Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Profiles of Adjustment in Pediatric Cancer Survivors and Their Prediction by Earlier Psychosocial Factors

Profiles of Adjustment in Pediatric Cancer Survivors and Their Prediction by Earlier Psychosocial... Abstract Objective To examine individual differences in pediatric cancer survivors’ psychosocial adjustment and test the psychosocial predictors, assessed 2–3 years earlier, of those differences. Method Pediatric cancer survivors (n = 209, aged 8–17 years at baseline) and their parents were followed for 4 years. They provided reports of survivors’ psychosocial adjustment at 3 years post-baseline, and latent profile analysis (LPA) was used to identify subgroups of survivors who differed on those reports. Multinomial logistic regression was used to predict group membership from self- and parent-reported psychosocial factors at baseline (child adjustment, disposition, and parental functioning) and at 1 year post-baseline (child social relations). Results The LPA revealed a 3-class model as the best fit: a “Resilient” group (65%), characterized by good psychosocial adjustment; a “Self-Reported At-Risk” group (23%), characterized by subclinical elevations in self-reported internalizing and attention problems; and a “Parent-Reported At-Risk” group (12%), characterized by subclinical elevations in parent-reported internalizing, externalizing, and attention problems and in self-reported attention problems. Several psychosocial predictors, including child posttraumatic stress, affectivity, and connectedness to school, as well as parental distress and overprotection, differentiated the Resilient group from the other groups, in expected directions. Conclusions The majority of pediatric cancer survivors exhibit enduring resilience. The protective factors identified for them—including positive affectivity and strong connectedness to school—may inform targeted prevention strategies for the minority of survivors who are at risk for maladjustment. adjustment, adolescents, cancer and oncology, longitudinal research, mental health, parenting, psychosocial functioning, resilience Although most pediatric cancer survivors maintain similar levels of psychosocial adjustment as healthy peers during treatment and survivorship (Eiser, Hill, & Vance, 2000; Langeveld, Stam, Grootenhuis, & Last, 2002; Robinson, Gerhardt, Vannatta, & Noll, 2009), a significant minority of survivors experience such psychosocial difficulties as depression, anxiety, attention problems, and externalizing problems compared with controls (Krull et al., 2010) and norms (Zeltzer et al., 2009). In addition, some studies have found that survivors, on average, may fare worse than controls in such areas as mood (Zeltzer et al., 1997), self-esteem (Servitzoglou, Papadatou, Tsiantis, & Vasilatou-Kosmidis, 2008), and relational functioning (Mackie, Hill, Kondryn, & McNally, 2000). To deliver targeted preventive services to survivors at risk for maladjustment, at-risk survivors first need to be identified. One way to do so is through the use of person-centered analytic methods, which identify groups of individuals who differ on outcomes. Such methods have been previously applied to the participants of the Childhood Cancer Survivor Study (CCSS) to show that a majority of adolescent survivors, including those who had received cranial radiation therapy (CRT), exhibited minimal parent-reported internalizing, externalizing, and social withdrawal symptoms (Brinkman et al., 2016). However, a significant minority, ranging from approximately 30% of those not having received CRT to 37% of those having received CRT, exhibited some combination of symptoms. Similar patterns are found in adulthood, with roughly two-thirds of CCSS participants reporting minimal self-reported symptoms of depression, anxiety, and somatization over time (Brinkman et al., 2013). Further replication with other samples of pediatric cancer survivors is needed. Moreover, risk and protective factors that differentiate between resilient survivors who are well-adjusted and those who experience maladjustment need to be identified. To date, most existing studies have focused on the predictive effects of demographic and medical or health-related factors (Langeveld et al., 2002), including the use of central nervous system-directed therapy and type of cancer diagnosis (Kahalley et al., 2013; Zeltzer et al., 2009). The predictive effects of psychosocial factors have not yet been studied widely, though associations have been found between survivors’ adjustment and such factors as self-reported anxiety (Ozono et al., 2007), peer relations (Maurice-Stam, Grootenhuis, Caron, & Last, 2007), and parent–child relationship quality (Orbuch, Parry, Chesler, Fritz, & Repetto, 2005). Furthermore, most studies on survivors’ psychosocial adjustment have used cross-sectional design and variable-centered analytic methods. They demonstrate associations between risk or protective factors and outcomes at the population level but cannot clarify whether those factors predict outcomes longitudinally or work differently for subsets of individuals. The present study sought to fill this gap by applying a person-centered analytic method to identify groups of survivors who differed on psychosocial outcomes and test for factors that prospectively differentiated those groups. Because prospective research on survivors’ adjustment is limited, we examined four sets of factors that affect patients’ adjustment, to see whether they also predict survivors’ adjustment. They were (a) child distress (posttraumatic stress [PTS], depression, and anxiety), (b) child disposition (optimism, pessimism, and positive and negative affectivity), (c) parental functioning (parental care, overprotection, PTS, and global distress), and (d) child social relations (perceived support and connectedness). Their effects are reviewed briefly in the following text. First, although longitudinal research examining the predictive effects of earlier distress is limited, existing studies suggest that child PTS symptoms are associated over time in pediatric patients (Landolt, Ystrom, Sennhauser, Gnehm, & Vollrath, 2012), and a small minority of long-term pediatric cancer survivors experiences persistent distress (Brinkman et al., 2013). In addition, previous experiences of depression, anxiety (Costello, Foley, & Angold, 2006), and PTS (Trickey, Siddaway, Meiser-Stedman, Serpell, & Field, 2012) have been linked to increased risk for future psychopathology in children and adolescents more generally. Thus, prior distress may predict later maladjustment among survivors. In addition to prior distress, disposition with respect to cognitive style and affectivity has been linked to adjustment. For example, optimism has been found to have a positive association with mental health functioning (Williams, Davis, Hancock, & Phipps, 2010), whereas pessimism has been negatively associated with emotional functioning (Sulkers et al., 2013). Optimism and pessimism have been found to covary with positive affectivity and negative affectivity, respectively, in pediatric cancer patients, and predict later psychosocial adjustment (Okado, Howard Sharp, Tillery, Long, & Phipps, 2016). Moreover, negative affectivity has been linked to anxiety and depression based on maternal report (Miller et al., 2009). Taken together, optimism and positive affectivity are expected to protect against maladjustment, whereas pessimism and negative affectivity are expected to increase risk for maladjustment. Parental factors that are known to influence child adjustment outcomes include parental well-being, such as parental distress and symptoms of anxiety and depression (Klassen, Anthony, Khan, Sung, & Klaassen, 2011). The parent–child bond is also known to influence child adjustment. For instance, a review on the associations between family functioning and child adjustment after pediatric cancer diagnosis found that families characterized by greater parental care (i.e., higher family cohesion, expressiveness, and support) had children with better adjustment (Van Schoors et al., 2017). In addition, parental overprotection has been linked to greater child distress (Tillery, Long, & Phipps, 2014). Thus, parental functioning characterized by minimal parental distress and better-quality (i.e., more caring and less overprotective) parent–child relationships are expected to predict better survivor adjustment. Similarly, social relationships and support are highly influential in the adjustment of pediatric cancer patients and survivors (Servitzoglou et al., 2008; Zebrack, 2011), with parents and peers being especially important sources of social support (Trask et al., 2003). Moreover, higher levels of connectedness to others and a greater variety of individuals to whom one feels connected are both positively associated with psychosocial adjustment (Howard Sharp et al., 2015). Finally, patients with low levels of distress report greater connectedness to peers than those who report some distress (Tillery, Cohen, Berlin, Long, & Phipps, 2017). Thus, greater levels of social support and connectedness to others are expected to predict better adjustment among survivors. In sum, the present study aimed to identify subgroups of pediatric cancer survivors who differ in their adjustment and test whether membership in these subgroups could be predicted by earlier psychosocial factors. Based on the existing literature, the present study examined outcomes that are of potential concern for survivors, including internalizing, externalizing, and attention problems, and difficulties with personal adjustment. We hypothesized that multiple subgroups would be found among survivors, with the largest group exhibiting minimal problems. Furthermore, we expected that these groups would be differentiated by child distress, disposition, and perceived social support and parental functioning that had been assessed 2–3 years earlier. Method Participants Participants were survivors of pediatric cancer (n = 209) and their primary caregiver (“parent”; 82.8% mothers, 12.4% fathers, and 4.8% other) enrolled in a longitudinal study on patient coping and adjustment who completed the study’s third time point. At baseline, they were of age 8–17 years, at least 1 month past their diagnosis, able to speak and read English, and without significant cognitive or sensory deficits. To achieve a heterogeneous yet balanced sample in terms of where patients were in the treatment trajectory, participants were recruited into one of four strata based on time elapsed since diagnosis: 1–6 months (n = 51; 24.4%), 6 months to 2 years (n = 50; 23.9%), 2–5 years (n = 55; 26.3%), and 5 years or more (n = 53; 25.4%). As described in an earlier report on baseline findings from this study (redacted for blind review), 68% of those approached agreed to participate; participants and nonparticipants did not differ by age, gender, race/ethnicity, or cancer diagnosis; and the final sample was representative of the population served by the hospital. Five additional participants had completed the longitudinal study’s third time point but were excluded from the present sample because they were on treatment. After baseline, follow-up assessments took place 1 year (T2) and 3 years (T3) later. Not all participants were invited to participate at T2, as some participants missed the 1-year follow-up window owing to a delay in the approval of a study amendment related to the longitudinal assessment, resulting in participation of 60.4% (n = 154) of the original sample (N = 255). No differences in baseline demographic, medical, or study variables were found between those who were assessed at T2 and those who were not. At T3, 83.9% of the original sample participated in the assessment, 6.3% were deceased (n = 16), and 9.8% (n = 25) did not participate. Participants included in the present sample did not differ in baseline demographic characteristics or predictor variables from those who were not included (Table I). Table I. Demographic Characteristics of the Study Sample At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) Note. Excluded participants refer to participants who were part of the longitudinal study (N = 255) but not included in the current sample. Dashes in cells represent frequencies that did not differ from baseline. Table I. Demographic Characteristics of the Study Sample At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) Note. Excluded participants refer to participants who were part of the longitudinal study (N = 255) but not included in the current sample. Dashes in cells represent frequencies that did not differ from baseline. Procedures At all three time points, participants were assessed in the outpatient psychology clinic of the hospital. Informed consent/assent was obtained from patients and their parents, and they completed questionnaires in separate rooms. Trained research assistants were available to assist and read items aloud if needed. At each assessment, each participant received a $25.00 gift card as compensation for their time, effort, and travel. Procedures were approved by the hospital’s institutional review board. Measures Survivor adjustment outcomes were assessed at T3, 3 years post-baseline, using both youth and parent report. At baseline, youths reported on their distress, disposition, and perceived parenting, and parents reported on their own distress. At T2, youths reported on their social functioning. Unless otherwise indicated, higher scores on the measures indicate greater amount of the assessed construct. Survivor Outcomes (T3) Survivors and parents reported on survivors’ psychosocial adjustment on the Behavior Assessment System for Children, Second Edition (BASC-2; Reynolds & Kamphaus, 2004), a well-validated and widely used measure of child behavioral problems. Items were rated on a true/false scale or a 4-point Likert scale ranging from 1 (never) to 4 (almost always). Gender-normed T-scores were obtained for self- and parent-reported scales. Self-reported scales included internalizing problems composite (α = .95–.96), consisting of subscales on atypicality, locus of control, social stress, anxiety, depression, sense of inadequacy, and somatization; attention problems subscale (α = .75–.80); and a personal adjustment composite (α = .88–.91), which is composed of subscales on relationship with parents (i.e., a positive regard toward parents and a feeling of being esteemed by them), interpersonal relations (i.e., the perception of having good social relationships and friendships with peers), self-esteem (i.e., feelings of self-esteem, self-respect, and self-acceptance), and self-reliance (i.e., confidence in one’s ability to solve problems and belief in one’s personal dependability and decisiveness). Parent-reported scales included were internalizing problems composite (consisting of anxiety, depression, and somatization; α = .89–.91); externalizing problems composite, consisting of subscales on hyperactivity, aggression, and conduct problems (α = .92–.95); and attention problems (α = .85–.90). With the exception of the personal adjustment composite, T-scores that fall between 60 and 69 are classified as at-risk, which reflects a level of symptoms that warrant further monitoring but do not yet require intervention, and T-scores of 70 or above are classified as clinically significant. For the personal adjustment composite, T-scores between 31 and 40 are classified as at-risk and 30 or below are classified as clinically significant. The BASC-2 has excellent psychometric properties (Reynolds & Kamphaus, 2004). Child Distress (Baseline) Children reported on their PTS, depression, and anxiety. PTS was assessed using the UCLA PTSD Reaction Index for DSM-IV Post-Traumatic Stress Disorder (PTSD) (Pynoos, Rodriguez, Steinberg, Stuber, & Frederick, 1998), a 22-item measure assessing DSM-IV Post-Traumatic Stress Disorder (PTSD) criteria met in the past month based on the most traumatic, stressful event identified by the respondent, regardless of whether or not it was cancer-related or met the A1 criterion. Children rated items (e.g., “I watch out for danger or things that I am afraid of”) on a 5-point Likert scale ranging from 0 (none) to 4 (most). PTSDI has excellent internal and test–retest reliability, and the full-scale Cronbach’s α was .90 in the present sample. Depression symptoms were assessed using Children’s Depression Inventory (CDI; Kovacs, 1992), a 27-item measure that asked children to select one of three statements that best described them over the past 2 weeks (e.g., “I am sad once in a while/many times/all the time”). Items were scored on a 0–2 scale and summed (α = .82). Anxiety symptoms were assessed using the Screen for Child Anxiety Related Emotional Disorders (SCARED; Birmaher et al., 1999), a 41-item measure that asked children to rate how much each item (e.g., “I am nervous”) described them over the past 3 months using a 3-point scale ranging from 0 (not/hardly ever true) to 2 (very/often true). The total sum score was used in the present study (α = .91). SCARED has good convergent and divergent validity (Birmaher et al., 1999). Child Disposition (Baseline) Child optimism and pessimism were assessed using the Youth Life Orientation Test (YLOT; Ey et al., 2005). Children rated seven items each for optimism and pessimism subscales (e.g., “I usually expect to have a good day”; “Things usually go wrong for me”) on a 4-point Likert scale ranging from 1 (not true for me) to 4 (true for me). Items were summed to obtain subscale scores for optimism (α = .76) and pessimism (α = .73). YLOT has good internal consistency, test–retest reliability, and convergent, discriminant, and predictive validity (Ey et al., 2005). Child affectivity was assessed using the Positive and Negative Affect Scale for Children (PANASC; Laurent et al., 1999), a 20-item measure. Children rated how often they have recently felt the emotion indicated by the item (e.g., happy, joyful, sad, and afraid) on a 5-point Likert scale ranging from 1 (very slightly or not at all) to 5 (extremely), and items were summed for positive affectivity (α = .90) and negative affectivity (α = .86) subscales. PANASC has good convergent and divergent validity (Laurent et al., 1999). Parental Functioning (Baseline) Children reported on perceived parental behavior on the Parent Bonding Instrument (PBI; Parker, Tupling, & Brown, 1979), a 25-item measure that assesses overprotection (e.g., “Tends to baby me”; α = .85) and care (e.g., “Is affectionate to me”; α = .76). Items are rated on a 4-point Likert scale ranging from 0 (very unlike) to 3 (very like) and summed. Parents reported on their own PTS, experienced within the past week, on the Impact of Events Scale, Revised (IESR; Weiss, 2004), a 22-item measure. They rated symptoms (e.g., “stayed away from reminders of it”) associated with the most traumatic event they had experienced, using a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely). Ratings were summed to obtain the total score (α = .94). Parents also reported on their own distress over the past week on the Brief Symptom Inventory (BSI; Derogatis & Melisaratos, 1983). Parents rated 53 symptoms (e.g., “Feeling blue”) on a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely). Gender-normed T-score for the Global Severity Index (GSI), normed for the adult nonpatient population, was used to capture parental distress (α = .95). Social Relations (T2) One year past the baseline assessment, children reported on perceived availability of social support through the support subscale from the Resiliency Scales for Children and Adolescents (RSCA; Prince-Embury, 2007). Participants rated items (e.g., “If something bad happens, I can ask my friends for help”) on a 5-point Likert scale ranging from 0 (never) to 4 (almost always). Scaled scores normed on age and gender were obtained (α = .79). Connectedness to others was assessed using Hemingway Measure of Adolescent Connectedness (HMAC; Karcher, 2012), a 57-item measure of positive connections to one’s social environment. Items (e.g., I “enjoy spending time with my parents”; “enjoy being at school”) were rated on a 5-point Likert scale ranging from 1 (not at all true) to 5 (very true). Mean scores were obtained for subscales reflecting connectedness to friends (α = .80), parents (α = .81), school (α = .77), peers (α = .77), and teacher (α = .72). Analytic Plan To examine individual differences in survivors’ psychosocial adjustment at T3, latent profile analysis (LPA) was applied. LPA is a person-centered analytic method that identifies homogenous subgroups of individuals, or latent classes, who differ on continuous outcome variables. The number of classes to be fitted to the data is specified a priori, and models with different numbers of classes are compared on indices of model fit and interpretability. In the present study, the model fit was compared using the Bayesian information criterion (BIC), entropy, and the Lo–Mendell Bayesian information criterion Rubin likelihood ratio test of model fit (LMRT; Lo, Mendell, & Rubin, 2001). Superior model fit is indicated by lower BIC, higher entropy, which is an index of how well the data are classified into latent classes, and significant result for the LMRT. After the best model was selected, its classes were compared on mean scores of the predictor variables using the Bolck–Croon–Hagenaars (BCH) method (Asparouhov & Muthén, 2014), with Holm–Bonferroni correction applied to control for familywise error. Then, the predictive effects of potential covariates and predictor variables were tested through multinomial logistic regression, using the three-step approach for testing the prediction of distal latent classes (Asparouhov & Muthén, 2013). As missing data are not permitted in predictors, cases with missing data in any predictor were removed from the regression analyses. There were no differences in demographic or medical characteristics or in study measure scores between those who were included versus excluded from these analyses. To avoid under-powering analyses and to maximize available data, predictors were grouped into four sets (child distress, child disposition, and parental functioning at baseline; child social functioning at Time 2) and tested by set; thus, four regressions were run. Missing data in outcome measures, which were consistent with the assumption that they are missing at random, were handled using full information maximum likelihood, with standard errors that are robust to non-normal data. Analyses were run in Mplus 7.31. Results Bivariate correlations between the predictor variables and the outcome variables, as well as among the outcome variables, are presented in Table II. On the whole, the variables were related in expected directions, though parent-reported outcomes were not associated with several predictors. Table II. Bivariate Correlations Between Outcome and Predictor Variables Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Note. M(SD) reported in the diagonals for the T3 outcome variables. PTS = posttraumatic stress; GSI = Global Severity Index from the Brief Symptom Inventory. * p < .05. **p < .01. ***p < .001. Table II. Bivariate Correlations Between Outcome and Predictor Variables Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Note. M(SD) reported in the diagonals for the T3 outcome variables. PTS = posttraumatic stress; GSI = Global Severity Index from the Brief Symptom Inventory. * p < .05. **p < .01. ***p < .001. LPA models with two to five classes were compared (Table III). The three-class model was selected as the final model, based on relatively low BIC, the largest drop in BIC compared with the model with one fewer class, high entropy, and significant LMRT result. This model also had theoretically meaningful profiles of scores on outcome variables. Table III. Model Fit Indicators for Latent Profile Analyses Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Note. BIC = Bayesian information criterion. Lower BIC and higher entropy values indicate better model fit. Significant results for the Lo–Mendell–Rubin test indicate superior model fit compared with the model with one fewer class. Table III. Model Fit Indicators for Latent Profile Analyses Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Note. BIC = Bayesian information criterion. Lower BIC and higher entropy values indicate better model fit. Significant results for the Lo–Mendell–Rubin test indicate superior model fit compared with the model with one fewer class. The three-class model is illustrated in Figure 1. The largest class, “Resilient” class (R; 65.4% of the sample), was characterized by lower scores on internalizing, externalizing, and attention problems and a higher score on personal adjustment than the normative mean (T = 50). The next largest class, the “Self-Reported At-Risk” class (SAR; 23.0%), was characterized by scores in the at-risk range on self-reported internalizing and attention problems and below average, though normal range, scores on personal adjustment. However, this class had roughly average, normal range scores based on parent-report. Finally, the smallest class, the “Parent-Reported At-Risk” class (PAR; 11.6%), was characterized by scores in the at-risk range in parent-reported internalizing, externalizing, and attention problems and self-reported attention problems. Overall, there was support for the hypothesis that multiple subgroups of survivors would be identified, with the largest group characterized by positive adjustment. Figure 1. View largeDownload slide Latent profiles of self- and parent-reported survivor outcomes. Figure 1. Mean scores for the three latent classes based on self-report (S) and parent-report (P). Percentages in the legend indicate the proportion of the sample that is estimated to belong to that latent class. T-score of 50 indicates the normative sample mean (SD = 10). BASC-2 = Behavior Assessment System for Children, Second Edition. Figure 1. View largeDownload slide Latent profiles of self- and parent-reported survivor outcomes. Figure 1. Mean scores for the three latent classes based on self-report (S) and parent-report (P). Percentages in the legend indicate the proportion of the sample that is estimated to belong to that latent class. T-score of 50 indicates the normative sample mean (SD = 10). BASC-2 = Behavior Assessment System for Children, Second Edition. Next, the three classes were compared on the mean scores for each predictor (Table IV). Significant differences were found in most of the predictors, except in self-reported perceived support (RSCA), connectedness to friends, and parental care, and parental PTS. Where significant differences were found, the Resilient class scored more favorably than the other two classes. Thus, the Resilient class was distinguished from the other two classes by better psychological adjustment and more optimal disposition, parental functioning, and social relations compared with the other two classes. Table IV. Class-Specific Means and Standard Errors for the Predictor Variables Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Note. Time 2 (T2) predictors were tested for the subset of the sample that had data for those predictors (n = 131). Holm–Bonferroni correction with α = .05 was applied to control for familywise error. Table IV. Class-Specific Means and Standard Errors for the Predictor Variables Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Note. Time 2 (T2) predictors were tested for the subset of the sample that had data for those predictors (n = 131). Holm–Bonferroni correction with α = .05 was applied to control for familywise error. Next, effects of potential covariates were tested. Demographic and medical factors, including age, race, socioeconomic status, gender, diagnostic category, time since diagnosis, and time since treatment completion, were not significant covariates. However, whether the survivor had any history of relapse had a significant effect and was controlled for in subsequent analyses. Several factors at baseline significantly predicted class membership at T3 (Table V), in expected directions. Baseline child PTS was associated with the odds of belonging to one of the non-Resilient classes. Child pessimism, positive and negative affectivity, and parental overprotection at baseline and connectedness to school at T2 significantly influenced the odds of belonging to the SAR class compared with the Resilient class, in expected directions. Baseline parental distress was the only predictor that affected the odds of belonging to the PAR class compared with the Resilient class. No predictor differentiated between the SAR and PAR classes. Overall, several predictors differentiated 2–3 years in advance those survivors who would belong to the Resilient class, but several other predictors, including parental PTS and child-reported depression, anxiety, optimism, perceived parental care, and connectedness to parents, friends, teacher, or peers, did not affect class membership. Table V. Multinomial Logistic Regression Results for Significant Predictors of Latent Class Membership Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Note. Model 1: N = 203; Model 2: N = 201; Model 3: N = 205; Model 4: N = 126. All four regression analyses controlled for relapse history. a “Compared with” indicates the reference class against which the odds of membership in another class was compared. * p < .05. **p < .01. Table V. Multinomial Logistic Regression Results for Significant Predictors of Latent Class Membership Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Note. Model 1: N = 203; Model 2: N = 201; Model 3: N = 205; Model 4: N = 126. All four regression analyses controlled for relapse history. a “Compared with” indicates the reference class against which the odds of membership in another class was compared. * p < .05. **p < .01. Discussion The present study found three distinct patterns of psychosocial adjustment in a sample of largely adolescent to young adult pediatric cancer survivors. Consistent with findings from previous research, nearly two-thirds (65%) of survivors exhibited long-term resilience to their cancer experience, enjoying the best psychosocial adjustment and interpersonal connectedness among the three identified groups during the 3-year study period. The remaining one-third of the survivors diverged into two groups. One group (SAR; 23%) reported at-risk levels of internalizing and attention problems, but only by self-report. In contrast, the smallest group (PAR; 12%) exhibited at-risk levels of parent-reported externalizing, internalizing, and attention problems and at-risk level of self-reported attention problems. As such, no group evidenced clinically significant levels of distress in the present study. This is inconsistent with previous studies that have found clinically elevated psychological symptoms in survivors (Brinkman et al., 2016; Zeltzer et al., 2009). One potential reason for the discrepancy may be that the BASC-2, the outcome measure used in the present study, identifies relatively few cases in the clinically significant range (Wolfe-Christensen, Mullins, Stinnett, Carpentier, & Fedele, 2009). The two non-Resilient groups differed primarily by the reporter that indicated maladjustment. Only the survivors in the SAR group reported internalizing and attention problems. These symptoms, especially in the absence of other accompanying symptoms (e.g., hyperactivity) and at subclinical levels, may not be readily observable to parents. This would be consistent with some previous findings indicating that parent–child agreement regarding internalizing problems may be lower compared with agreement regarding externalizing problems (De Los Reyes & Kazdin, 2005). In the PAR group, survivors and parents agreed that the survivor had at-risk levels of attention problems, but only parents reported internalizing and externalizing problems. One possible reason for this discrepancy is that parents themselves are distressed, which can contribute to higher endorsement of symptoms for their children (Youngstrom, Loeber, & Stouthamer-Loeber, 2000). This view is also consistent with our findings that higher levels of parental distress at baseline predicted membership in this group. Another possible explanation for the discrepancy is that the youths in this group may be reluctant or unaware of the existence of internalizing or externalizing problems (De Los Reyes & Kazdin, 2005). Of note, both groups were characterized by self-reported attention problems in the at-risk range. This may be because survivors tend to experience attention problems at a greater rate than comparison groups (Krull et al., 2010), possibly because of late effects of treatment, or because attention problems can be associated with internalizing or externalizing problems (Kim & Deater-Deckard, 2011). Because no predictor differentiated between the two distressed groups, how they diverged over time is unclear. Further research is needed to identify factors that predict this divergence. Also, as externalizing problems were assessed only by parent-report owing to the absence of a self-report scale for externalizing problems in the BASC-2, the two groups may differ based on whether distress is externalized and noticeable to others. Survivors in the SAR group may internalize their difficulties and be less outwardly symptomatic, whereas those in the PAR group may more outwardly exhibit their distress. In contrast, several psychosocial predictors significantly differentiated the Resilient group from the two distressed groups 3 years later. Child-reported PTS and parents’ self-reported distress increased the odds that the survivors would later belong to the PAR group instead of the Resilient group. Thus, these two predictors may reflect heightened or shared distress within the parent–child dyad that negatively impacts survivors’ adjustment. Child-reported pessimism, negative affectivity, and parental overprotection increased the odds of later belonging to the SAR group, and these predictors may be associated with survivors’ internalizing tendencies. Findings are consistent with previous studies suggesting that child and parental distress, child disposition characterized by negative cognitions and affect, and overprotective parenting all increase risk for maladjustment (Okado et al., 2016; Tillery et al., 2014; Zeltzer et al., 1997). Moreover, elevations in these factors may identify survivors who are at risk for later maladjustment and could benefit from preventive services. With regard to protective factors, child positive affectivity and connectedness to school significantly reduced the odds of later belonging to the SAR group though not the PAR group. Positive affectivity may protect survivors against self-perceived internalizing symptoms or social maladjustment, which were elevated in the SAR group. Connectedness to school, surprisingly, had a protective effect, whereas perceived social support and connectedness to others (e.g., parents and friends), which have been previously documented as being important to survivors’ well-being (Tillery et al., 2017; Zebrack, 2011), did not. However, the present finding is consistent with previous research showing that connectedness to school partially mediates the effects of attachment to parents on depressive symptoms (Shochet, Homel, Cockshaw, & Montgomery, 2008) among adolescents. Thus, educational and social engagement in school may be a powerful and developmentally salient factor influencing survivors’ adjustment. Overall, the findings in the present study have several clinical implications. First, a majority of pediatric cancer patients and survivors can be expected to show enduring resilience and maintain good psychosocial adjustment over time. The protective characteristics observed in these survivors may inform preventive services offered to the minority of youth who are at risk for maladjustment, for instance those in the targeted or clinical/treatment classifications described in the Pediatric Psychosocial Preventative Health Model (Kazak, 2006). These characteristics included lower levels of PTS, pessimism, and negative affectivity; higher levels of positive affect; parental functioning characterized by low overprotection and minimal parental distress; and strong connection to school. As such, providing psychosocial services during treatment and early survivorship that facilitate patient and parent adjustment to the cancer experience encourage a developmentally and personally appropriate amount of autonomy within the parent–child relationship and promote engagement in school is recommended. Because the resilient survivors appear to be buffered from maladjustment especially through their positive affectivity and connectedness to school, these factors warrant special emphasis in preventive intervention. Although positive affectivity may be less malleable than parental behaviors and social relations, numerous intervention approaches are being developed to increase positive affect (Carl, Soskin, Kerns, & Barlow, 2013) and may be useful. To facilitate survivors’ engagement in school, formalized school reintegration interventions and strategies (Prevatt, Heffer, & Lowe, 2000) may be considered, though some research suggests that the evidence base for such programs is still weak (Thompson et al., 2015). Even without formalized interventions, however, pediatric psychologists may facilitate the transition to school by providing psychological testing if needed and assisting the survivor in securing appropriate accommodations; offering psychoeducation regarding the survivorship experience to patients, family, school staff, and peers; and providing referrals to ongoing mental health care as needed. Another clinical implication is that it is important to collect information from both survivors and their parents to rule out maladjustment, as the present study found that the two non-Resilient groups were characterized by discrepancies in survivor and parent reports. Such discrepancies may indicate elevated risk for poorer outcomes (De Los Reyes, 2011), and thus, it is important to follow-up with further assessment and monitoring when any discrepancies are found. Furthermore, as self-reported attention problems were in the at-risk range for the two distressed groups, it may be important to assess for other areas of psychosocial difficulties when survivors report attention difficulties. The present study has several limitations. Outcome data were missing from approximately 10% of living and eligible participants. Although those who were not included in the present sample did not differ from the present sample, it is still possible that inclusion of these missing participants would have changed the profiles of survivor outcomes. In addition, owing to the design of the longitudinal study, social functioning at T2 was assessed for only 60.4% of the sample, and its measures had adequate but lower reliability than most other measures used in the present study. Thus, results need to be interpreted with caution. Also, the separation between the Resilient class and the other two classes was much more evident in self-reported symptoms than with parent-reported symptoms at T3 and was also largely predicted by self-reported factors. To reduce effects attributable to the reporter and to shared method variance, future studies might incorporate more information from reporters other than the survivors. Furthermore, survivors’ externalizing problems were assessed only by parent-report and not by self-report. Thus, the distinction between the two distressed groups may have been affected by this methodological difference. Also, as the present study was conducted at a single site, with a primarily Caucasian sample, replication of findings at other treatment sites with more diverse samples is needed. Conclusion The majority of pediatric cancer survivors appear to be well-adjusted during adolescence and young adulthood, and their resilience is apparent throughout the course of a few years. Of the one-third of survivors who evidenced some distress, a majority exhibited subclinical elevations in internalizing and attention problems by self-report, whereas the rest exhibited subclinical elevations in parent-reported externalizing, internalizing, and attention problems and in self-reported attention problems. Several psychosocial factors predicted the distinction between resilient and distressed survivors 3 years later, and they may provide multiple avenues for preventing maladjustment. Encouragingly, empirically supported therapeutic interventions that ameliorate these factors, including negative cognitive and affective tendencies, parental distress, and parental overprotection, exist. Furthermore, efforts are underway in the field to address the remaining factors, including those enhancing positive affectivity and facilitating school re-entry. Further research identifying malleable mediators and interventions that promote survivor resilience is encouraged. Acknowledgments The authors thank Kristoffer Berlin for sharing his methodological expertise. Funding This work was supported by the National Institutes of Health (grant number R01 CA136782 awarded to S. P.), the American Lebanese-Syrian Associated Charities (ALSAC), and the College of Humanities and Social Sciences, California State University, Fullerton (funding awarded to Y. O.). Conflicts of interest: None declared. References Asparouhov T. , Muthén B. ( 2013 ). Auxiliary variables in mixture modeling: A 3-step approach using Mplus. Retrieved from http://www.statmodel.com/examples/webnotes/AuxMixture_submitted_corrected_webnote.pdf Asparouhov T. , Muthén B. ( 2014 ). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Retrieved from https://www.statmodel.com/examples/webnotes/webnote21.pdf Birmaher B. , Brent D. A. , Chiappetta L. , Bridge J. , Monga S. , Baugher M. ( 1999 ). Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED): A replication study . Journal of the American Academy of Child & Adolescent Psychiatry , 38 , 1230 – 1236 . Google Scholar CrossRef Search ADS Brinkman T. M. , Li C. , Vannatta K. , Marchak J. G. , Lai J.-S. , Prasad P. K. , Kimberg C. , Vuotto S. , Di C. , Srivastava D. , Robison L. L. , Armstrong G. T. , Krull K. R. ( 2016 ). Behavioral, social, and emotional symptom comorbidities and profiles in adolescent survivors of childhood cancer: A report from the Childhood Cancer Survivor Study . Journal of Clinical Oncology , 34 , 3417 – 3425 . Google Scholar CrossRef Search ADS Brinkman T. M. , Zhu L. , Zeltzer L. K. , Recklitis C. J. , Kimberg C. , Zhang N. , Muriel A. C. , Stovall M. , Srivastava D. K. , Robison L. L. , Krull K. R. ( 2013 ). Longitudinal patterns of psychological distress in adult survivors of childhood cancer . British Journal of Cancer , 109 , 1373 – 1381 . Google Scholar CrossRef Search ADS Carl J. R. , Soskin D. P. , Kerns C. , Barlow D. H. ( 2013 ). Positive emotion regulation in emotional disorders: A theoretical review . Clinical Psychology Review , 33 , 343 – 360 . Google Scholar CrossRef Search ADS Costello E. J. , Foley D. L. , Angold A. ( 2006 ). 10-year research update review: The epidemiology of child and adolescent psychiatric disorders: II. Developmental epidemiology . Journal of the American Academy of Child & Adolescent Psychiatry , 45 , 8 – 25 . Google Scholar CrossRef Search ADS De Los Reyes A. ( 2011 ). Introduction to the special section: More than measurement error: Discovering meaning behind informant discrepancies in clinical assessments of children and adolescents . Journal of Clinical Child and Adolescent Psychology , 40 , 1 – 9 . Google Scholar CrossRef Search ADS De Los Reyes A. , Kazdin A. E. ( 2005 ). Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study . Psychological Bulletin , 131 , 483 – 509 . Google Scholar CrossRef Search ADS Derogatis L. , Melisaratos N. ( 1983 ). The Brief Symptom Inventory: An introductory report . Psychological Medicine , 13 , 595 – 605 . Google Scholar CrossRef Search ADS Eiser C. , Hill J. J. , Vance Y. H. ( 2000 ). Examining the psychological consequences of surviving childhood cancer: Systematic review as a research method in pediatric psychology . Journal of Pediatric Psychology , 25 , 449 – 460 . Google Scholar CrossRef Search ADS Ey S. , Hadley W. , Allen D. N. , Palmer S. , Klosky J. , Deptula D. , Thomas J. , Cohen R. ( 2005 ). A new measure of children's optimism and pessimism: The Youth Life Orientation Test . Journal of Child Psychology and Psychiatry , 46 , 548 – 558 . Google Scholar CrossRef Search ADS Howard Sharp K. M. , Willard V. W. , Okado Y. , Tillery R. , Barnes S. , Long A. , Phipps S. ( 2015 ). Profiles of connectedness: Processes of resilience and growth in children with cancer . Journal of Pediatric Psychology , 40 , 904 – 913 . Google Scholar CrossRef Search ADS Kahalley L. S. , Wilson S. J. , Tyc V. L. , Conklin H. M. , Hudson M. M. , Wu S. , Xiong X. , Stancel H. H. , Hinds P. S. ( 2013 ). Are the psychological needs of adolescent survivors of pediatric cancer adequately identified and treated? Psycho-Oncology , 22 , 447 – 458 . doi: 10.1002/pon.3021 Google Scholar CrossRef Search ADS Karcher M. ( 2012 ). The Hemingway: Measure of Adolescent Connectedness: A manual for scoring and interpretation. University of Texas at San Antonio . Unpublished manuscript. Retrieved from http://adolescentconnectedness.com/media/HemingwayManual2012.pdf Kazak A. E. ( 2006 ). Pediatric Psychosocial Preventative Health Model (PPPHM): Research, practice, and collaboration in pediatric family systems medicine . Families, Systems, and Health , 24 , 381 – 395 . Google Scholar CrossRef Search ADS Kim J. , Deater-Deckard K. ( 2011 ). Dynamic changes in anger, externalizing and internalizing problems: Attention and regulation . Journal of Child Psychology and Psychiatry , 52 , 156 – 166 . Google Scholar CrossRef Search ADS Klassen A. F. , Anthony S. J. , Khan A. , Sung L. , Klaassen R. ( 2011 ). Identifying determinants of quality of life of children with cancer and childhood cancer survivors: A systematic review . Supportive Care in Cancer , 19 , 1275 – 1287 . Google Scholar CrossRef Search ADS Kovacs M. ( 1992 ). Children's Depression Inventory (CDI) manual. North Tonawanda, NY : Multi-Health Systems, Inc . Krull K. R. , Huang S. , Gurney J. G. , Klosky J. L. , Leisenring W. , Termuhlen A. , Ness K. K. , Kumar Srivastava D. , Mertens A. , Stovall M. , Robison L. L. , Hudson M. M. ( 2010 ). Adolescent behavior and adult health status in childhood cancer survivors . Journal of Cancer Survivorship: Research and Practice , 4 , 210 – 217 . Google Scholar CrossRef Search ADS Landolt M. A. , Ystrom E. , Sennhauser F. H. , Gnehm H. E. , Vollrath M. E. ( 2012 ). The mutual prospective influence of child and parental post-traumatic stress symptoms in pediatric patients . Journal of Child Psychology and Psychiatry , 53 , 767 – 774 . Google Scholar CrossRef Search ADS Langeveld N. , Stam H. , Grootenhuis M. , Last B. ( 2002 ). Quality of life in young adult survivors of childhood cancer . Supportive Care in Cancer , 10 , 579 – 600 . Google Scholar CrossRef Search ADS Laurent J. , Catanzaro S. J. , Joiner T. E. , Rudolph K. D. , Potter K. I. , Lambert S. , Osborne L. , Gathright T. ( 1999 ). A measure of positive and negative affect for children: Scale development and preliminary validation . Psychological Assessment , 11 , 326 – 338 . Google Scholar CrossRef Search ADS Lo Y. , Mendell N. R. , Rubin D. B. ( 2001 ). Testing the number of components in a normal mixture . Biometrika , 88 , 767 – 778 . Google Scholar CrossRef Search ADS Mackie E. , Hill J. , Kondryn H. , McNally R. ( 2000 ). Adult psychosocial outcomes in long-term survivors of acute lymphoblastic leukaemia and Wilms' tumour: A controlled study . The Lancet , 355 , 1310 – 1314 . Google Scholar CrossRef Search ADS Maurice-Stam H. , Grootenhuis M. A. , Caron H. N. , Last B. F. ( 2007 ). Course of life of survivors of childhood cancer is related to quality of life in young adulthood . Journal of Psychosocial Oncology , 25 , 43 – 58 . Google Scholar CrossRef Search ADS Miller K. S. , Vannatta K. , Compas B. E. , Vasey M. , McGoron K. D. , Salley C. G. , Gerhardt C. A. ( 2009 ). The role of coping and temperament in the adjustment of children with cancer . Journal of Pediatric Psychology , 34 , 1135 – 1143 . Google Scholar CrossRef Search ADS Okado Y. , Howard Sharp K. M. , Tillery R. , Long A. M. , Phipps S. ( 2016 ). Profiles of dispositional expectancies and affectivity predict later psychosocial functioning in children and adolescents with cancer . Journal of Pediatric Psychology , 41 , 298 – 308 . Google Scholar CrossRef Search ADS Orbuch T. L. , Parry C. , Chesler M. , Fritz J. , Repetto P. ( 2005 ). Parent-child relationships and quality of life: Resilience among childhood cancer survivors . Family Relations , 54 , 171 – 183 . Google Scholar CrossRef Search ADS Ozono S. , Saeki T. , Mantani T. , Ogata A. , Okamura H. , Yamawaki S. ( 2007 ). Factors related to posttraumatic stress in adolescent survivors of childhood cancer and their parents . Supportive Care in Cancer , 15 , 309 – 317 . Google Scholar CrossRef Search ADS Parker G. , Tupling H. , Brown L. B. ( 1979 ). A parental bonding instrument . British Journal of Medical Psychology , 52 , 1 – 10 . Google Scholar CrossRef Search ADS Prevatt F. F. , Heffer R. W. , Lowe P. A. ( 2000 ). A review of school reintegration programs for children with cancer . Journal of School Psychology , 38 , 447 – 467 . Google Scholar CrossRef Search ADS Prince-Embury S. ( 2007 ). Resiliency scales for children and adolescents: Profiles of personal strengths . San Antonio, TX : Harcourt Assessments . Pynoos R. S. , Rodriguez N. , Steinberg A. , Stuber M. , Frederick C. ( 1998 ). The University of California at Los Angeles Posttraumatic Stress Disorder Reaction Index (UCLA-PTSD RI) for DSM-IV (Revision 1). Los Angeles, CA : UCLA Trauma Psychiatry Program . Unpublished manual. Reynolds C. , Kamphaus R. ( 2004 ). BASC-2: Behavior Assessment System for Children, Second Edition . Circle Pines, MN : AGS Publishing . Robinson K. E. , Gerhardt C. A. , Vannatta K. , Noll R. B. ( 2009 ). Survivors of childhood cancer and comparison peers: The influence of early family factors on distress in emerging adulthood . Journal of Family Psychology , 23 , 23 – 31 . Google Scholar CrossRef Search ADS Servitzoglou M. , Papadatou D. , Tsiantis I. , Vasilatou-Kosmidis H. ( 2008 ). Psychosocial functioning of young adolescent and adult survivors of childhood cancer . Supportive Care in Cancer , 16 , 29 – 36 . Google Scholar CrossRef Search ADS Shochet I. M. , Homel R. , Cockshaw W. D. , Montgomery D. T. ( 2008 ). How do school connectedness and attachment to parents interrelate in predicting adolescent depressive symptoms? Journal of Clinical Child and Adolescent Psychology , 37 , 676 – 681 . Google Scholar CrossRef Search ADS Sulkers E. , Fleer J. , Brinksma A. , Roodbol P. F. , Kamps W. A. , Tissing W. J. E. , Sanderman R. ( 2013 ). Dispositional optimism in adolescents with cancer: Differential associations of optimism and pessimism with positive and negative aspects of well-being . British Journal of Health Psychology , 18 , 474 – 489 . Google Scholar CrossRef Search ADS Thompson A. L. , Christiansen H. L. , Elam M. , Hoag J. , Irwin M. K. , Pao M. , Voll M. , Noll R. B. , Kelly K. P. ( 2015 ). Academic continuity and school reentry support as a standard of care in pediatric oncology . Pediatric Blood and Cancer , 62 , S805 – S817 . Google Scholar CrossRef Search ADS Tillery R. , Cohen R. , Berlin K. S. , Long A. , Phipps S. ( 2017 ). Youth’s adjustment to cancer: Examination of patterns of adjustment and the role of peer relations . Journal of Pediatric Psychology , 42 , 1123 – 132 . doi: 10.1093/jpepsy/jsx067 Google Scholar CrossRef Search ADS Tillery R. , Long A. , Phipps S. ( 2014 ). Child perceptions of parental care and overprotection in children with cancer and healthy children . Journal of Clinical Psychology in Medical Settings , 21 , 165 – 172 . Google Scholar CrossRef Search ADS Trask P. C. , Paterson A. G. , Trask C. L. , Bares C. B. , Birt J. , Maan C. ( 2003 ). Parent and adolescent adjustment to pediatric cancer: Associations with coping, social support, and family function . Journal of Pediatric Oncology Nursing , 20 , 36 – 47 . Google Scholar CrossRef Search ADS Trickey D. , Siddaway A. P. , Meiser-Stedman R. , Serpell L. , Field A. P. ( 2012 ). A meta-analysis of risk factors for post-traumatic stress disorder in children and adolescents . Clinical Psychology Review , 32 , 122 – 138 . Google Scholar CrossRef Search ADS Van Schoors M. , Caes L. , Knoble N. B. , Goubert L. , Verhofstadt L. L. , Alderfer M. A. ( 2017 ). Systematic review: Associations between family functioning and child adjustment after pediatric cancer diagnosis: A meta-analysis . Journal of Pediatric Psychology , 42 , 6 – 18 . Weiss D. ( 2004 ). The Impact of Event Scale-Revised. In Wilson J. , Keane T. (Eds.), Assessing psychological trauma and PTSD ( 2nd ed ., pp. 168 – 189 ). New York, NY : Guilford . Williams N. A. , Davis G. , Hancock M. , Phipps S. ( 2010 ). Optimism and pessimism in children with cancer and healthy children: Confirmatory factor analysis of the Youth Life Orientation Test and relations with health-related quality of life . Journal of Pediatric Psychology , 35 , 672 – 682 . Google Scholar CrossRef Search ADS Wolfe-Christensen C. , Mullins L. L. , Stinnett T. A. , Carpentier M. Y. , Fedele D. A. ( 2009 ). Use of the Behavioral Assessment System for Children 2nd edition: Parent report scale in pediatric cancer populations . Journal of Clinical Psychology in Medical Settings , 16 , 322 – 330 . Google Scholar CrossRef Search ADS Youngstrom E. , Loeber R. , Stouthamer-Loeber M. ( 2000 ). Patterns and correlates of agreement between parent, teacher, and male adolescent ratings of externalizing and internalizing problems . Journal of Consulting and Clinical Psychology , 68 , 1038 – 1050 . Google Scholar CrossRef Search ADS Zebrack B. J. ( 2011 ). Psychological, social, and behavioral issues for young adults with cancer . Cancer , 117 , 2289 – 2294 . Google Scholar CrossRef Search ADS Zeltzer L. K. , Chen E. , Weiss R. , Guo M. D. , Robison L. L. , Meadows A. T. , Mills J. L. , Nicholson H. S. , Byrne J. ( 1997 ). Comparison of psychologic outcome in adult survivors of childhood acute lymphoblastic leukemia versus sibling controls: A cooperative Children's Cancer Group and National Institutes of Health study . Journal of Clinical Oncology , 15 , 547 – 556 . Google Scholar CrossRef Search ADS Zeltzer L. K. , Recklitis C. , Buchbinder D. , Zebrack B. , Casillas J. , Tsao J. C. , Lu Q. , Krull K. ( 2009 ). Psychological status in childhood cancer survivors: A report from the Childhood Cancer Survivor Study . Journal of Clinical Oncology , 27 , 2396 – 2404 . Google Scholar CrossRef Search ADS © 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/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Pediatric Psychology Oxford University Press

Profiles of Adjustment in Pediatric Cancer Survivors and Their Prediction by Earlier Psychosocial Factors

Download PDF
12 pages

Loading next page...
 
/lp/ou_press/profiles-of-adjustment-in-pediatric-cancer-survivors-and-their-vRTnmUMMnU

References (45)

Publisher
Oxford University Press
Copyright
© 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
ISSN
0146-8693
eISSN
1465-735X
DOI
10.1093/jpepsy/jsy037
Publisher site
See Article on Publisher Site

Abstract

Abstract Objective To examine individual differences in pediatric cancer survivors’ psychosocial adjustment and test the psychosocial predictors, assessed 2–3 years earlier, of those differences. Method Pediatric cancer survivors (n = 209, aged 8–17 years at baseline) and their parents were followed for 4 years. They provided reports of survivors’ psychosocial adjustment at 3 years post-baseline, and latent profile analysis (LPA) was used to identify subgroups of survivors who differed on those reports. Multinomial logistic regression was used to predict group membership from self- and parent-reported psychosocial factors at baseline (child adjustment, disposition, and parental functioning) and at 1 year post-baseline (child social relations). Results The LPA revealed a 3-class model as the best fit: a “Resilient” group (65%), characterized by good psychosocial adjustment; a “Self-Reported At-Risk” group (23%), characterized by subclinical elevations in self-reported internalizing and attention problems; and a “Parent-Reported At-Risk” group (12%), characterized by subclinical elevations in parent-reported internalizing, externalizing, and attention problems and in self-reported attention problems. Several psychosocial predictors, including child posttraumatic stress, affectivity, and connectedness to school, as well as parental distress and overprotection, differentiated the Resilient group from the other groups, in expected directions. Conclusions The majority of pediatric cancer survivors exhibit enduring resilience. The protective factors identified for them—including positive affectivity and strong connectedness to school—may inform targeted prevention strategies for the minority of survivors who are at risk for maladjustment. adjustment, adolescents, cancer and oncology, longitudinal research, mental health, parenting, psychosocial functioning, resilience Although most pediatric cancer survivors maintain similar levels of psychosocial adjustment as healthy peers during treatment and survivorship (Eiser, Hill, & Vance, 2000; Langeveld, Stam, Grootenhuis, & Last, 2002; Robinson, Gerhardt, Vannatta, & Noll, 2009), a significant minority of survivors experience such psychosocial difficulties as depression, anxiety, attention problems, and externalizing problems compared with controls (Krull et al., 2010) and norms (Zeltzer et al., 2009). In addition, some studies have found that survivors, on average, may fare worse than controls in such areas as mood (Zeltzer et al., 1997), self-esteem (Servitzoglou, Papadatou, Tsiantis, & Vasilatou-Kosmidis, 2008), and relational functioning (Mackie, Hill, Kondryn, & McNally, 2000). To deliver targeted preventive services to survivors at risk for maladjustment, at-risk survivors first need to be identified. One way to do so is through the use of person-centered analytic methods, which identify groups of individuals who differ on outcomes. Such methods have been previously applied to the participants of the Childhood Cancer Survivor Study (CCSS) to show that a majority of adolescent survivors, including those who had received cranial radiation therapy (CRT), exhibited minimal parent-reported internalizing, externalizing, and social withdrawal symptoms (Brinkman et al., 2016). However, a significant minority, ranging from approximately 30% of those not having received CRT to 37% of those having received CRT, exhibited some combination of symptoms. Similar patterns are found in adulthood, with roughly two-thirds of CCSS participants reporting minimal self-reported symptoms of depression, anxiety, and somatization over time (Brinkman et al., 2013). Further replication with other samples of pediatric cancer survivors is needed. Moreover, risk and protective factors that differentiate between resilient survivors who are well-adjusted and those who experience maladjustment need to be identified. To date, most existing studies have focused on the predictive effects of demographic and medical or health-related factors (Langeveld et al., 2002), including the use of central nervous system-directed therapy and type of cancer diagnosis (Kahalley et al., 2013; Zeltzer et al., 2009). The predictive effects of psychosocial factors have not yet been studied widely, though associations have been found between survivors’ adjustment and such factors as self-reported anxiety (Ozono et al., 2007), peer relations (Maurice-Stam, Grootenhuis, Caron, & Last, 2007), and parent–child relationship quality (Orbuch, Parry, Chesler, Fritz, & Repetto, 2005). Furthermore, most studies on survivors’ psychosocial adjustment have used cross-sectional design and variable-centered analytic methods. They demonstrate associations between risk or protective factors and outcomes at the population level but cannot clarify whether those factors predict outcomes longitudinally or work differently for subsets of individuals. The present study sought to fill this gap by applying a person-centered analytic method to identify groups of survivors who differed on psychosocial outcomes and test for factors that prospectively differentiated those groups. Because prospective research on survivors’ adjustment is limited, we examined four sets of factors that affect patients’ adjustment, to see whether they also predict survivors’ adjustment. They were (a) child distress (posttraumatic stress [PTS], depression, and anxiety), (b) child disposition (optimism, pessimism, and positive and negative affectivity), (c) parental functioning (parental care, overprotection, PTS, and global distress), and (d) child social relations (perceived support and connectedness). Their effects are reviewed briefly in the following text. First, although longitudinal research examining the predictive effects of earlier distress is limited, existing studies suggest that child PTS symptoms are associated over time in pediatric patients (Landolt, Ystrom, Sennhauser, Gnehm, & Vollrath, 2012), and a small minority of long-term pediatric cancer survivors experiences persistent distress (Brinkman et al., 2013). In addition, previous experiences of depression, anxiety (Costello, Foley, & Angold, 2006), and PTS (Trickey, Siddaway, Meiser-Stedman, Serpell, & Field, 2012) have been linked to increased risk for future psychopathology in children and adolescents more generally. Thus, prior distress may predict later maladjustment among survivors. In addition to prior distress, disposition with respect to cognitive style and affectivity has been linked to adjustment. For example, optimism has been found to have a positive association with mental health functioning (Williams, Davis, Hancock, & Phipps, 2010), whereas pessimism has been negatively associated with emotional functioning (Sulkers et al., 2013). Optimism and pessimism have been found to covary with positive affectivity and negative affectivity, respectively, in pediatric cancer patients, and predict later psychosocial adjustment (Okado, Howard Sharp, Tillery, Long, & Phipps, 2016). Moreover, negative affectivity has been linked to anxiety and depression based on maternal report (Miller et al., 2009). Taken together, optimism and positive affectivity are expected to protect against maladjustment, whereas pessimism and negative affectivity are expected to increase risk for maladjustment. Parental factors that are known to influence child adjustment outcomes include parental well-being, such as parental distress and symptoms of anxiety and depression (Klassen, Anthony, Khan, Sung, & Klaassen, 2011). The parent–child bond is also known to influence child adjustment. For instance, a review on the associations between family functioning and child adjustment after pediatric cancer diagnosis found that families characterized by greater parental care (i.e., higher family cohesion, expressiveness, and support) had children with better adjustment (Van Schoors et al., 2017). In addition, parental overprotection has been linked to greater child distress (Tillery, Long, & Phipps, 2014). Thus, parental functioning characterized by minimal parental distress and better-quality (i.e., more caring and less overprotective) parent–child relationships are expected to predict better survivor adjustment. Similarly, social relationships and support are highly influential in the adjustment of pediatric cancer patients and survivors (Servitzoglou et al., 2008; Zebrack, 2011), with parents and peers being especially important sources of social support (Trask et al., 2003). Moreover, higher levels of connectedness to others and a greater variety of individuals to whom one feels connected are both positively associated with psychosocial adjustment (Howard Sharp et al., 2015). Finally, patients with low levels of distress report greater connectedness to peers than those who report some distress (Tillery, Cohen, Berlin, Long, & Phipps, 2017). Thus, greater levels of social support and connectedness to others are expected to predict better adjustment among survivors. In sum, the present study aimed to identify subgroups of pediatric cancer survivors who differ in their adjustment and test whether membership in these subgroups could be predicted by earlier psychosocial factors. Based on the existing literature, the present study examined outcomes that are of potential concern for survivors, including internalizing, externalizing, and attention problems, and difficulties with personal adjustment. We hypothesized that multiple subgroups would be found among survivors, with the largest group exhibiting minimal problems. Furthermore, we expected that these groups would be differentiated by child distress, disposition, and perceived social support and parental functioning that had been assessed 2–3 years earlier. Method Participants Participants were survivors of pediatric cancer (n = 209) and their primary caregiver (“parent”; 82.8% mothers, 12.4% fathers, and 4.8% other) enrolled in a longitudinal study on patient coping and adjustment who completed the study’s third time point. At baseline, they were of age 8–17 years, at least 1 month past their diagnosis, able to speak and read English, and without significant cognitive or sensory deficits. To achieve a heterogeneous yet balanced sample in terms of where patients were in the treatment trajectory, participants were recruited into one of four strata based on time elapsed since diagnosis: 1–6 months (n = 51; 24.4%), 6 months to 2 years (n = 50; 23.9%), 2–5 years (n = 55; 26.3%), and 5 years or more (n = 53; 25.4%). As described in an earlier report on baseline findings from this study (redacted for blind review), 68% of those approached agreed to participate; participants and nonparticipants did not differ by age, gender, race/ethnicity, or cancer diagnosis; and the final sample was representative of the population served by the hospital. Five additional participants had completed the longitudinal study’s third time point but were excluded from the present sample because they were on treatment. After baseline, follow-up assessments took place 1 year (T2) and 3 years (T3) later. Not all participants were invited to participate at T2, as some participants missed the 1-year follow-up window owing to a delay in the approval of a study amendment related to the longitudinal assessment, resulting in participation of 60.4% (n = 154) of the original sample (N = 255). No differences in baseline demographic, medical, or study variables were found between those who were assessed at T2 and those who were not. At T3, 83.9% of the original sample participated in the assessment, 6.3% were deceased (n = 16), and 9.8% (n = 25) did not participate. Participants included in the present sample did not differ in baseline demographic characteristics or predictor variables from those who were not included (Table I). Table I. Demographic Characteristics of the Study Sample At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) Note. Excluded participants refer to participants who were part of the longitudinal study (N = 255) but not included in the current sample. Dashes in cells represent frequencies that did not differ from baseline. Table I. Demographic Characteristics of the Study Sample At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) At baseline T3 Present sample (n = 209) Excluded participants (n = 46) Present sample (n = 209) M (SD) Age (in years) 12.48 (2.86) 13.20 (2.93) 15.64 (2.93) Time since diagnosis (in years) 3.87 (4.29) 3.38 (4.35) 6.99 (4.26) n (%) Gender  Male 105 (50.2) 27 (58.7) –  Female 104 (49.8) 19 (41.3) – Race  White 155 (74.2) 30 (65.2) –  Black 44 (21.1) 14 (30.4) –  Other 10 (4.8) 2 (4.3) – Socioeconomic strata  I 25 (12.0) 6 (13.0) 27 (12.9)  II 31 (14.9) 9 (19.6) 33 (15.8)  III 72 (34.6) 9 (19.6) 66 (31.6)  IV 44 (21.2) 15 (32.6) 51 (24.4)  V 36 (17.3) 7 (15.2) 32 (15.3) Diagnosis  Acute lymphoblastic leukemia 53 (25.4) 8 (17.4) –  Acute myeloid leukemia 14 (6.7) 4 (8.7) –  Lymphoma 29 (13.9) 5 (10.9) –  Solid tumor 82 (39.2) 17 (37.0) –  Brain tumor 31 (14.8) 12 (26.1) – On treatment  Yes 111 (53.1) 23 (50.0) 0 (0)  No 98 (46.9) 23 (50.0) 209 (100) Relapse history  Yes 24 (11.5) 10 (21.7) 32 (15.3)  No 185 (88.5) 36 (78.3) 177 (84.7) Note. Excluded participants refer to participants who were part of the longitudinal study (N = 255) but not included in the current sample. Dashes in cells represent frequencies that did not differ from baseline. Procedures At all three time points, participants were assessed in the outpatient psychology clinic of the hospital. Informed consent/assent was obtained from patients and their parents, and they completed questionnaires in separate rooms. Trained research assistants were available to assist and read items aloud if needed. At each assessment, each participant received a $25.00 gift card as compensation for their time, effort, and travel. Procedures were approved by the hospital’s institutional review board. Measures Survivor adjustment outcomes were assessed at T3, 3 years post-baseline, using both youth and parent report. At baseline, youths reported on their distress, disposition, and perceived parenting, and parents reported on their own distress. At T2, youths reported on their social functioning. Unless otherwise indicated, higher scores on the measures indicate greater amount of the assessed construct. Survivor Outcomes (T3) Survivors and parents reported on survivors’ psychosocial adjustment on the Behavior Assessment System for Children, Second Edition (BASC-2; Reynolds & Kamphaus, 2004), a well-validated and widely used measure of child behavioral problems. Items were rated on a true/false scale or a 4-point Likert scale ranging from 1 (never) to 4 (almost always). Gender-normed T-scores were obtained for self- and parent-reported scales. Self-reported scales included internalizing problems composite (α = .95–.96), consisting of subscales on atypicality, locus of control, social stress, anxiety, depression, sense of inadequacy, and somatization; attention problems subscale (α = .75–.80); and a personal adjustment composite (α = .88–.91), which is composed of subscales on relationship with parents (i.e., a positive regard toward parents and a feeling of being esteemed by them), interpersonal relations (i.e., the perception of having good social relationships and friendships with peers), self-esteem (i.e., feelings of self-esteem, self-respect, and self-acceptance), and self-reliance (i.e., confidence in one’s ability to solve problems and belief in one’s personal dependability and decisiveness). Parent-reported scales included were internalizing problems composite (consisting of anxiety, depression, and somatization; α = .89–.91); externalizing problems composite, consisting of subscales on hyperactivity, aggression, and conduct problems (α = .92–.95); and attention problems (α = .85–.90). With the exception of the personal adjustment composite, T-scores that fall between 60 and 69 are classified as at-risk, which reflects a level of symptoms that warrant further monitoring but do not yet require intervention, and T-scores of 70 or above are classified as clinically significant. For the personal adjustment composite, T-scores between 31 and 40 are classified as at-risk and 30 or below are classified as clinically significant. The BASC-2 has excellent psychometric properties (Reynolds & Kamphaus, 2004). Child Distress (Baseline) Children reported on their PTS, depression, and anxiety. PTS was assessed using the UCLA PTSD Reaction Index for DSM-IV Post-Traumatic Stress Disorder (PTSD) (Pynoos, Rodriguez, Steinberg, Stuber, & Frederick, 1998), a 22-item measure assessing DSM-IV Post-Traumatic Stress Disorder (PTSD) criteria met in the past month based on the most traumatic, stressful event identified by the respondent, regardless of whether or not it was cancer-related or met the A1 criterion. Children rated items (e.g., “I watch out for danger or things that I am afraid of”) on a 5-point Likert scale ranging from 0 (none) to 4 (most). PTSDI has excellent internal and test–retest reliability, and the full-scale Cronbach’s α was .90 in the present sample. Depression symptoms were assessed using Children’s Depression Inventory (CDI; Kovacs, 1992), a 27-item measure that asked children to select one of three statements that best described them over the past 2 weeks (e.g., “I am sad once in a while/many times/all the time”). Items were scored on a 0–2 scale and summed (α = .82). Anxiety symptoms were assessed using the Screen for Child Anxiety Related Emotional Disorders (SCARED; Birmaher et al., 1999), a 41-item measure that asked children to rate how much each item (e.g., “I am nervous”) described them over the past 3 months using a 3-point scale ranging from 0 (not/hardly ever true) to 2 (very/often true). The total sum score was used in the present study (α = .91). SCARED has good convergent and divergent validity (Birmaher et al., 1999). Child Disposition (Baseline) Child optimism and pessimism were assessed using the Youth Life Orientation Test (YLOT; Ey et al., 2005). Children rated seven items each for optimism and pessimism subscales (e.g., “I usually expect to have a good day”; “Things usually go wrong for me”) on a 4-point Likert scale ranging from 1 (not true for me) to 4 (true for me). Items were summed to obtain subscale scores for optimism (α = .76) and pessimism (α = .73). YLOT has good internal consistency, test–retest reliability, and convergent, discriminant, and predictive validity (Ey et al., 2005). Child affectivity was assessed using the Positive and Negative Affect Scale for Children (PANASC; Laurent et al., 1999), a 20-item measure. Children rated how often they have recently felt the emotion indicated by the item (e.g., happy, joyful, sad, and afraid) on a 5-point Likert scale ranging from 1 (very slightly or not at all) to 5 (extremely), and items were summed for positive affectivity (α = .90) and negative affectivity (α = .86) subscales. PANASC has good convergent and divergent validity (Laurent et al., 1999). Parental Functioning (Baseline) Children reported on perceived parental behavior on the Parent Bonding Instrument (PBI; Parker, Tupling, & Brown, 1979), a 25-item measure that assesses overprotection (e.g., “Tends to baby me”; α = .85) and care (e.g., “Is affectionate to me”; α = .76). Items are rated on a 4-point Likert scale ranging from 0 (very unlike) to 3 (very like) and summed. Parents reported on their own PTS, experienced within the past week, on the Impact of Events Scale, Revised (IESR; Weiss, 2004), a 22-item measure. They rated symptoms (e.g., “stayed away from reminders of it”) associated with the most traumatic event they had experienced, using a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely). Ratings were summed to obtain the total score (α = .94). Parents also reported on their own distress over the past week on the Brief Symptom Inventory (BSI; Derogatis & Melisaratos, 1983). Parents rated 53 symptoms (e.g., “Feeling blue”) on a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely). Gender-normed T-score for the Global Severity Index (GSI), normed for the adult nonpatient population, was used to capture parental distress (α = .95). Social Relations (T2) One year past the baseline assessment, children reported on perceived availability of social support through the support subscale from the Resiliency Scales for Children and Adolescents (RSCA; Prince-Embury, 2007). Participants rated items (e.g., “If something bad happens, I can ask my friends for help”) on a 5-point Likert scale ranging from 0 (never) to 4 (almost always). Scaled scores normed on age and gender were obtained (α = .79). Connectedness to others was assessed using Hemingway Measure of Adolescent Connectedness (HMAC; Karcher, 2012), a 57-item measure of positive connections to one’s social environment. Items (e.g., I “enjoy spending time with my parents”; “enjoy being at school”) were rated on a 5-point Likert scale ranging from 1 (not at all true) to 5 (very true). Mean scores were obtained for subscales reflecting connectedness to friends (α = .80), parents (α = .81), school (α = .77), peers (α = .77), and teacher (α = .72). Analytic Plan To examine individual differences in survivors’ psychosocial adjustment at T3, latent profile analysis (LPA) was applied. LPA is a person-centered analytic method that identifies homogenous subgroups of individuals, or latent classes, who differ on continuous outcome variables. The number of classes to be fitted to the data is specified a priori, and models with different numbers of classes are compared on indices of model fit and interpretability. In the present study, the model fit was compared using the Bayesian information criterion (BIC), entropy, and the Lo–Mendell Bayesian information criterion Rubin likelihood ratio test of model fit (LMRT; Lo, Mendell, & Rubin, 2001). Superior model fit is indicated by lower BIC, higher entropy, which is an index of how well the data are classified into latent classes, and significant result for the LMRT. After the best model was selected, its classes were compared on mean scores of the predictor variables using the Bolck–Croon–Hagenaars (BCH) method (Asparouhov & Muthén, 2014), with Holm–Bonferroni correction applied to control for familywise error. Then, the predictive effects of potential covariates and predictor variables were tested through multinomial logistic regression, using the three-step approach for testing the prediction of distal latent classes (Asparouhov & Muthén, 2013). As missing data are not permitted in predictors, cases with missing data in any predictor were removed from the regression analyses. There were no differences in demographic or medical characteristics or in study measure scores between those who were included versus excluded from these analyses. To avoid under-powering analyses and to maximize available data, predictors were grouped into four sets (child distress, child disposition, and parental functioning at baseline; child social functioning at Time 2) and tested by set; thus, four regressions were run. Missing data in outcome measures, which were consistent with the assumption that they are missing at random, were handled using full information maximum likelihood, with standard errors that are robust to non-normal data. Analyses were run in Mplus 7.31. Results Bivariate correlations between the predictor variables and the outcome variables, as well as among the outcome variables, are presented in Table II. On the whole, the variables were related in expected directions, though parent-reported outcomes were not associated with several predictors. Table II. Bivariate Correlations Between Outcome and Predictor Variables Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Note. M(SD) reported in the diagonals for the T3 outcome variables. PTS = posttraumatic stress; GSI = Global Severity Index from the Brief Symptom Inventory. * p < .05. **p < .01. ***p < .001. Table II. Bivariate Correlations Between Outcome and Predictor Variables Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Survivor outcomes Self-report Parent-report Variables Internalizing problems Attention problems Personal adjustment Internalizing problems Attention problems Externalizing problems Baseline  Child distress   PTS .37*** .33*** −.34*** .15* .17* .20**   Depression .29*** .33*** −.31*** .20** .08 .14*   Anxiety .24** .21** −.23** .21** .14* .11  Child disposition   Optimism −.24** −.32*** .26*** −.10 −.02 −.08   Pessimism .28*** .29*** −.30*** .15* .09 .19**   Positive affect −.18* −.22** .23** −.15* −.04 −.22**   Negative affect .24** .25*** −.25*** .18* .07 .10  Parental functioning   Care −.19** −.17* .21** .06 −.06 −.11   Overprotection .23** .25*** −.29*** .14* .21** .23**   PTS .22** .17* −.12 .16* .11 .16*   GSI .28*** .22** −.21** .37*** .27*** .33*** T2 child social relations  Perceived support −.28** −.21* .38*** −.14 −.18* −.30**  Connectedness to   Friends −.11 −.02 .23** −.05 −.17 −.11   Parents −.43*** −.29** .45*** .01 −.14 −.24**   School −.50*** −.57*** .51*** −.10 −.19* −.24**   Peers −.44*** −.41*** .50*** −.08 −.11 −.26**   Teacher −.28** −.39*** .36*** −.04 −.19* −.27** T3 survivor outcomes  Self-report   Internalizing problems 47.32 (11.18)   Attention problems .57*** 51.25 (11.40)   Personal Adjustment −.76*** −.53*** 53.04 (9.88)  Parent-report   Internalizing problems .26*** .18* −.27*** 49.13 (10.65)   Attention problems .25*** .40*** −.28*** .47*** 49.74 (10.62)   Externalizing problems .34*** .35*** −.33*** .56*** .67*** 47.22 (9.14) Note. M(SD) reported in the diagonals for the T3 outcome variables. PTS = posttraumatic stress; GSI = Global Severity Index from the Brief Symptom Inventory. * p < .05. **p < .01. ***p < .001. LPA models with two to five classes were compared (Table III). The three-class model was selected as the final model, based on relatively low BIC, the largest drop in BIC compared with the model with one fewer class, high entropy, and significant LMRT result. This model also had theoretically meaningful profiles of scores on outcome variables. Table III. Model Fit Indicators for Latent Profile Analyses Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Note. BIC = Bayesian information criterion. Lower BIC and higher entropy values indicate better model fit. Significant results for the Lo–Mendell–Rubin test indicate superior model fit compared with the model with one fewer class. Table III. Model Fit Indicators for Latent Profile Analyses Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Number of classes BIC Entropy Lo–Mendell–Rubin test p-value 2 8839.62 .79 .39 3 8788.30 .87 .02 4 8759.30 .91 .21 5 8752.95 .91 .14 Note. BIC = Bayesian information criterion. Lower BIC and higher entropy values indicate better model fit. Significant results for the Lo–Mendell–Rubin test indicate superior model fit compared with the model with one fewer class. The three-class model is illustrated in Figure 1. The largest class, “Resilient” class (R; 65.4% of the sample), was characterized by lower scores on internalizing, externalizing, and attention problems and a higher score on personal adjustment than the normative mean (T = 50). The next largest class, the “Self-Reported At-Risk” class (SAR; 23.0%), was characterized by scores in the at-risk range on self-reported internalizing and attention problems and below average, though normal range, scores on personal adjustment. However, this class had roughly average, normal range scores based on parent-report. Finally, the smallest class, the “Parent-Reported At-Risk” class (PAR; 11.6%), was characterized by scores in the at-risk range in parent-reported internalizing, externalizing, and attention problems and self-reported attention problems. Overall, there was support for the hypothesis that multiple subgroups of survivors would be identified, with the largest group characterized by positive adjustment. Figure 1. View largeDownload slide Latent profiles of self- and parent-reported survivor outcomes. Figure 1. Mean scores for the three latent classes based on self-report (S) and parent-report (P). Percentages in the legend indicate the proportion of the sample that is estimated to belong to that latent class. T-score of 50 indicates the normative sample mean (SD = 10). BASC-2 = Behavior Assessment System for Children, Second Edition. Figure 1. View largeDownload slide Latent profiles of self- and parent-reported survivor outcomes. Figure 1. Mean scores for the three latent classes based on self-report (S) and parent-report (P). Percentages in the legend indicate the proportion of the sample that is estimated to belong to that latent class. T-score of 50 indicates the normative sample mean (SD = 10). BASC-2 = Behavior Assessment System for Children, Second Edition. Next, the three classes were compared on the mean scores for each predictor (Table IV). Significant differences were found in most of the predictors, except in self-reported perceived support (RSCA), connectedness to friends, and parental care, and parental PTS. Where significant differences were found, the Resilient class scored more favorably than the other two classes. Thus, the Resilient class was distinguished from the other two classes by better psychological adjustment and more optimal disposition, parental functioning, and social relations compared with the other two classes. Table IV. Class-Specific Means and Standard Errors for the Predictor Variables Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Note. Time 2 (T2) predictors were tested for the subset of the sample that had data for those predictors (n = 131). Holm–Bonferroni correction with α = .05 was applied to control for familywise error. Table IV. Class-Specific Means and Standard Errors for the Predictor Variables Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Predictors Resilient (R) Self-reported at-risk (SAR) Parent-reported at-risk (PAR) Significant differences Baseline  Child distress   Posttraumatic Stress (PTSDI) 14.11 (0.98) 28.12 (2.59) 26.51 (3.62) R < SAR, PAR   Depression (CDI) 57.07 (0.36) 60.88 (0.70) 60.58 (1.27) R < SAR, PAR   Anxiety (SCARED) 16.02 (0.88) 25.32 (2.14) 23.35 (3.51) R < SAR, PAR  Child disposition   Optimism (YLOT) 24.23 (0.27) 21.91 (0.74) 21.45 (1.08) R > SAR, PAR   Pessimism (YLOT) 12.87 (0.36) 16.70 (0.64) 15.51 (1.04) R < SAR, PAR   Positive affect (PANASC) 38.87 (0.76) 33.11 (1.31) 33.41 (2.13) R > SAR, PAR   Negative affect (PANASC) 15.74 (0.51) 21.23 (1.21) 20.15 (1.67) R < SAR, PAR  Parental functioning   Parental care (PBI) 30.97 (0.40) 29.25 (0.75) 30.03 (1.20) ns   Parental overprotection (PBI) 13.17 (0.48) 17.24 (1.13) 16.10 (1.43) R < SAR   Posttraumatic stress (IESR) 20.84 (1.36) 26.02 (3.10) 26.74 (4.27) ns   Global Severity Index (BSI) 52.88 (0.97) 57.60 (1.94) 61.80 (2.05) R < SAR, PAR T2  Child social relations   Perceived support (RSCA) 11.14 (0.26) 10.05 (0.61) 8.89 (1.16) ns   Connectedness (HMAC) to    Friends 4.07 (0.09) 3.79 (0.16) 3.69 (0.27) ns    Parents 4.27 (0.07) 3.78 (0.15) 3.71 (0.33) R > SAR    School 4.12 (0.07) 3.28 (0.15) 3.52 (0.18) R > SAR, PAR    Peers 4.01 (0.07) 3.38 (0.17) 3.67 (0.24) R > SAR    Teacher 4.22 (0.07) 3.78 (0.15) 3.73 (0.24) R > SAR, PAR Note. Time 2 (T2) predictors were tested for the subset of the sample that had data for those predictors (n = 131). Holm–Bonferroni correction with α = .05 was applied to control for familywise error. Next, effects of potential covariates were tested. Demographic and medical factors, including age, race, socioeconomic status, gender, diagnostic category, time since diagnosis, and time since treatment completion, were not significant covariates. However, whether the survivor had any history of relapse had a significant effect and was controlled for in subsequent analyses. Several factors at baseline significantly predicted class membership at T3 (Table V), in expected directions. Baseline child PTS was associated with the odds of belonging to one of the non-Resilient classes. Child pessimism, positive and negative affectivity, and parental overprotection at baseline and connectedness to school at T2 significantly influenced the odds of belonging to the SAR class compared with the Resilient class, in expected directions. Baseline parental distress was the only predictor that affected the odds of belonging to the PAR class compared with the Resilient class. No predictor differentiated between the SAR and PAR classes. Overall, several predictors differentiated 2–3 years in advance those survivors who would belong to the Resilient class, but several other predictors, including parental PTS and child-reported depression, anxiety, optimism, perceived parental care, and connectedness to parents, friends, teacher, or peers, did not affect class membership. Table V. Multinomial Logistic Regression Results for Significant Predictors of Latent Class Membership Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Note. Model 1: N = 203; Model 2: N = 201; Model 3: N = 205; Model 4: N = 126. All four regression analyses controlled for relapse history. a “Compared with” indicates the reference class against which the odds of membership in another class was compared. * p < .05. **p < .01. Table V. Multinomial Logistic Regression Results for Significant Predictors of Latent Class Membership Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Likelihood of class membership at Time 3 Compared with Resilient classa Compared with SAR classa Self-reported at-risk (SAR) class Parent-reported at-risk (PAR) class PAR class Model/Predictors OR 95% CI OR 95% CI OR 95% CI 1. Baseline distress  Posttraumatic stress (PTSDI) 1.06** [1.02, 1.10] 1.05* [1.01, 1.10] 1.00 [0.95, 1.04] 2. Baseline disposition  Pessimism (YLOT) 1.20** [1.07, 1.35] 1.13 [0.97, 1.31] 0.94 [0.81, 1.09]  Positive affectivity (PANASC) 0.95* [0.90, 1.00] 0.97 [0.90, 1.06] 1.02 [0.94, 1.12]  Negative affectivity (PANASC) 1.11** [1.03, 1.19] 1.06 [0.97, 1.16] 0.96 [0.87, 1.06] 3. Baseline parental functioning  Parental overprotection (PBI) 1.12** [1.03, 1.21] 1.07 [0.96, 1.19] 0.96 [0.85, 1.08]  Parent distress - GSI (BSI) 1.03 [0.98, 1.08] 1.09** [1.02, 1.17] 1.06 [0.99, 1.15] 4. Time 2 social functioning  Connectedness to school (HMAC) 0.17** [0.05, 0.61] 0.18 [0.03, 1.18] 1.07 [0.13, 8.45] Note. Model 1: N = 203; Model 2: N = 201; Model 3: N = 205; Model 4: N = 126. All four regression analyses controlled for relapse history. a “Compared with” indicates the reference class against which the odds of membership in another class was compared. * p < .05. **p < .01. Discussion The present study found three distinct patterns of psychosocial adjustment in a sample of largely adolescent to young adult pediatric cancer survivors. Consistent with findings from previous research, nearly two-thirds (65%) of survivors exhibited long-term resilience to their cancer experience, enjoying the best psychosocial adjustment and interpersonal connectedness among the three identified groups during the 3-year study period. The remaining one-third of the survivors diverged into two groups. One group (SAR; 23%) reported at-risk levels of internalizing and attention problems, but only by self-report. In contrast, the smallest group (PAR; 12%) exhibited at-risk levels of parent-reported externalizing, internalizing, and attention problems and at-risk level of self-reported attention problems. As such, no group evidenced clinically significant levels of distress in the present study. This is inconsistent with previous studies that have found clinically elevated psychological symptoms in survivors (Brinkman et al., 2016; Zeltzer et al., 2009). One potential reason for the discrepancy may be that the BASC-2, the outcome measure used in the present study, identifies relatively few cases in the clinically significant range (Wolfe-Christensen, Mullins, Stinnett, Carpentier, & Fedele, 2009). The two non-Resilient groups differed primarily by the reporter that indicated maladjustment. Only the survivors in the SAR group reported internalizing and attention problems. These symptoms, especially in the absence of other accompanying symptoms (e.g., hyperactivity) and at subclinical levels, may not be readily observable to parents. This would be consistent with some previous findings indicating that parent–child agreement regarding internalizing problems may be lower compared with agreement regarding externalizing problems (De Los Reyes & Kazdin, 2005). In the PAR group, survivors and parents agreed that the survivor had at-risk levels of attention problems, but only parents reported internalizing and externalizing problems. One possible reason for this discrepancy is that parents themselves are distressed, which can contribute to higher endorsement of symptoms for their children (Youngstrom, Loeber, & Stouthamer-Loeber, 2000). This view is also consistent with our findings that higher levels of parental distress at baseline predicted membership in this group. Another possible explanation for the discrepancy is that the youths in this group may be reluctant or unaware of the existence of internalizing or externalizing problems (De Los Reyes & Kazdin, 2005). Of note, both groups were characterized by self-reported attention problems in the at-risk range. This may be because survivors tend to experience attention problems at a greater rate than comparison groups (Krull et al., 2010), possibly because of late effects of treatment, or because attention problems can be associated with internalizing or externalizing problems (Kim & Deater-Deckard, 2011). Because no predictor differentiated between the two distressed groups, how they diverged over time is unclear. Further research is needed to identify factors that predict this divergence. Also, as externalizing problems were assessed only by parent-report owing to the absence of a self-report scale for externalizing problems in the BASC-2, the two groups may differ based on whether distress is externalized and noticeable to others. Survivors in the SAR group may internalize their difficulties and be less outwardly symptomatic, whereas those in the PAR group may more outwardly exhibit their distress. In contrast, several psychosocial predictors significantly differentiated the Resilient group from the two distressed groups 3 years later. Child-reported PTS and parents’ self-reported distress increased the odds that the survivors would later belong to the PAR group instead of the Resilient group. Thus, these two predictors may reflect heightened or shared distress within the parent–child dyad that negatively impacts survivors’ adjustment. Child-reported pessimism, negative affectivity, and parental overprotection increased the odds of later belonging to the SAR group, and these predictors may be associated with survivors’ internalizing tendencies. Findings are consistent with previous studies suggesting that child and parental distress, child disposition characterized by negative cognitions and affect, and overprotective parenting all increase risk for maladjustment (Okado et al., 2016; Tillery et al., 2014; Zeltzer et al., 1997). Moreover, elevations in these factors may identify survivors who are at risk for later maladjustment and could benefit from preventive services. With regard to protective factors, child positive affectivity and connectedness to school significantly reduced the odds of later belonging to the SAR group though not the PAR group. Positive affectivity may protect survivors against self-perceived internalizing symptoms or social maladjustment, which were elevated in the SAR group. Connectedness to school, surprisingly, had a protective effect, whereas perceived social support and connectedness to others (e.g., parents and friends), which have been previously documented as being important to survivors’ well-being (Tillery et al., 2017; Zebrack, 2011), did not. However, the present finding is consistent with previous research showing that connectedness to school partially mediates the effects of attachment to parents on depressive symptoms (Shochet, Homel, Cockshaw, & Montgomery, 2008) among adolescents. Thus, educational and social engagement in school may be a powerful and developmentally salient factor influencing survivors’ adjustment. Overall, the findings in the present study have several clinical implications. First, a majority of pediatric cancer patients and survivors can be expected to show enduring resilience and maintain good psychosocial adjustment over time. The protective characteristics observed in these survivors may inform preventive services offered to the minority of youth who are at risk for maladjustment, for instance those in the targeted or clinical/treatment classifications described in the Pediatric Psychosocial Preventative Health Model (Kazak, 2006). These characteristics included lower levels of PTS, pessimism, and negative affectivity; higher levels of positive affect; parental functioning characterized by low overprotection and minimal parental distress; and strong connection to school. As such, providing psychosocial services during treatment and early survivorship that facilitate patient and parent adjustment to the cancer experience encourage a developmentally and personally appropriate amount of autonomy within the parent–child relationship and promote engagement in school is recommended. Because the resilient survivors appear to be buffered from maladjustment especially through their positive affectivity and connectedness to school, these factors warrant special emphasis in preventive intervention. Although positive affectivity may be less malleable than parental behaviors and social relations, numerous intervention approaches are being developed to increase positive affect (Carl, Soskin, Kerns, & Barlow, 2013) and may be useful. To facilitate survivors’ engagement in school, formalized school reintegration interventions and strategies (Prevatt, Heffer, & Lowe, 2000) may be considered, though some research suggests that the evidence base for such programs is still weak (Thompson et al., 2015). Even without formalized interventions, however, pediatric psychologists may facilitate the transition to school by providing psychological testing if needed and assisting the survivor in securing appropriate accommodations; offering psychoeducation regarding the survivorship experience to patients, family, school staff, and peers; and providing referrals to ongoing mental health care as needed. Another clinical implication is that it is important to collect information from both survivors and their parents to rule out maladjustment, as the present study found that the two non-Resilient groups were characterized by discrepancies in survivor and parent reports. Such discrepancies may indicate elevated risk for poorer outcomes (De Los Reyes, 2011), and thus, it is important to follow-up with further assessment and monitoring when any discrepancies are found. Furthermore, as self-reported attention problems were in the at-risk range for the two distressed groups, it may be important to assess for other areas of psychosocial difficulties when survivors report attention difficulties. The present study has several limitations. Outcome data were missing from approximately 10% of living and eligible participants. Although those who were not included in the present sample did not differ from the present sample, it is still possible that inclusion of these missing participants would have changed the profiles of survivor outcomes. In addition, owing to the design of the longitudinal study, social functioning at T2 was assessed for only 60.4% of the sample, and its measures had adequate but lower reliability than most other measures used in the present study. Thus, results need to be interpreted with caution. Also, the separation between the Resilient class and the other two classes was much more evident in self-reported symptoms than with parent-reported symptoms at T3 and was also largely predicted by self-reported factors. To reduce effects attributable to the reporter and to shared method variance, future studies might incorporate more information from reporters other than the survivors. Furthermore, survivors’ externalizing problems were assessed only by parent-report and not by self-report. Thus, the distinction between the two distressed groups may have been affected by this methodological difference. Also, as the present study was conducted at a single site, with a primarily Caucasian sample, replication of findings at other treatment sites with more diverse samples is needed. Conclusion The majority of pediatric cancer survivors appear to be well-adjusted during adolescence and young adulthood, and their resilience is apparent throughout the course of a few years. Of the one-third of survivors who evidenced some distress, a majority exhibited subclinical elevations in internalizing and attention problems by self-report, whereas the rest exhibited subclinical elevations in parent-reported externalizing, internalizing, and attention problems and in self-reported attention problems. Several psychosocial factors predicted the distinction between resilient and distressed survivors 3 years later, and they may provide multiple avenues for preventing maladjustment. Encouragingly, empirically supported therapeutic interventions that ameliorate these factors, including negative cognitive and affective tendencies, parental distress, and parental overprotection, exist. Furthermore, efforts are underway in the field to address the remaining factors, including those enhancing positive affectivity and facilitating school re-entry. Further research identifying malleable mediators and interventions that promote survivor resilience is encouraged. Acknowledgments The authors thank Kristoffer Berlin for sharing his methodological expertise. Funding This work was supported by the National Institutes of Health (grant number R01 CA136782 awarded to S. P.), the American Lebanese-Syrian Associated Charities (ALSAC), and the College of Humanities and Social Sciences, California State University, Fullerton (funding awarded to Y. O.). Conflicts of interest: None declared. References Asparouhov T. , Muthén B. ( 2013 ). Auxiliary variables in mixture modeling: A 3-step approach using Mplus. Retrieved from http://www.statmodel.com/examples/webnotes/AuxMixture_submitted_corrected_webnote.pdf Asparouhov T. , Muthén B. ( 2014 ). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Retrieved from https://www.statmodel.com/examples/webnotes/webnote21.pdf Birmaher B. , Brent D. A. , Chiappetta L. , Bridge J. , Monga S. , Baugher M. ( 1999 ). Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED): A replication study . Journal of the American Academy of Child & Adolescent Psychiatry , 38 , 1230 – 1236 . Google Scholar CrossRef Search ADS Brinkman T. M. , Li C. , Vannatta K. , Marchak J. G. , Lai J.-S. , Prasad P. K. , Kimberg C. , Vuotto S. , Di C. , Srivastava D. , Robison L. L. , Armstrong G. T. , Krull K. R. ( 2016 ). Behavioral, social, and emotional symptom comorbidities and profiles in adolescent survivors of childhood cancer: A report from the Childhood Cancer Survivor Study . Journal of Clinical Oncology , 34 , 3417 – 3425 . Google Scholar CrossRef Search ADS Brinkman T. M. , Zhu L. , Zeltzer L. K. , Recklitis C. J. , Kimberg C. , Zhang N. , Muriel A. C. , Stovall M. , Srivastava D. K. , Robison L. L. , Krull K. R. ( 2013 ). Longitudinal patterns of psychological distress in adult survivors of childhood cancer . British Journal of Cancer , 109 , 1373 – 1381 . Google Scholar CrossRef Search ADS Carl J. R. , Soskin D. P. , Kerns C. , Barlow D. H. ( 2013 ). Positive emotion regulation in emotional disorders: A theoretical review . Clinical Psychology Review , 33 , 343 – 360 . Google Scholar CrossRef Search ADS Costello E. J. , Foley D. L. , Angold A. ( 2006 ). 10-year research update review: The epidemiology of child and adolescent psychiatric disorders: II. Developmental epidemiology . Journal of the American Academy of Child & Adolescent Psychiatry , 45 , 8 – 25 . Google Scholar CrossRef Search ADS De Los Reyes A. ( 2011 ). Introduction to the special section: More than measurement error: Discovering meaning behind informant discrepancies in clinical assessments of children and adolescents . Journal of Clinical Child and Adolescent Psychology , 40 , 1 – 9 . Google Scholar CrossRef Search ADS De Los Reyes A. , Kazdin A. E. ( 2005 ). Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study . Psychological Bulletin , 131 , 483 – 509 . Google Scholar CrossRef Search ADS Derogatis L. , Melisaratos N. ( 1983 ). The Brief Symptom Inventory: An introductory report . Psychological Medicine , 13 , 595 – 605 . Google Scholar CrossRef Search ADS Eiser C. , Hill J. J. , Vance Y. H. ( 2000 ). Examining the psychological consequences of surviving childhood cancer: Systematic review as a research method in pediatric psychology . Journal of Pediatric Psychology , 25 , 449 – 460 . Google Scholar CrossRef Search ADS Ey S. , Hadley W. , Allen D. N. , Palmer S. , Klosky J. , Deptula D. , Thomas J. , Cohen R. ( 2005 ). A new measure of children's optimism and pessimism: The Youth Life Orientation Test . Journal of Child Psychology and Psychiatry , 46 , 548 – 558 . Google Scholar CrossRef Search ADS Howard Sharp K. M. , Willard V. W. , Okado Y. , Tillery R. , Barnes S. , Long A. , Phipps S. ( 2015 ). Profiles of connectedness: Processes of resilience and growth in children with cancer . Journal of Pediatric Psychology , 40 , 904 – 913 . Google Scholar CrossRef Search ADS Kahalley L. S. , Wilson S. J. , Tyc V. L. , Conklin H. M. , Hudson M. M. , Wu S. , Xiong X. , Stancel H. H. , Hinds P. S. ( 2013 ). Are the psychological needs of adolescent survivors of pediatric cancer adequately identified and treated? Psycho-Oncology , 22 , 447 – 458 . doi: 10.1002/pon.3021 Google Scholar CrossRef Search ADS Karcher M. ( 2012 ). The Hemingway: Measure of Adolescent Connectedness: A manual for scoring and interpretation. University of Texas at San Antonio . Unpublished manuscript. Retrieved from http://adolescentconnectedness.com/media/HemingwayManual2012.pdf Kazak A. E. ( 2006 ). Pediatric Psychosocial Preventative Health Model (PPPHM): Research, practice, and collaboration in pediatric family systems medicine . Families, Systems, and Health , 24 , 381 – 395 . Google Scholar CrossRef Search ADS Kim J. , Deater-Deckard K. ( 2011 ). Dynamic changes in anger, externalizing and internalizing problems: Attention and regulation . Journal of Child Psychology and Psychiatry , 52 , 156 – 166 . Google Scholar CrossRef Search ADS Klassen A. F. , Anthony S. J. , Khan A. , Sung L. , Klaassen R. ( 2011 ). Identifying determinants of quality of life of children with cancer and childhood cancer survivors: A systematic review . Supportive Care in Cancer , 19 , 1275 – 1287 . Google Scholar CrossRef Search ADS Kovacs M. ( 1992 ). Children's Depression Inventory (CDI) manual. North Tonawanda, NY : Multi-Health Systems, Inc . Krull K. R. , Huang S. , Gurney J. G. , Klosky J. L. , Leisenring W. , Termuhlen A. , Ness K. K. , Kumar Srivastava D. , Mertens A. , Stovall M. , Robison L. L. , Hudson M. M. ( 2010 ). Adolescent behavior and adult health status in childhood cancer survivors . Journal of Cancer Survivorship: Research and Practice , 4 , 210 – 217 . Google Scholar CrossRef Search ADS Landolt M. A. , Ystrom E. , Sennhauser F. H. , Gnehm H. E. , Vollrath M. E. ( 2012 ). The mutual prospective influence of child and parental post-traumatic stress symptoms in pediatric patients . Journal of Child Psychology and Psychiatry , 53 , 767 – 774 . Google Scholar CrossRef Search ADS Langeveld N. , Stam H. , Grootenhuis M. , Last B. ( 2002 ). Quality of life in young adult survivors of childhood cancer . Supportive Care in Cancer , 10 , 579 – 600 . Google Scholar CrossRef Search ADS Laurent J. , Catanzaro S. J. , Joiner T. E. , Rudolph K. D. , Potter K. I. , Lambert S. , Osborne L. , Gathright T. ( 1999 ). A measure of positive and negative affect for children: Scale development and preliminary validation . Psychological Assessment , 11 , 326 – 338 . Google Scholar CrossRef Search ADS Lo Y. , Mendell N. R. , Rubin D. B. ( 2001 ). Testing the number of components in a normal mixture . Biometrika , 88 , 767 – 778 . Google Scholar CrossRef Search ADS Mackie E. , Hill J. , Kondryn H. , McNally R. ( 2000 ). Adult psychosocial outcomes in long-term survivors of acute lymphoblastic leukaemia and Wilms' tumour: A controlled study . The Lancet , 355 , 1310 – 1314 . Google Scholar CrossRef Search ADS Maurice-Stam H. , Grootenhuis M. A. , Caron H. N. , Last B. F. ( 2007 ). Course of life of survivors of childhood cancer is related to quality of life in young adulthood . Journal of Psychosocial Oncology , 25 , 43 – 58 . Google Scholar CrossRef Search ADS Miller K. S. , Vannatta K. , Compas B. E. , Vasey M. , McGoron K. D. , Salley C. G. , Gerhardt C. A. ( 2009 ). The role of coping and temperament in the adjustment of children with cancer . Journal of Pediatric Psychology , 34 , 1135 – 1143 . Google Scholar CrossRef Search ADS Okado Y. , Howard Sharp K. M. , Tillery R. , Long A. M. , Phipps S. ( 2016 ). Profiles of dispositional expectancies and affectivity predict later psychosocial functioning in children and adolescents with cancer . Journal of Pediatric Psychology , 41 , 298 – 308 . Google Scholar CrossRef Search ADS Orbuch T. L. , Parry C. , Chesler M. , Fritz J. , Repetto P. ( 2005 ). Parent-child relationships and quality of life: Resilience among childhood cancer survivors . Family Relations , 54 , 171 – 183 . Google Scholar CrossRef Search ADS Ozono S. , Saeki T. , Mantani T. , Ogata A. , Okamura H. , Yamawaki S. ( 2007 ). Factors related to posttraumatic stress in adolescent survivors of childhood cancer and their parents . Supportive Care in Cancer , 15 , 309 – 317 . Google Scholar CrossRef Search ADS Parker G. , Tupling H. , Brown L. B. ( 1979 ). A parental bonding instrument . British Journal of Medical Psychology , 52 , 1 – 10 . Google Scholar CrossRef Search ADS Prevatt F. F. , Heffer R. W. , Lowe P. A. ( 2000 ). A review of school reintegration programs for children with cancer . Journal of School Psychology , 38 , 447 – 467 . Google Scholar CrossRef Search ADS Prince-Embury S. ( 2007 ). Resiliency scales for children and adolescents: Profiles of personal strengths . San Antonio, TX : Harcourt Assessments . Pynoos R. S. , Rodriguez N. , Steinberg A. , Stuber M. , Frederick C. ( 1998 ). The University of California at Los Angeles Posttraumatic Stress Disorder Reaction Index (UCLA-PTSD RI) for DSM-IV (Revision 1). Los Angeles, CA : UCLA Trauma Psychiatry Program . Unpublished manual. Reynolds C. , Kamphaus R. ( 2004 ). BASC-2: Behavior Assessment System for Children, Second Edition . Circle Pines, MN : AGS Publishing . Robinson K. E. , Gerhardt C. A. , Vannatta K. , Noll R. B. ( 2009 ). Survivors of childhood cancer and comparison peers: The influence of early family factors on distress in emerging adulthood . Journal of Family Psychology , 23 , 23 – 31 . Google Scholar CrossRef Search ADS Servitzoglou M. , Papadatou D. , Tsiantis I. , Vasilatou-Kosmidis H. ( 2008 ). Psychosocial functioning of young adolescent and adult survivors of childhood cancer . Supportive Care in Cancer , 16 , 29 – 36 . Google Scholar CrossRef Search ADS Shochet I. M. , Homel R. , Cockshaw W. D. , Montgomery D. T. ( 2008 ). How do school connectedness and attachment to parents interrelate in predicting adolescent depressive symptoms? Journal of Clinical Child and Adolescent Psychology , 37 , 676 – 681 . Google Scholar CrossRef Search ADS Sulkers E. , Fleer J. , Brinksma A. , Roodbol P. F. , Kamps W. A. , Tissing W. J. E. , Sanderman R. ( 2013 ). Dispositional optimism in adolescents with cancer: Differential associations of optimism and pessimism with positive and negative aspects of well-being . British Journal of Health Psychology , 18 , 474 – 489 . Google Scholar CrossRef Search ADS Thompson A. L. , Christiansen H. L. , Elam M. , Hoag J. , Irwin M. K. , Pao M. , Voll M. , Noll R. B. , Kelly K. P. ( 2015 ). Academic continuity and school reentry support as a standard of care in pediatric oncology . Pediatric Blood and Cancer , 62 , S805 – S817 . Google Scholar CrossRef Search ADS Tillery R. , Cohen R. , Berlin K. S. , Long A. , Phipps S. ( 2017 ). Youth’s adjustment to cancer: Examination of patterns of adjustment and the role of peer relations . Journal of Pediatric Psychology , 42 , 1123 – 132 . doi: 10.1093/jpepsy/jsx067 Google Scholar CrossRef Search ADS Tillery R. , Long A. , Phipps S. ( 2014 ). Child perceptions of parental care and overprotection in children with cancer and healthy children . Journal of Clinical Psychology in Medical Settings , 21 , 165 – 172 . Google Scholar CrossRef Search ADS Trask P. C. , Paterson A. G. , Trask C. L. , Bares C. B. , Birt J. , Maan C. ( 2003 ). Parent and adolescent adjustment to pediatric cancer: Associations with coping, social support, and family function . Journal of Pediatric Oncology Nursing , 20 , 36 – 47 . Google Scholar CrossRef Search ADS Trickey D. , Siddaway A. P. , Meiser-Stedman R. , Serpell L. , Field A. P. ( 2012 ). A meta-analysis of risk factors for post-traumatic stress disorder in children and adolescents . Clinical Psychology Review , 32 , 122 – 138 . Google Scholar CrossRef Search ADS Van Schoors M. , Caes L. , Knoble N. B. , Goubert L. , Verhofstadt L. L. , Alderfer M. A. ( 2017 ). Systematic review: Associations between family functioning and child adjustment after pediatric cancer diagnosis: A meta-analysis . Journal of Pediatric Psychology , 42 , 6 – 18 . Weiss D. ( 2004 ). The Impact of Event Scale-Revised. In Wilson J. , Keane T. (Eds.), Assessing psychological trauma and PTSD ( 2nd ed ., pp. 168 – 189 ). New York, NY : Guilford . Williams N. A. , Davis G. , Hancock M. , Phipps S. ( 2010 ). Optimism and pessimism in children with cancer and healthy children: Confirmatory factor analysis of the Youth Life Orientation Test and relations with health-related quality of life . Journal of Pediatric Psychology , 35 , 672 – 682 . Google Scholar CrossRef Search ADS Wolfe-Christensen C. , Mullins L. L. , Stinnett T. A. , Carpentier M. Y. , Fedele D. A. ( 2009 ). Use of the Behavioral Assessment System for Children 2nd edition: Parent report scale in pediatric cancer populations . Journal of Clinical Psychology in Medical Settings , 16 , 322 – 330 . Google Scholar CrossRef Search ADS Youngstrom E. , Loeber R. , Stouthamer-Loeber M. ( 2000 ). Patterns and correlates of agreement between parent, teacher, and male adolescent ratings of externalizing and internalizing problems . Journal of Consulting and Clinical Psychology , 68 , 1038 – 1050 . Google Scholar CrossRef Search ADS Zebrack B. J. ( 2011 ). Psychological, social, and behavioral issues for young adults with cancer . Cancer , 117 , 2289 – 2294 . Google Scholar CrossRef Search ADS Zeltzer L. K. , Chen E. , Weiss R. , Guo M. D. , Robison L. L. , Meadows A. T. , Mills J. L. , Nicholson H. S. , Byrne J. ( 1997 ). Comparison of psychologic outcome in adult survivors of childhood acute lymphoblastic leukemia versus sibling controls: A cooperative Children's Cancer Group and National Institutes of Health study . Journal of Clinical Oncology , 15 , 547 – 556 . Google Scholar CrossRef Search ADS Zeltzer L. K. , Recklitis C. , Buchbinder D. , Zebrack B. , Casillas J. , Tsao J. C. , Lu Q. , Krull K. ( 2009 ). Psychological status in childhood cancer survivors: A report from the Childhood Cancer Survivor Study . Journal of Clinical Oncology , 27 , 2396 – 2404 . Google Scholar CrossRef Search ADS © 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/legal/notices)

Journal

Journal of Pediatric Psychology – Oxford University Press

Published: May 24, 2018

There are no references for this article.