Multimethod Assessment of Medication Nonadherence and Barriers in Adolescents and Young Adults With Solid Organ Transplants

Multimethod Assessment of Medication Nonadherence and Barriers in Adolescents and Young Adults... Abstract Objective To (a) examine levels of medication nonadherence in adolescent and young adult (AYA) solid organ transplant recipients based on AYA- and caregiver proxy-reported nonadherence to different medication types and the medication-level variability index (MLVI) for tacrolimus, and (b) examine associations of adherence barriers and AYA and caregiver emotional distress symptoms with reported nonadherence and the MLVI. Method The sample included 47 AYAs (M age = 16.67 years, SD = 1.74; transplant types: 25% kidney, 47% liver, 28% heart) and their caregivers (94 total participants). AYAs and caregivers reported on AYAs’ adherence barriers and their own emotional functioning. Nonadherence was measured with AYA self- and caregiver proxy-report and the MLVI for tacrolimus. Results The majority of AYAs and caregivers denied nonadherence, with lower rates of nonadherence reported for antirejection medications. In contrast, 40% of AYAs’ MLVI values indicated nonadherence to tacrolimus. AYAs and caregivers who verbally acknowledged nonadherence had more AYA barriers and greater caregiver emotional distress symptoms compared with those who denied nonadherence. AYAs with MLVIs indicating nonadherence had more barriers than AYAs with MLVIs indicating adherence. Conclusions Multimethod nonadherence evaluations for AYA transplant recipients should assess objective nonadherence using the MLVI, particularly in light of low reported nonadherence rates for antirejection medications. Assessments should include adherence barriers measures, given associations with the MLVI, and potentially prioritize assessing barriers over gauging nonadherence via self- or proxy-reports. Caregiver emotional distress symptoms may also be considered to provide insight into family or environmental barriers to adherence. adherence, adolescents, assessment, organ transplantation Solid organ transplantation involves a lifelong commitment to taking antirejection and other medications as prescribed to maintain organ graft health and to prevent severe consequences (i.e., organ rejection, hospitalization, death; Fredericks et al., 2007; Shemesh et al., 2017a). Medication adherence is vital to maintaining patients’ health but, according to a review of studies using multiple nonadherence assessment methods, up to 43% of adolescent and young adult (AYA) transplant recipients are nonadherent (Dobbels et al., 2009). Given the critical consequences of nonadherence in this population, accurate assessments of nonadherence and contributing factors (i.e., barriers) are paramount to guiding when and how to intervene. Extensive research has informed best practices for assessing nonadherence (Quittner et al., 2008), examined relations between assessment methods (Loiselle et al., 2016), and guided the development of measures to assess adherence barriers (Simons & Blount, 2007). All evaluation approaches have advantages and disadvantages (Hommel, Ramsey, Rich, & Ryan, 2017), but objective nonadherence assessments (e.g., electronic monitoring, biomarkers) should be incorporated into evaluations to enhance the validity of the data and reduce bias (Ingerski, Hente, Modi, & Hommel, 2011). Self-report and clinical interview are the most common methods of assessing nonadherence because of their convenience, efficiency, and low cost, but are susceptible to social desirability and recall concerns (Stirratt et al., 2015; Wu et al., 2013). Reporting nonadherence may be especially challenging for patients who follow complex daily medication regimens, including transplant recipients. Recall may be difficult because of regimen complexity and social desirability concerns may influence the accuracy of reports. Given the variety of medications that AYA transplant recipients take, reported nonadherence rates and barriers endorsed may vary by medication type. For example, adult transplant recipients have reported more nonadherence to non-antirejection versus antirejection medications (De Bleser et al., 2011). A meta-analysis found that for children with sickle cell disease, adherence was lowest for prophylactic antibiotics and iron chelators versus hydoxyurea and other medications (Loiselle et al.,2016). In children with inflammatory bowel disease (IBD), different reported adherence rates were found by medication type (Greenley et al., 2013) and barriers exhibited differential relations with nonadherence by medication and measurement type (Ingerski, Baldassano, Denson, & Hommel, 2010). These prior findings suggest that variability in reported nonadherence and barriers rates may be observed by medication type in AYA transplant recipients, warranting further investigation to inform assessment practices. In contrast to self-report, the medication-level variability index (MLVI) for tacrolimus is based on the SD of serum immunosuppressant laboratory values and is an objective index of nonadherence. The MLVI captures the degree of variability in tacrolimus blood levels over time (Shemesh et al., 2017a). Tacrolimus is typically prescribed to patients on a precise schedule (every 12 hr) to maintain stable therapeutic levels to prevent organ graft rejection. Greater MLVI levels suggest more erratic medication-taking and evidence greater risk for rejection episodes in pediatric patients (Pollock-BarZiv et al., 2010; Shemesh et al., 2017b; Venkat, Nick, Wang, & Bucuvalas, 2007) with less conclusive evidence available to date for analyzing variability in these values for other antirejection medications (e.g., sirolimus, cyclosporine) as measures of nonadherence (Shemesh et al., 2004). Less is known about how the MLVI compares with reported nonadherence rates or relates to adherence barriers, which include organizational issues, social concerns, medication ingestion issues, and AYA or caregiver emotional problems (Bishay & Sawicki, 2016; Simons & Blount, 2007). In studies examining medication-level variability and these barriers in pediatric samples (e.g., transplant, IBD), methodology for analyzing assay data has differed (Danziger-Isakov et al., 2016; Fredericks et al., 2007; Ingerski et al., 2010; Killian, 2017; Simons, McCormick, Devine, & Blount, 2010), which limits comparability between studies. Research using current standard procedures for calculating the MLVI with pediatric transplant recipients (Shemesh et al., 2017a) is needed to contextualize how this method compares with reported nonadherence and is associated with barriers. Given evidence that the MLVI is an indicator of nonadherence to tacrolimus (Pollock-BarZiv et al., 2010; Shemesh et al., 2017a), it is likely that higher barriers will be associated with greater MLVIs. Researchers have examined numerous correlates of nonadherence (e.g., internalizing symptoms, barriers, parent supervision, family functioning; see Hommel et al., 2017 for review) but less is known about how these factors relate to the MLVI or reported nonadherence to different medication types. These data have applicability for assessing nonadherence in AYAs with transplants and potentially AYAs with other diagnoses. The goals of this preliminary study were to (a) evaluate medication nonadherence rates by assessment method, and (b) identify associations between barriers and AYA and caregiver emotional functioning with reported nonadherence to medications types and the MLVI for tacrolimus. Study variables were selected based on factors identified in prior literature as impeding adherence, including a multifactor barriers assessment (Simons & Blount 2007) and AYA and caregiver emotional functioning (Cousino, Rea, Schumacher, Magee, & Fredericks, 2017; McCormick King et al., 2014). Based on the literature, it was expected that (a) AYAs and caregivers would report low rates of nonadherence, especially for missed and late antirejection medication doses, while the MLVI would indicate comparatively higher rates of nonadherence; and (b) AYA- and caregiver proxy-reported nonadherence and MLVIs indicating nonadherence would be associated with higher levels of barriers and AYA and caregiver emotional distress symptoms. Method Procedures Study procedures received institutional review board approval before recruiting participants from an outpatient transition readiness clinic at a pediatric transplant center in the Southeastern United States. Inclusion criteria were being: (a) a 12- to 21-year-old clinic patient who received a kidney, liver, or heart transplant >1 year before recruitment; (b) a caregiver of an eligible patient; and (c) able to speak and read English. Patients with significant developmental or cognitive delays per the medical record or caregiver report were excluded. AYAs and the majority of caregivers were enrolled in the study by a trained research assistant during an outpatient clinic visit. Participants completed informed consent/assent and Health Information Portability and Accountability Act release forms before completing paper-and-pencil surveys during this clinic visit. A subset of caregivers whose AYAs were >18 years old were recruited by a research assistant via telephone, as they were not present during the clinic appointment. These caregivers completed and returned written informed consent forms and surveys via mail. Each participant received a retail store gift card as compensation for their time. Measures Demographic and Medical Information Caregivers completed a questionnaire to provide demographic data about themselves and the AYA. An electronic medical record review was conducted to calculate the AYA’s time since transplantation and age at which they underwent transplantation and to confirm that they were prescribed tacrolimus. Barriers to Adherence AYA Self-Report The Adolescent Medication Barriers Scale (AMBS; Simons & Blount, 2007) assessed AYAs’ perceived barriers to overall medication adherence. The AMBS contains three factors, Disease Frustration/Adolescent Issues (DF), Regimen Adaptation/Cognitive Issues (RA), and Ingestion Issues (II), and a Total score. AYAs indicated the extent to which they endorsed a barrier (e.g., “I find it hard to stick to a fixed medication schedule”) using a five-point Likert scale. Higher scores reflect more barriers and relate to more nonadherence and negative health outcomes (Simons et al., 2010). In the current sample, internal reliability was good for the DF (α = .83), II (α = .83), and RA (α = .80) scales, and excellent for the Total (α = .91) scale. Caregiver Proxy-Report The Parent Medication Barriers Scale (PMBS; Simons & Blount, 2007) assessed caregivers’ perceptions of their AYAs’ barriers to overall medication adherence. The PMBS contains four factors, Disease Frustration/Adolescent Issues (DF), Regimen Adaptation/Cognitive Issues (RA), Ingestion Issues (II), and Parent Reminder (PR), and a Total score. Caregivers indicated the extent to which they endorsed a barrier for their AYA (e.g., “My child feels that it gets in the way of his/her activities”) using a five-point Likert scale. Higher scores indicate more barriers and relate to more nonadherence (Simons & Blount, 2007). In this sample, internal reliability was good for the DF (α = .80) and the Total (α = .82) scales, adequate for the RA (α = .75) scale, and questionable for the II (α = .67) scale. Emotional Distress Symptoms AYA Self-Report The Behavior Assessment System of Children-2nd Edition Self-Report of Personality, Adolescent Version (BASC-2-SRP-A; Reynolds & Kamphaus, 2004) is an assessment of AYAs’ emotional and behavioral problems. The Depression and Anxiety subscales were used to evaluate AYAs’ emotional distress symptoms. The Somatization subscale was not administered given the potential for people with chronic medical conditions to endorse elevated symptoms because of their underlying medical condition rather than psychosomatic symptoms (Grover & Sarkar, 2012). The BASC-2-SRP-A was selected for ease of interpreting subscales derived from the same overall scale. AYAs responded to items with True or False responses or a four-point Likert scale. Raw scores were converted to age- and gender-normed T-scores. Higher scores indicated greater symptom severity. In this sample, internal consistency was good for the Depression subscale (α = .83) and excellent for the Anxiety subscale (α = .91). Caregiver Self-Report The Brief Symptom Inventory-18 (BSI-18; Derogatis, 2001) is a self-report measure of adult psychiatric symptoms, with depression, anxiety, and somatization subscales and an overall emotional distress scale, the Global Severity Index (GSI). Only the GSI was analyzed to reduce the number of statistical tests conducted. Caregivers responded to how often they experienced symptoms of distress in the past 7 days (e.g., “Feeling lonely”) using a five-point Likert scale. Scale items were summed and converted to gender-normed T-scores (Derogatis, 2001). Higher T-scores indicate greater symptom severity. In this sample, internal consistency was excellent for the GSI scale (α = .94). Medication Nonadherence Reported Nonadherence The Medication Adherence Measure (MAM; Zelikovsky & Schast, 2008) is a semi-structured interview of medication nonadherence in the preceding 7 days. AYAs provided information about the number of medication doses (prescription and over-the-counter) that they missed in the past 7 days and caregivers reported parallel information. The MAM was administered separately to AYAs and caregivers by a trained research assistant and away from medical providers to minimize response bias. All AYAs and the majority of caregivers (n = 43) completed the MAM during the AYAs’ clinic visit in a private room. There were four caregivers who completed the MAM by telephone with a research assistant because they were not present during their AYAs’ appointment (these caregivers were also recruited by telephone). A medical record review was conducted before administering the MAM to ensure that all prescribed medications were assessed rather than relying on reporter recall. If the respondent did not report a medication on the AYA’s list of prescribed medications, the respondent was prompted to provide nonadherence information for the medication. Medications taken on an “as needed” basis were not assessed. Percentages of missed or late medication doses and binary nonadherence categorizations were calculated for any missed medications (antirejection and non-antirejection medications), missed antirejection medications, missed non-antirejection medications (any medication other than antirejection), and late antirejection medications. Percentages of missed or late doses were calculated by dividing the total number of missed or late doses by the total number of prescribed doses and multiplying by 100. AYAs and caregivers who reported AYAs missing one or more medication dose(s) were categorized as Reported nonadherence, and AYAs and caregivers who denied AYAs missing any medication doses (i.e., 0 missed doses) were categorized as Denied nonadherence. For late antirejection medications, AYAs and caregivers who reported AYAs taking one or more antirejection medication dose(s) late (i.e., >1 hr after the scheduled time) were categorized as Reported nonadherence, and AYAs and caregivers who denied AYAs taking any antirejection doses late (i.e., 0 late doses) were categorized as Denied nonadherence. Medication-Level Variability Index A trained research assistant extracted all assay values for tacrolimus from AYAs’ electronic medical records in the 6 months before and 6 months after their study enrollment date. Laboratory values collected during inpatient stays were excluded. AYAs prescribed cyclosporine (n = 7) and sirolimus (n = 9) were excluded because of less established criteria for using the MLVI to measure nonadherence to these medications (Shemesh et al., 2004) and concerns about aggregately analyzing variation in different antirejection medications. To compute the MLVI, the SDs of all extracted laboratory values (≥3 values are needed) were calculated for each AYA (Shemesh et al., 2017a). Higher SD values reflect less consistent medication intake (i.e., nonadherence). Higher SD values have been associated with increased incidences of rejection episodes in children with liver, kidney, and heart transplants (Pollock-BarZiv et al., 2010; Shemesh et al., 2017a), supporting the validity of measuring nonadherence to tacrolimus with the MLVI. AYAs had, on average, 7.85 assays (SD = 4.32, range = 3–21) during the assessment period. Based on published guidelines for using the MLVI, SD levels that were >2 were interpreted as Nonadherent and SD levels that were ≤2 were interpreted as Adherent (Shemesh et al., 2017a). Statistical Analyses Statistical analyses were conducted using IBM Statistical Package for the Social Sciences, Version 24 (IBM Corp., Armonk, NY, USA). For hypothesis testing, alpha for statistical significance was set at .05. Preliminary analyses were conducted to examine differences on demographic variables between those enrolled in the study versus declined using Pearson product-moment correlation and chi-squared tests. Preliminary analyses were conducted for descriptive purposes to examine relations between study variables and transplant type, AYA age, and time since transplantation using Pearson product-moment and point biserial correlations and one-way analysis of variances. Descriptive statistics were used to examine percentage rates of nonadherence by assessment method. Welch’s t-tests were used to examine differences in AYA and caregiver proxy-reported barriers and AYA and caregiver emotional functioning by nonadherence assessment method. The Welch’s t-test was selected because it accounts for unequal variance between groups, which was observed for some variables, and is robust against Type I error (Delacre, Lakens, & Leys, 2017; Derrick, Toher, & White, 2016; Ruxton, 2006). Given the preliminary nature of this study and relatively small sample size, a correction procedure to further control for Type I error with multiple comparisons was not applied. This decision is consistent with previous researchers who conducted preliminary studies with important implications for smaller clinical populations (Main et al., 2014). Effect size d was used to quantify the magnitude of differences. Results Recruitment and Characteristics of the Study Sample Of the 74 families approached during recruitment, 11 declined because of lack of interest (86% participation rate). Of the 63 enrolled families, AYAs who took cyclosporine or sirolimus were excluded (n = 16). The final sample included 47 AYA-caregiver dyads (94 total participants). All AYAs in the final sample were prescribed tacrolimus. There were no significant differences between the final sample and those who declined on AYA organ type, age, sex, race, or family income. Of the caregivers who completed the MAM by telephone (n = 4; AYAs were 18–19 years old, 50% female), none reported that the AYA missed antirejection medications, one reported that the AYA missed one or more non-antirejection medication, and two reported that the AYA took one or more of their antirejection medications late. Detailed demographic data for the final sample are in Table I. The average AYA age was 16.67 years (SD = 1.74, range = 12–19 years). The majority of AYAs were male and Caucasian, had private health insurance, and had a liver transplant. AYAs reported being in middle school (11%, n = 5), in high school (74%, n = 35), or in college/recently graduated from high school (15%, n = 7). The average time since transplantation was 7.71 years (SD = 5.41; range = 1.23–18.30 years). The average age of AYAs when they received their transplanted organ was 8.95 years (SD = 5.48, range = .07–17.71 years). The average caregiver age was 45.29 years (SD = 7.32) and 93% (n = 42) of caregivers identified as the AYA’s biological parent. The majority of caregivers were female and married. Approximately half of the sample reported an annual family income of ≥$50,000. Table I. AYA and Caregiver Demographic Data AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 Note. N = 47 AYAs and 47 caregivers. AYA = adolescent and young adult. Table I. AYA and Caregiver Demographic Data AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 Note. N = 47 AYAs and 47 caregivers. AYA = adolescent and young adult. Preliminary analyses indicated that older AYA age was associated with higher barriers on the AMBS DF (r = .42, p = .004) and Total (r = .33, p = .03) scales and lower barriers on the PMBS PR (r = −.30, p = .04) scale. Longer time since transplantation was associated with fewer barriers on the PMBS DF (r = −.43, p = .002) and Total (r = −.33, p = .03) scales and adherence to tacrolimus (i.e., MLVI ≤ 2; r = −.31, p = .04). AYAs with heart transplants endorsed more barriers than AYAs with liver transplants on the AMBS RA (F = 3.79, p = .03; heart M = 9.46, SD = 3.71; liver M = 6.50, SD = 2.52), II (F = 4.55, p = .02; heart M = 12.77, SD = 6.03; liver M = 8.36, SD = 3.23), and Total (F = 4.38, p = .02; heart M = 43.31, SD = 15.38; liver M = 31.27, SD = 10.69) scales. AYA age, time since transplant, and transplant type were unrelated to AYA or caregiver proxy-reported nonadherence or AYA and caregiver emotional functioning. What Was the Prevalence of Nonadherence Based on Assessment Type? AYAs, on average, reported missing 1.88–9.30% of their medication doses in the past week, with the lowest rates reported for missed antirejection medications. AYAs, on average, reportedly took 4.01% of their antirejection medication doses late in the past week. Categorically, 26% of AYAs reported missing one or more doses of any medications (antirejection and non-antirejection medications) in the past week, only 15% reported missing one or more doses of antirejection medications, 26% reported missing one or more doses of non-antirejection medications, and 26% reported taking one or more doses of antirejection medications late. Caregivers reported that AYAs, on average, missed 1.93–9.16% of their medication doses in the past week, with the lowest rates reported for missed antirejection medications. Caregivers reported that their AYA took, on average, 4.10% of their antirejection medication doses late in the past week. Categorically, 21% of caregivers reported that their AYA missed one or more doses of any medications (antirejection and non-antirejection medications) in the past week, followed by only 6% missing one or more doses of antirejection medications, 21% missing one or more doses of non-antirejection medications, and 28% taking one or more doses of antirejection medications late. The MLVI indicated that 40% of AYAs were nonadherent to tacrolimus as evidenced by SD values that were >2. See Table II for detailed results. Table II. Rates of Medication Nonadherence in the Sample Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Note. Nonadherence data for non-antirejection medications were obtained for 42 AYAs, as 5 AYAs were not prescribed any medications beyond their antirejection medications. Nonadherence % = average percentage of missed or late medication doses reported plus SD. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed or late dose(s) of medications. AYA = adolescent and young adult; MLVI = medication level variability index. Table II. Rates of Medication Nonadherence in the Sample Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Note. Nonadherence data for non-antirejection medications were obtained for 42 AYAs, as 5 AYAs were not prescribed any medications beyond their antirejection medications. Nonadherence % = average percentage of missed or late medication doses reported plus SD. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed or late dose(s) of medications. AYA = adolescent and young adult; MLVI = medication level variability index. How Were Barriers Associated With Reported Nonadherence to Different Medication Types? AYAs who reported nonadherence to any medications (antirejection and non-antirejection medications) had significantly higher barriers on the AMBS RA and Total scales than AYAs who denied nonadherence, with large effect sizes; there were no statistically significant differences on the PMBS. Caregiver report of AYA nonadherence to any medications was associated with significantly higher barriers on the PMBS DF, II, and Total scales than caregiver denial of nonadherence, with large effect sizes; there were no significant differences on the AMBS, though effect sizes ranged from medium to large. See Table III for details. Table III. Differences in Study Variables by Reported Nonadherence to Any Prescribed Medication (Antirejection and Non-antirejection) AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 Note. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Table III. Differences in Study Variables by Reported Nonadherence to Any Prescribed Medication (Antirejection and Non-antirejection) AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 Note. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. AYAs who reported nonadherence to antirejection medications had higher barriers on the AMBS RA scale than AYAs who denied nonadherence, with a large effect size; there were no statistically significant differences on the PMBS. There were no significant differences between caregivers who reported versus denied AYA nonadherence to antirejection medications on the AMBS or PMBS. There were no significant differences on the AMBS or PMBS based on AYA or caregiver proxy-report of late antirejection medications and effect sizes were mostly small. See Table IV (missed antirejection medications) and Supplementary Table S1 (late antirejection medications) for details. Table IV. Differences in Study Variables by Reported Nonadherence to Antirejection Medications AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 Note. Denied nonadherence = reported 0 missed antirejection medication doses; Reported nonadherence = categorically reported ≥1 missed antirejection medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05. Table IV. Differences in Study Variables by Reported Nonadherence to Antirejection Medications AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 Note. Denied nonadherence = reported 0 missed antirejection medication doses; Reported nonadherence = categorically reported ≥1 missed antirejection medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05. AYAs who reported nonadherence to non-antirejection medications had significantly higher barriers on the AMBS RA, II, and Total scales than AYAs who denied nonadherence, with large effect sizes (d = −1.08, −0.84, and −0.89, respectively); there were no significant differences on the PMBS. Caregiver report of AYA nonadherence to non-antirejection medications was associated with significantly higher barriers on the PMBS DF and Total scales with large effect sizes (d = −0.85 and −1.17, respectively); there were no significant differences on the AMBS scales (see Supplementary Table S2). How Were AYA and Caregiver Emotional Distress Symptoms Associated With Reported Nonadherence to Different Medication Types? There were no differences on AYA depression or anxiety symptoms based on AYA or caregiver report of missed doses of any (antirejection and non-antirejection medications), antirejection, or non-antirejection medications or late doses of antirejection medications. For AYAs reporting nonadherence to any and non-antirejection medications, caregiver emotional distress symptoms were significantly higher than AYAs who denied nonadherence, with medium and large effect sizes (d = −0.72 and −1.01, respectively). For caregivers reporting AYA nonadherence to any and non-antirejection medications, caregiver emotional distress symptoms were significantly higher than caregivers who denied nonadherence, with large effect sizes (d = −1.30 and −1.48, respectively). There were no differences on caregiver emotional distress symptoms based on AYA- or caregiver proxy-reported missed or late doses of antirejection medications. See Tables III and IV and Supplementary Tables S1 and S2 for details. How Were Barriers and AYA and Caregiver Emotional Distress Symptoms Associated With the MLVI for Tacrolimus? AYAs with MLVIs >2 (i.e., nonadherent to tacrolimus) had significantly higher scores on the AMBS DF, II, and Total scales and PMBS II scale than AYAs with MLVIs ≤2 (i.e., adherent to tacrolimus; see Table V), with medium to large effect sizes. There were no differences on AYA or caregiver emotional functioning symptoms based on the MLVI. Table V. Differences in Study Variables Based on the MLVI for Tacrolimus MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 Note. For the MLVI, SD > 2 was “nonadherent” and SD ≤ 2 was “adherent.” Effect size = d. AYA = adolescent and young adult; MLVI = medication level variability index. BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Table V. Differences in Study Variables Based on the MLVI for Tacrolimus MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 Note. For the MLVI, SD > 2 was “nonadherent” and SD ≤ 2 was “adherent.” Effect size = d. AYA = adolescent and young adult; MLVI = medication level variability index. BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Discussion Inconsistencies in nonadherence rates based on assessment method are well known (Stirratt et al., 2015), but there is limited information on differences in reported nonadherence by medication type compared with the MLVI in AYAs with transplants. Barriers to adherence have demonstrated relations with nonadherence in AYAs with solid organ transplant (McCormick King et al., 2014), but less is known about associations with nonadherence to medication types and the MLVI. This study uniquely illustrates potential issues with underreporting nonadherence in AYAs with transplants and their caregivers and is the first study to link barriers to adherence with the MLVI. Preliminary analyses also revealed that older AYA age, shorter time since transplantation, and having a heart transplant may be risk factors for more barriers, and longer time since transplantation may be associated with more stable MLVIs for tacrolimus. These results may help providers contextualize how nonadherence is reported in this population and highlight the types of barriers related to different nonadherence assessment approaches. AYAs and caregivers reported nonadherence at low rates, especially for antirejection medications (De Bleser et al., 2011). In contrast, nonadherence rates obtained with the MLVI were consistent with aggregated estimates from a prior review of nonadherence in AYA transplant recipients (Dobbels et al., 2009). The MLVI is relatively free from social desirability issues and totally free from recall concerns, which further highlights potential issues with underreporting nonadherence. These data emphasize the need to refine methods for clinically assessing nonadherence, given that face-to-face discussions remain the primary modalities for assessment and intervention (Wu et al., 2013). Differences in nonadherence rates by assessment method reiterate guidance to use multimethod assessments that include objective measures (Quittner et al., 2008). Consistent with prior findings (McCormick King et al., 2014; Simons et al., 2010), AYAs and caregivers who reported nonadherence also endorsed more barriers, potentially because of the severity of AYAs’ challenges with following their regimen. Of note, far fewer AYAs and caregivers endorsed antirejection medication nonadherence, which may have contributed to just one association between AYA-reported missed antirejection medications and the AMBS RA scale and no differences in barriers based on caregiver-report. These results suggest that if an AYA transplant recipient or their caregiver acknowledges medication nonadherence, the AYA may be experiencing significant obstacles to following their prescribed regimen that warrant more detailed assessment and potentially clinical intervention. Given associations with AYA and caregiver reported nonadherence to any and non-antirejection medications, higher levels of caregiver emotional distress may serve as barriers to adherence by reducing the degree to which caregivers are emotionally available to supervise and support AYA adherence. More parental monitoring has shown associations with higher adherence in adolescents with other chronic medical conditions (Ellis et al., 2007). The lack of differences in AYA emotional functioning based on AYA or caregiver reported nonadherence may reflect lower levels of emotional problems endorsed by AYAs in this sample. Caregivers may experience more emotional distress symptoms when their AYA is nonadherent than AYAs experience themselves. Alternatively, the AMBS and PMBS may be more relevant to problems with nonadherence than AYAs’ general feelings of sadness or anxiety. This is the first study to link barriers and the MLVI for tacrolimus. Notably, the MLVI is an index of medication intake, which underscores the significance of associations with the AMBS and PMBS II subscales. A prior study attempted to relate serum assays to barriers but only obtained one tacrolimus value instead of the MLVI (Danziger-Isakov et al., 2016). Another study linked one PMBS item to medication variability levels combining three antirejection medications (Simons et al., 2010). This study also found that higher scores on the PMBS and AMBS II scales related to higher rates of death and hospitalizations in the sample of adolescents with solid organ transplants. Together, findings from Simons and colleagues (2010) and the current study suggest that issues related to ingesting medications are critical barriers to assess and treat to prevent nonadherence and negative health outcomes. The current study advances the literature with its methodology and clinical significance by connecting barriers to an index of actual medication intake patterns over 1 year. These findings provide further evidence for the clinical use of the AMBS and PBMS to evaluate barriers and add to the literature in support of using the MLVI to assess nonadherence to tacrolimus. Evaluating caregiver emotional functioning may provide insight into family or environmental barriers to adherence. Assessing barriers with the AMBS or PMBS may be more useful than probing AYA depression or anxiety symptoms when evaluating nonadherence. The MLVI is an increasingly publicized objective tool for measuring nonadherence to tacrolimus. An advantage of the MLVI is that it is easy to calculate from data collected as part of standard care and is clinically meaningful to pediatric psychologists, physicians, and pharmacists who frequently provide interdisciplinary adherence intervention to this population. Providers may calculate the MLVI to evaluate AYAs’ nonadherence to tacrolimus and, if >2, conduct an in-depth assessment of adherence barriers, and also deliver clinical recommendations for overcoming these barriers. Patients whose MLVI values are ≤2 may still benefit from clinical recommendations for managing common barriers to adherence. The current findings shed light on known issues with reporting nonadherence. Although it was emphasized that reports would not impact clinical care, low rates of reported nonadherence, especially for antirejection medications, may reflect challenges patients, and caregivers have with discussing potentially uncomfortable topics with providers and researchers or recall issues. In adolescents with type 1 diabetes, patient-centered communication related to higher adherence (Croom et al., 2011) and may be applicable to AYAs with transplants. Electronic monitoring methods would address recall concerns. Future researchers should investigate whether AYAs and caregivers who exhibit greater recognition of problems with nonadherence are more open to addressing the concerns via intervention. This study had limitations, including a smaller sample size, which was further reduced by examining the MLVI for tacrolimus only, and use of multiple statistical comparisons. Welch’s t-test was selected because it is relatively robust to type I error; effect sizes for statistically significant results were medium to large, but results should be interpreted as preliminary data that lay the groundwork for studies with more rigorous methodology. There were high numbers of participants who denied nonadherence, owing to likely issues with reporting in contrast to the MLVI, but the reasons why these contrasts were observed were not identified. Nonadherence rates on the MLVI may have been influenced by inherent methodological weaknesses (e.g., interactions with other medications, white coat compliance, lack of protocol for handling different numbers of assays per individuals, variable lengths of time between assays). The MAM and MLVI assessment periods occurred over different lengths of time (i.e., 1 week for the MAM, 1 year for the MLVI), and the two assessments should not be interpreted as completely equivalent. Barriers may have different associations with nonadherence based on assessment period. Some of the PMBS subscales had low internal consistency and the AMBS and PMBS measured overall barriers rather than barriers to specific medications. Participants were recruited from one site and caregivers mostly identified as female, which may impact generalizability. Older AYAs may have unique environmental circumstances influencing nonadherence, especially if they live away from caregivers, which were not measured in this study. Clinical assessment of nonadherence remains a challenge as evidenced by low rates of reported nonadherence to different medication types in contrast to the MLVI. The MLVI offers a viable and potentially more valid alternative to assessing nonadherence to tacrolimus via self-report. The current study provides preliminary support for associations between the MLVI and adherence barriers and adds to growing evidence that pediatric psychologists should assess barriers to adherence given associations with multiple methods of evaluating nonadherence. These findings underscore the importance for the pediatric psychology field to link behavioral variables, such as barriers to adherence, with objective, clinical outcomes, such as the MLVI, to strengthen the scientific and clinical impact of our research. Future researchers should investigate whether barriers to adherence should be prioritized in pediatric clinical assessment over attempting to gauge nonadherence via clinical interview. This approach may offer insight into the types of challenges AYAs face when following complex regimens and provide clinical opportunities to address these concerns; however, this proposal awaits empirical investigation. Supplementary Data Supplementary data can be found at: http://www.jpepsy.oxfordjournals.org/. Acknowledgments We are grateful to the participants who provided us with their time and made this study possible. We also thank Mary Gray Stolz for her involvement in this study. Funding This study was funded by the Transplant Services Research Fund at Children's Healthcare of Atlanta. This study also received funding from the Psi Chi Graduate Research Grant, the American Psychological Association of Graduate Students Nancy B. Forest and L. Michael Honaker Master's Grant, the University of Georgia (UGA) Center for Research and Engagement in Diversity Seed Grant, and the UGA Graduate School Dean’s Award (to A.M.G.-C.). Disclosures: R.R. is a recipient of research funding from Gilead Sciences, Inc.: References Bishay L. C. , Sawicki G. S. ( 2016 ). Strategies to optimize treatment adherence in adolescent patients with cystic fibrosis . 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Eliciting accurate reports of adherence in a clinical interview: development of the Medical Adherence Measure . Pediatric Nursing , 34 , 141 – 146 . Retrieved from https://search.proquest.com Google Scholar PubMed © The Author(s) 2018. 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/lega l/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Pediatric Psychology Oxford University Press

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Abstract

Abstract Objective To (a) examine levels of medication nonadherence in adolescent and young adult (AYA) solid organ transplant recipients based on AYA- and caregiver proxy-reported nonadherence to different medication types and the medication-level variability index (MLVI) for tacrolimus, and (b) examine associations of adherence barriers and AYA and caregiver emotional distress symptoms with reported nonadherence and the MLVI. Method The sample included 47 AYAs (M age = 16.67 years, SD = 1.74; transplant types: 25% kidney, 47% liver, 28% heart) and their caregivers (94 total participants). AYAs and caregivers reported on AYAs’ adherence barriers and their own emotional functioning. Nonadherence was measured with AYA self- and caregiver proxy-report and the MLVI for tacrolimus. Results The majority of AYAs and caregivers denied nonadherence, with lower rates of nonadherence reported for antirejection medications. In contrast, 40% of AYAs’ MLVI values indicated nonadherence to tacrolimus. AYAs and caregivers who verbally acknowledged nonadherence had more AYA barriers and greater caregiver emotional distress symptoms compared with those who denied nonadherence. AYAs with MLVIs indicating nonadherence had more barriers than AYAs with MLVIs indicating adherence. Conclusions Multimethod nonadherence evaluations for AYA transplant recipients should assess objective nonadherence using the MLVI, particularly in light of low reported nonadherence rates for antirejection medications. Assessments should include adherence barriers measures, given associations with the MLVI, and potentially prioritize assessing barriers over gauging nonadherence via self- or proxy-reports. Caregiver emotional distress symptoms may also be considered to provide insight into family or environmental barriers to adherence. adherence, adolescents, assessment, organ transplantation Solid organ transplantation involves a lifelong commitment to taking antirejection and other medications as prescribed to maintain organ graft health and to prevent severe consequences (i.e., organ rejection, hospitalization, death; Fredericks et al., 2007; Shemesh et al., 2017a). Medication adherence is vital to maintaining patients’ health but, according to a review of studies using multiple nonadherence assessment methods, up to 43% of adolescent and young adult (AYA) transplant recipients are nonadherent (Dobbels et al., 2009). Given the critical consequences of nonadherence in this population, accurate assessments of nonadherence and contributing factors (i.e., barriers) are paramount to guiding when and how to intervene. Extensive research has informed best practices for assessing nonadherence (Quittner et al., 2008), examined relations between assessment methods (Loiselle et al., 2016), and guided the development of measures to assess adherence barriers (Simons & Blount, 2007). All evaluation approaches have advantages and disadvantages (Hommel, Ramsey, Rich, & Ryan, 2017), but objective nonadherence assessments (e.g., electronic monitoring, biomarkers) should be incorporated into evaluations to enhance the validity of the data and reduce bias (Ingerski, Hente, Modi, & Hommel, 2011). Self-report and clinical interview are the most common methods of assessing nonadherence because of their convenience, efficiency, and low cost, but are susceptible to social desirability and recall concerns (Stirratt et al., 2015; Wu et al., 2013). Reporting nonadherence may be especially challenging for patients who follow complex daily medication regimens, including transplant recipients. Recall may be difficult because of regimen complexity and social desirability concerns may influence the accuracy of reports. Given the variety of medications that AYA transplant recipients take, reported nonadherence rates and barriers endorsed may vary by medication type. For example, adult transplant recipients have reported more nonadherence to non-antirejection versus antirejection medications (De Bleser et al., 2011). A meta-analysis found that for children with sickle cell disease, adherence was lowest for prophylactic antibiotics and iron chelators versus hydoxyurea and other medications (Loiselle et al.,2016). In children with inflammatory bowel disease (IBD), different reported adherence rates were found by medication type (Greenley et al., 2013) and barriers exhibited differential relations with nonadherence by medication and measurement type (Ingerski, Baldassano, Denson, & Hommel, 2010). These prior findings suggest that variability in reported nonadherence and barriers rates may be observed by medication type in AYA transplant recipients, warranting further investigation to inform assessment practices. In contrast to self-report, the medication-level variability index (MLVI) for tacrolimus is based on the SD of serum immunosuppressant laboratory values and is an objective index of nonadherence. The MLVI captures the degree of variability in tacrolimus blood levels over time (Shemesh et al., 2017a). Tacrolimus is typically prescribed to patients on a precise schedule (every 12 hr) to maintain stable therapeutic levels to prevent organ graft rejection. Greater MLVI levels suggest more erratic medication-taking and evidence greater risk for rejection episodes in pediatric patients (Pollock-BarZiv et al., 2010; Shemesh et al., 2017b; Venkat, Nick, Wang, & Bucuvalas, 2007) with less conclusive evidence available to date for analyzing variability in these values for other antirejection medications (e.g., sirolimus, cyclosporine) as measures of nonadherence (Shemesh et al., 2004). Less is known about how the MLVI compares with reported nonadherence rates or relates to adherence barriers, which include organizational issues, social concerns, medication ingestion issues, and AYA or caregiver emotional problems (Bishay & Sawicki, 2016; Simons & Blount, 2007). In studies examining medication-level variability and these barriers in pediatric samples (e.g., transplant, IBD), methodology for analyzing assay data has differed (Danziger-Isakov et al., 2016; Fredericks et al., 2007; Ingerski et al., 2010; Killian, 2017; Simons, McCormick, Devine, & Blount, 2010), which limits comparability between studies. Research using current standard procedures for calculating the MLVI with pediatric transplant recipients (Shemesh et al., 2017a) is needed to contextualize how this method compares with reported nonadherence and is associated with barriers. Given evidence that the MLVI is an indicator of nonadherence to tacrolimus (Pollock-BarZiv et al., 2010; Shemesh et al., 2017a), it is likely that higher barriers will be associated with greater MLVIs. Researchers have examined numerous correlates of nonadherence (e.g., internalizing symptoms, barriers, parent supervision, family functioning; see Hommel et al., 2017 for review) but less is known about how these factors relate to the MLVI or reported nonadherence to different medication types. These data have applicability for assessing nonadherence in AYAs with transplants and potentially AYAs with other diagnoses. The goals of this preliminary study were to (a) evaluate medication nonadherence rates by assessment method, and (b) identify associations between barriers and AYA and caregiver emotional functioning with reported nonadherence to medications types and the MLVI for tacrolimus. Study variables were selected based on factors identified in prior literature as impeding adherence, including a multifactor barriers assessment (Simons & Blount 2007) and AYA and caregiver emotional functioning (Cousino, Rea, Schumacher, Magee, & Fredericks, 2017; McCormick King et al., 2014). Based on the literature, it was expected that (a) AYAs and caregivers would report low rates of nonadherence, especially for missed and late antirejection medication doses, while the MLVI would indicate comparatively higher rates of nonadherence; and (b) AYA- and caregiver proxy-reported nonadherence and MLVIs indicating nonadherence would be associated with higher levels of barriers and AYA and caregiver emotional distress symptoms. Method Procedures Study procedures received institutional review board approval before recruiting participants from an outpatient transition readiness clinic at a pediatric transplant center in the Southeastern United States. Inclusion criteria were being: (a) a 12- to 21-year-old clinic patient who received a kidney, liver, or heart transplant >1 year before recruitment; (b) a caregiver of an eligible patient; and (c) able to speak and read English. Patients with significant developmental or cognitive delays per the medical record or caregiver report were excluded. AYAs and the majority of caregivers were enrolled in the study by a trained research assistant during an outpatient clinic visit. Participants completed informed consent/assent and Health Information Portability and Accountability Act release forms before completing paper-and-pencil surveys during this clinic visit. A subset of caregivers whose AYAs were >18 years old were recruited by a research assistant via telephone, as they were not present during the clinic appointment. These caregivers completed and returned written informed consent forms and surveys via mail. Each participant received a retail store gift card as compensation for their time. Measures Demographic and Medical Information Caregivers completed a questionnaire to provide demographic data about themselves and the AYA. An electronic medical record review was conducted to calculate the AYA’s time since transplantation and age at which they underwent transplantation and to confirm that they were prescribed tacrolimus. Barriers to Adherence AYA Self-Report The Adolescent Medication Barriers Scale (AMBS; Simons & Blount, 2007) assessed AYAs’ perceived barriers to overall medication adherence. The AMBS contains three factors, Disease Frustration/Adolescent Issues (DF), Regimen Adaptation/Cognitive Issues (RA), and Ingestion Issues (II), and a Total score. AYAs indicated the extent to which they endorsed a barrier (e.g., “I find it hard to stick to a fixed medication schedule”) using a five-point Likert scale. Higher scores reflect more barriers and relate to more nonadherence and negative health outcomes (Simons et al., 2010). In the current sample, internal reliability was good for the DF (α = .83), II (α = .83), and RA (α = .80) scales, and excellent for the Total (α = .91) scale. Caregiver Proxy-Report The Parent Medication Barriers Scale (PMBS; Simons & Blount, 2007) assessed caregivers’ perceptions of their AYAs’ barriers to overall medication adherence. The PMBS contains four factors, Disease Frustration/Adolescent Issues (DF), Regimen Adaptation/Cognitive Issues (RA), Ingestion Issues (II), and Parent Reminder (PR), and a Total score. Caregivers indicated the extent to which they endorsed a barrier for their AYA (e.g., “My child feels that it gets in the way of his/her activities”) using a five-point Likert scale. Higher scores indicate more barriers and relate to more nonadherence (Simons & Blount, 2007). In this sample, internal reliability was good for the DF (α = .80) and the Total (α = .82) scales, adequate for the RA (α = .75) scale, and questionable for the II (α = .67) scale. Emotional Distress Symptoms AYA Self-Report The Behavior Assessment System of Children-2nd Edition Self-Report of Personality, Adolescent Version (BASC-2-SRP-A; Reynolds & Kamphaus, 2004) is an assessment of AYAs’ emotional and behavioral problems. The Depression and Anxiety subscales were used to evaluate AYAs’ emotional distress symptoms. The Somatization subscale was not administered given the potential for people with chronic medical conditions to endorse elevated symptoms because of their underlying medical condition rather than psychosomatic symptoms (Grover & Sarkar, 2012). The BASC-2-SRP-A was selected for ease of interpreting subscales derived from the same overall scale. AYAs responded to items with True or False responses or a four-point Likert scale. Raw scores were converted to age- and gender-normed T-scores. Higher scores indicated greater symptom severity. In this sample, internal consistency was good for the Depression subscale (α = .83) and excellent for the Anxiety subscale (α = .91). Caregiver Self-Report The Brief Symptom Inventory-18 (BSI-18; Derogatis, 2001) is a self-report measure of adult psychiatric symptoms, with depression, anxiety, and somatization subscales and an overall emotional distress scale, the Global Severity Index (GSI). Only the GSI was analyzed to reduce the number of statistical tests conducted. Caregivers responded to how often they experienced symptoms of distress in the past 7 days (e.g., “Feeling lonely”) using a five-point Likert scale. Scale items were summed and converted to gender-normed T-scores (Derogatis, 2001). Higher T-scores indicate greater symptom severity. In this sample, internal consistency was excellent for the GSI scale (α = .94). Medication Nonadherence Reported Nonadherence The Medication Adherence Measure (MAM; Zelikovsky & Schast, 2008) is a semi-structured interview of medication nonadherence in the preceding 7 days. AYAs provided information about the number of medication doses (prescription and over-the-counter) that they missed in the past 7 days and caregivers reported parallel information. The MAM was administered separately to AYAs and caregivers by a trained research assistant and away from medical providers to minimize response bias. All AYAs and the majority of caregivers (n = 43) completed the MAM during the AYAs’ clinic visit in a private room. There were four caregivers who completed the MAM by telephone with a research assistant because they were not present during their AYAs’ appointment (these caregivers were also recruited by telephone). A medical record review was conducted before administering the MAM to ensure that all prescribed medications were assessed rather than relying on reporter recall. If the respondent did not report a medication on the AYA’s list of prescribed medications, the respondent was prompted to provide nonadherence information for the medication. Medications taken on an “as needed” basis were not assessed. Percentages of missed or late medication doses and binary nonadherence categorizations were calculated for any missed medications (antirejection and non-antirejection medications), missed antirejection medications, missed non-antirejection medications (any medication other than antirejection), and late antirejection medications. Percentages of missed or late doses were calculated by dividing the total number of missed or late doses by the total number of prescribed doses and multiplying by 100. AYAs and caregivers who reported AYAs missing one or more medication dose(s) were categorized as Reported nonadherence, and AYAs and caregivers who denied AYAs missing any medication doses (i.e., 0 missed doses) were categorized as Denied nonadherence. For late antirejection medications, AYAs and caregivers who reported AYAs taking one or more antirejection medication dose(s) late (i.e., >1 hr after the scheduled time) were categorized as Reported nonadherence, and AYAs and caregivers who denied AYAs taking any antirejection doses late (i.e., 0 late doses) were categorized as Denied nonadherence. Medication-Level Variability Index A trained research assistant extracted all assay values for tacrolimus from AYAs’ electronic medical records in the 6 months before and 6 months after their study enrollment date. Laboratory values collected during inpatient stays were excluded. AYAs prescribed cyclosporine (n = 7) and sirolimus (n = 9) were excluded because of less established criteria for using the MLVI to measure nonadherence to these medications (Shemesh et al., 2004) and concerns about aggregately analyzing variation in different antirejection medications. To compute the MLVI, the SDs of all extracted laboratory values (≥3 values are needed) were calculated for each AYA (Shemesh et al., 2017a). Higher SD values reflect less consistent medication intake (i.e., nonadherence). Higher SD values have been associated with increased incidences of rejection episodes in children with liver, kidney, and heart transplants (Pollock-BarZiv et al., 2010; Shemesh et al., 2017a), supporting the validity of measuring nonadherence to tacrolimus with the MLVI. AYAs had, on average, 7.85 assays (SD = 4.32, range = 3–21) during the assessment period. Based on published guidelines for using the MLVI, SD levels that were >2 were interpreted as Nonadherent and SD levels that were ≤2 were interpreted as Adherent (Shemesh et al., 2017a). Statistical Analyses Statistical analyses were conducted using IBM Statistical Package for the Social Sciences, Version 24 (IBM Corp., Armonk, NY, USA). For hypothesis testing, alpha for statistical significance was set at .05. Preliminary analyses were conducted to examine differences on demographic variables between those enrolled in the study versus declined using Pearson product-moment correlation and chi-squared tests. Preliminary analyses were conducted for descriptive purposes to examine relations between study variables and transplant type, AYA age, and time since transplantation using Pearson product-moment and point biserial correlations and one-way analysis of variances. Descriptive statistics were used to examine percentage rates of nonadherence by assessment method. Welch’s t-tests were used to examine differences in AYA and caregiver proxy-reported barriers and AYA and caregiver emotional functioning by nonadherence assessment method. The Welch’s t-test was selected because it accounts for unequal variance between groups, which was observed for some variables, and is robust against Type I error (Delacre, Lakens, & Leys, 2017; Derrick, Toher, & White, 2016; Ruxton, 2006). Given the preliminary nature of this study and relatively small sample size, a correction procedure to further control for Type I error with multiple comparisons was not applied. This decision is consistent with previous researchers who conducted preliminary studies with important implications for smaller clinical populations (Main et al., 2014). Effect size d was used to quantify the magnitude of differences. Results Recruitment and Characteristics of the Study Sample Of the 74 families approached during recruitment, 11 declined because of lack of interest (86% participation rate). Of the 63 enrolled families, AYAs who took cyclosporine or sirolimus were excluded (n = 16). The final sample included 47 AYA-caregiver dyads (94 total participants). All AYAs in the final sample were prescribed tacrolimus. There were no significant differences between the final sample and those who declined on AYA organ type, age, sex, race, or family income. Of the caregivers who completed the MAM by telephone (n = 4; AYAs were 18–19 years old, 50% female), none reported that the AYA missed antirejection medications, one reported that the AYA missed one or more non-antirejection medication, and two reported that the AYA took one or more of their antirejection medications late. Detailed demographic data for the final sample are in Table I. The average AYA age was 16.67 years (SD = 1.74, range = 12–19 years). The majority of AYAs were male and Caucasian, had private health insurance, and had a liver transplant. AYAs reported being in middle school (11%, n = 5), in high school (74%, n = 35), or in college/recently graduated from high school (15%, n = 7). The average time since transplantation was 7.71 years (SD = 5.41; range = 1.23–18.30 years). The average age of AYAs when they received their transplanted organ was 8.95 years (SD = 5.48, range = .07–17.71 years). The average caregiver age was 45.29 years (SD = 7.32) and 93% (n = 42) of caregivers identified as the AYA’s biological parent. The majority of caregivers were female and married. Approximately half of the sample reported an annual family income of ≥$50,000. Table I. AYA and Caregiver Demographic Data AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 Note. N = 47 AYAs and 47 caregivers. AYA = adolescent and young adult. Table I. AYA and Caregiver Demographic Data AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 AYA Caregiver Factor % n % n Sex  Female 45 21 92 43  Male 55 26 8 4 Race  Caucasian 60 28 67 31  Black or African-American 23 11 21 10  Asian 6 3 6 3  Multiracial 11 5 6 3 Transplant type  Kidney 25 12 – –  Liver 47 22 – –  Heart 28 13 – – Health insurance  Private 60 28 – –  Public 40 19 – – Marital status  Single, never married – – 11 5  Married/committed partnership – – 72 34  Divorced – – 17 8 Caregiver education level  High school or less – – 41 19  Associates or Bachelor’s degree – – 36 17  Graduate degree – – 21 10  Prefer not to report – – 2 1 Family annual income  <$25,000 – – 15 7  $25,000–$49,999 – – 32 15  $50,000–$74,999 – – 15 7  $75,000–$99,999 – – 13 6  ≥$100,000 – – 23 11  Prefer not to report – – 2 1 Note. N = 47 AYAs and 47 caregivers. AYA = adolescent and young adult. Preliminary analyses indicated that older AYA age was associated with higher barriers on the AMBS DF (r = .42, p = .004) and Total (r = .33, p = .03) scales and lower barriers on the PMBS PR (r = −.30, p = .04) scale. Longer time since transplantation was associated with fewer barriers on the PMBS DF (r = −.43, p = .002) and Total (r = −.33, p = .03) scales and adherence to tacrolimus (i.e., MLVI ≤ 2; r = −.31, p = .04). AYAs with heart transplants endorsed more barriers than AYAs with liver transplants on the AMBS RA (F = 3.79, p = .03; heart M = 9.46, SD = 3.71; liver M = 6.50, SD = 2.52), II (F = 4.55, p = .02; heart M = 12.77, SD = 6.03; liver M = 8.36, SD = 3.23), and Total (F = 4.38, p = .02; heart M = 43.31, SD = 15.38; liver M = 31.27, SD = 10.69) scales. AYA age, time since transplant, and transplant type were unrelated to AYA or caregiver proxy-reported nonadherence or AYA and caregiver emotional functioning. What Was the Prevalence of Nonadherence Based on Assessment Type? AYAs, on average, reported missing 1.88–9.30% of their medication doses in the past week, with the lowest rates reported for missed antirejection medications. AYAs, on average, reportedly took 4.01% of their antirejection medication doses late in the past week. Categorically, 26% of AYAs reported missing one or more doses of any medications (antirejection and non-antirejection medications) in the past week, only 15% reported missing one or more doses of antirejection medications, 26% reported missing one or more doses of non-antirejection medications, and 26% reported taking one or more doses of antirejection medications late. Caregivers reported that AYAs, on average, missed 1.93–9.16% of their medication doses in the past week, with the lowest rates reported for missed antirejection medications. Caregivers reported that their AYA took, on average, 4.10% of their antirejection medication doses late in the past week. Categorically, 21% of caregivers reported that their AYA missed one or more doses of any medications (antirejection and non-antirejection medications) in the past week, followed by only 6% missing one or more doses of antirejection medications, 21% missing one or more doses of non-antirejection medications, and 28% taking one or more doses of antirejection medications late. The MLVI indicated that 40% of AYAs were nonadherent to tacrolimus as evidenced by SD values that were >2. See Table II for detailed results. Table II. Rates of Medication Nonadherence in the Sample Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Note. Nonadherence data for non-antirejection medications were obtained for 42 AYAs, as 5 AYAs were not prescribed any medications beyond their antirejection medications. Nonadherence % = average percentage of missed or late medication doses reported plus SD. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed or late dose(s) of medications. AYA = adolescent and young adult; MLVI = medication level variability index. Table II. Rates of Medication Nonadherence in the Sample Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Nonadherence % Denied nonadherence Reported nonadherence M (SD) % (n) % (n) AYA self-report  Missed any prescribed medications (antirejection and non-antirejection) 5.74 (13.00) 74 (35) 26 (12)  Missed antirejection medications 1.88 (5.79) 85 (40) 15 (7)  Missed non-antirejection medications (excludes antirejection medications) 9.30 (21.17) 74 (31) 26 (11)  Late antirejection medications 4.01 (9.10) 74 (35) 26 (12) Caregiver proxy-report  Missed any prescribed medications (antirejection and non-antirejection) 5.11 (12.68) 79 (37) 21 (10)  Missed antirejection medications 1.93 (8.05) 94 (44) 6 (3)  Missed non-antirejection medications (excludes antirejection medications) 9.16 (21.30) 79 (33) 21 (9)  Late antirejection medications 4.10 (7.73) 72 (34) 28 (13) MLVI Adherent (SD ≤ 2) Nonadherent (SD > 2) M (SD) % (n) % (n) MLVI MLVI for tacrolimus 2.00 (1.43) 60 (28) 40 (19) Note. Nonadherence data for non-antirejection medications were obtained for 42 AYAs, as 5 AYAs were not prescribed any medications beyond their antirejection medications. Nonadherence % = average percentage of missed or late medication doses reported plus SD. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed or late dose(s) of medications. AYA = adolescent and young adult; MLVI = medication level variability index. How Were Barriers Associated With Reported Nonadherence to Different Medication Types? AYAs who reported nonadherence to any medications (antirejection and non-antirejection medications) had significantly higher barriers on the AMBS RA and Total scales than AYAs who denied nonadherence, with large effect sizes; there were no statistically significant differences on the PMBS. Caregiver report of AYA nonadherence to any medications was associated with significantly higher barriers on the PMBS DF, II, and Total scales than caregiver denial of nonadherence, with large effect sizes; there were no significant differences on the AMBS, though effect sizes ranged from medium to large. See Table III for details. Table III. Differences in Study Variables by Reported Nonadherence to Any Prescribed Medication (Antirejection and Non-antirejection) AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 Note. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Table III. Differences in Study Variables by Reported Nonadherence to Any Prescribed Medication (Antirejection and Non-antirejection) AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 AYA self-report Caregiver proxy-report Denied nonadherence(n = 35) Reported nonadherence(n = 12) Denied nonadherence(n = 37) Reported nonadherence(n = 10) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.47 (5.84) 22.75 (8.75) 3.79 −0.71 17.44 (5.67) 23.90 (9.22) 4.45 −0.84 AMBS RA 6.80 (2.52) 10.42 (3.92) 8.95* −1.10 7.32 (2.90) 9.20 (4.37) 1.65 −0.50 AMBS II 9.37 (3.71) 13.08 (6.14) 3.90 −0.73 9.57 (4.25) 13.10 (5.34) 3.73 −0.73 AMBS Total 33.64 (9.73) 46.25 (17.89) 5.41* −0.88 34.34 (11.04) 46.20 (17.20) 4.28 −0.82 Depression 46.17 (8.82) 50.17 (9.38) 1.67 −0.44 46.32 (8.82) 50.40 (8.56) 1.48 −0.47 Anxiety 42.74 (10.42) 46.17 (10.42) .99 −0.33 42.19 (9.67) 48.90 (11.72) 2.77 −0.62 Caregiver report PMBS DF 14.14 (5.13) 15.42 (5.81) .46 −0.23 13.62 (5.08) 17.60 (5.04) 4.89* −0.79 PMBS RA 9.66 (3.76) 10.50 (5.11) .28 −0.19 9.32 (3.82) 11.90 (4.70) 2.55 −0.60 PMBS II 4.57 (2.25) 5.25 (2.14) .88 −0.31 4.22 (1.80) 6.70 (2.63) 7.94* −1.10 PMBS PR 2.17 (1.25) 2.25 (1.14) .04 0.07 2.08 (1.26) 2.60 (.97) 1.98 −0.46 PMBS Total 30.54 (8.42) 33.42 (11.29) .65 −0.29 29.24 (8.47) 38.80 (8.07) 10.82** −1.16 BSI-18 GSI 44.06 (12.74) 53.17 (12.55) 4.67* −0.72 43.22 (11.99) 58.10 (10.92) 14.02** −1.30 Note. Denied nonadherence = reported 0 missed doses of medications; reported nonadherence = categorically reported ≥1 missed medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. AYAs who reported nonadherence to antirejection medications had higher barriers on the AMBS RA scale than AYAs who denied nonadherence, with a large effect size; there were no statistically significant differences on the PMBS. There were no significant differences between caregivers who reported versus denied AYA nonadherence to antirejection medications on the AMBS or PMBS. There were no significant differences on the AMBS or PMBS based on AYA or caregiver proxy-report of late antirejection medications and effect sizes were mostly small. See Table IV (missed antirejection medications) and Supplementary Table S1 (late antirejection medications) for details. Table IV. Differences in Study Variables by Reported Nonadherence to Antirejection Medications AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 Note. Denied nonadherence = reported 0 missed antirejection medication doses; Reported nonadherence = categorically reported ≥1 missed antirejection medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05. Table IV. Differences in Study Variables by Reported Nonadherence to Antirejection Medications AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 AYA self-report Caregiver proxy-report Denied nonadherence Reported nonadherence Denied nonadherence Reported nonadherence (n = 40) (n = 7) (n = 44) (n = 3) Factor M (SD) M (SD) Welch’s t-test d M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 18.14 (6.66) 22.71 (8.14) 1.98 −0.61 18.74 (6.84) 20.00 (10.82) 0.04 −0.14 AMBS RA 7.15 (2.88) 11.00 (3.88) 6.31* −1.13 7.66 (3.18) 8.67 (5.69) 0.09 −0.22 AMBS II 10.03 (4.45) 12.00 (5.92) 0.71 −0.38 10.27 (4.70) 11.00 (5.29) 0.05 −0.15 AMBS Total 35.31 (12.14) 45.71 (17.17) 2.36 −0.70 36.67 (13.08) 39.67 (19.63) 0.07 −0.18 Depression 46.80 (9.30) 49.43 (7.52) 0.67 −0.31 47.11 (9.13) 48.33 (9.07) 0.05 −0.13 Anxiety 43.35 (10.65) 45.14 (9.25) 0.21 −0.18 43.25 (10.21) 49.00 (13.75) 0.51 −0.48 Caregiver report PMBS DF 14.28 (5.20) 15.57 (6.00) 0.29 −0.23 14.39 (5.21) 15.67 (7.37) 0.09 −0.20 PMBS RA 9.40 (3.67) 12.57 (5.62) 2.07 −0.67 9.70 (3.95) 12.33 (6.51) 0.48 −0.49 PMBS II 4.68 (2.25) 5.14 (2.19) 0.27 −0.21 4.66 (2.13) 6.00 (3.61) 0.41 −0.45 PMBS PR 2.10 (1.19) 2.71 (1.25) 1.45 −0.50 2.11 (1.19) 3.33 (1.15) 3.12 −1.04 PMBS Total 30.45 (8.57) 36.00 (11.82) 1.41 −0.54 30.86 (8.95) 37.33 (12.74) 0.75 −0.59 BSI-18 GSI 45.03 (12.78) 54.14 (13.69) 2.69 −0.69 45.84 (13.39) 54.33 (6.51) 3.97 −0.81 Note. Denied nonadherence = reported 0 missed antirejection medication doses; Reported nonadherence = categorically reported ≥1 missed antirejection medication dose(s). Effect size = d. AYA = AYA = adolescent and young adult; BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05. AYAs who reported nonadherence to non-antirejection medications had significantly higher barriers on the AMBS RA, II, and Total scales than AYAs who denied nonadherence, with large effect sizes (d = −1.08, −0.84, and −0.89, respectively); there were no significant differences on the PMBS. Caregiver report of AYA nonadherence to non-antirejection medications was associated with significantly higher barriers on the PMBS DF and Total scales with large effect sizes (d = −0.85 and −1.17, respectively); there were no significant differences on the AMBS scales (see Supplementary Table S2). How Were AYA and Caregiver Emotional Distress Symptoms Associated With Reported Nonadherence to Different Medication Types? There were no differences on AYA depression or anxiety symptoms based on AYA or caregiver report of missed doses of any (antirejection and non-antirejection medications), antirejection, or non-antirejection medications or late doses of antirejection medications. For AYAs reporting nonadherence to any and non-antirejection medications, caregiver emotional distress symptoms were significantly higher than AYAs who denied nonadherence, with medium and large effect sizes (d = −0.72 and −1.01, respectively). For caregivers reporting AYA nonadherence to any and non-antirejection medications, caregiver emotional distress symptoms were significantly higher than caregivers who denied nonadherence, with large effect sizes (d = −1.30 and −1.48, respectively). There were no differences on caregiver emotional distress symptoms based on AYA- or caregiver proxy-reported missed or late doses of antirejection medications. See Tables III and IV and Supplementary Tables S1 and S2 for details. How Were Barriers and AYA and Caregiver Emotional Distress Symptoms Associated With the MLVI for Tacrolimus? AYAs with MLVIs >2 (i.e., nonadherent to tacrolimus) had significantly higher scores on the AMBS DF, II, and Total scales and PMBS II scale than AYAs with MLVIs ≤2 (i.e., adherent to tacrolimus; see Table V), with medium to large effect sizes. There were no differences on AYA or caregiver emotional functioning symptoms based on the MLVI. Table V. Differences in Study Variables Based on the MLVI for Tacrolimus MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 Note. For the MLVI, SD > 2 was “nonadherent” and SD ≤ 2 was “adherent.” Effect size = d. AYA = adolescent and young adult; MLVI = medication level variability index. BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Table V. Differences in Study Variables Based on the MLVI for Tacrolimus MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 MLVI Adherent (n = 28) Nonadherent 19) Factor M (SD) M (SD) Welch’s t-test d AYA report AMBS DF 17.07 (6.69) 21.39 (6.80) 4.62* −0.64 AMBS RA 7.82 (3.40) 7.58 (3.24) 0.06 0.07 AMBS II 8.82 (4.17) 12.53 (4.60) 7.91** −0.85 AMBS Total 33.71 (13.05) 41.49 (12.64) 4.18* −0.61 Depression 47.11 (9.76) 47.32 (8.10) 0.01 −0.02 Anxiety 42.18 (11.09) 45.74 (9.10) 1.45 −0.35 Caregiver report PMBS DF 13.36 (5.22) 16.11 (5.05) 3.26 −0.54 PMBS RA 10.36 (4.06) 9.16 (4.18) 0.95 0.29 PMBS II 4.11 (1.71) 5.68 (2.58) 5.46* −0.72 PMBS PR 2.29 (1.27) 2.05 (1.13) 0.44 0.20 PMBS Total 30.11 (9.46) 33.00 (8.74) 1.16 −0.32 BSI-18 GSI 44.93 (11.92) 48.53 (14.92) 0.77 −0.27 Note. For the MLVI, SD > 2 was “nonadherent” and SD ≤ 2 was “adherent.” Effect size = d. AYA = adolescent and young adult; MLVI = medication level variability index. BSI-18 = Brief Symptom Inventory-18; DF = Disease Frustration/Adolescent Issues; GSI = Global Severity Index; II = Ingestion Issues; PMBS = Parent Medication Barriers Scale; PR = Parent Reminder; RA = Regimen Adaptation/Cognitive Issues. * p < .05; **p < .01. Discussion Inconsistencies in nonadherence rates based on assessment method are well known (Stirratt et al., 2015), but there is limited information on differences in reported nonadherence by medication type compared with the MLVI in AYAs with transplants. Barriers to adherence have demonstrated relations with nonadherence in AYAs with solid organ transplant (McCormick King et al., 2014), but less is known about associations with nonadherence to medication types and the MLVI. This study uniquely illustrates potential issues with underreporting nonadherence in AYAs with transplants and their caregivers and is the first study to link barriers to adherence with the MLVI. Preliminary analyses also revealed that older AYA age, shorter time since transplantation, and having a heart transplant may be risk factors for more barriers, and longer time since transplantation may be associated with more stable MLVIs for tacrolimus. These results may help providers contextualize how nonadherence is reported in this population and highlight the types of barriers related to different nonadherence assessment approaches. AYAs and caregivers reported nonadherence at low rates, especially for antirejection medications (De Bleser et al., 2011). In contrast, nonadherence rates obtained with the MLVI were consistent with aggregated estimates from a prior review of nonadherence in AYA transplant recipients (Dobbels et al., 2009). The MLVI is relatively free from social desirability issues and totally free from recall concerns, which further highlights potential issues with underreporting nonadherence. These data emphasize the need to refine methods for clinically assessing nonadherence, given that face-to-face discussions remain the primary modalities for assessment and intervention (Wu et al., 2013). Differences in nonadherence rates by assessment method reiterate guidance to use multimethod assessments that include objective measures (Quittner et al., 2008). Consistent with prior findings (McCormick King et al., 2014; Simons et al., 2010), AYAs and caregivers who reported nonadherence also endorsed more barriers, potentially because of the severity of AYAs’ challenges with following their regimen. Of note, far fewer AYAs and caregivers endorsed antirejection medication nonadherence, which may have contributed to just one association between AYA-reported missed antirejection medications and the AMBS RA scale and no differences in barriers based on caregiver-report. These results suggest that if an AYA transplant recipient or their caregiver acknowledges medication nonadherence, the AYA may be experiencing significant obstacles to following their prescribed regimen that warrant more detailed assessment and potentially clinical intervention. Given associations with AYA and caregiver reported nonadherence to any and non-antirejection medications, higher levels of caregiver emotional distress may serve as barriers to adherence by reducing the degree to which caregivers are emotionally available to supervise and support AYA adherence. More parental monitoring has shown associations with higher adherence in adolescents with other chronic medical conditions (Ellis et al., 2007). The lack of differences in AYA emotional functioning based on AYA or caregiver reported nonadherence may reflect lower levels of emotional problems endorsed by AYAs in this sample. Caregivers may experience more emotional distress symptoms when their AYA is nonadherent than AYAs experience themselves. Alternatively, the AMBS and PMBS may be more relevant to problems with nonadherence than AYAs’ general feelings of sadness or anxiety. This is the first study to link barriers and the MLVI for tacrolimus. Notably, the MLVI is an index of medication intake, which underscores the significance of associations with the AMBS and PMBS II subscales. A prior study attempted to relate serum assays to barriers but only obtained one tacrolimus value instead of the MLVI (Danziger-Isakov et al., 2016). Another study linked one PMBS item to medication variability levels combining three antirejection medications (Simons et al., 2010). This study also found that higher scores on the PMBS and AMBS II scales related to higher rates of death and hospitalizations in the sample of adolescents with solid organ transplants. Together, findings from Simons and colleagues (2010) and the current study suggest that issues related to ingesting medications are critical barriers to assess and treat to prevent nonadherence and negative health outcomes. The current study advances the literature with its methodology and clinical significance by connecting barriers to an index of actual medication intake patterns over 1 year. These findings provide further evidence for the clinical use of the AMBS and PBMS to evaluate barriers and add to the literature in support of using the MLVI to assess nonadherence to tacrolimus. Evaluating caregiver emotional functioning may provide insight into family or environmental barriers to adherence. Assessing barriers with the AMBS or PMBS may be more useful than probing AYA depression or anxiety symptoms when evaluating nonadherence. The MLVI is an increasingly publicized objective tool for measuring nonadherence to tacrolimus. An advantage of the MLVI is that it is easy to calculate from data collected as part of standard care and is clinically meaningful to pediatric psychologists, physicians, and pharmacists who frequently provide interdisciplinary adherence intervention to this population. Providers may calculate the MLVI to evaluate AYAs’ nonadherence to tacrolimus and, if >2, conduct an in-depth assessment of adherence barriers, and also deliver clinical recommendations for overcoming these barriers. Patients whose MLVI values are ≤2 may still benefit from clinical recommendations for managing common barriers to adherence. The current findings shed light on known issues with reporting nonadherence. Although it was emphasized that reports would not impact clinical care, low rates of reported nonadherence, especially for antirejection medications, may reflect challenges patients, and caregivers have with discussing potentially uncomfortable topics with providers and researchers or recall issues. In adolescents with type 1 diabetes, patient-centered communication related to higher adherence (Croom et al., 2011) and may be applicable to AYAs with transplants. Electronic monitoring methods would address recall concerns. Future researchers should investigate whether AYAs and caregivers who exhibit greater recognition of problems with nonadherence are more open to addressing the concerns via intervention. This study had limitations, including a smaller sample size, which was further reduced by examining the MLVI for tacrolimus only, and use of multiple statistical comparisons. Welch’s t-test was selected because it is relatively robust to type I error; effect sizes for statistically significant results were medium to large, but results should be interpreted as preliminary data that lay the groundwork for studies with more rigorous methodology. There were high numbers of participants who denied nonadherence, owing to likely issues with reporting in contrast to the MLVI, but the reasons why these contrasts were observed were not identified. Nonadherence rates on the MLVI may have been influenced by inherent methodological weaknesses (e.g., interactions with other medications, white coat compliance, lack of protocol for handling different numbers of assays per individuals, variable lengths of time between assays). The MAM and MLVI assessment periods occurred over different lengths of time (i.e., 1 week for the MAM, 1 year for the MLVI), and the two assessments should not be interpreted as completely equivalent. Barriers may have different associations with nonadherence based on assessment period. Some of the PMBS subscales had low internal consistency and the AMBS and PMBS measured overall barriers rather than barriers to specific medications. Participants were recruited from one site and caregivers mostly identified as female, which may impact generalizability. Older AYAs may have unique environmental circumstances influencing nonadherence, especially if they live away from caregivers, which were not measured in this study. Clinical assessment of nonadherence remains a challenge as evidenced by low rates of reported nonadherence to different medication types in contrast to the MLVI. The MLVI offers a viable and potentially more valid alternative to assessing nonadherence to tacrolimus via self-report. The current study provides preliminary support for associations between the MLVI and adherence barriers and adds to growing evidence that pediatric psychologists should assess barriers to adherence given associations with multiple methods of evaluating nonadherence. These findings underscore the importance for the pediatric psychology field to link behavioral variables, such as barriers to adherence, with objective, clinical outcomes, such as the MLVI, to strengthen the scientific and clinical impact of our research. Future researchers should investigate whether barriers to adherence should be prioritized in pediatric clinical assessment over attempting to gauge nonadherence via clinical interview. This approach may offer insight into the types of challenges AYAs face when following complex regimens and provide clinical opportunities to address these concerns; however, this proposal awaits empirical investigation. Supplementary Data Supplementary data can be found at: http://www.jpepsy.oxfordjournals.org/. Acknowledgments We are grateful to the participants who provided us with their time and made this study possible. We also thank Mary Gray Stolz for her involvement in this study. Funding This study was funded by the Transplant Services Research Fund at Children's Healthcare of Atlanta. This study also received funding from the Psi Chi Graduate Research Grant, the American Psychological Association of Graduate Students Nancy B. Forest and L. Michael Honaker Master's Grant, the University of Georgia (UGA) Center for Research and Engagement in Diversity Seed Grant, and the UGA Graduate School Dean’s Award (to A.M.G.-C.). Disclosures: R.R. is a recipient of research funding from Gilead Sciences, Inc.: References Bishay L. C. , Sawicki G. S. ( 2016 ). Strategies to optimize treatment adherence in adolescent patients with cystic fibrosis . 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Published: Mar 17, 2018

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