss more school days than peers without chronic medical conditions because of the intrusiveness of their conditions, and that the unpredictable nature of their illness may contribute to avoidance of valued activities and increased distressed (Carpentier, Mullins, & Van Pelt, 2007). Further, college students with health challenges are at risk for anxiety and depression, above and beyond their peers without chronic medical conditions, rendering it important to investigate potential factors that promote well-being in this population (Herts et al., 2014; Wodka & Barakat, 2007). Given these challenges, young adults, specifically college students, with chronic medical conditions are the ideal population to investigate the role of the positive health construct of grit in adjustment. Furthermore, the identification of potential mediating factors, which align with Aspinwall and Pengchit’s (2013) model, would add to the understanding of the mechanisms through which grit relates to adjustment outcomes in this population. Although the extant literature on factors that contribute to distress or well-being among college students with chronic medical conditions is limited, at least two clear predictors of negative psychological adjustment have been determined in this population: illness uncertainty (IU) and illness intrusiveness (II). IU has been defined as a cognitive experience within the circumstances of illness in which outcomes are unpredictable and the illness is characterized by ambiguity (Pai et al., 2006). Extensive research has shown consistent associations between IU and negative adjustment outcomes, including depression and anxiety within adolescent and young adult chronic medical condition populations (Szulczewski, Mullins, Bidwell, Eddington, & Pai, 2017). II is a cognitive appraisal mechanism that reflects the extent to which illness factors impede the ability to participate in daily valued activities (Devins, 2010; Mullins et al., 2001). II is associated with increased depressive and anxious symptoms, as well as reduced health-related quality of life (Carpentier et al., 2007; Mullins et al., 2001). Although these predictors have been identified as targets for psychosocial interventions to reduce risk, it is also important to ascertain factors that may promote resilient outcomes (Hilliard, McQuaid, Nabors, & Hood, 2015). In this vein, grit could be targeted as a positive factor that buffers against perceptions of uncertainty and intrusiveness, and in turn against the negative psychological effects of illness. Thus, the current study aimed to fill the gap in understanding grit, as it relates to physical and mental health by evaluating grit as a potential positive factor that inversely relates to depressive and anxious symptomatology, and thereby contributes to psychological well-being among young adults with a chronic medical condition. In addition, we sought to examine the possible mediating role of cognitive appraisals, namely, IU and II. Therefore, the overall goal of this initial examination within a chronic medical condition population was to evaluate the main effects of grit, and two potential mechanisms through which grit is associated with better adjustment and well-being. It was hypothesized that grit would have significant direct and indirect effects through IU and II on symptoms of depression and anxiety, as well as emotional well-being (EWB). Methods Participants College students with and without a self-reported chronic medical condition were recruited from a large Midwestern university via an online survey system in which students could choose to enroll in any number of several available studies throughout the entire academic year. Among a sample of 589 college students, 120 students (Mage = 21.13 years, SD = 5.45) reported having a chronic medical condition of some type (e.g., asthma, inflammatory bowel disease, type 1 diabetes). Students consented to the study and filled out all questionnaires online. All participants who completed measures were compensated with course credit, a requirement of many undergraduate courses. The study was approved by the institutional review board, and all procedures adhered to the American Psychological Association’s ethical guidelines. Measures Demographic Characteristics Demographic information, including age, gender, ethnicity, education level, and medical condition, was collected. Participants are asked to report if they have a chronic medical condition. They are then asked to specify their condition in a multiple-choice question, which includes options of medical conditions commonly present in this population, along with a text box to include any additional conditions. Owing to sample size considerations, ethnicity was collapsed into a dichotomized variable (i.e., White and non-White), and education was collapsed into a dichotomized variable (i.e., underclassmen, which refers to freshmen and sophomores, and upperclassmen, which refers to juniors and seniors). Short Grit Scale The Short Grit scale is an eight-item self-report Likert-scale questionnaire that measures an individual’s ability to persevere and sustain passion for long-term goals (Duckworth & Quinn, 2009). The scale includes items such as “I finish whatever I begin.” An average of the items is calculated to form the grit score, with higher scores indicating higher levels of grittiness. Previous research has indicated the Grit scale has good reliability and validity (Duckworth & Quinn, 2009). In the present study, internal consistency of the measure was adequate and consistent with the literature (α = .77). Center for Epidemiological Studies Depression Scale The Center for Epidemiological Studies Depression (CES-D) is a 20-item self-report Likert-scale measure of depressive symptomatology (Radloff, 1977). A sum score of the items is calculated and higher scores represent higher levels of depressive symptomatology. Previous research has indicated the CES-D has strong reliability and validity (Hann, Winter, & Jacobsen, 1999; Radloff, 1977). The internal consistency of the measure was excellent in the present study, and was consistent with the literature (α = .93). Zung Self-Rating Anxiety Scale The Self-Rating Anxiety Scale (SAS) is a 20-item self-report Likert-scale measure of anxious symptomatology (Zung, 1971). The items are summed to create a raw score, which is then converted to an anxiety index. Higher scores on the questionnaire indicate higher levels of anxiety. Previous research has indicated the SAS has good reliability and validity (Zung, 1971). In the current study, the internal consistency of the measure was good, and was consistent with the literature (α = .86). Rand SF-36 Health Survey The SF-36 Health Survey (SF-36) is a 36-item self-report Likert-scale measure assessing health-related quality of life across eight domains (Hays, Sherbourne, & Mazel, 1993). The EWB subscale, calculated by a normed scoring method of five items, was used in this study as a measure of positive EWB. Previous research has indicated that overall the Rand SF-36 has good reliability and validity (Hays, Sherbourne, & Mazel, 1993). In the present study, internal consistency of the subscale was good (α = .87). Illness Intrusiveness Ratings Scale The II is a 13-item, self-report instrument, which assesses II, or the appraisal of the degree to which an illness interferes with valued life activities, on a seven-point Likert scale (Devins, 2010). Previous research has indicated that the II has excellent reliability and validity (Devins, 2010; Devins et al., 2001). The measure had excellent internal consistency (α = .93) in the current study, which was consistent with the literature. Mishel Uncertainty in Illness Scale, community form The IU is a 23-item self-report Likert-scale questionnaire, which assesses IU, the cognitive experience when the meaning of illness-related events is ambiguous (Mishel, 1981). Previous research has indicated the IU scale has strong reliability and validity (Mishel, 1981). In the present study, internal consistency was excellent and consistent with the literature (α = .91). Overview of Analyses First, bivariate correlations were conducted to assess the presence of significant relationships between all variables of interest. Next, to examine the interrelationships between the variables, we tested the multiple mediator pathways simultaneously using structural equation modeling. The path models were tested using Mplus version 7.4 with full information maximum likelihood to accommodate missing data at the scale level (Baraldi & Enders, 2010; Little, Jorgensen, Lang, & Moore, 2014). Each measure had one participant who either missed the entire scale or an item. Thus, even with the missing data, the path analyses were based on the complete sample of N = 120. Grit was entered as an independent variable, and depression, anxiety, and EWB were entered as outcome variables. IU and II were entered as mediators. The model also controlled for demographic characteristics (i.e., age, sex, race/ethnicity, and grade level). All direct and indirect effects of grit were estimated in the model (see Figure 1). This model was based on the a priori hypothesis that the direct effects of grit on the outcomes of interest would remain meaningful in the presence of the mediating variables, in accordance with the model suggested by Aspinwall and Pengchit (2013), which included additional mediated pathways that were not included in the current study. Thus, an additional model without the direct effects of grit (i.e., a model constraining the relations between grit and the outcomes to zero) was also estimated, to examine the importance of the direct effects in the presently estimated model. Figure 1. View largeDownload slide Path analysis model. Mediated effects are Grit → IU → CES-D = −0.08*, Grit → II → CES-D = −0.07*, Grit → IU → SAS = −0.08*, Grit → II → SAS = −0.07*, Grit → IU → EWB = 0.07*, Grit → II → EWB = 0.04. Note. Demographic variables (i.e., age, sex, race/ethnicity, education level) were controlled for in the model, but are not depicted. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. *p < .05; **p < .01; ***p < .001. Figure 1. View largeDownload slide Path analysis model. Mediated effects are Grit → IU → CES-D = −0.08*, Grit → II → CES-D = −0.07*, Grit → IU → SAS = −0.08*, Grit → II → SAS = −0.07*, Grit → IU → EWB = 0.07*, Grit → II → EWB = 0.04. Note. Demographic variables (i.e., age, sex, race/ethnicity, education level) were controlled for in the model, but are not depicted. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. *p < .05; **p < .01; ***p < .001. Results The present sample was primarily Caucasian (78.3%), female (73.3%), and in their freshman year of college (42.5%). Demographic characteristics of the current sample are present in Table I. The participants reported significant distress, with 62.18% of the sample indicating depressive symptomatology above the clinically concerning cutoff for the CES-D, 31.9% of the sample reporting anxious symptomatology above the screening cutoff for the SAS, and 66.4% of the sample reporting lower EWB than a normative sample (Hays, Sherbourne, & Mazel, 1993; Zung, 1971). There was significant overlap, such that 91.7% of those with clinically concerning CES-D scores also reported clinically concerning SAS scores. Owing to this high level of distress, independent t-tests were conducted to compare outcomes between those students with and without a self-reported chronic medical condition. The sample of controls was derived from a previous project conducted by Sharkey and colleagues (Sharkey et al., 2017), which consisted of 470 college students between the ages of 18 and 23 years. Owing to violations of the homogeneity of variance assumption, some tests are presented with a Welch F-test correction. Students with a chronic medical condition reported significantly higher depressive (t(162.18) = 6.38, p < .001, 95% confidence interval (CI) [5.53, 10.48]) and anxious (t(160.90) = 8.07, p < .001, 95% CI [6.18, 10.19]) symptomatology, and significantly lower EWB (t(165.18) = −6.44, p < .001, 95% CI [−19.04, −10.11]) and grit (t(587) = −3.40, p < .001, 95% CI [−0.35, −0.09]) than peers without chronic medical conditions. Ms and SDs for those with chronic medical conditions are reported in Table II. Table I. Demographic Characteristics (N = 120) Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Note. Of those who reported that they have allergies, 55% also reported that they have asthma. Table I. Demographic Characteristics (N = 120) Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Characteristic  N (%)  Ethnicity      Caucasian  94 (78.3)    African-American  4 (3.3)    Hispanic  5 (4.2)    Native American  7 (5.8)    Asian  3 (2.5)    Multiracial  7 (5.8)  Age—M (SD)  21.13 (5.45)  Sex      Female  88 (73.3)  Grade level      Freshman  51 (42.5)    Sophomore  30 (25.0)    Junior  18 (15.0)    Senior+  21 (17.5)  Chronic medical conditions reported      Asthma and/or allergies  68 (56.7)    Gastrointestinal disorders (i.e., inflammatory bowel disease, irritable bowel syndrome)  23 (19.2)    Type 1 diabetes  8 (6.7)    Other (e.g., epilepsy, obesity, juvenile rheumatoid arthritis)  21 (17.5)  Note. Of those who reported that they have allergies, 55% also reported that they have asthma. Table II. Measure Average Total Scores and SDs Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. a Below community M. b Above screening clinical cutoff. Table II. Measure Average Total Scores and SDs Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Measures  M  SD  Range  Grit  03.28a  00.64  1.75–4.75  CES-D  20.37b  12.61  1.00–60.00  SAS  42.05b  10.22  25.00–70.00  EWB  58.12a  22.63  0.00–100.00  IU  61.45  16.86  23.00–99.00  II  37.45  18.14  13.00–84.00  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. a Below community M. b Above screening clinical cutoff. Preliminary Analyses Partial correlations, controlling for demographics (i.e., age, sex, race/ethnicity, and grade level), were conducted for the relationships between Grit, II, and IU, because of detectable sex differences in reporting. Specifically, student sex was significantly related to several outcomes, with females reporting higher grit (p < .05), anxiety (p < .01), IU (p < .01), and II (p < .05) than males. Grit was significantly (p < .05) correlated with all outcomes of interest (i.e., EWB, SAS, CES-D) and both mediators (i.e., II and IU). The correlation matrix can be found in Table III. Table III. Bivariate Correlations Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. * p < .05; **p < .01; ***p < .001. a Partial correlations are reported, controlling for demographic variables. Table III. Bivariate Correlations Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Variables  1  2  3  4  5  6  1. Grit  –            2. CES-D  −.29**  –          3. SAS  −.28**  .80***  –        4. EWB  .37***  −.83***  −.75***  –      5. IU  −.28*,a  .57***  .63***  −.53***  –    6. II  −.30*,a  .59***  .61***  −.43***  .57***  –  7. Age  .13  −.09  −.03  −.02  .12  −.03  8. Sex  .18*  .12  .27**  −1.3  .24**  .18*  9. Ethnicity  .08  .02  .05  .05  .00  −.06  10. Grade level  .06  −.19*  −.03  .07  .17  .01  Note. CES-D = Center for Epidemiological Studies Depression scale; EWB = emotional well-being scale; II = illness intrusiveness; IU = illness uncertainty; SAS = Self-Rating Anxiety Scale. * p < .05; **p < .01; ***p < .001. a Partial correlations are reported, controlling for demographic variables. Model Specification The a priori hypothesized model is shown in Figure 1. Although omitted from the diagram, demographic characteristics (i.e., age, gender, race/ethnicity, and grade level) were estimated on all endogenous variables (i.e., II, IU, EWB, depression, and anxiety). As depicted in the figure, we allowed the residuals of the two mediators to correlate (II and IU) and the residuals of the outcome variables (EWB, depression, and anxiety) to correlate. In total, 5,000 bias-corrected bootstrapped samples were used to test conditional and indirect effects, based on current methodological recommendations (Fritz & MacKinnon, 2007). Path Analysis A fully saturated model was estimated (χ2(4) = 6.698, p = .15; CFI = 0.993; TLI = 0.942; SRMR = 0.04; RMSEA = 0.08). Results of our analysis demonstrate that grit had a significant direct effect on depressive symptoms (β = −0.18, SE = 0.08, p < .01) and anxious symptoms (β = −0.18, SE = 0.06, p < .01) such that higher grit was associated with lower self-reported symptomatology. Grit also had a significant direct effect on EWB (β = 0.29, SE = 0.07, p < .001) such that higher levels of grit were related to higher levels of EWB. Grit also had a significant direct effect on II (β = −0.22, SE = .10, p < .05) and IU (β = −0.21, SE = 0.11, p < .05), such that higher grit was directly associated with lower II and IU. Mediated path results indicated that grit had an indirect effect on depressive symptoms through IU (β = −0.08, SE = 0.04, 95% BC [−0.18, −0.01]) and through II (β = −0.07, SE = 0.03, 95% BC [−0.15, −0.02]). Grit also had an indirect effect on anxious symptoms through IU (β = −0.08, SE = 0.04, 95% BC [−0.17, −0.01]) and II (β = −0.07, SE = 0.04, 95% BC [−0.16, −0.02]). Finally, grit had an indirect effect on EWB through IU (β = 0.07, SE = 0.04, 95% BC [0.01, 0.17]) and II (β = 0.04, SE = 0.03, 95% BC [0.01, 0.11]). These results suggest that the relationship between grit and psychological distress or well-being is partially accounted for by cognitive appraisal mechanisms, among college students with a chronic medical condition. The model without any direct effects showed adequate to poor fit (χ2(7) = 22.33, p < .01; CFI = 0.963; TLI = 0.814; SRMR = 0.05; RMSEA = 0.14). To fully assess whether the direct paths between grit and the outcomes (i.e., EWB, anxiety, and depression) should be included in the model, we compared the fit of the two nested models (one with and one without the direct paths) using the likelihood ratio test (the χ2 difference test; Bentler & Bonett, 1980). If statistically significant, the test would suggest that the constraints on the more restricted model, without the direct paths, may be too strict. Results suggested that the model with direct effects (i.e., the model in Figure 1) provides better fit to the data (χ2 (3) = 15.63, p < .01). This is consistent with our hypothesis that the direct effects would remain meaningful in the presence of the mediators. Discussion The current study evaluated the role of grit, a relatively novel construct, as a contributor to resilience among college students with a chronic medical condition, an understudied and uniquely challenged population. This study expands on previously limited literature linking grit and positive health outcomes (Reed, Pritschet, & Cutton, 2013; Sharkey et al., 2017; Graham et al., 2015), by finding that grit may indeed serve as a positive factor that is inversely related to depressive and anxious symptomatology. Higher grit was also directly associated with increased EWB, suggesting that grit may not only be related to reduced negative outcomes but is also associated with more positive adjustment outcomes. Importantly, this finding aligns with the primary tenet of positive health, which asserts that well-being, beyond the absence of negative symptoms, is a valued objective (Seligman, 2008). The overall path analysis demonstrated that the positive association between grit and psychological outcomes is partially a function of its relation with reduced negative illness appraisals (i.e., IU and II). Grit was associated with lower levels of both II and IU, and in turn, was related to decreased distress, which has been substantiated by previous studies (Szulczewski et al., 2017). Specifically, the negative effects of II and IU reported by Carpentier and colleagues (Carpentier et al., 2007) are particularly relevant to the current findings, as both studies examined samples that largely consisted of students with asthma and/or allergies. Although speculative, this suggests that having higher levels of grit may influence the manner in which individuals perceive illness-related events, which in turn may decrease the likelihood of illness-related distress. Thus, the findings foster a more nuanced understanding of the relationship between cognitive appraisals and psychological outcomes in college students with a chronic medical condition, and provide support for the cognitive pathway of Aspinwall and Pengchit’s (2013) model for the relationship between positive phenomena, such as grit, and health outcomes. The direct effects of grit on depressive/anxious symptomatology and EWB, which remained significant in the presence of the mediators, are consistent with the theoretical model and suggest the existence of additional mechanisms that might influence the relationship between grit and mental health outcomes. For instance, future research could evaluate the additive or interactive effect of social support or coping strategies on the existing model in an effort to better understand how grit operates. Furthermore, the present findings are consistent with research indicating that adolescents and young adults (AYAs) with a chronic medical condition are at risk for clinically concerning anxious and depressive symptomatology, as well as reduced well-being (Barakat & Wodka, 2006; Herts, Wallis, & Maslow, 2014). However, the current study adds to the literature, as previous studies assessed only limited demographic groups (e.g., freshman only, few illness groups, small samples), whereas the current findings are across multiple illness groups and education levels. Additionally, roughly one third to two third of the current sample reported symptomatology that exceeded screening cutoffs, with twice the rate of clinically significant depressive versus anxious symptoms and significant overlap between the two outcomes, again underscoring the heightened risk for this population. Such findings support the positive role of grit in the context of interventions aimed at fostering perseverance and passion among college students who struggle to cope with their illness (Kichler & Kaugars, 2015). Indeed, research shows that building positive states alleviates depression, and future research might reveal that building grit can reduce such negative symptomatology for young adults with a chronic medical condition (Seligman, Rashid, & Parks, 2006; Seligman, Steen, Park, & Peterson, 2005). Currently, an empirically supported grit-based intervention does not exist, but it has been theorized that cognitive-behavioral techniques, such as cognitive restructuring to address distorted expectancies for success, or values-based interventions, such as Acceptance and Commitment Therapy, might cultivate grit by helping individuals to align their actions and thoughts with the valued long-term goal of successfully managing a chronic medical condition (Eskreis-Winkler, Gross, & Duckworth, 2016; Sharkey et al., 2017). Additionally, because of the high rates of depressive symptoms in this population, universities may wish to offer general wellness programs that promote well-being among students with chronic illness. For example, a peer-mentoring model that has shown benefits for both mentors and mentees, or interventions that have targeted IU as a modifiable factor associated with distress could be implemented (Ahola Kohut, Stinson, Forgeron, Luca, & Harris, 2017; Szulczewski et al., 2017). Previous findings, from a related investigation of a sample of college students without a chronic medical condition, also demonstrated a connection between grit and health-care management skills among healthy youth, suggesting that grit may be targeted to improve self-management and medical outcomes (Sharkey et al., 2017). However, the relationship between grit and such outcomes must first be tested among pediatric illness populations to facilitate future intervention development. Alternatively, assessing grit may be more appropriately used as a screening process for identifying those at risk for negative outcomes, or to assist in determining the most advantageous treatment plans (Sharkey et al., 2017). For instance, a student with a chronic medical condition who has depressive symptoms, and a high grit score, may be likely to benefit from cognitive techniques that require a great deal of practice and determination, whereas a more behaviorally focused treatment might be of larger benefit to a student with lower levels of grit. Assessing grit may also be valuable for determining if a grit-focused component must be added to increase the efficacy of interventions that use goal-setting to improve outcomes for AYAs with chronic medical conditions (Rosenberg et al., 2015). Campus student health clinics, mental health centers, or student disability services could also use this measure to screen for students at risk or in need of specific supports. Certainly, greater research is needed to test these hypotheses and to better understand the clinical implications of grit. The findings of the current study must be considered in light of several limitations. First, causal conclusions cannot be assumed because of the study’s cross-sectional design. Longitudinal assessments within the health context are necessary to fully ascertain the role of grit. Alternative theoretical models should also be considered, as the current study did not test multiple path directions. Generalizability of the present findings are limited, as our sample was not ethnically diverse and was collected from a single university. As females reported higher levels of grit and greater psychological problems, generalizability to male college students may also be limited. Although the heterogeneity of the diagnoses in our sample could be considered to have bolstered the generalizability of our findings across illness groups, the role of grit should still be tested among specific diagnostic populations, as research has shown that the effect of certain variables may differ across illness groups (Mullins et al., 2017). In particular, as our study relied on self-report measures and lacked information regarding illness severity, findings may differ for clinic-based populations. Confirmation of diagnoses and medical chart reviews conducted with campus student health services could improve future study designs by providing objective medical data. Although the current study provides support for the role of grit among young adults with chronic medical conditions, the developmental trajectory of grit is not well-established, and investigations of grit in younger pediatric populations are needed. Further, the incremental validity of grit within the pediatric psychology literature could not be established by the current study. Comparisons between grit and other commonly tested positive personal assets, such as self-efficacy and self-control, are necessary to determine the added value of grit. Despite these limitations, the current examination broadens the understanding of the role of grit within the context of health and illness. Taken together, the findings suggest that grit is an understudied positive factor among college students with a chronic medical condition, and has the potential to be a target of intervention focused on aiding those who are struggling to manage their health. Future research is warranted to explore the role of grit in reducing distress and promoting well-being among pediatric illness populations. Acknowledgments The authors would like to thank the participants and research assistants for their time and contributions to this study. Funding This study was approved by the institutional review board, and all procedures were in compliance with APA ethical standards. Conflicts of interest: None declared. References Ahola Kohut S., Stinson J., Forgeron P., Luca S., Harris L. ( 2017). 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Journal of Pediatric PsychologyOxford University Press

Published: Dec 12, 2017

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