Psychosocial, health-promotion, and neurocognitive interventions for survivors of childhood cancer: a systematic review.

Health Psychology 2015, Vol. 34, No. 2, 130 –148

© 2014 American Psychological Association 0278-6133/15/$12.00 http://dx.doi.org/10.1037/hea0000119

Psychosocial, Health-Promotion, and Neurocognitive Interventions for Survivors of Childhood Cancer: A Systematic Review Moriah J. Brier

Lisa A. Schwartz

University of Pennsylvania

Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, and University of Pennsylvania

Anne E. Kazak This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Nemours Children’s Health System, Wilmington, Delaware, and Thomas Jefferson University Objective: Survivors of childhood cancer must contend with a number of medical and psychosocial vulnerabilities after their cancer treatment ends. Interventions have been developed to alleviate or prevent adverse outcomes among this population. This systematic review summarizes the efficacy of psychosocial, health behavior, and neurocognitive interventions for survivors of pediatric cancer. Method: Multiple databases were searched for studies published between January 1970 and June 2013. Studies were coded by 2 raters for methodological quality using the Effective Public Health Practice Project quality assessment tool. Results: Twenty-four interventions were identified (7 psychosocial, 10 health behavior, and 7 neurocognitive). Eleven were controlled trials, of which 7 achieved medium to large effect sizes. Survivor interest, as demonstrated by consent rates, was high for interventions that did not require travel. Conclusions: Interventions using delivery methods varying from traditional counseling to computers achieved moderate to strong efficacy and merit replication. Survivor needs related to transition to adult-oriented health care and school reentry were not addressed by existing interventions. This review also revealed the absence of health behavior interventions for survivors in middle childhood and late adolescence. Intervention formats that are cost-effective and reduce participant burden should be prioritized for further testing. To broaden the reach and appeal of interventions, alternative delivery methods, such as mobile phone software applications, should be evaluated. Keywords: childhood cancer survivorship, intervention studies, health behaviors, psychosocial wellbeing, cognitive remediation Supplemental materials: http://dx.doi.org/10.1037/hea0000119.supp

ages of 0 and 19 are greater than 79% (Ries et al., 2007). Despite the relief that survival may bring, it bears its own unique challenges. Many survivors must grapple with medical and psychosocial vulnerabilities resulting from diagnosis and/or treatment (Castellino et al., 2011; Hile et al., 2012; Stuber et al., 2010). These challenges occur in the context of normal development, which has its own difficulties— especially for adolescents struggling with tasks such as identity development, school achievement, peer pressures, and the formation of close relationships. Survivors of childhood cancer may benefit from evidence-based interventions to prevent, reduce, or help manage survivorship-related challenges. This review will describe interventions that have been tested for this population and will evaluate their efficacy.

Of the more than 12,000 children and adolescents diagnosed each year with cancer in the United States (American Cancer Society, 2013), 5-year survival rates for individuals between the

Editor’s Note. Elizabeth Klonoff served as Action Editor.

This article was published Online First August 18, 2014. Moriah J. Brier, Department of Psychology, University of Pennsylvania; Lisa A. Schwartz, Division of Oncology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, and Perelman School of Medicine, University of Pennsylvania; Anne E. Kazak, Center for Healthcare Delivery Science, Nemours Children’s Health System, Wilmington, Delaware and Department of Pediatrics, Jefferson Medical College, Thomas Jefferson University. Preparation of this review was supported, in part, by grants to the third author (K05CA128805). The authors would like to extend their gratitude to Angelica Frausto, Anne Marie Roepke, and Christopher Speicher for their assistance in conducting reliability coding. Correspondence concerning this article should be addressed to Moriah J. Brier, Department of Psychology, University of Pennsylvania, 3720 Walnut St., Solomon Lab Building, Philadelphia, PA 19104. E-mail: [email protected]

Challenges Associated With Survivorship The following section summarizes the major obstacles and difficulties childhood cancer survivors face that are potentially fruitful targets for intervention.

Health Behavior Challenges The most tangible consequences of childhood cancer are medical “late effects”—the physical consequences of cancer treatment, 130

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

INTERVENTIONS FOR CHILDHOOD CANCER SURVIVORS

which can include cardiopulmonary toxicity, endocrine problems, infertility, osteoporosis, and second malignancies (Hudson et al., 2003; Oeffinger et al., 2006). Approximately 40% to 45% of survivors experience one moderate to serious adverse health outcome (Hudson et al., 2003). Consequently, survivors of childhood cancer are recommended to regularly attend cancer-related medical appointments so that late effects can be prevented or quickly identified (Landier, 2007). A large portion of survivors (58.1%; Oeffinger et al., 2004) do not attend such appointments, with fewer attending as time since diagnosis increases. One possible explanation for poor follow-up is that more than two thirds of patients do not successfully transition from pediatric to adult-oriented cancer care (Nathan et al., 2008; Oeffinger et al., 2004). Some may continue care at pediatric centers, where it is challenging to assure that care is medically and developmentally appropriate (Freyer & Brugieres, 2008). There are many multifactorial challenges to preparing survivors and their parents for the transition to adultoriented care (Pai & Schwartz, 2011; L. A. Schwartz et al., 2013). Interventions that guide families through this process and address both logistical and emotional aspects of the transition may be useful. Although exercise, healthy diet, and abstinence from smoking and substance use are beneficial for everyone, the importance of a healthy lifestyle is critical for survivors who are at increased risk of potentially preventable health conditions. In general, survivors are not engaging in behaviors that promote their physical wellbeing, such as physical activity and diet, at recommended levels (Florin et al., 2007; Robien, Ness, Klesges, Baker, & Gurney, 2008). Substance use is also a problem: 17% of survivors are current smokers, according to the Childhood Cancer Survivor Study (CCSS; Emmons et al., 2002), despite the fact that smoking can exacerbate the organ damage associated with chemotherapy or irradiation (Nathan et al., 2009). Interventions can educate survivors about the importance of certain health behaviors, as well as provide assistance to those who may be having difficulty making behavior changes on their own.

Neurocognitive Challenges One medical late effect that is of particular concern for survivors is neurocognitive deficits. Brain tumors, and cancer treatments that target the central nervous system, can have long-lasting negative impacts on executive function, attention, and processing speed (Butler et al., 2013; Peterson et al., 2008). Some are more at risk for neurocognitive late effects, such as female survivors and those treated at younger ages (Ellenberg et al., 2009; Mulhern et al., 2001). Interventions that help survivors develop compensatory strategies may help minimize the impact of their deficits on daily functioning.

Psychosocial Challenges The transitions associated with ending treatment are often accompanied by a range of emotional reactions, including relief and joy, to abandonment and isolation (Cantrell & Conte, 2009; Duffey-Lind et al., 2006). Though the majority of survivors are psychologically resilient, a subset does experience distress at clinical levels. For example, survivors were more than four times as likely as siblings to meet criteria for PTSD (Stuber et al., 2010), and five times as likely as healthy controls (L. Schwartz & Drotar,

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2006). Studies examining children and adolescents in Sweden and Hong Kong found survivors to have significantly higher depression levels and lower levels of self-esteem than healthy peers (Li, Chung, Ho, Chiu, & Lopez, 2012; von Essen, Enskär, Kreuger, Larsson, & Sjödén, 2000). Alleviating psychological distress among survivors may be best served by interventions that are sensitive to unique aspects of the cancer experience. Many survivors of childhood cancer also struggle with achieving autonomy and key developmental tasks. Reentry into school and related activities can be particularly challenging, especially when a survivor suffers from neurocognitive late effects. Survivors of multiple cancer types were shown to miss significantly more days of school than population controls, even after absences because of hospital and clinic visits were controlled for (French et al., 2013). Experiences missed in childhood as a result of treatment can have ripple effects into adulthood (Hobbie, Hudson, Rowland, & Schwartz, 2009). According to the CCSS, pediatric cancer survivors are less likely to be employed (Gurney et al., 2009) and more than twice as likely to be living dependently (with a family member or caregiver) than their siblings (Kunin-Batson et al., 2011). Survivors also have more difficulty establishing romantic and sexual relationships than their peers (Frobisher, Lancashire, Winter, Jenkinson, & Hawkins, 2007; Gurney et al., 2009). Interventions that assist survivors through the challenges of reintegration, whether through direct involvement with schools, or by training families to obtain the resources their children need, may improve the school reentry process.

The Present Review The present review seeks to organize findings of interventions that target health behavior, neurocognitive, and psychosocial outcomes among survivors of childhood cancer; to summarize conclusions that can inform future intervention research; and to identify neglected intervention targets that are important for improving the wellbeing of this population. The following questions will be addressed in this review: (a) What health behavior, neurocognitive, and psychosocial outcomes do existing interventions target? How does this correspond to survivors’ needs? (b) What is the methodological quality of existing interventions? (c) What intervention characteristics are common among trials with the greatest efficacy? (d) To what degree do survivors show a desire to engage in these interventions?

Method Eligibility Criteria Studies had to meet the following five criteria: (a) all study participants were diagnosed with cancer before the age of 21; (b) all participants were in remission or had completed treatment (and were not in palliative care); (c) the intervention targeted a psychosocial, health behavior, or neurocognitive outcome; (d) survivor outcomes were reported separately when other family members were also assessed; and (e) outcome measures quantitatively assessed the efficacy of the intervention. (As the purpose of this review was to help clarify what intervention approaches may be effective, qualitative studies or studies that measured the feasibility of interventions without measuring efficacy were excluded.) Mul-

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tiple articles that provided results from the same study were grouped together for all analyses. For intervention studies that had been preceded by published pilot studies, only the more recent, nonpilot version was discussed. To help identify potentially effective approaches that may be worth testing in randomized controlled trials (RCTs), uncontrolled studies were included.


Search Strategy Four databases were searched (PubMed, EMBASE, PsycINFO, CINAHL) for peer-reviewed articles and dissertations published between January 1970 and June 2013. Three stems of search terms were formed describing the following: (a) childhood cancer survivors; (b) health behavior, neurocognitive, and psychosocial outcomes; and (c) interventions. The stems were combined for each database search, and all searches were limited to English-language publications. A list of the search terms in each stem is provided in Appendix Table A1 of the online supplemental materials.

Study Selection The first author screened article titles and abstracts resulting from the database searches. Full-text versions of articles that potentially met the eligibility criteria were retrieved, and two raters independently determined whether the studies qualified for inclusion. Any discrepancies between coders were discussed until an agreement was reached. Reference sections of included articles were also searched for additional studies that may have been missed in the initial search.

Data Extraction For each study, data regarding sample characteristics, methodology, results, and intervention characteristics were extracted into a spreadsheet. Whether or not interventions were tailored was also noted (tailoring refers to whether an intervention was customized to individual differences identified prior to the intervention; Kreuter, Farrell, Olevitch, & Brennan, 1999). A summary of each data category is provided in Appendix Table A2 of the online supplemental materials.

coded for quality by two coders and interrater reliability was assessed. Disagreements between coders were discussed until a consensus was reached.

Calculation of Effect Sizes In many studies, sample sizes were very small and thus had insufficient power. Effect sizes were therefore calculated to highlight findings that were reported as being nonsignificant, but may have been significant if larger sample sizes had been used. They also provide information about the magnitude of effect for results that were found to be significant. Data to calculate effect sizes were extracted from the articles, and included means, standard deviations, and t and F values. Different effect size formulas were used for controlled versus uncontrolled trials. For one-group pre–post designs, a withingroup effect size was calculated. For controlled trials, a betweengroups effect size was calculated to summarize differences between the treatment and control groups (the effect size formulas can be found in Appendix B of the online supplemental materials). The computer program Comprehensive Meta-Analysis Version 2 (Borenstein, Hedges, Higgins, & Rothstein, 2005) was used to make all effect size calculations.

Willingness to Engage in Treatment Consent rates for intervention studies may provide some indication of survivors’ initial impressions of treatment acceptability. Though many other factors are likely to influence survivors’ consent rates, identifying relationships between certain intervention characteristics and consent-rate levels may offer some guidance for the development of future protocols on how to appeal to the population that interventionists are trying to serve. Average consent rates were calculated for the following intervention characteristics: intervention target, mode of delivery, method of delivery, inclusion of family members, and whether participants had to make a special trip to participate.

Results

Study Quality

Study Selection and Coding

To assess the methodological quality of the selected studies, the Effective Public Health Practice Project (EPHPP) quality assessment tool was used. EPHPP has demonstrated content and construct validity (Thomas, Ciliska, Dobbins, & Micucci, 2004). In a report assessing over 190 bias assessment tools for intervention studies, the EPHPP was one of six shown to be appropriate for use in systematic reviews (Deeks et al., 2003).1 The quality categories that were rated included selection bias (Were participants recruited from a representative sample and what proportion agreed to participate?), study design (Was there a control group?), confounders (Were differences between treatment groups controlled for in analyses?), data collection methods (Were outcome measures reliable and valid?), withdrawals and dropouts (What percentage dropped out of the study before postintervention data could be collected?), fidelity measurement (Was the integrity of the intervention measured?), and blinding (Was the outcome assessor aware of the intervention status of participants?). All studies were

A summary of the study selection process is provided in Figure 1. Full-text versions of 60 articles were retrieved and read by two raters. Agreement between the two raters for study inclusion was excellent (␬ ⫽ .83) and disagreements were easily resolved through discussion, leading to the inclusion of 32 records. Three additional studies were identified through searching the reference sections of selected articles. In sum, 35 articles were identified. After accounting for redundancy resulting from pilot studies preceding larger studies, and multiple articles examining the same sample, 24 unique interventions remained, representing 2,572 participants. 1 EPHPP was chosen over the Cochrane Collaboration Risk of Bias Tool (CCRBT) because it is more appropriate than the CCRBT for assessing nonrandomized study designs, and has been found to have superior interrater agreement (Armijo-Olivo, Stiles, Hagen, Biondo, & Cummings, 2012).


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Records identified through database searching (n = 5,351a) Records excluded for not meeting inclusion criteria (n = 5,291)


Full-text records assessed for eligibility (n = 60)

Records excluded for not meeting inclusion criteria (n = 28) Reasons: 1. All or a portion of sample is still on treatment (n = 5) 2. All or some participants did not receive diagnosis as a child (n = 6) 3. Intervention does not target a health behavior or psychosocial outcome (n = 4) 4. No quantitative measures of treatment's efficacy (n = 9) 5. Not an intervention (n = 4)

Additional records identified through reference sections (n=3)

Included studies (n = 35) Unique studiesb (n = 24) a Includes

duplicate entries across databases This excludes pilot studies preceding larger studies and studies conducting secondary analyses on the same sample after an initial study

b

Figure 1.

Flow diagram of search strategy results.

Agreement between raters for coding of study quality varied by category but was all in the excellent range (Landis & Koch, 1977). For study design and blinding, agreement was 100%; for ratings of confounders, data collection methods, fidelity measurement, and withdrawals and dropouts, agreement ranged from ␬ ⫽ 0.77 to ␬ ⫽ 0.93.

Psychosocial, Health Behavior, and Neurocognitive Outcomes of Existing Interventions Seven interventions targeted psychosocial outcomes, including three that focused on improving social skills, and four that centered on psychological factors, such as posttraumatic stress or coping skills. The majority of the interventions (n ⫽ 10) targeted behaviors related to health promotion and follow-up care. A total of seven interventions focused on neurocognitive outcomes, including one that also targeted social skills. All interventions are summarized in Tables 1, 2, and 3. The social skills interventions were designed for children who had survived a cancer that had affected the central nervous system. Two employed a group format that allowed participants to immediately practice the social skills they were learning (Barakat et al., 2003; Barrera & Schulte, 2009). The group interventions also had overlapping content: skills related to forming friendships, cooperation, conflict resolution, and empathy. The third intervention was delivered in individual format and employed a cognitive– behavioral approach to address behavioral problems and social

skills deficits (Poggi et al., 2009). Two studies had a noticeable imbalance in the gender ratio of participants, with approximately 70% being boys (Barakat et al., 2003; Poggi et al., 2009). Only one of the social skills trials was a controlled study. Four interventions focused on psychological well-being, including targets such as posttraumatic stress, coping with uncertainty, self-acceptance, and benefit finding. Half of these interventions included parents, one with 57% mothers (Kazak et al., 2004) and the other with 90% (Santacroce, Asmus, Kadan-Lottick, & Grey, 2010). Survivors ranged in age from 8 to 29 across the studies, with two studies focusing on survivors older than 18 (Santacroce et al., 2010; L. E. Schwartz, Feinberg, Jilinskaia, & Applegate, 1999). Within each study, age at diagnosis spanned many different developmental periods. A couple of health behavior interventions addressed a broad range of health domains in the form of 1-day educational group workshops (Cox et al., 2008; Cox, McLaughlin, Rai, Steen, & Hudson, 2005; Cox, McLaughlin, Steen, & Hudson, 2006; Hudson et al., 2002; Mays et al., 2011; Mays, Black, Mosher, Shad, & Tercyak, 2011). The majority of the health behavior interventions, however, were more narrowly focused on one health behavior, such as smoking cessation, medical screening, physical activity, or drug and alcohol use. Methods of delivery ranged from telephone therapy (Emmons et al., 2005; Tyc et al., 2003), to mailings of personalized care plans (Oeffinger et al., 2011), to group adventure activities (Li et al., 2012). Two interventions, developed by groups

Readiness to change behavior; attitude to clinic

Attitude to follow-up care; readiness to change; self-efficacy

Adherence to 6-week exercise intervention; endurance, strength, functional mobility, and quality of life

Mammogram or echocardiogram screening

Eiser, Hill, & Blacklay (2000) (Information package)

Gilliam et al. (2011) (Community-based exercise intervention)

Oeffinger et al. (2010) (Mailed Survivorship Care Plan)

Target of intervention

Absolom et al. (2004) (Minimal intervention)

Study

Table 1 Description of Health Behavior Interventions Study design

Uncontrolled trials Booklet provided to survivors at clinic One group appointment; contains information pretest/posttest about cancer, cancer treatment, the purpose of follow-up appointments, potential late effects, and the importance of health behaviors such as exercise and sun protection Information package provided to One group survivor by physician at follow-up pretest/posttest care appointment; package includes a personalized summary of cancer treatment and 12 information sheets tailored to survivors’ medical risks and problems One-on-one exercise training led by One group young adult community mentors; pretest/posttest training included problem solving about barriers to adherence and practicing physical exercises; tailored to the participants’ ability; a token economy was used to enhance adherence; daily physical activity was assigned as homework (Six sessions over 6 weeks – face-toface) Personalized one-page care plan One group mailed to survivors who had not pretest/posttest received a mammogram or echocardiogram in the past 2 years; care plan includes information regarding the patient’s cancer therapy, potential late effects, and recommendations for risk-based screening; access to educational website with information about Hodgkin’s lymphoma and late effects (website could display information using either lay terms or medical terms)

Intervention description

T: 62 F/U: 6 months

T: 20 F/U: 0 months

T: 229 F/U: 2 weeks

T: 48 F/U: ⬍ 1 month

N/First F/U

Age range: 30–56 years Cancer type: 100% Hodgkin lymphoma

Age range: 16–32 years Cancer type: 25% lymphomas, 30% solid tumors, 37% leukemia, 8% CNS tumors Age range: 6–18 years Cancer type: 55% ALL, 45% brain tumor

Age range: 10–16 years Cancer type: 41% leukemia/lymphoma, 21% CNS tumors, 38% solid tumors

Agea and cancer type


(Effect sizes not calculable)e

Pediatric Quality of Life (parent and survivor report)

(Effect sizes not available)d

Attitude to followup

Outcomes with effect sizes ⬎ 0.2b,c

134 BRIER, SCHWARTZ, AND KAZAK

Smoking cessation

Decision-making quality; risk motivation; smoking, drinking, and illicit drug use

Health knowledge; health perceptions; multiple health behaviors

Physical activity

Hollen et al. (2013) (Decision-Aid Program)

Hudson et al. (2002); Cox et al. (2005) (Multi-component behavioral intervention)

Li et al. (2013) (Adventure-based training)


Emmons et al. (2005); Park et al. (2006) (Partnership for Health Study)

Study

Table 1 (continued) Study design

One-on-one risk behavior counseling tailored to the participant’s risklevel; CD-ROM activities and videos, accompanied by worksheets focusing on quality decision making (to be completed at home) (One session face-to-face and an additional telephone booster at 9 months for survivors at high risk for substance use; CD-ROM videos at 2, 4, and 6 months) One-on-one health behavior training in survivor’s chosen goal; training involved a review of the advantages and disadvantages of the health behavior, an explanation of how to engage in the health behavior, problem solving of potential barriers, a commitment to engage in the health behavior; follow-up reinforcement was offered (one session face-to-face and two reinforcements via telephone at 3 and 6 months) Group format; educational talks which focused on the importance of exercise, how to overcome barriers to exercise, how much exercise is appropriate, and strategies for maintaining regular exercise; workshops for developing physical activity action plans; adventurebased training activities (e.g. wall climbing, mini-Olympics) (4 days over 6 months – face-to-face) RCT (C: Leisure activities organized by a community center

RCT (C: standard care)

RCT (C: standard care plus sham CDROM related to study skills)

Controlled trials One-on-one peer-delivered counseling; RCT (C: self-help sessions tailored to stage of smoking readiness to quit and personal cessation health goals; emphasis on manual) enhancing social support; Nicotine Replacement Therapy was discussed with all participants and made available at no cost (Up to six sessions over 7 months – via telephone)


T: 34 C: 37 F/U: 0 months

T: 131 C: 135 F/U: 12 months

T: 120 C: 123 F/U: 0 months

T: 398 C: 398 F/U: 12 monthsf

N/First F/U

Age range: 9–16 years Cancer type: 49% leukemia, 25% lymphoma, 11% bone tumor, 15% other

Age range: 12–18 years Cancer type: 55% leukemia/lymphoma, 45% solid tumor

Age (M [SD]) ⫽ 31.0 (6.7) Cancer type: 26% leukemia, 18% Hodgkin’s disease, 12% CNS malignancy, 11% non-Hodgkin’s lymphoma, 11% bone cancer, 22% other Age range: 14–19 years Cancer type: 40% ALL, 20% embryonal, 12% brain tumors, 28% other



(table continues)

CUHK-PARCY: Physical activity Physical Activity Self-Efficacy Pediatric Quality of Life Inventory

Health Practices: breast self-exam, junk food, testicular selfexam Perceived seriousness

(Effect sizes not calculable)g

Smoking quit rate



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Knowledge about tobacco risks; perceived vulnerability of tobacco-related health risk; intentions to use tobacco

Tyc et al., 2003 (Tobacco intervention)

Group-based health education and behavioral workshop; emphasis was placed on increasing awareness of late effects, helping survivors reduce barriers and increase perceived benefits of engaging in health behaviors, and enhancing self-efficacy (Single half-day session – face-toface) One-on-one late effects risk counseling; educational video about the consequences of tobacco use; goal setting of either tobacco cessation or continued abstinence; physician feedback letter about tobacco use; follow-up telephone counseling to reinforce goals and problem solve about barriers (Three sessions – one face-to-face, two via telephone at 1 and 3 months)



RCT (C: waitlist)

Study design

T: 53 C: 50 F/U: 12 months

T: 38 C: 37 F/U: 1 month

N/First F/U

Age range: 10–18 years Cancer type: 57% leukemia, 43% solid tumors

Age range: 11–21 years Cancer type: 52% leukemia, 48% other


Intentions to use tobacco Knowledge Perceived vulnerability

Dietary calcium intake Mean # of days with calcium supplement Milk consumption frequency Total sun safety behaviors


Note. ALL ⫽ acute lymphoblastic leukemia; C ⫽ control group; CNS ⫽ central nervous system; CUHK-PARCY ⫽ Chinese University of Hong Kong: Physical Activity Rating for Children and Youth; F/U ⫽ follow-up; RCT ⫽ randomized controlled trial; SF-12 ⫽ 12-item Short Form Health Survey; T ⫽ treatment group. a If age range was not available, the mean and standard deviation were provided instead. b Effect sizes in bold have significant confidence intervals at p ⬍ .05. c Unless otherwise specified, all outcomes are based on survivor self-report data. d There were significant improvements in Readiness to Change and Self-Efficacy; however, data was not available to calculate effect sizes. e It was not possible to calculate effect sizes due to the study design. Postintervention, 41% of the sample obtained a mammogram and 20% obtained an echocardiogram. f 12-month follow-up was used instead of earlier follow-up because more data was available. g There were significant improvements (reductions) in risk motivation for alcohol and illicit drug use; however, data was not available to calculate effect sizes.

Bone health and sun safety behaviors


Mays, Black, Mosher, Heinly, et al. (2011); Mays, Black, Mosher, Shad, et al. (2011) (SHARE Program)

Study

Table 1 (continued)



Educational performance

Inattention and working memory

Neuromotor skills; visuomotor integration; cognitive functioning

Cognitive flexibility, attention, and working memory

Hardy et al. (2011) (Captain’s Log)

Kanitz et al. (2013) (Eurythmy therapy)

Kesler et al. (2011) (Cognitive rehabilitation curriculum)


Anderson et al. (2000) (Education intervention)

Study

Table 2 Description of Neurocognitive Interventions

Uncontrolled trials Amount of feedback tailored to survivor’s performance on tests of intellectual and educational abilities; feedback included one or more of the following, depending on the level of survivor’s impairment: verbal feedback, written report, and/or school liaison (Feedback provided once) Internet-based games; 33 multilevel “brain-training” exercises aimed at improving attention, concentration, memory, hand-eye coordination, fundamental numeric concepts, and basic problem-solving skills; program is already used in over 650 schools in the United States (50 min per week over 12 weeks) One-on-one exercises in rising and falling speech rhythms, spatial orientation, and boundary formation; rod exercises, stepping exercises, and central speech sound exercises; exercises tailored to patient’s developmental status (25 sessions over 6 months – face-toface) Internet-based exercises focusing on cognitive flexibility, attention, and working memory; program difficulty adapts to child’s performance (20 min per session/5 sessions per week over 8 weeks)


One group pretest/posttest




Study design

T: 23 F/U: 0 months

T: 7 F/U: 0 months

T: 9 F/U: 0 months

T: 35 F/U: ⬃1 year

N/First F/U

Age and cancer type

Age range: 7–19 years Cancer type: 61% ALL, 39% posterior fossa brain tumor

Age range: 7–17 years Cancer type: 100% posterior fossa tumor

Age range: 10–17 years Cancer type: 33% ALL, 67% brain tumor

Age range: 7–13 years Cancer type: 100% ALL


WISC-IV: Processing Speed Index Working Memory Index Sort Test (NEPSY II or DKEFS) WJ-III Cancellation Test WRAML2: List Memory, Picture Memory MVPT-3 Visual Perception (table continues)

WISC-IV: Working Memory Index, Digit Span subtest, LetterNumber Sequencing subtest CPRS Inattention (parent report) WISC-IV: Fullscale IQ, Working memory index, Processing speed index

WRAT-R: Reading and Spelling

Outcomes with effect sizes ⬎ 0.2a,b


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Academic achievement, attention, working memory, memory recall, and vigilance

Working memory, attention, and learning problems

Butler et al. (2008); Butler & Copeland (2002) (Cognitive Remediation Program)

Hardy et al., 2013 (CogmedRM)

Home-based computerized cognitive training targeting visuospatial and auditory working memory skills; program difficulty level adapts to child’s performance (25 training sessions over 5–8 weeks)

Controlled trials One-on-one hierarchically graded attentional exercises, teaching of metacognitive strategies (including checking one’s work or approaching an activity in a systematic fashion), and cognitive behavioral interventions (such as developing encouraging self-talk) (20 sessions over 4–5 months – face-toface)

One-on-one counseling in behavioral study skills, metacognitive strategies, information processing strategies, and academic mastery techniques (7–15 sessions – face-to-face)


RCT (C: identical to treatment arm except program’s difficulty level does not adapt)

RCT (C: wait list)


Study design

T: 13 C: 7 F/U: 0 months

T: 109 C: 54 F/U: 0 months

T: 15 F/U: 0 months

N/First F/U

Age range: 6–17 years Cancer type: brain tumors, leukemia, bone marrow transplant, nonHodgkin’s lymphoma (proportions not available) Age range: 8–16 years Cancer type: 55% ALL, 45% brain tumor

Age range: 7–19 years Cancer type: 75% brain tumor, 17% leukemia, 8% CNS histiocytosis

Age and cancer type

WRAML2: Finger Windows, Number Letter, Symbolic Working Memory CPRS: Inattention, Learning problems (parent report)

Learning strategies CPRS:LV-R: Inattention, ADHD (parent report) CTRS:LV-R Inattention (teacher report)

WJR: Writing, Passage Composition WISC-III Digit Span CPT: Overall Index, Hits Percentile, Hits Reaction Time, Omissions Percentile, Commissions TScore

Outcomes with effect sizes ⬎ 0.2a,b

Note. ALL ⫽ acute lymphoblastic leukemia; C ⫽ control group; CBCL ⫽ Child Behavior Checklist; CPRS ⫽ Conners’ Parent Rating Scale; CPT ⫽ Conners’ Continuous Performance Test; CTRS:LV-R ⫽ Conners’ Teacher Rating Scale: Long Version-Revised; CVLT-C ⫽ The California Verbal Learning Test for Children; F/U ⫽ follow-up; MVPT-3 ⫽ Motor Free Test of Visual Perception 3rd Edition; DKEFS ⫽ Delis Kaplin Executive System; RCT ⫽ randomized controlled trial; T ⫽ treatment group; WISC ⫽ Wechsler Intelligence Scale for Children; WJ ⫽ Woodcock-Johnson; WJR ⫽ Woodcock Johnson Test of Achievement-Revised; WRAT-R ⫽ Wide Range Achievement Test-Revised; WRAML2 ⫽ Wide Range Assessment of Memory and Learning, 2nd ed. a Effect sizes in bold have significant confidence intervals at p ⬍ .05. b Unless otherwise specified, all outcomes are based on survivor self-report data. c This intervention is also described in Table 3 as a psychosocial intervention.

Daily problem solving, attention, memory, and academic performance


Patel et al. (2009)c (Cognitive and problemsolving training)

Study

Table 2 (continued)



Social competence

Social competence

Barrera & Schulte (2009) (Group social skills intervention program)


Barakat et al. (2003) (Social skills training group)

Study

Table 3 Description of Psychosocial Interventions Study design

Group sessions centered around six specific social skills; education; modeling; role-plays; fun activities and games; sessions were informed by cognitive behavior strategies as well as music, art, and drama therapy (Eight sessions over 8 weeks – face-toface)

One group time series design

Uncontrolled trials Separate parent and child groups; child One group intervention included discussions, pretest/posttest modeling, and guided role-plays; homework to practice a specific social skill was assigned each week; emphasis was placed on skills that would help survivors improve their friendships and minimize their isolation; parent intervention included information, problem solving, and discussion (Six sessions – face-to-face)


T: 32 F/U: 0 months

T: 18 F/U: 9–10 months

N/First F/U


Age range: 8–18 years Cancer type: 100% brain tumor



CBCL: Internalizing, Externalizing, Total Competence (parent report) SSRS: Problem Behaviors (teacher and parent report), Social Skills (parent and survivor report) TRF: Externalizing, Internalizing (teacher report) YSR Internalizing, Externalizing, and Total Competence CBCL: Social competence, Social problems (parent report) PedsQL (survivor and parent report) SSRS: Self-control, Total (parent report) YSR: Externalizing, Social problems (survivor report) (table continues)



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Information-seeking behavior, relaxation, social competence, positive thinking

Social competence

Psychological well-being


Patel et al. (2009)e (Cognitive and problem solving training)

Schwartz et al. (1999) (Moving On program)

Study


Maurice-Stam et al. (2009) (OK Onco)

Study

Table 3 (continued)

One-on-one problem-solving skills training in the context of social difficulties; problems the survivor experienced in the past week were discussed and the interventionist helped the participants apply a standardized step-by-step problemsolving procedure to the issue; parents were asked to review skills at home and positively reinforce (7–15 sessions – face-to-face) Group-based intervention with focus on psychosocial support, education, and recreation; intervention intended to enhance self-esteem through physical and interpersonal group activities, to help survivors establish a social network of other survivors, and to allow survivors the chance to incorporate their cancer story into their identity (3 consecutive days – face-to-face) Controlled trials Intervention description

Group-based cognitive behavioral intervention; intervention includes modeling, contingency management, exposure exercises, and cognitive reframing; intervention goals included improving participants’ abilities to seek out information regarding their health, learning relaxation, and improving social competence and positive thinking (Six sessions – face-to-face)


Study design




Study design

N/First F/U

T: 22 F/U: 0 months

T: 15 F/U: 0 months

T: 11 F/U: 0–4 weeks

N/First F/U



Global Quality of Life Ryff: Personal growth, Positive relations with others, Purposes in life, Self-acceptance SF-12 Physical functioning


Age range: 18–29 years Cancer type: 41% acute lymphocytic leukemia, 14% brain tumor, 45% other


Age range: 8–12 (Effect sizes not years available)d Cancer type: 40% ALL, 20% Wilms tumor, 10% acute myeloid leukemia, 10% Burkitt lymphoma, 10% rhabdomyosarcoma, 10% brain tumor Age range: 7–19 CBCL: years Externalizing, Cancer type: 75% Internalizing brain tumor, (parent report) 17% leukemia, SSRS Total 8% CNS histiocytosis



Posttraumatic stress

Posttraumatic stress, anxiety, benefit finding, health promotion behavior

Kazak et al. (2004) (Surviving Cancer Competently Intervention Program)

Santacroce et al. (2010) (Coping skills training)

Group sessions aimed at enhancing coping skills; two sessions focused on reducing distress using cognitive behavioral techniques (identifying bothersome memories related to the cancer experience and learning how to use self-talk to reframe experiences); two sessions based on family therapy approaches (family group discussions about how cancer has affected the family) (Four sessions in one day – face-toface) One-on-one anxiety coping-skills training including relaxation, cognitive reframing, managing uncertainty through self-talk, communication skills, and problemsolving skills; parents of participants also received individual counseling (Seven sessions – via telephone)

One-on-one cognitive and behavioral techniques including changing dysfunctional cognitive schema, reinforcement strategies, relaxation training, modeling, shaping, prompting, fading, and systematic desensitization; tailored to participant’s age; psychoeducational sessions for parents



RCT (C: wait list)

QE (C: Intervention refusers, standard care) (Sessions number varied; over 4to 8-month period – faceto-face)

Study design

T: 9 C: 11 F/U: 4 weeks

T: 76 C: 74 F/U: 3–5 months

T: 17 C: 23 F/U: 4–8 months

N/First F/U

Age (M [SD]): 21.0 (3.7) years Cancer type: 29% leukemia, 19% lymphoma, 10% central nervous system tumor, 42% other solid tumor

Age range: 10–19 years Cancer type: 31% leukemia, 23% solid tumors, 23% lymphoma, 24% other



(Effect sizes not calculable)f

CBCL: Attention problems, Externalizing, Internalizing, Social Problems, Somatic complaints, Total Problems, Withdrawn (parent report) VABS Social skills (parent report) IES-R: Arousal, Intrusion PTSD-RI: Posttraumatic stress


Note. C ⫽ control group; CBCL ⫽ Child Behavior Checklist; CNS ⫽ central nervous system; F/U ⫽ follow-up; GTUS ⫽ Growth Through Uncertainty Scale; IES-R ⫽ Impact of Events Scale-Revised; PCP ⫽ Primary care physician; PTGI ⫽ Posttraumatic Growth Inventory; PTSD-RI ⫽ Posttraumatic Stress Disorder Reaction Index; QE ⫽ quasi-experimental; RCT ⫽ randomized controlled trial; SSRS ⫽ Social-Skills Rating System; T ⫽ treatment group; TRF ⫽ Teacher Report Form; YSR ⫽ Youth Self-Report; VABS ⫽ Vineland Adaptive Behavior Scales. a If age range was not available, the mean and standard deviation were provided instead. b Effect sizes in bold have significant confidence intervals at p ⬍ .05. c Unless otherwise specified, all outcomes are based on survivor self-report data. d Children showed trends of improvement in social competence and positive thinking; however, data was not available to calculate effect sizes. e This intervention is also described in Table 2 as a neurocognitive intervention. f Participants showed trends of improvement in survivors’ benefit finding, posttraumatic stress, uncertainty levels, anxiety, and health-promotion behaviors compared with controls; however, data was not available to calculate effect sizes.

Behavioral and social problems


Poggi et al. (2009) (Psychological intervention for brain tumor survivors)

Study

Table 3 (continued)



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with overlapping investigators (Absolom, Eiser, Greco, & Davies, 2004; Eiser, Hill, & Blacklay, 2000), used information booklets to target improved health awareness, attitude to follow-up care, and stages of change for health behaviors. Notably, only two of the 10 health-behavior interventions included children under the age of 10 (Gilliam et al., 2011; Li, Chung, Ho, Chui, & Lopez, 2013). Additionally, many of these interventions recruited survivors into the same study who had been diagnosed at very different stages of their lives. For example, Hollen and colleagues (2013) recruited survivors who had been diagnosed with cancer anywhere from 0 to 14 years. The seven interventions addressing cognitive late effects employed a variety of approaches. Three aimed to improve working memory and attention, in addition to other secondary outcomes, through programs that survivors accessed through their personal computers (Hardy, Willard, Allen, & Bonner, 2013; Hardy, Willard, & Bonner, 2011; Kesler, Lacayo, & Jo, 2011). Butler and colleagues (2008) combined interventions from brain injury rehabilitation, education, and cognitive– behavioral therapy in a three-pronged approach of massed attentional exercises, learning strategies, and cognitive counseling to improve attention. Patel, Katz, Richardson, Rimmer, and Kilian (2009) emphasized improving cognitive functioning in the broader context of everyday problem solving, including social interactions, and helping children improve their study and memory skills. Anderson, Godber, Smibert, Weiskop, and Ekert (2000) examined whether survivors showed improvements in academic and intellectual functioning after receiving tailored feedback about their abilities. Finally, Kanitz and colleagues (2013) took an approach rooted in holistic medicine and tested whether eurythmy therapy, which focuses on movement and meditative practices, could improve intellectual functioning, neuromotor competence, and visuomotor integration. Participants across all neurocognitive interventions were between the ages of 6 and 19. For the majority of studies, participants had been diagnosed with either acute lymphoblastic leukemia or a brain tumor. The gender ratio was typically split evenly.

Methodological Quality Results of the EPHPP coding— categorized as weak, moderate, or strong—are summarized in Table 4. A substantial portion (29.2%) of interventions was coded as weak for selection bias. This is mainly driven by the fact that, during recruitment, these studies achieved less than 60% agreement to participate, which automatically placed them in the lowest quality category. This is unsurprising, given that recruitment is a well-documented challenge in psychosocial research among childhood cancer survivors. Many studies that achieved a moderate ranking identified participants through referrals from doctors’ offices or survivor clinics as opposed to studies with strong rankings that accessed more comprehensive lists of survivors, such as tumor registries (Kazak et al., 2004) or epidemiological databases (Emmons et al., 2005), which more accurately reflect the target population. For the study design category, 41.7% of the studies were rated as strong for being randomized controlled trials. Most of the remaining studies were graded as moderate for having one group pre–post designs. The confounders section had overall high ratings; for most controlled trials, either there were no identified differences between the treatment and control group or confounds that were identified were controlled for in analyses. A substantial portion (29.2%) of studies were rated as weak for data collection methods because they

Table 4 Methodological Quality Quality category

Weak

Moderate

Strong

Selection bias Study design Confoundersa Data collection methods Withdrawals and drop-outs

29.2% 0% 18.2% 29.2% 12.5%

58.3% 58.3% 0% 0% 29.2%

12.5% 41.7% 81.8% 70.8% 58.3%

Blinding Fidelity measurement

Yes

No

Not relevant

16.7% 20.8%

20.8% 54.2%

62.5%b 25.0%c

a Confounders were not assessed for one-group studies. b Interventions that used a one-group design, or that did not require staff to interact with participants when collecting outcome assessments, were considered irrelevant for blinding. c Interventions that did not involve an interventionist (but rather consisted of booklets, information sheets, or computer programs) were considered irrelevant for fidelity measurement.

had used study-specific measures that were not thoroughly validated. Study completion rates were equal to or greater than 80% for over half the studies, but 29.2% of studies only achieved completion rates between 60% and 79%. The wide range of completion rates may be partially explained by the wide range of initial follow-up periods among studies, which spanned from immediately after the intervention to 12 months postintervention. For 44% of controlled trials in which outcome measures were test data or surveys administered by phone, studies reported that outcome assessors were blind to participant group. Finally, the majority of studies did not report fidelity measurement. Though most studies did mention supervision of interventionists, only a small portion of these noted that they had systematically measured the integrity of the intervention.

Intervention Efficacy and Characteristics of Trials With the Largest Effect Sizes For studies with continuous outcomes that did not provide means and standard deviations for postintervention data, effect sizes were not possible to calculate. When multiple follow-up points were provided, the one closest to the end of the intervention was selected for effect size analysis. Exact effect size values and their confidence intervals are provided in Appendix C of the online supplemental materials. Of the nine controlled trials for which effect sizes could be calculated, seven achieved medium to large effect sizes for at least one outcome (four of which were health behavior interventions, two were neurocognitive interventions, and one was a psychosocial intervention).2 Seven of the 10 uncontrolled trials with calculable effect sizes also achieved medium to large effect sizes (one health behavior 2 The cutoff for a medium effect size for continuous measures was 0.5 (Cohen, 1988). The Partnership for Health Study (Emmons et al., 2005) had a dichotomous outcome and was judged to have a medium to large effect size (odds ratio [OR] ⫽ 1.99, 95% confidence interval [CI] [1.27, 3.14]). This judgment was made based on a previous meta-analysis of behavioral smoking cessation interventions, which found an aggregated effect size that was lower (OR ⫽ 1.58, 95% Cl [1.15, 2.29]; Mottillo et al., 2009). Additionally, because smoking has such a severe impact on health, an odds ratio indicating double the chance of quitting suggests the intervention was quite impactful.


intervention, three neurocognitive interventions, and three psychosocial interventions). No study characteristic, such as a particular delivery mode or method, appeared to be associated with higher efficacy for either controlled or uncontrolled trials. However, because of the small sample size of studies, it was not possible to answer this question using inferential statistics.


Survivor Willingness to Engage in Interventions Average consent rates by intervention characteristic are summarized in Table 5. As randomized trials may be less appealing to potential participants because they risk being assigned to the control group, RCTs were separated from nonrandomized trials. As the sample size of studies in this review is small, it was not possible to make statistical comparisons of consent-rate levels. Rather, general patterns of the consent rates are noted. Unsurprisingly, interventions that did not require participants to make extra trips to receive the intervention (the intervention was incorporated into a routine medical visit, took place over the phone, home-based computer program, etc.) tended to have higher consent rates (especially for nonrandomized studies). Health behavior and neurocognitive interventions compared with social skill and psychological interventions appeared to attract the most interest. This may be partly related to the fact that a large number of these interventions did not require extra travel time from participants. Interventions that required family participation had lower consent rates for randomized trials, perhaps because of the extra demands of time, difficulty finding child care for younger siblings, and more complex scheduling coordination required by family interventions. Individual-based interventions were preferred to group-based interventions; however, this may be explained by the

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fact that many one-on-one interventions required no extra travel, whereas almost all group interventions did. Study designs that included randomization did not appear to have considerably lower consent rates than nonrandomized trials. Randomization, therefore, was not a major deterrent for participating in intervention trials (alternatively, the appeal of interventions in RCTs may have outweighed any perceived costs of randomization.) These comparisons, however, must be interpreted cautiously, as other factors may have influenced participation rates, such as the number of assessments that participants were asked to complete.

Discussion A total of 24 interventions targeting health-behavior, neurocognitive, and psychosocial outcomes were identified. Fourteen achieved significant, medium to large effect sizes for various targets: health outcomes, including bone and sun safety behaviors, knowledge of tobacco-related risks, physical activity, smoking cessation, and attitude to coming to clinic; neurocognitive outcomes, including working memory, attention, and processing speed; and psychosocial outcomes, including internalizing and externalizing problems, social skills, and quality of life. No specific intervention characteristics (such as method or mode of delivery) appeared to be associated with superior effect sizes. Among both controlled and uncontrolled trials, a diverse array of intervention modalities and delivery methods produced promising results, suggesting that replications are warranted. Of note, some interventions achieved medium to large effect sizes and had characteristics that are potentially cost-saving, less burdensome, and more amenable to dissemination (e.g., one-session interventions, group treatments, Internet-based exercises, or

Table 5 Average Consent Rates Randomized studies Intervention characteristic Intervention focus Psychological Social skillsa Health behaviors Neurocognitivea Delivery method In-person Phone In-person and phone follow-up Written documents Home-basedb Delivery mode Individual Group Family involvement Yes No Travel Extra travel required No extra travel required

Nonrandomized studies

Mean

Mdn

SD

Mean

Mdn

SD

45.5% — 78.2% 91.0%

45.5% — 86.0% 91.0%

0.7% — 16.4% 4.2%

58.0% 55.3% 80.0% 65.5%

58.0% 54.5% 86.0% 65.5%

53.7% 23.3% 11.3% 48.8%

68.8% 64.5% 86.3% — 80.0%

68.0% 64.5% 86.3% — 80.0%

25.3% 26.2% 0.4% — NA

63.0% — — 86.6% —

66.0% — — 86.6% —

29.7% — — 0.8% —

80.6% 60.3%

86.3% 49.0%

17.3% 23.2%

75.7% 55.8%

84.5% 53.5%

24.3% 32.5%

45.5% 81.9%

45.5% 86.5%

0.7% 14.9%

64.0% 70.2%

62.5% 76.5%

32.8% 27.4%

68.8% 77.9%

68.0% 86.0%

25.3% 17.9%

63.0% 86.6%

66.0% 86.6%

29.7% 0.8%

Note. Five studies were not included because they did not provide data about consent rates. Mdn ⫽ median; NA ⫽ not applicable; SD ⫽ standard deviation. a One of these studies includes both neurocognitive and social skills outcomes. b There was only one study in this category that described a consent rate; therefore, a standard deviation was not calculated.


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telephone-delivered counseling). In a qualitative study assessing intervention format and delivery preferences, young adult survivors emphasized the need for convenience and accessibility through the phone, web, or e-mail (Rabin, Simpson, Morrow, & Pinto, 2013). Telephone counseling offers the advantage of eliminating travel burden while still maintaining the benefit of human interaction and social support. Substantial empirical evidence exists for its efficacy in relation to health and psychosocial outcomes among other health-compromised populations (e.g., Dorstyn, Mathias, & Denson, 2011; Muller & Yardley, 2011). Comparing interventions to identify elements that may have been associated with greater efficacy was difficult because of small samples, varying outcomes and follow-up periods, and study design differences. Additionally, a very limited degree of process analysis was conducted, thereby limiting the ability to draw conclusions about potential mechanisms of change in trials that were effective. Analysis of efficacy was also challenged by the failure of most studies to report clinically significant change (Barakat et al., 2003, is an exception). Though calculating effect sizes was possible for most studies, effect sizes do not provide sufficient information for understanding how many participants changed to a noticeable, meaningful degree (Chambless & Hollon, 2012). Stipulating what counts as clinically significant change is challenging because many of the studies used new outcome measures without population norms or clinical cutoffs (Velicer, Rossi, Prochaska, & Diclemente, 1996). Furthermore, some behavioral interventions measured behaviors on a Likert-type scale (e.g., never to always). To facilitate interpretation of clinically meaningful change, behavior measures should rather capture the exact frequency of the behavior so that meaningful cutoffs can be established that stipulate the behavior frequency needed to prevent or cause a negative health outcome. There are some potentially important interventions that are notably absent. One is interventions that facilitate the transition of survivors from pediatric to adult-oriented care. This is a clinically relevant area, with various approaches employed but little evaluation (Pai & Schwartz, 2011). Another is school reentry: Although collaborations with schools are already widely recognized as important in promoting academic potential and social and peer relationships (Tesauro, Rowland, & Lustig, 2002), there is a need for more research on optimal approaches for helping young survivors transition back to the classroom.

Limitations A number of potentially informative studies were excluded from this review because their participant pool was not exclusively composed of survivors (e.g., Bingen & Kupst, 2010; Rabin, Dunsiger, Ness, & Marcus, 2011). Another subset of interventions that were not included reported only qualitative outcomes (e.g., Elad, Yagil, Cohen, & Meller, 2003; Zebrack, Oeffinger, Hou, & Kaplan, 2006). Interventions that are currently in development or have been tested, but did not yet have published outcomes at the time of the database search, were also excluded (e.g., Casillas, 2011; Sansom-Daly et al., 2012). Additionally, there may be relevant studies that are not represented in this review because they were not published because of null effects. This is especially a concern in this field, in which small samples are frequently used and trials are therefore prone to being underpowered.

Future Directions The average age of participants in the studies was rather narrow and clustered around either early adolescence (13 to 15 years) or the 30s. Notably absent were health behavior interventions designed for survivors in middle childhood (8 to 12 years) and late adolescence. In middle childhood, survivors are less likely to have well-ingrained health habits, and therefore the impact of preventative health interventions may have greater payoff than interventions aimed at those who have developed health-threatening lifestyles. This may involve intervening at a family level, especially for health behaviors such as diet, which is highly influenced by parent behaviors. Attention to health behaviors is also very important for older adolescents, for whom the temptations of alcohol and drug abuse are highest. Almost half of full-time college students engage in abuse of illegal drugs, prescription drugs, and/or alcohol (Casa, 2007), and survivors exhibit only slightly less risky behavior than peers (Lown et al., 2008). Additionally, many collegeaged adolescents may be living away from home, and may benefit from education and guidance related to management of their diet, physical activity, and sleep. To maximize what can be gained from intervention research with childhood cancer survivors, more work is needed at the preintervention stage. Measure development should be a main priority. Many health behavior interventions piloted measures that were created specifically for that study. The extent to which these measures may be sensitive to capture meaningful change is unknown. Additionally, for the health behavior interventions, the majority of studies relied exclusively on self-report. Unfortunately, recall of health behaviors has been shown to be prone to bias (Shiffman et al., 1997). Other methods of measurement, such as ecological momentary assessment, could be considered (Berkman, Dickenson, Falk, & Lieberman, 2011). The bogus pipeline procedure (used by Emmons and colleagues, 2005, in a smoking cessation intervention covered in this review) is also a potentially effective way to reduce response bias. Some methods of intervention delivery, such as the Internet, are worth further exploration. Oeffinger and colleagues (2011) saw fairly low use of their website in their surveillance intervention (only 29% of participants accessed it); however, it was not a central aspect of the intervention. Kesler and colleagues (2011) found promising results with an online cognitive rehabilitation program, but it was only tested in an uncontrolled trial. Other Internet interventions were not eligible for this review (e.g., Cantrell & Conte, 2008; de Moor et al., 2011). Results for webbased interventions are mixed, and feasibility is not yet clear. SMS text messages can also be used and sent to participants’ phones, allowing for the delivery of individually tailored interventions at minimal cost (Fjeldsoe, Marshall, & Miller, 2009). Randomized clinical trials with other populations have shown that text-message interventions improve physical activity and smoking cessation rates (Obermayer, Riley, Asif, & Jean-Mary, 2004; Rodgers et al., 2005). Mobile phone software applications are also a promising avenue for testing, given their already popular use among the general public for tracking health behaviors (Fox & Duggan, 2012; Luxton, McCann, Bush, Mishkind, & Reger, 2011). Finally, tailoring of interventions merits further investigation. Ryan and Lauver (2002) found that tailored health behavior interventions were either equivalent or superior in efficacy to standard-



ized informational interventions. Tailored interventions in this review were customized to participants’ treatment history, stage of readiness to change, exercise ability, age, cognitive flexibility, or individual health goals. Other survivor characteristics around which interventions can be tailored may be worth studying. Survivor characteristics that have been found to be associated with psychosocial outcomes are possibilities (e.g., perceived barriers to healthy living [Arroyave et al., 2008], health competence beliefs [Kazak et al., 2010; Brier et al., 2011]). Many studies covered in this review recruited participants who had been diagnosed with cancer at varying developmental phases of childhood, and therefore the content of the intervention was not explicitly tailored to the age of diagnosis. For some intervention targets, however, this may be a very important consideration. The development period in which the survivor was diagnosed influences how that event was encoded and appraised (Salmon & Bryant, 2002), and interventions targeting posttraumatic stress symptoms, for example, may therefore be more effective if tailored accordingly.

Conclusion A number of interventions for survivors of childhood cancer have yielded promising results. For future investigations, improving outcome measures will help further clarify the significance of treatment effects. More experimentation with different treatment delivery methods is important for identifying efficacious interventions that are cost-effective, relatively easy to disseminate, and can reach a geographically diverse set of survivors. As more interventions are developed, close attention must be paid to ensuring that survivors of certain developmental stages or age groups are not neglected.

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Received March 11, 2013 Revision received March 13, 2014 Accepted May 8, 2014 䡲

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