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. 2023 Oct 4;48(11):952–959. doi: 10.1093/jpepsy/jsad066

Grit and Health-Related Quality of Life in Adolescents and Young Adults with Cancer: Mediating Role of Health Self-Efficacy and Treatment Adherence

Elise R McKelvey 1,2, Nataliya Zelikovksy 3, Alexandra M Psihogios 4,✉
PMCID: PMC10653349  PMID: 37794751

Abstract

Objective

Challenges with health-related quality of life (HRQOL) are common among adolescents and young adults (AYA) with cancer. Literature on HRQOL has largely been focused on individual deficits, rather than individual strengths. The present study investigated the relations between a strengths-based concept called grit (i.e., perseverance and passion for long-term goals), self-management (i.e., health self-efficacy and adherence), and HRQOL among AYA with cancer.

Methods

Sixty-seven AYA receiving cancer treatment (Mage=17.1; 50.7% female; 25.4% Black, Hispanic, Asian, or a race other than white) and their caregivers (73.0% mothers) completed a semistructured, validated interview about adherence. AYA also completed self-report questionnaires about perceptions of their grit, health self-efficacy, and HRQOL.

Results

After controlling for sex, health self-efficacy (i.e., a cognitive self-management variable) mediated the relation between grit and HRQOL (95% confidence interval = .74–6.52). When testing adherence to medications, diet, or physical activity as mediators of the relation between grit and HRQOL, mediation models were non-significant.

Conclusions

Among AYA with cancer, this study identified grit as an individual strength associated with more positive self-management beliefs, which in turn, related to better HRQOL. This adds to a growing body of literature supporting the need for resiliency-oriented, strengths-based approaches to AYA HRQOL research. Future directions include exploring the role of caregiver grit in relation to AYA cancer self-management, given that caregivers have demonstrated a high degree of involvement in AYA cancer care.

Keywords: adherence, AYA, cancer, grit, self-efficacy

Introduction

Each year, over 90,000 adolescents and young adults (AYA; ages 15-39 years old) are diagnosed with cancer (Close et al., 2019). A developmental period dedicated to forming close peer bonds and romantic relationships, pursuing academics/work, establishing autonomy, and advancing identity development now also involves navigating a complicated medical regimen of frequent hospital and clinic visits, chemotherapy/radiation, symptom management, lifestyle changes (e.g., diet and physical activity), and multiple medications (Hullmann et al., 2015). Health-related quality of life (HRQOL) is a multidimensional construct of the impact of chronic disease and treatment on a patient’s overall functioning and well-being (Varni et al., 2002). Compared to older adults with cancer and healthy age-matched peers, AYA with cancer report worse physical, psychological, social, and spiritual HRQOL (Lang et al., 2015). These HRQOL challenges can impact other areas of AYA life, including greater disruption to work/education goals and increased financial burden (Close et al., 2019). Researchers have identified both behavioral (e.g., treatment adherence) and cognitive (e.g., health self-efficacy) factors that are associated with HRQOL problems in this population (Hoyt et al., 2013; Psihogios et al., 2020). However, much of this research has been deficit-focused—neglecting how individual strengths can positively influence HRQOL during cancer. Moreover, exploration of the interrelations among these cognitive and behavioral processes and HRQOL is lacking. To address these gaps, the present study investigated relations between a positive psychology construct called grit, treatment adherence, health self-efficacy, and HRQOL among AYA receiving cancer treatment.

Grit, defined as perseverance and passion for long-term goals (Duckworth et al., 2007), is a contemporary positive psychology construct that has only recently been applied to chronic illness populations. Grit has been associated with success in a variety of domains, including academics (Cosgrove et al., 2018), military training (Duckworth et al., 2007), job retention (Eskreis-Winkler et al., 2014) and physical activity (Dunston et al., 2022). Grit appears to be modifiable, as interventions have successfully enhanced the grit of adolescents through structured mentoring programs (Major, 2013), intentional reflections on past failures (DiMenichi & Richmond, 2015), education about grit, goal-setting, and intentional practice (Song, 2019).

Among AYA without chronic illness, grit has been positively associated with indices of psychological well-being (Datu et al., 2019; Salles et al., 2014; Vainio & Daukantaitė, 2016), health care management skills, and HRQOL (Sharkey et al., 2017). Grit’s relations to well-being and success have been less studied in medically complex populations. In a sample of college-attending AYA with various chronic health conditions (<2% with cancer), greater grit was linked to better health care management skills and better mental and physical HRQOL, suggesting a possible mechanism for HRQOL (Traino et al., 2019). While grit has never been studied in AYA with cancer, the emphasis on maintaining effort over years despite failures, adversity, or plateaus in progress has conceptual relevance for a few reasons. First, cancer treatment can be lengthy and requires perseverance in disease management, as is the case for AYA with acute lymphoblastic leukemia who undergo intensive treatment and then must maintain a high degree of adherence to a daily oral chemotherapy regimen for approximately 18 months to prevent relapse (Bhatia et al., 2012, 2014). Second, across cancer diagnoses, treatments and their associated side effects can fluctuate (Leahy et al., 2018), requiring perseverance (e.g., with adherence, self-efficacy) through bouts of high symptom burden and periods of medical uncertainty. Third, AYA with cancer experience disruptions in their goals and autonomy, requiring effort to maintain developmental momentum during cancer treatment (Schwartz and Drotar, 2009). It has also been argued that successful disease self-management should move past the simple reduction of symptoms or psychological distress and toward human flourishing (e.g., meaning-making and valued action while managing one’s disease; Seligman, 2008).

The present study is the first to investigate grit in a disease-specific cohort of AYA with cancer—a group at risk for poor treatment adherence (adherence rates ranging from 21% to 60%; McGrady & Pai, 2019) and worse HRQOL (Lang et al., 2015). Guided by the Pediatric Self-Management Model (Modi et al., 2012)—a social-ecological self-management model that posits multi-level self-management factors (e.g., individual beliefs, caregiver/family functioning) influence health behaviors (e.g., medication adherence), and in turn, impact health outcomes (i.e., HRQOL)—we first aimed to study the bivariate relations between grit and a cognitive self-management variable (health self-efficacy), a behavioral self-management variable (treatment adherence), and a self-management outcome (HRQOL). While recent studies of AYA with chronic health conditions have linked personality to disease self-management (Quast et al., 2020), dispositional characteristics are an important individual-level variable currently omitted from the Pediatric Self-Management Model. Consequently, this study is also informed by Aspinwall and Pengchit’s (2013) Positive Health Psych Model which emphasizes how strength-based dispositional pathways may influence health outcomes (i.e., HRQOL) through mechanisms including cognitions and health behaviors. Higher self-reported grit was hypothesized to be associated with better health self-efficacy, adherence, and HRQOL. Because screening of potential mediating factors would advance our understanding of the mechanisms through which grit relates to HRQOL in AYA with cancer, in a secondary aim, we investigated if the relation between grit and HRQOL was mediated by treatment adherence or health self-efficacy. It was hypothesized that individuals with higher grit would report better adherence and better health self-efficacy, indirectly leading to better HRQOL.

Method

Participants and Procedures

This study involved secondary analysis of data from a cross-sectional, mixed methods study conducted in the Cancer Center at The Children’s Hospital of Philadelphia (CHOP; Psihogios et al., 2020). CHOP’s Institutional Review Board approved the original study involving AYA receiving treatment for cancer, their primary caregiver, and oncology clinicians. La Salle University’s IRB approved the use of archival data for current analyses. The data are available at request. Only AYA self-reported survey data and AYA-caregiver joint reports of medical adherence were used for the current study. Participants were recruited in person during an oncology clinic visit, during an inpatient admission, or via phone. Inclusion criteria for AYA were as follows: (1) aged 14–24 (guided by the NCI definition of AYA but adjusted to capture the younger age range of AYA receiving cancer treatment at CHOP); (2) actively receiving cancer treatment (chemotherapy and/or radiation) with curative intent for leukemia/lymphoma, solid tumor, or brain tumor; (3) diagnosed ≥1 month ago; and (4) English language literacy. AYA were excluded if they had cognitive impairments that would limit their ability to complete study measures. Eligible participants were identified through the hospital’s tumor registry and by screening the electronic health record (EHR). After study objectives and procedures were thoroughly explained, informed consent (assent for AYA <18 years old) was obtained. AYA participants completed a series of questionnaires via REDCAP and AYA-caregiver dyads completed a validated, semistructured adherence interview together. There was no monetary compensation for participation. Below, we describe the measures that were utilized in this study.

Measures

Disease Factors and Health Insurance Status

Reviews of each AYA’s EHR were conducted to identify cancer diagnosis (categorized as leukemia/lymphoma, solid tumor, brain tumor), days after initial cancer diagnosis, and primary health insurance (categorized as public or private). The Intensity of Treatment Rating 3.0 (Kazak et al., 2012) was completed by a pediatric oncologist to categorize treatment intensity (least, moderate, very, or most intense).

Demographic Survey

AYA reported on their own sex, age, race, and ethnicity on demographic questionnaires.

Short Grit Scale (Grit-S)

Grit-S is an eight-item self-report measure designed to assess trait-level perseverance and passion for long-term goals (Duckworth & Quinn, 2009). Participants were instructed to indicate how true an item is for them, with answers on a 5-point Likert-type scale ranging from 1 (very much like me) to 5 (not like me at all) with half of the items reverse scored. Total score is calculated as the mean of all eight items. A higher score is reflective of greater grit. In the current study, internal consistency for Grit-S was acceptable (α = .75).

Health Competence Beliefs Inventory

The Health Competence Beliefs Inventory (HCBI) (DeRosa et al., 2011) is a measure of health self-efficacy validated in a large study of AYA survivors of childhood cancer. This 21-item self-report measure assesses AYA’s health-related competence beliefs across four subscales: (1) Health Perceptions—current health status and perceived likelihood of future illness, reflecting anxieties about health; (2) Satisfaction With Healthcare—satisfaction with the health care team’s ability to understand and take care of them; (3) Cognitive Competence—the ability to learn information relative to their peers; (4) Autonomy—independence from parents, in a medical setting and more generally. A total score was derived from the sum of the four factors, and internal consistency was acceptable (α=.68). Responses on a 4-point scale range from 1 (strongly disagree) to 4 (strongly agree), with higher scores representing more adaptive health competence beliefs.

Medical Adherence Measure

The Medical Adherence Measure (MAM) is a valid and reliable semistructured interview assessing multiple domains of medical adherence. It has been widely used in pediatric solid organ transplant, generalized to other disease groups, and shown strong convergent validity with health outcomes such as rejection episodes (Plevinsky et al., 2020; Zelikovsky & Schast, 2008). For the current study, modules on medication, physical activity, and nutrition were used. EHR review was conducted before administering the MAM to determine all prescribed treatments (by reviewing current medication lists, the most recent clinic notes from oncologists, nutritionists, and physical/occupational therapists). Since diet and physical activity prescriptions were not consistently documented, we also relied on reporter recall. Together, AYA and caregivers reported the number of missed doses for each prescribed daily medication (which included oral chemotherapies, prophylactic antibiotics, and supportive medications that were prescribed daily, such as Zofran for nausea), as well as the number of days the AYA fulfilled diet (e.g., increase caloric intake) and physical activity (e.g., physical therapy) recommendations over the past week. Dyads answered questions jointly. Disagreements about adherence between AYA and caregivers were rare, but when they occurred, the interviewer encouraged further discussion until an agreement was reached.

Adherence was calculated by dividing the number of days per week AYA fulfilled recommendations and multiplied by 100 to obtain percent adherence for each domain. In the current sample, approximately half of the participants reported 100% adherence to medication and diet, which raises concerns for the ceiling effects. Consequentially, adherence was dichotomized into “Perfect” (100% adherent) and “Imperfect” (<100%) for each of the three adherence tasks. This approach is consistent with prior studies (Eaton et al., 2018; Hullmann et al., 2015) and captures participants who were having any difficulty with adherence.

Pediatric Quality of Life Inventory Cancer Module Scales (Peds-QL)

HRQOL was measured via the widely used Peds-QL (Varni et al., 2002). This cancer-specific measure of quality of life is composed of 27 items assessing eight domains: Pain, Nausea, Procedural Anxiety, Treatment Anxiety, Worry, Cognitive Problems, Perceived Physical Appearance, and Communication. Participants reported how much of a problem each item has been for them over the past month on a 5-point Likert-type scale from 0 (never) to 4 (almost always). All responses were reverse coded. A mean score is obtained for each domain. The total score is the mean of all items. Higher scores indicate fewer problems or a better quality of life. The total score’s internal consistency in the current sample was .96.

Data Analysis

Assuming an alpha level of .05, power of .80, and an estimated R2 of .15 (a medium effect size), a post hoc power analysis confirmed the sample size of 67 AYAs adequately powered the following analyses with two predictors and one covariate (G*Power 3.1; Faul et al., 2007). Using the Statistical Package for Social Sciences software program (SPSS Version 24), preliminary analyses were conducted to examine the relations among the variables of interest and AYA demographic/disease variables. T-tests and analysis of variance (ANOVA) were used to examine categorical variables (sex, ethnicity, specific diagnoses), whereas correlational analyses were used to examine continuous variables (age, time since diagnosis). AYA demographic/disease variables that were significantly related to the outcome variable (HRQOL) were included as covariates in the subsequent mediation models. We also explored if AYA in this study reported similar mean grit scores to those reported in other studies of AYA with chronic health conditions other than cancer (Sharkey et al., 2018; Traino et al.,2019). Bivariate correlations and ANOVAS were used to determine the associations between grit and HRQOL, health self-efficacy, and treatment adherence (i.e., diet, medications, and physical activity). To determine if health self-efficacy mediated the relation between grit and HRQOL, a mediation analysis with bootstrapping was conducted using the SPSS macro PROCESS (Hayes, 2022). The three mediation models testing “Perfect” (100% adherent) versus “Imperfect” (<100%) medication, diet, or physical activity adherence were analyzed using mPlus with bootstrapping (Muthén & Muthén, 2010) because the PROCESS macro is not equipped to examine binary mediators.

Results

The final study sample who completed all measures consisted of 67 AYA participants aged 14–24 (M = 17.1) on active treatment for cancer and their matched caregivers (n = 67; 73.0% Mothers). The majority of AYA were female (50.7%) and 25.4% identified as Black, Hispanic, Asian, or a race other than white (Table I). Cancer diagnoses of participants in the study included leukemia/lymphoma (50.7%), solid tumor (22.4%), and brain tumor (26.9%). Intensity of treatment was rated as 1 (1.6%; least intense), 2 (18.8%), 3 (62.5%), or 4 (17.2%; most intense) by a pediatric oncologist. Of 67 participants, prescribed treatments included medication(s) (98.4%), diet (74.6%), and physical activity (53.7%).

Table I.

Means, Standard Deviations, and Ranges for AYA Demographic and Study Variables

Variables N (%) M SD Min–Max
Agea 67 17.10 2.54 14–24
Days since diagnosisc 67 491.22 924.57 33–6391
Sex (female)a 34 (50.7%) – – –
Cancer typec 67 – – –
 Leukemia/lymphoma 34 (50.7%) – – –
 Solid tumor 15 (22.4%) – – –
 Brain tumor 18 (26.9%) – – –
Intensity of treatment ratingc 64
 1 1 (1.6%)
 2 12 (18.8%)
 3 40 (62.5%)
 4 11 (17.2%)
Racea 67 – – –
 White 52 (77.6%) – – –
 Asian 4 (6.0%) – – –
 Black 8 (11.9%) – – –
 Other 3 (4.5%) – – –
Ethnicity (non-Hispanic)a 63 (94.0%) – – –
Perfect medication adherenceb 29 (46.0%)
Perfect diet adherenceb 26 (52.0%)
Perfect physical activityb Adherence 14 (38.9%)
Grit-Sa 67 3.53 .59 2.50–4.71
HRQOLa 67 69.00 12.48 27.78–93.52
HCBIa 67 57.34 7.01 38.00–77.00
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Note. HCBI = health competence belief inventory; HRQOL = health-related quality of life; SD = standard deviation.

a

AYA report.

b

AYA-caregiver joint report.

c

Based on oncologist rating and/or chart review; Total N for each adherence variable varied due to differing treatment recommendations (medication N = 63; nutrition N = 50; physical activity N = 36). Measure ranges: Grit-S (1–5); HRQOL (0–100); HCBI (21–84).

Preliminary Demographic/Disease Analyses

Grit

A one-way ANOVA showed that there was a significant difference in AYA self-reported grit between diagnosis types (F(2, 64)=3.25, p =.04), with brain tumor patients reporting greater perceived grit (M = 3.81) than leukemia/lymphoma patients (M = 3.39) and solid tumor patients (M = 3.49). There was also a significant difference in time since diagnosis between diagnosis types (F(2, 64)=3.84, p=.03) with brain tumor patients reporting the greatest time since diagnosis (M = 965.89 days), followed by leukemia/lymphoma patients (M = 383.76 days) and solid tumor patients (M = 165.20 days). AYA who self-identified as Black, Hispanic, Asian, or a race other than white reported significantly lower grit (M = 3.27) than non-Hispanic white- identifying AYA (M = 3.61; t(65)=−2.11, p =.04). All other demographic/disease variables (i.e., age, primary health insurance type, and intensity of treatment) were not significantly related to grit (p’s>.05). Descriptively, average AYA-reported grit in this cancer sample (M = 3.53) was comparable to averages reported among AYA with various chronic health conditions (M = 3.28; Sharkey et al., 2018; M = 3.29; Traino et al., 2019).

Adherence

Chi-square tests were performed to examine the relation between AYA sex and the categorical “Perfect” or “Imperfect” adherence variables (to medications, diet, and physical activity). There was not a significant difference in adherence to medication by sex, χ2 (1, N = 63) =.77, p > .05. However, there was a significant relation between sex and adherence to diet and physical activity. Males were more likely to report “Imperfect” adherence to physical activity recommendations (χ2 (1, N = 36) = 6.22, p = .01) and females were more likely to report “Imperfect” adherence to diet recommendations (χ2 (1, N = 50) = 3.98, p = .046).

AYA who self-identified as Black, Hispanic, Asian, or race other than white were more likely to report “Imperfect” adherence to physical activity (χ2 (1, N = 36) = 4.86, p = .03) compared to white, non-Hispanic AYA. There were no significant differences in adherence to diet or medication between these two groups. All other demographic/disease variables (i.e., age, time since diagnosis, diagnosis type, primary health insurance type) were not significantly associated with the three categorical adherence variables (p’s>.05).

Health Self-Efficacy

No demographic/disease variables (i.e., age, sex, race, ethnicity, time since diagnosis, diagnosis type, primary health insurance type, and intensity of treatment) were significantly associated with health self-efficacy beliefs.

HRQOL

Female AYA reported significantly worse HRQOL (M = 64.82) than males (M = 73.29; t(65)=−2.93, p <.01). Consequently, AYA sex was controlled for in mediation analyses since HRQOL was the primary outcome. All other study demographic or disease variables were non-significant (p’s>.05).

Bivariate Relations Between Grit, Health Self-Efficacy, Adherence, and HRQOL

Higher AYA-reported health self-efficacy beliefs were associated with both greater grit (r =.27, p <.05) and better HRQOL (r =.54, p<.01; see Table II). AYA with “Perfect” medication adherence in the past week reported better HRQOL (M = 74.26) than those with “Imperfect” adherence (M = 65.22; t(61)=3.06, p =.003). “Perfect” adherence to diet and physical activity were not significantly associated with HRQOL. Contrary to hypotheses, grit was not significantly associated with HRQOL or “Perfect adherence” across the three tasks of medications, diet, or physical activity (p’s> .05).

Table II.

Pearson Correlations for Continuous AYA Demographic and Study Variables

Variables 1. 2. 3. 4. 5.
1. Age (AYA) 1
2. Days since diagnosis (AYA) .31* 1
3. Grit-S (AYA report) .10 −.05 1
4. HCBI (AYA report) .22 .20 .27* 1
5. HRQOL (AYA report) −.06 .01 −.02 .54** 1
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Notes. HCBI = health competence belief inventory; HRQOL = health-related quality of life.

*

p < .05.

**

p < .01.

Mediation Models

Health Self-Efficacy

After controlling for AYA sex, grit was positively related to health self-efficacy beliefs that related to higher HRQOL, as evidenced by the indirect effect of the confidence interval (CI) not containing zero, 95% CI (.74–6.52). Figure 1 shows the mediation model and identifies the bootstrapped estimate of the indirect effect and unstandardized B weights for path coefficients.

Figure 1.

Figure 1.

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Cross-sectional mediation model for grit predicting health self-efficacy and HRQOL. Note. Controlled for sex. Path coefficients are unstandardized B weights. Estimate of the indirect effect = (3.40*); bootstrapped at 95% confidence interval = (.74–6.52). *p < .05, **p < .01.

Medication Adherence

While controlling for sex, the indirect effect of grit on HRQOL through the binary medication adherence variable (“Perfect” vs. “Imperfect” in the past week) was non-significant as evidenced by the indirect effect of the CI containing zero, 95% CI (−2.35 to 3.77).

Physical Activity Adherence

Controlling for sex, the indirect effect of grit on HRQOL through the binary physical activity adherence variable (“Perfect” vs. “Imperfect” in the past week) was non-significant as evidenced by indirect effect of the CI containing zero, 95% CI (−4.07 to 4.30).

Diet Adherence

While controlling for sex, the indirect effect of grit on HRQOL through the binary diet adherence variable (“Perfect” vs. “Imperfect” in the past week) was non-significant as evidenced by the indirect effect of the CI containing zero, 95% CI (−2.05 to 3.55).

Discussion

The current study represents the first to evaluate grit in relation to AYA self-management constructs (health self-efficacy, adherence, and HRQOL) during cancer treatment. Strengths of this study included the use of evidence-based theories of disease self-management (Modi et al., 2012) and positive health psychology (Aspinwall & Pengchit, 2013) as well as the use of dyads to report adherence behaviors. Consistent with our study hypothesis and prior research (e.g., Cho et al., 2018), we found a significant correlation between grit and health self-efficacy, suggesting AYA with higher self-reported grit also endorsed more adaptive beliefs about their self- management abilities. A mediation analysis then revealed that grit indirectly related to HRQOL through perceived health self-efficacy. This is consistent with previous research on academic outcomes in which self-efficacy mediated the relation between grit and academic success (Wolters & Hussain, 2015). Still, contrary to our hypothesis and previous research by Peña et al. (2019), grit did not relate to adherence to medications, diet, or physical activity. Together, these findings contribute to a growing and likely necessary shift toward incorporating resiliency-oriented, strength-based characteristics and approaches into AYA self-management clinical research and interventions, including interventions aimed at improving HRQOL during cancer treatment (e.g., Rosenberg et al., 2018, 2019).

Although grit was not directly associated with HRQOL, we determined that health self-efficacy mediated the relation between grit and HRQOL. This finding is salient because AYA have reported poor HRQOL during cancer treatment (Lang et al., 2015), which persisted for up to five years after cancer treatment (Husson et al., 2017). Moreover, Sansom-Daly et al. (2012) state interventions aimed at improving HRQOL have not yielded consistent benefits and suggest that HRQOL interventions are more likely to be efficacious when measuring positive adjustment or resiliency factors rather than symptom reduction alone. Indeed, an RCT where the intervention group was receiving resiliency skills training showed improvements in benefit finding, resilience, cancer-specific quality of life, and psychological distress (Rosenberg et al., 2018, 2019). Ishibashi et al. (2016) found that developing a sense of purpose—a strength factor of the adolescent resilience model—was associated with resilience in AYA with newly diagnosed cancer. Interventions aimed at improving grit have demonstrated success in fostering a growth mindset, perseverance, and self-control, and include intervention targets such as facing “intense moments of choice” with mentorship, engaging in deliberate practice, and goal-setting (Alan et al., 2019; Major, 2013; Song, 2019). While longitudinal research is needed to understand how grit relates to AYA health beliefs and HRQOL over time, it is possible that incorporating these targets into HRQOL interventions may be beneficial for AYA with cancer.

In this study, grit was not significantly correlated with adherence to cancer-related medications, diet recommendations, or physical activity recommendations, nor did adherence mediate a relation between grit and HRQOL. This was contrary to one study that found a relation between grit and adherence (Peña et al., 2019), though notably, this was in an older population of adults who had been managing diabetes for an average of 17 years. Another important difference is that the caregivers of AYA with cancer are highly involved in adherence tasks. In this study, 73.2% of AYA reported their caregiver has primary responsibility for managing medication (Psihogios et al., 2020). Perhaps, the parent’s “grittiness” may be more relevant to adherence, and investigating the relations between parental grit and adherence is a potential future direction.

We acknowledge that the construct of grit has received its fair share of criticism when interpreted and applied in such a way that suggests individuals can only succeed if they “will” themselves into working harder than their peers. This interpretation of grit fails to account for systemic inequities faced by marginalized groups that limit opportunities for success. In the present study, AYA who identified as Black, Hispanic, Asian, or a race other than white reported significantly lower grit than non-Hispanic white participants; however, it is important to note that setting long-term goals and steadily working in pursuit of those goals is often a privilege reserved for those whose progress is not impeded by structural racism, poverty, discrimination, and health care access inequities. Given that AYA who identify as Black or Hispanic have demonstrated lower adherence to critical cancer treatments (e.g., oral chemotherapies; Bhatia et al., 2012, 2014) and worse cancer survival outcomes (Miller et al., 2020), it is important to better understand how relevant the concept of grit is to youth of color. As a first step, future research could employ qualitative methods with AYA to understand the relevance of grit to their personal experiences and what they are passionate about and preserving toward during cancer treatment.

Study findings should be interpreted within the context of key study limitations. First, due to the cross-sectional nature of these data, causal inferences cannot be made. For example, it is possible that grit influenced health self-efficacy during cancer, or health self-efficacy influenced perceptions of grit. Likewise, the use of cross-sectional data to test for mediation is not ideal but helped provide preliminary evidence about an HRQOL mechanism to evaluate in future longitudinal studies. Second, participants in the sample were primarily middle class, non-Hispanic White. Future research should address these limitations through including a more diverse and larger sample, such as including Spanish-speaking AYA and caregivers. Third, the measure of adherence in this study relied on AYA and caregiver self-report (rather than objective measures such as electronic medication monitors or actigraphy), which may be impacted by recency and social desirability biases (i.e., adherence ratings may have been inflated). This limitation is lessened by using a validated adherence assessment measure that assesses adherence in a short timeframe and prior results that adherence was not correlated with a measure of social desirability (Psihogios et al., 2020). Also related to measurement, our reliance on AYA self-report was not ideal (posing a risk for common method variance) and there may have been conceptual overlap between the HCBI Health Perceptions subscale and the Peds-QL. However, these constructs are theoretically distinct and have been analyzed as unique variables in prior studies (e.g., Black et al., 2023). Fourth, the sample was heterogeneous regarding cancer type, time since diagnosis, and AYA age– which could be considered both a strength (few studies have focused on AYA cancer self-management broadly, beyond adherence to oral chemotherapy), but also a limitation. Future studies investigating grit in the context of AYA cancer self-management could consider narrowing inclusion criteria to cancers that have more homogenous treatment demands. Finally, it is possible that dichotomizing adherence to address ceiling effects resulted in the loss of important variability in adherence behaviors. Clinical cut points for “good enough” adherence for all medications or tasks like physical activity are currently lacking. The smaller sample sizes observed for diet and physical activity recommendations reflect, in part, limited standardization of how diet and physical activity are prescribed, documented, and routinely assessed during pediatric cancer treatment.

In summary, select study findings aligned with Aspinwall and Pengchit’s (2013) model of positive health psychology, which states that positive psychology constructs, such as grit, have links to biological, cognitive, coping, social, and behavioral processes that ultimately influence health outcomes (i.e., HRQOL). While we found the cognitive pathway (i.e., health self-efficacy) was associated with HRQOL, the relation between behavioral adherence and HRQOL was non-significant. Caregiver grit may be an important factor to consider in future work as the family context is critical for pediatric self-management (Modi et al., 2012), and AYA in this sample had a high degree of parental involvement in their medical regimen (Psihogios et al., 2020). Together, including strengths-based constructs, such as grit, in future studies may help to reveal novel targets for HRQOL interventions that move past symptom reduction toward helping AYA flourish in the context of a cancer diagnosis.

Acknowledgments

The authors thank the participating AYA and their caregivers, as well as Bryn Czerniecki, Kylie Ewing, Heather Fellmeth, and Yael Gross for their support with study recruitment.

Contributor Information

Elise R McKelvey, Children’s Hospital of Philadelphia, USA; La Salle University, USA.

Nataliya Zelikovksy, La Salle University, USA.

Alexandra M Psihogios, Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, USA.

Author Contributions

Elise R. McKelvey (Conceptualization [lead], Data curation [lead], Formal analysis [lead], Investigation [equal], Methodology [equal], Writing—original draft [lead], Writing—review & editing [lead]), Nataliya Zelikovsky (Conceptualization [supporting], Supervision [supporting], Writing—review & editing [supporting]) and Alexandra Psihogios (Conceptualization [equal], Data curation [equal], Funding acquisition [lead], Investigation [equal], Methodology [equal], Writing—review & editing [supporting])

Funding

This work was supported by grants from the American Cancer Society (PF-16-166-01-CPPB; ACS IRG-21-144-27) and the National Cancer Institute (NCI K08CA241335) awarded to Alexandra Psihogios, PhD.

Conflicts of interest

None declared.

References

  1. Alan S., Boneva T., Ertac S. (2019). Ever failed, try again, succeed better: results from a randomized educational intervention on grit. The Quarterly Journal of Economics, 134, 1121–1162. 10.1093/qje/qjz006. [DOI] [Google Scholar]
  2. Aspinwall L. G., Pengchit W. (2013). Positive psychology. In: Gellman M. D., Turner J. R. (Eds.) Encyclopedia of behavioral medicine (pp. 1511–1517). Springer. https://doi.org/gpkj [Google Scholar]
  3. Bhatia S., Landier W., Hageman L., Kim H., Chen Y., Crews K. R., Evans W. E., Bostrom B., Casillas J., Dickens D. S., Maloney K. W., Neglia J. P., Ravindranath Y., Ritchey A. K., Wong F. L., Relling M. V. (2014). 6MP adherence in a multiracial cohort of children with acute lymphoblastic leukemia: A children's oncology group study. Blood, 124(15), 2345–2353. 10.1182/blood-2014-01-552166 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bhatia S., Landier W., Shangguan M., Hageman L., Schaible A. N., Carter A. R., Hanby C. L., Leisenring W., Yasui Y., Kornegay N. M., Mascarenhas L., Ritchey A. K., Casillas J. N., Dickens D. S., Meza J., Carroll W. L., Relling M. V., Wong F. L. (2012). Nonadherence to oral mercaptopurine and risk of relapse in Hispanic and non-Hispanic white children with acute lymphoblastic leukemia: A report from the children's oncology group. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 30(17), 2094–2101. https://doi.org/f32w4b [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Black L. L., Peugh J. L., Pai A. L. (2023). Health competence beliefs and health-related quality of life among adolescent and young adult survivors of childhood cancer and Healthy peers. Journal of Adolescent and Young Adult Oncology.   10.1089/jayao.2022.0162 [DOI] [PubMed] [Google Scholar]
  6. Cho S. H., Yun K. S., Jung S. (2018). Factors influencing self-efficacy, grit, symptom clusters on self-care agency in brain neoplasms patients. Asian Oncology Nursing, 18(4), 188. 10.5388/aon.2018.18.4.188 [DOI] [Google Scholar]
  7. Close A. G., Dreyzin A., Miller K. D., Seynnaeve B. K. N., Rapkin L. B. (2019). Adolescent and young adult oncology—Past, present, and future. CA: A Cancer Journal for Clinicians, 69(6), 485–496. 10.3322/caac.21585 [DOI] [PubMed] [Google Scholar]
  8. Cosgrove J. M., Chen Y. T., Castelli D. M. (2018). Physical fitness, grit, school attendance, and academic performance among adolescents. BioMed Research International, 2018, 9801258–9801257. 10.1155/2018/9801258 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Datu J. A. D., King R. B., Valdez J. P. M., Eala M. S. M. (2019). Grit is Associated with lower depression via meaning in life among Filipino high school students. Youth & Society, 51(6), 865–876. 10.1177/0044118X18760402 [DOI] [Google Scholar]
  10. DeRosa B. W., Kazak A. E., Doshi K., Schwartz L. A., Ginsberg J., Mao J. J., Straton J., Hobbie W., Rourke M. T., Carlson C., Ittenbach R. F. (2011). Development and validation of the Health Competence Beliefs Inventory in young adults with and without a history of childhood cancer. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 41(1), 48–58. 10.1007/s12160-010-9228-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. DiMenichi B. C., Richmond L. L. (2015). Reflecting on past failures leads to increased perseverance and sustained attention. Journal of Cognitive Psychology, 27(2), 180–193. https://doi.org/jc3s [Google Scholar]
  12. Duckworth A. L., Peterson C., Matthews M. D., Kelly D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101. 10.1037/0022-3514.92.6.1087 [DOI] [PubMed] [Google Scholar]
  13. Duckworth A. L., Quinn P. D. (2009). Development and validation of the Short Grit Scale (Grit–S). Journal of Personality Assessment, 91(2), 166–174. https://doi.org/ch7rk8 [DOI] [PubMed] [Google Scholar]
  14. Dunston E. R., Messina E. S., Coelho A. J., Chriest S. N., Waldrip M. P., Vahk A., Taylor K. (2022). Physical activity is associated with grit and resilience in college students: Is intensity the key to success?  Journal of American College Health, 70(1), 216–222. https://doi.org/gpkc [DOI] [PubMed] [Google Scholar]
  15. Eaton C. K., Gutierrez-Colina A. M., Quast L. F., Liverman R., Lee J. L., Mee L. L., Reed-Knight B., Cushman G., Chiang G., Romero R., Mao C., Garro R., Blount R. L. (2018). Multimethod assessment of medication nonadherence and barriers in adolescents and young adults with solid organ transplants. Journal of Pediatric Psychology, 43(7), 789–799. 10.1093/jpepsy/jsy016 [DOI] [PubMed] [Google Scholar]
  16. Eskreis-Winkler L., Duckworth A. L., Shulman E. P., Beal S. (2014). The grit effect: Predicting retention in the military, the workplace, school and marriage. Frontiers in Psychology, 5, 36. 10.3389/fpsyg.2014.00036 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Faul F., Erdfelder E., Lang A.-G., Buchner A. (2007). GPower 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. 10.3758/BF03193146 [DOI] [PubMed] [Google Scholar]
  18. Hayes A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. (3rd edn).  The Guilford Press. [Google Scholar]
  19. Hoyt M. A., Cano S. J., Saigal C. S., Stanton A. L. (2013). Health-related quality of life in young men with testicular cancer: Validation of the Cancer Assessment for Young Adults (CAYA). Journal of Cancer Survivorship, 7(4), 630–640. https://doi.org/f5jhsc [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hullmann S. E., Brumley L. D., Schwartz L. A. (2015). Medical and psychosocial associates of nonadherence in adolescents with cancer. Journal of Pediatric Oncology Nursing: Official Journal of the Association of Pediatric Oncology Nurses, 32(2), 103–113. 10.1177/1043454214553707 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Husson O., Zebrack B. J., Block R., Embry L., Aguilar C., Hayes-Lattin B., Cole S. (2017). Health-related quality of life in adolescent and young adult patients with cancer: A longitudinal study. Journal of Clinical Oncology, 35(6), 652–659. 10.1200/JCO.2016.69.7946 [DOI] [PubMed] [Google Scholar]
  22. Ishibashi A., Okamura J., Ueda R., Sunami S., Kobayashi R., Ogawa J. (2016). Psychosocial strength enhancing resilience in adolescents and young adults with cancer. Journal of Pediatric Oncology Nursing: Official Journal of the Association of Pediatric Oncology Nurses, 33(1), 45–54. https://doi.org/gpkf [DOI] [PubMed] [Google Scholar]
  23. Kazak A. E., Hocking M. C., Ittenbach R. F., Meadows A. T., Hobbie W., DeRosa B. W., Leahey A., Kersun L., Reilly A. (2012). A revision of the intensity of treatment rating scale: Classifying the intensity of pediatric cancer treatment. Pediatric Blood & Cancer, 59(1), 96–99. 10.1002/pbc.23320 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lang M. J., David V., Giese-Davis J. (2015). The age conundrum: A scoping review of younger age or adolescent and young adult as a risk factor for clinical distress, depression, or anxiety in cancer. Journal of Adolescent and Young Adult Oncology, 4(4), 157–173. 10.1089/jayao.2015.0005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Leahy A. B., Feudtner C., Basch E. (2018). Symptom monitoring in pediatric oncology using patient-reported outcomes: Why, how, and where next. The Patient, 11(2), 147–153. https://doi.org/10.1007%2Fs40271-017-0279-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Major C. (2013). Youth mentoring partnership’s friend fitness program: Theoretical foundations and promising preliminary findings from a new positive psychology intervention for grit and positive youth development. Master of Applied Positive Psychology (MAPP) Capstone Projects. University of Pennsylvania. https://repository.upenn.edu/cgi/viewcontent.cgi?article=1049&context=mapp_capstone
  27. McGrady M. E., Pai A. L. (2019). A systematic review of rates, outcomes, and predictors of medication non-adherence among adolescents and young adults with cancer. Journal of Adolescent and Young Adult Oncology, 8(5), 485–494. 10.1089/jayao.2018.0160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Miller K. D., Fidler-Benaoudia M., Keegan T. H., Hipp H. S., Jemal A., Siegel R. L. (2020). Cancer statistics for adolescents and young adults, 2020. CA: A Cancer Journal for Clinicians, 70(6), 443–459. 10.3322/caac.21637 [DOI] [PubMed] [Google Scholar]
  29. Modi A. C., Pai A. L., Hommel K. A., Hood K. K., Cortina S., Hilliard M. E., Guilfoyle S. M., Gray W. N., Drotar D. (2012). Pediatric self-management: A framework for research, practice, and policy. Pediatrics, 129(2), e473–e485. https://doi.org/fxsmjx [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Muthén L. K., Muthén B. O. (2010). Mplus User’s Guide. (8th ed.) Muthén & Muthén. [Google Scholar]
  31. Peña P. A., Pérez-Díaz I., Pulido-Ayala A. K., Osorio-Landa H. K., López-Navarro J. M., Duckworth A. L., Jena A. B. (2019). Association of grit scores with treatment adherence and biomarkers in patients with type 2 diabetes. JAMA Network Open, 2(9), e1911476. https://doi.org/gpkk [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Plevinsky J. M., Gutierrez-Colina A. M., Carmody J. K., Hommel K. A., Crosby L. E., McGrady M. E., Pai A. L., Ramsey R. R., Modi A. C. (2020). Patient-reported outcomes for pediatric adherence and self-management: A systematic review. Journal of Pediatric Psychology, 45(3), 340–357. 10.1093/jpepsy/jsz096 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Psihogios A. M., Schwartz L. A., Ewing K. B., Czerniecki B., Kersun L. S., Pai A. L. H., Deatrick J. A., Barakat L. P. (2020). Adherence to multiple treatment recommendations in adolescents and young adults with cancer: A mixed methods, multi-informant investigation. Journal of Adolescent and Young Adult Oncology, 9(6), 651–661. https://doi.org/gpkg [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Quast L. F., Gutiérrez-Colina A. M., Cushman G. K., Rea K. E., Eaton C. K., Lee J. L., George R. P., Blount R. L. (2020). Adherence barriers for adolescent and young adult transplant recipients: Relations to personality. Journal of Pediatric Psychology, 45(5), 540–549. 10.1093/jpepsy/jsaa017 [DOI] [PubMed] [Google Scholar]
  35. Rosenberg A., Bradford M., McCauley E., Curtis J., Wolfe J., Baker K., Yi-Frazier J. (2018). Promoting resilience in adolescents and young adults with cancer: Results from the PRISM randomized controlled trial. Cancer, 124(19), 3909–3917. https://doi.org/gfp78s [DOI] [PubMed] [Google Scholar]
  36. Rosenberg A., Bradford M., Barton K., Etsekson N., McCauley E., Curtis J. R., Wolfe J., Baker K. S., Yi-Frazier J. (2019). Hope and benefit finding: Results from the PRISM randomized controlled trial. Pediatric Blood & Cancer, 66(1), e27485. https://doi.org/ggwn2r [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Salles A., Cohen G. L., Mueller C. M. (2014). The relationship between grit and resident well-being. The American Journal of Surgery, 207(2), 251–254. https://doi.org/bxr5 [DOI] [PubMed] [Google Scholar]
  38. Sansom-Daly U. M., Peate M., Wakefield C. E., Bryant R. A., Cohn R. J. (2012). A systematic review of psychological interventions for adolescents and young adults living with chronic illness. Health Psychology: Official Journal of the Division of Health Psychology, American Psychological Association, 31(3), 380–393. 10.1037/a0025977 [DOI] [PubMed] [Google Scholar]
  39. Schwartz L. A., Drotar D. (2009). Health-related hindrance of personal goal pursuit and well-being of young adults with cystic fibrosis, pediatric cancer survivors, and peers without a history of chronic illness. Journal of Pediatric Psychology, 34(9), 954–965. 10.1093/jpepsy/jsn144 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Seligman M. E. (2008). Positive health. Applied Psychology, 57(s1), 3–18. https://doi.org/crxbnf [Google Scholar]
  41. Sharkey C. M., Bakula D. M., Gamwell K. L., Mullins A. J., Chaney J. M., Mullins L. L. (2017). The role of grit in college student health care management skills and health-related quality of life. Journal of Pediatric Psychology, 42(9), 952–961. https://doi.org/gb4kw6 [DOI] [PubMed] [Google Scholar]
  42. Sharkey C. M., Bakula D. M., Baraldi A. N., Perez M. N., Suorsa K. I., Chaney J. M., Mullins L. L. (2018). Grit, illness-related distress, and psychosocial outcomes in college students with a chronic medical condition: A path analysis. Journal of Pediatric Psychology, 43(5), 552–560. 10.1093/jpepsy/jsx145 [DOI] [PubMed] [Google Scholar]
  43. Song M. S. (2019). The effect of grit enhancing program on grit, mindset and self-control of elementary school students [Master’s thesis, Gyeongin National University of Education, Korea].
  44. Traino K. A., Bakula D. M., Sharkey C. M., Roberts C. M., Ruppe N. M., Chaney J. M., Mullins L. L. (2019). The role of grit in health care management skills and health-related quality of life in college students with chronic medical conditions. Journal of Pediatric Nursing, 46, 72–77. 10.1016/j.pedn.2019.02.035 [DOI] [PubMed] [Google Scholar]
  45. Vainio M. M., Daukantaitė D. (2016). Grit and different aspects of well-being: Direct and indirect relationships via sense of coherence and authenticity. Journal of Happiness Studies, 17(5), 2119–2147. 10.1007/s10902-015-9688-7 [DOI] [Google Scholar]
  46. Varni J. W., Burwinkle T. M., Katz E. R., Meeske K., Dickinson P. (2002). The PedsQLTM in pediatric cancer. Cancer, 94(7), 2090–2106. 10.1002/cncr.10428 [DOI] [PubMed] [Google Scholar]
  47. Wolters C. A., Hussain M. (2015). Investigating grit and its relations with college students’ self-regulated learning and academic achievement. Metacognition and Learning, 10(3), 293–311. 10.1007/s11409-014-9128-9 [DOI] [Google Scholar]
  48. Zelikovsky N., Schast A. P. (2008). Eliciting accurate reports of adherence in a clinical interview: Development of the medical adherence measure. Pediatric Nursing, 34(2), 141–146. [PubMed] [Google Scholar]

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