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Article

Characterization of Patient Activation among Childhood Cancer Survivors in the St. Jude Lifetime Cohort Study (SJLIFE)

by
Megan E. Ware
1,2,*,
Angelica De La Cruz
3,
Qian Dong
1,
Kyla Shelton
1,
Tara M. Brinkman
4,
I-Chan Huang
1,
Rachel Webster
4,
Brian Potter
4,
Kevin Krull
4,
Sedigheh Mirzaei
5,
Matthew Ehrhardt
1,
Melissa M. Hudson
1,6,
Gregory Armstrong
1 and
Kirsten Ness
1
1
Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
2
Department of Kinesiology, Health Promotion, and Recreation, University of North Texas, Denton, TX 76201, USA
3
Department of Biology, University of Puerto Rico—Rio Piedras Campus, San Juan, PR 00925, USA
4
Department of Psychology and Biobehavioral Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
5
Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
6
Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(18), 3220; https://doi.org/10.3390/cancers16183220
Submission received: 9 August 2024 / Revised: 12 September 2024 / Accepted: 19 September 2024 / Published: 21 September 2024
(This article belongs to the Special Issue Quality of Life and Management of Pediatric Cancer)
Browse Figure
Versions Notes

Abstract

:

Simple Summary

Patient activation is a very important psychological construct to examine in individuals who have chronic conditions, because it assesses the one’s confidence in managing their own health and care. For childhood cancer survivors, continued follow-up is imperative to monitor late effects conditions; yet many do not adhere to surveillance guidelines. Therefore, investigating this construct could highlight risk factors in the population that contribute to low activation. Furthermore, examining the long-term impact of patient activation on psychological health as well as its contribution to health behavior could provide a reasonable target for interventions to enhance health outcomes in survivors.

Abstract

Background: Patient activation describes a willingness to take action to manage health and is associated with health outcomes. The purpose of this study was to characterize patient activation and its association with psychological outcomes and health behaviors in childhood cancer survivors. Methods: Participants were from the St. Jude Lifetime Cohort Study (SJLIFE). Activation levels (1–4, 4 = highest activation) were measured with the Patient Activation Measure (PAM). Psychological outcomes and health behaviors were obtained via self-report. Cognitive function was assessed by trained examiners. ANOVA or chi-squared tests were utilized to assess group-level differences in activation. Multivariable regression models were used to assess associations between PAM scores and outcomes of interest. Results: Among 2708 survivors and 303 controls, more survivors endorsed lower activation levels than the controls (11.3 vs. 4.7% in level 1) and fewer survivors endorsed the highest level of activation than the controls (45.3 vs. 61.5% in level 4). Not endorsing depression (OR: 2.37, 95% CI 1.87–2.99), anxiety (OR: 2.21, 95% CI 1.73–2.83), and somatization symptoms (OR: 1.99, 95% CI 1.59–2.50), general fear (OR: 1.45, 95% CI 1.23–1.71) and body-focused (OR: 2.21, 95% CI 1.83–2.66), cancer-related worry, and physical (OR: 2.57, 95% CI 2.06–3.20) and mental (OR: 2.08, 95% CI 1.72–2.52) HRQOL was associated with higher levels of activation. Lower activation was associated with not meeting physical activity guidelines (OR: 2.07, 95% CI 1.53–2.80). Conclusions: Survivors endorsed lower activation levels than peers. Interventions to improve physical and psychological health outcomes could leverage these results to identify survivors who benefit from support in patient activation.

1. Introduction

Childhood cancer survival rates have increased in recent decades due to a better understanding of cancer biology, improvements in diagnostic technology, and the development of effective, risk-stratified treatment strategies [1,2]. However, treatment has lasting impacts, and survivors face continued challenges to their health as late effects (health complications that develop after cancer treatment has ended) develop and progress throughout survivorship; some of these late effects include conditions such as congestive heart failure, coronary artery disease, stroke, renal failure, and second malignant neoplasms [3,4]. These late effects have serious implications for survivors’ long-term health and mortality [5,6] as well as psychological well-being and quality of life [7,8]. Data suggest that engaging in optimal health behaviors, such as engaging in physical activity and refraining from smoking, risky drinking, and illicit drug use, decreases the risk of adverse health outcomes [9,10] and improves psychological well-being and quality of life [11]. Survivors do not always engage in healthy behaviors, even when provided with an adequate education to understand the future risk of poor engagement [12,13,14]. The reasons for a lack of engagement are likely multiple. However, one reason may be that they lack the skills and confidence to manage their own health and healthcare. If this is the case, care models need to be developed to provide survivors with these skills.
Patient activation is defined as the “skills and confidence a person has in managing their own health and health care” [15], which focuses on a patient’s “willingness and ability to take independent actions to manage their health and care” [16]. This is incredibly important, as patient involvement has been linked to improved health outcomes and improved outcomes of healthcare in patients who are more involved in their care [15,16,17,18,19]. However, survivors face challenges as they transition from pediatric or adolescent care to adult care; a retrospective study of 370 survivors (median age at diagnosis 10.2 years (range 1–21 years) found the probability of continued engagement in long-term follow-up 6 to 10 years from treatment completion to be 68.5%, dropping to 47.7% by years 11 to 15 [20]. One potential framework with which to examine this decline is outlined in the Life Course Health Development (LCHD) framework, in which it is posited that biopsychosocial influences affect an individual’s health trajectories in different manners across the lifespan [21]. In line with the LCHD, a survivor’s cancer-specific or individual challenges could be further exacerbated by socioeconomic status, health behaviors, and familial or other close relationships in different ways across the lifespan [22]. In combination, these factors could contribute to lower levels of activation, but could also be exacerbated by lower levels of activation, leading to poor health outcomes in survivors.
Associations between patient activation, health behaviors, and psychological outcomes have not been explored in a large cohort of childhood cancer survivors. Understanding the risk factors among survivors for low activation, and the potential contribution of patient activation to health behaviors and psychological outcomes will provide insight for the design of interventions to promote optimal health behaviors among survivors. Therefore, the aim of this study is to characterize patient activation in the St. Jude Lifetime Cohort Study (SJLIFE) and to identify the associations between, as follows: (1) patient activation and health behaviors; and (2) psychological factors and patient activation to identify factors associated with low activation.

2. Materials and Methods

2.1. Participants

Participants in this study were enrolled in the St. Jude Lifetime Cohort Study (SJLIFE) [23,24], a study that includes childhood cancer survivors treated at St. Jude Children’s Research Hospital between 1962 and 2012, who were at least 5 years from their primary cancer diagnosis, and at least 18 years of age at assessment. A comparison group comprised of a community who did not have childhood cancer was also included to assess differences in patient activation level between otherwise healthy adults and survivors. Eligible participants for this analysis were members of the cohort who completed survey assessments at a single cross-sectional timepoint. Study measures and documents were approved by the SJCRH Institutional Review Board.Participants provided written informed consent prior to study activities.

2.2. Measures

2.2.1. Patient Activation

Patient activation was measured using the short-form Patient Activation Measure (PAM) [18]. The short form of the PAM is a 13-item measure instructing participants to report personal levels of agreement or disagreement with statements related to knowledge, skill, and confidence for self-managing their own health and healthcare. Responses to items are Likert-scored on a 0 to 4 scale, with 0 indicating “disagree strongly”, 1 indicating “disagree”, 2 indicating “agree”, 3 indicating “agree strongly”, and 4 indicating “not applicable” [18]. PAM short-form raw scores are calculated as follows: total score = [raw score]/[number of items answered excepting “non applicable” items] × 13. Raw scores are converted to four activation levels [25]: Level 1 (Score 0.0–47.0)—“People are passive and feel overwhelmed about managing their health. They may be unprepared to take an active role”; Level 2 (Score 47.1–55.1)—“People may lack specific knowledge and confidence to self-manage their health”; Level 3—(Score 55.2–67.0) “People are beginning to take action but may lack the confidence and skill to sustain the activity”; Level 4 (Score 67.1–100.0)—“People have adopted behaviors to support their health, but may not be able to maintain them over time when they are facing life stressors” [26].

2.2.2. Psychological Factors

Anxiety, somatization, and depression symptoms were assessed using the Brief Symptom Inventory (BSI-18) [27]. T-scores were created for each participant, with scores ≥ 63 (top 10th percentile) classified as elevated anxiety, somatization, and depression symptoms [28]. Physical and mental-health-related quality of life (HRQOL) were assessed using the 8 subscales measuring general health, physical function, role limitations caused by physical factors, bodily pain, social function, mental health, role limitations caused by emotional factors, and vitality from the Short-Form Health Survey (SF-36) [29]. T-scores were created for each participant, with scores ≤ 40 representing poor HRQOL.
Cancer-related worry (CRW) was assessed via self-report using six questionnaire items: (1) “I have general fears about cancer”, (2) “I am worried about my cancer coming back”, (3) “I mostly worry about my cancer and its treatment right before I go for a check-up”, (4) “I am concerned about physical problems related to my cancer”, (5) “I am worried about my appearance”, and (6) “Do you currently have anxieties/fears as a result of your cancer or similar illness, or it’s treatment?”. Factor analysis was employed to create two independent CRW factors, as follows: body-focused and general fear. The averages of respective items were calculated to create factor scores, which were categorized as <3 (not endorsing CRW) and ≥3 (endorsing CRW) [30].

2.2.3. Health Behavior

Physical activity (PA) was assessed by self-report of the frequency and amount of moderate to vigorous intensity PA per week. Self-report values were then categorized into meeting or not meeting Centers for Disease Control and Prevention (CDC) PA guidelines of 150 min of moderate or 75 min of vigorous PA per week [31]. Smoking status was captured via self-report, with those endorsing current smoking (within the past 30 days) being categorized as smokers. Heavy or risky drinking was captured via self-report and categorized into endorsing or not endorsing the behavior according to the National Institute on Alcohol Abuse and Alcoholism (NIAAA) criteria for risky drinking (>3 per day or >7 per week (females) >4 per day or >14 per week (males)). Diet quality was assessed via the Healthy Eating Index (HEI) [25]. HEI scores were categorized into <51 (poor diet), 50–80 (needs improvement), and >80 (good). Sleep quality was assessed using the PROMIS Sleep Disturbance, 8a [27]. T-scores were calculated for the sample, and then categorized into <25 (none to slight), 25> and ≤30 (mild), and >30 (moderate to severe).

2.2.4. Sociodemographic and Clinical Covariates

Personal sociodemographic data were self-reported and included sex, gender, self-identified race/ethnicity, age at assessment, insurance status (uninsured vs. insured), and educational attainment (high school or less, some post-high school, college degree or higher). Neighborhood-level socioeconomic status was assessed using the Area Deprivation Index (ADI), which is a composite measure derived from American Community Survey components reflective of 17 neighborhood-level SES measures within US Census blocks [32]. Each block was assigned a percentile and quartiles were created, with lower quartiles representing higher socioeconomic disadvantage. Clinical data were abstracted from medical records and included age at diagnosis and primary diagnosis. Chronic condition presence and severity was assessed for each participant utilizing the Common Terminology Criteria for Adverse Events (CTCAE) [33] grading of 13 organ systems. Those with grades of 3 or more in any of the systems were considered as having a condition within the respective system. Perceived instrumental support was assessed using the PROMIS Instrumental Support, 6a [34]. T-scores were calculated for each participant.

2.2.5. Cognitive Function Assessments

Testing of intelligence [35], executive functioning [36], attention [37], processing speed [36,38], and memory [39] were completed in standardized order and administered by certified examiners under the supervision of a board-certified clinical neuropsychologist. Scores were referenced to national normative sample data to generate age-adjusted Z scores, with mild impairment representing more than −1.5 to −1.0, moderate impairment representing more than −2.0 to −1.5, or severe impairment representing −2.0 or less [40]. Only intelligence was selected as an eligible covariate for analysis.

2.3. Analyses

Descriptive statistics were calculated to characterize the sample. Distributions of activation level across both survivors and controls were compared using the chi-squared test. Further analyses focused on the distribution of activation level across demographic and clinical factors in survivors only and were performed using chi-squared or AVOVA tests. Multivariable logistic regression models, adjusted for demographic and clinical covariates, were used to assess the associations between patient activation and health behaviors in survivors only; multivariable ordinal logistic regression models were used to assess the associations between psychological factors and patient activation in survivors only. Covariates with p < 10 in univariate analyses were selected for the multivariable models. Patient activation levels, age at patient activation assessment, age at diagnosis, sex, primary cancer diagnosis, and educational attainment were retained in all models. Categorical variables indicating patient activation level were utilized in analyses. All analyses were completed in SAS (SAS 9.4, Cary, NC, USA).

3. Results

A total of 2708 survivors and 303 controls were eligible for analysis. Those with insufficient data (did not provide responses for survey assessments), survivors with a non-cancer primary diagnosis, and controls with a prior cancer history, were excluded from analyses (Figure 1). Survivors differed from controls on distributions of sex (50.6 vs. 41.6% male), race/ethnicity (82.0 vs. 80.2% non-Hispanic White), educational attainment (40.9 vs. 58.2% college degree or higher), and ADI quartile (23.3 vs. 36.3% quartile 1). Survivors also differed from the controls with respect to the presence of cardiovascular (8.6 vs. 1.7%), endocrine (37.5 vs. 24.8%), auditory (12.8 vs. 2.0%), ocular (10.6 vs. 2.0%), neurological (5.8 vs. 3.0%), and sexual or reproductive conditions (10.0 vs. 1.0%). Survivors were, on average, older than the controls at survey (33.8 ±10.5 vs. 30.7 ± 9.8 years). The largest percentage of survivors was diagnosed with leukemia as a primary cancer (32.0%), followed by lymphoma (18.2%), CNS tumor (15.6%), sarcoma (13.2%), embryonal (12.4%), and other cancers (8.5%). Over half of the survivors received radiation (53.6%), chemotherapy (83.7%), and surgery (93.5%) during treatment (Table 1).
Survivors differed from the controls in distributions of patient activation, with a larger percentage of survivors endorsing lower levels of patient activation than the controls (11.3 vs. 4.7% in level 1 and 13.8 vs. 9.7% in level 2) and a larger percentage of the controls endorsing the highest level of patient activation than survivors (61.5 vs. 45.3%) (Table 1).Among survivors only, differences in patient activation were observed by diagnosis, where a larger percentage of those with a history of lymphoma or CNS tumors endorsed level 1 rather than level 4 activation (19.4 vs. 18.9% and 27.3 vs. 13.2%). A larger percentage of those treated with radiation reported level 1 rather than level 4 activation, compared to those who were not treated with radiation (60.2% vs. 50.8%). A larger percentage of survivors with cardiovascular, endocrine, immune, neurological, and auditory conditions endorsed level 1 patient activation rather than level 4 activation. Distributions of educational attainment, insurance coverage, and ADI quartile differed between patient activation levels, such that persons with a high school or lower attainment, who were uninsured, or who lived in ADI quartile 4 were more likely to endorse level 1 vs. level 4 patient activation (Table 2). Across cognitive function covariates, distributions of impairment differed between patient activation levels, such that a higher percentage of persons in the impaired function categories endorsed level 1 vs. level 4 patient activation (Table 3).
Survivors in levels 1 and 4 patient activation differed in distributions of health behaviors, such that those who endorsed currently smoking (18% vs. 12%), did not meet CDC PA guidelines (56% vs. 32%), and those who had poor diet quality (31% vs. 18%) were more likely to endorse level 1 vs. 4 patient activation (Table 4). The opposite trend was observed with respect to risky drinking, wherein a larger percentage of those who endorsed level 4 (vs. level 1) activation also reported risky drinking (37% vs. 23%). Moderate or severe sleep disturbance did not differ across patient activation levels (9.3% in level 1 vs. 9.8% in level 4, p = 0.42). Across all psychological factors, distributions of impairment differed by patient activation levels. The percentages of those who reported depression symptoms (28% vs. 7%), anxiety symptoms (24% vs. 7%), somatization symptoms (29% vs. 9%), general (42% vs. 29%) and body-focused (42% vs. 16%) CRW, and suboptimal physical (40% vs. 10%) and mental (40% vs. 15%) health-related quality of life were of a larger proportion for level 1 patient activation than for level 4 (Table 5).
Patient activation levels were not associated with risky drinking, smoking, diet quality, or sleep disturbance (Supplementary Tables S1–S4). However, in multivariable models adjusted for age at survey, age at diagnosis, race, educational attainment, gender, diagnosis, intelligence, and CTCAE grade 3+ cardiovascular, endocrine, auditory, hematological, neurological, pulmonary, and renal conditions, the endorsing of patient activation levels 3 vs. 1 (OR: 1.53, 95% CI: 1.13–2.09) or 4 vs. 1 (OR: 2.07, 95% CI: 1.53–2.80) was associated with meeting CDC PA guidelines (Table 6).
Multivariable ordinal logistic regression models assessing associations between psychological factors (respectively) and patient activation were adjusted for age at survey, age at diagnosis, race, educational attainment, gender, diagnosis, insurance status, perceived instrumental support, and CTCAE grade 3+ auditory, cardiovascular, endocrine, immunologic, neurological, and pulmonary conditions. Compared to those who endorsed symptoms of anxiety, depression, somatization, general fear CRW, and body-focused CRW, those who did not endorse symptoms of anxiety (OR: 2.21, 95% CI 1.73–2.83), depression (OR: 2.37, 95% CI 1.87–2.99), somatization (OR: 1.99, 95% CI 1.59–2.50), general fear (OR: 1.45, 95% CI 1.23–1.71) and body-focused (OR: 2.21, 95% CI 1.83–2.66) CRW, and physical (OR: 2.57, 95% CI 2.06–3.20) and mental (OR: 2.08, 95% CI 1.72–2.52) HRQOL had greater odds of endorsing higher levels of patient activation (Table 7).

4. Discussion

This study characterized patient activation, a construct related to more positive health outcomes, in a large sample of childhood cancer survivors. The study findings highlight demographic and clinical factors placing survivors at higher risk for low patient activation, such as a primary diagnosis of lymphoma and CNS tumor, receiving radiation therapy as part of treatment, and the presence of cardiovascular, endocrine, immune, neurological, and auditory chronic conditions. Additionally, social factors, such as lower educational attainment, a lack of insurance, and lower socioeconomic status, were identified as risk factors for low patient activation in this population. These data are essential for identifying survivors who may benefit from interventions to improve health outcomes, which is of concern because of this population’s vulnerability to adverse health outcomes. Using an LCHD lens, these results lend themselves to identifying how patient activation contributes to survivors’ health trajectories in a biopsychosocial context.
The extant literature demonstrates evidence of differing survival outcomes among diagnosis groups, which could be an underpinning of lower patient activation among certain diagnosis groups in the present study. Numerous studies have highlighted long-term functional, neurocognitive, and social outcomes of childhood CNS tumor survival, indicating that survivors of CNS tumors are at risk of not achieving independence as adults, neurocognitive impairment, and delayed or disrupted attainment of adult social milestones [41,42]. Additionally, there is evidence to indicate that survivors of lymphoma experience a similar risk of impaired neurocognitive function, which is associated with lower attainment of social milestones [43]. Neurocognitive impairment in both of these groups could lead to lower educational attainment and fewer downstream opportunities for socioeconomic attainment (i.e., employment, independent living, obtaining insurance coverage), all of which synergistically contribute to patient activation [44]. Unfortunately, because of the cross-sectional nature of the present study, no inference can be made with regard to the directionality of patient activation and psychological functioning; future studies should seek to address the causal nature of these associations. However, the present results could be utilized to identify survivors with psychological comorbidities who need more resources to manage self-health and care.
A novel finding in the present study is the association between ADI and patient activation, such that those in less desirable ADIs also reported lower patient activation. The direction of this association is as expected, sheds light on the potential role of SES or SES-related factors in the development of a survivors’ patient activation and is in line with some findings in the extant literature. In a study of prospective spine surgery patients, increased patient activation was associated with an annual income >$80,000 compared to <$30,000 (OR 1.72, 95% CI 1.18–2.50, p = 0.01), and reporting employment compared to not reporting employment (OR 1.37, 95% CI 1.03–1.84, p = 0.03) [45]. Similarly, a study conducted in the United States on a random sample of chronically ill adults found that employment (β = 3.11, p < 0.001) and an income >$75,000 (β = 2.22, p < 0.001) were associated with higher levels of patient activation compared to unemployment and an income of <$35,000 [46]. It is important to note, however, that in a sample of older adults, socioeconomic characteristics only explained 5–6% of the variations in patient activation scores [47]; therefore, further research should continue to examine other factors that could influence variations in patient activation measures beyond socioeconomic characteristics.
The investigation of health behaviors across patient activation levels was a novel aspect of the present study. While the frequencies of engagement in suboptimal health behaviors differed across patient activation levels in expected patterns, after adjustment for relevant covariates, associations were only seen between patient activation levels and PA. Similarly, in a study of patient activation in older adults with multimorbidity, the authors found positive associations between patient activation levels and PA (posterior probability: 0.847, Bayes factor: 5.54), and between patient activation level and medication adherence (posterior probability: 0.059, Bayes factor: 0.063) [48], but not between patient activation levels and either smoking or diet quality [48]. Similar observations were made in a sample of persons with atrial fibrillation; patients endorsing the highest level of patient activation also endorsed more physical activity than those endorsing the second highest level [49].
The associations between patient activation and physical activity and patient activation and psychological factors in multivariate analyses indicate that increased patient activation is linked to more optimal behavioral and psychological factors, even with adjustment for factors like SES. Within the context of LCHD, patient activation could be a potential protective psychosocial factor on a survivor’s health trajectory [22]. Therefore, maximizing patient activation could lead to better health outcomes in survivors. Commonly utilized strategies to address patient activation during interventions to improve health-related outcomes include problem solving, feedback, individualized care plans, peer support, health advisement, theory-based counseling, and skill-building [50]. One, or several of these types, of these strategies have been utilized in interventions delivered remotely [51,52,53,54,55], face-to-face [56,57,58], and in hybrid [59,60,61,62] models in various populations that experience chronic disease and/or disability, including childhood cancer survivors [63,64]. Studies of patient activation interventions on self-managed health behaviors in patients with type II diabetes have demonstrated increases in PA post-patient activation interventions [65,66,67,68]. These studies utilized several models of interventions on patient activation, including diabetes education and patient empowerment [65], motivational interviewing [66], education on medication adherence and lifestyle changes [67], and goal-setting and monitoring [68].
This study is not without limitations. The limited ethnic diversity in our study cohort underscores the need for evaluations of patient activation in more diverse samples. Health behaviors were obtained via self-report; while this type of ascertainment is typical, responses can be subject to social desirability bias. Associations between patient activation and anxiety, depression, and somatization symptoms must be interpreted with caution, as the BSI-18 is a symptom inventory and does not diagnose anxiety, depression, and somatization. Longitudinal healthcare utilization, follow-up care engagement, and adverse clinical outcomes were not examined in this study; future studies are warranted to evaluate associations between patient activation and these long-term outcomes in survivors.

5. Conclusions

Survivors enrolled in SJLIFE endorsed lower patient activation levels than the controls. These results highlight unique risk factors for low patient activation and the psychological contributors to low patient activation and highlight the role of patient activation as a contributor to health behavior. Further interventions to improve engagement in optimal health behaviors and improve psychological health could leverage these results to identify survivors who would benefit from support in patient activation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16183220/s1, Table S1: Multivariable Logistic Regression of Smoking Behavior; Table S2: Multivariable Logistic Regression of Risky Drinking; Table S3: Multivariable Logistic Regression of Diet Quality; Table S4: Multivariable Logistic Regression of Sleep Disturbance1

Author Contributions

Conceptualization, M.E.W., T.M.B., I.-C.H., R.W., B.P., K.K., S.M., M.E., G.A., M.M.H. and K.N.; methodology, M.E.W. and S.M.; formal analysis, M.E.W. and Q.D.; data curation, K.S.; writing—original draft preparation, M.E.W., A.D.L.C. and K.N.; writing—review and editing, M.E.W., A.D.L.C., Q.D., K.S., T.M.B., I.-C.H., R.W., B.P., K.K., S.M., M.E., G.A., M.M.H. and K.N.; supervision, K.N.; funding acquisition, K.N., M.M.H. and K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by National Institutes of Health, NCI T32CA225590 (Krull KR), NCI U01CA195547 (Hudson MM/Ness KK), and the American Lebanese Syrian Associated Charities (ALSAC).

Institutional Review Board Statement

The St. Jude Lifetime Cohort Study was approved by the Institutional Review Board at St. Jude Children’s Research Hospital with a current approval date of 13 March 2023.

Informed Consent Statement

All participants gave consent to participate in the St. Jude Lifetime Cohort Study.

Data Availability Statement

Data utilized for these analyses is available via Zenodo (doi: 10.5281/zenodo.13800123).

Conflicts of Interest

The authors declare no conflicts of interest.

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Cancers 16 03220 g001
Figure 1. Consort diagram.
Figure 1. Consort diagram.
Cancers 16 03220 g001
Table 1. Demographic characteristics of survivors and controls.
Table 1. Demographic characteristics of survivors and controls.
CharacteristicSurvivors (n = 2708)Controls (n = 303)p Value
No. (%)No (%)
Sex 0.0003
  Male1370 (50.6)126 (41.6)
  Female1338 (49.4)177 (58.4)
Race and Ethnicity <0.0001
  Non-Hispanic White2220 (82.0)243 (80.2)
  Non-Hispanic Black380 (14.0)20 (6.6)
  Others108 (4.0)40 (13.2)
Primary Cancer Diagnosis
  Leukemia867 (32.0)--
  Lymphoma464 (18.2)--
  Sarcoma358 (13.2)--
  CNS Tumor423 (15.6)--
  Embryonal337 (12.4)--
  Others229 (8.5)--
Radiation
  Yes1452 (53.6)--
  No1256 (46.4)--
Chemotherapy
  Yes2267 (83.7)--
  No441 (16.3)--
Surgery
  Yes2531 (83.7)--
  No177 (6.5)--
CTCAE 1 Grade 3+ Conditions
Cardiovascular <0.0001
  Yes232 (8.6)5 (1.7)
  No2476 (91.4)298 (98.3)
Endocrine <0.0001
  Yes1015 (37.5)75 (24.8)
  No1693 (62.5)228 (75.2)
Pulmonary 0.32
  Yes203 (7.5)18 (5.9)
  No2505 (92.5)285 (94.1)
Musculoskeletal 0.50
  Yes23 (0.8)1 (0.3)
  No2685 (99.2)302 (99.7)
Neurological 0.04
  Yes158 (5.8)9 (3.0)
  No2550 (94.2)294 (97.0)
Auditory <0.0001
  Yes346 (12.8)6 (2.0)
  No2362 (87.2)297 (98.0)
Gastrointestinal 0.17
  Yes38 (1.4)1 (0.3)
  No2670 (98.6)302 (99.7)
Hematologic 1.00
  Yes8 (0.3)0 (0.0)
  No2700 (99.7)303 (100.00)
Immunologic 1.00
  Yes24 (0.9)2 (0.7)
  No2684 (99.1)301 (99.3)
Ocular <0.0001
  Yes286 (10.6)6 (2.0)
  No2442 (89.4)297 (98.0)
Renal 0.07
  Yes31 (1.1)0 (0.0)
  No2677 (98.9)303 (100.0)
Reproductive <0.0001
  Yes270 (10.0)3 (1.0)
  No2438 (99.0)300 (99.0)
Subsequent neoplasm 0.16
  Yes24 (0.9)0.0 (0.0)
  No2684 (99.1)303 (100.0)
Educational Attainment <0.0001
  High school or less665 (26.0)38 (12.8)
  Some post-high school847 (33.1)86 (29.1)
  College degree or higher1047 (40.9)172 (58.1)
Insurance Coverage 0.43
  Insured2379 (88.5)272 (90.1)
  Uninsured308 (11.5)30 (9.9)
ADI 2 Quartiles <0.0001
  Quartile 1631 (23.3)110 (36.3)
  Quartile 2679 (25.1)84 (27.7)
  Quartile 3707 (26.1)64 (21.1)
  Quartile 4691 (25.5)45 (14.9)
Patient Activation Level <0.0001
  Level 1 3304 (11.3)14 (4.7)
  Level 2 4371 (13.8)29 (9.7)
  Level 3 5800 (29.7)72 (24.1)
  Level 4 61220 (45.3)184 (61.5)
Mean (SD)Mean (SD)
Age at diagnosis (y)8.9 (5.8)----
Age at evaluation33.8 (10.5)30.7 (9.8)<0.0001
1 CTCAE: Common Terminology Criteria for Adverse Events. 2 ADI: Area Deprivation Index. 3 People are passive and feel overwhelmed about managing their health. They may be unprepared to take an active role. 4 People may lack specific knowledge and confidence to self-manage their health. 5 People are beginning to take actions but may lack the confidence and skill to sustain the activity. 6 People have adopted behaviors to support their health but may not be able to maintain them over time when they are facing life stressors.
Table 2. Distribution of survivor demographic characteristics across patient activation levels.
Table 2. Distribution of survivor demographic characteristics across patient activation levels.
CharacteristicLevel 1 (n = 304)Level 2 (n = 371)Level 3 (n = 800)Level 4 (n = 1220)p Value
No. (%)No (%)No (%)No. (%)
Sex 0.33
  Male150 (49.3)194 (52.3)421 (52.6)596 (48.9)
  Female154 (50.7)177 (47.7)379 (47.4)624 (51.1)
Race and Ethnicity
  Non-Hispanic White250 (82.2)302 (81.4)664 (83.0)995 (81.6)
  Non-Hispanic Black44 (14.5)52 (14.0)104 (13.0)176 (14.4)
  Others10 (3.3)17 (4.6)32 (4.0)49 (4.0)0.95
Primary Cancer Diagnosis <0.0001
  Leukemia80 (26.3)130 (35.0)260 (32.5)393 (32.2)
  Lymphoma59 (19.4)62 (16.7)140 (17.5)230 (18.9)
  Sarcoma34 (11.2)57 (15.4)107 (13.4)159 (13.0)
  CNS Tumor83 (27.3)55 (14.8)121 (15.1)161 (13.2)
  Embryonal34 (11.2)35 (9.4)105 (13.1)163 (13.4)
  Others14 (4.6)32 (8.6)67 (8.4)114 (9.3)
Radiation 0.01
  Yes183 (60.2)211 (56.9)430 (53.8)620 (50.8)
  No121 (39.8)160 (43.1)370 (46.3)600 (49.2)
Chemotherapy 0.11
  Yes247 (81.3)323 (87.1)658 (82.3)1029 (84.3)
  No57 (18.8)48 (12.9)142 (17.8)191 (15.7)
Surgery 0.23
  Yes287 (94.4)354 (95.4)739 (92.4)1139 (93.4)
  No17 (5.6)17 (4.6)61 (7.6)81 (6.6)
CTCAE 1 Grade 3+ Conditions
Cardiovascular 0.004
  Yes24 (7.9)44 (11.9)81 (10.1)82 (6.7)
  No280 (92.1)327 (88.1)719 (89.9)1138 (93.3)
Endocrine 0.005
  Yes130 (42.8)161 (43.4)290 (36.3)427 (35.0)
  No174 (57.2)210 (56.6)510 (63.8)793 (65.0)
Pulmonary 0.07
  Yes33 (10.9)29 (7.8)60 (7.5)78 (6.4)
  No271 (89.1)342 (92.2)740 (92.5)1142 (93.6)
Musculoskeletal 0.90
  Yes3 (1.0)3 (0.8)8 (1.0)9 (0.7)
  No301 (99.0)368 (99.2)792 (99.0)1211 (99.3)
Neurological <0.0001
  Yes42 (13.8)17 (4.6)49 (6.1)47 (3.9)
  No262 (86.2)354 (95.4)751 (93.9)1173 (96.1)
Auditory <0.0001
  Yes67 (22.0)49 (13.2)103 (12.9)126 (10.3)
  No237 (78.0)322 (86.8)697 (87.1)1094 (89.7)
Gastrointestinal 0.82
  Yes5 (1.6)6 (1.6)9 (1.1)18 (1.5)
  No299 (98.4)365 (98.4)791 (98.9)1202 (98.5)
Hematologic 0.48
  Yes1 (0.3)1 (0.3)4 (0.5)2 (0.2)
  No303 (99.7)370 (99.7)796 (99.5)1218 (99.8)
Immunologic 0.01
  Yes3 (1.0)9 (2.4)6 (0.8)6 (0.5)
  No301 (99.0)362 (97.6)794 (99.3)1214 (99.5)
Ocular 0.28
  Yes32 (10.5)41 (11.1)97 (12.1)115 (9.4)
  No272 (89.5)330 (88.9)703 (87.9)1105 (90.6)
Renal 0.70
  Yes4 (1.3)6 (1.6)9 (1.1)12 (1.0)
  No300 (98.7)365 (98.4)791 (98.9)1208 (99.0)
Reproductive 0.83
  Yes34 (11.2)35 (9.4)83 (10.4)118 (9.7)
  No270 (88.8)336 (90.6)717 (89.6)1102 (90.3)
Subsequent neoplasm 0.84
  Yes3 (1.0)3 (0.8)5 (0.6)12 (1.0)
  No301 (99.0)368 (99.2)795 (99.4)1208 (99.0)
Educational Attainment <0.0001
  High school or less116 (41.9)100 (28.3)223 (29.3)221 (19.1)
  Some post-high school94 (33.9)129 (36.5)273 (35.8)348 (30.0)
  College degree or higher67 (24.2)124 (35.1)266 (34.9)590 (50.9)
Insurance Coverage 0.01
  Insured261 (87.0)321 (87.2)688 (86.3)1098 (90.8)
  Uninsured39 (13.0)47 (12.8)109 (13.7)111 (9.2)
ADI 2 Quartiles <0.0001
  Quartile 151 (16.8)73 (19.7)171 (21.4)335 (27.5)
  Quartile 277 (25.3)95 (25.6)187 (23.4)318 (26.1)
  Quartile 381 (26.6)94 (25.3)235 (29.4)293 (24.0)
  Quartile 495 (31.3)109 (29.4)207 (25.9)274 (22.5)
   Mean (SD)Mean (SD)Mean (SD)Mean (SD)
Age at diagnosis (y)8.7 (5.6)9.5 (5.9)8.8 (5.7)8.9 (5.7)0.17
Age at evaluation33.6 (10.3)35.3 (11.3)33.7 (10.8)33.5 (10.1)0.04
1 CTCAE: Common Terminology Criteria for Adverse Events. 2 ADI: Area Deprivation Index.
Table 3. Distribution of survivor cognitive function across patient activation levels.
Table 3. Distribution of survivor cognitive function across patient activation levels.
DomainLevel 1Level 2Level 3Level 4p Value
No. (%)No (%)No (%)No. (%)
Intelligence <0.0001
  No impairment180 (65.5)282 (84.4)621 (83.9)996 (89.3)
  Mild impairment33 (12.0)24 (7.2)60 (8.1)65 (5.8)
  Moderate impairment16 (5.8)13 (3.9)29 (3.9)30 (2.7)
  Severe impairment46 (16.7)15 (4.5)30 (4.1)24 (2.2)
Attention
Focused Attention <0.0001
  No impairment 198 (66.7)308 (84.6)685 (87.5)1078 (89.6)
  Mild impairment 18 (6.06)14 (3.85)30 (3.8)49 (4.07)
  Moderate impairment 14 (4.7)8 (2.2)19 (2.4)20 (1.7)
  Severe impairment67 (22.6)34 (9.3)49 (6.3)56 (4.7)
Sustained Attention <0.0001
  No impairment 199 (71.1)308 (85.8)643 (83.8)1040 (88.2)
  Mild impairment19 (6.8)18 (5.0)47 (6.1)56 (4.8)
  Moderate impairment18 (6.4)12 (3.4)21 (2.7)26 (2.2)
  Severe impairment44 (15.7)21 (5.9)56 (7.3)57 (4.8)
Attention Span <0.0001
  No impairment 198 (65.8)288 (78.7)642 (81.1)1005 (83.2)
  Mild impairment52 (17.3)54 (14.8)100 (12.6)148 (12.3)
  Moderate impairment24 (7.8)16 (4.4)41 (5.2)41 (3.4)
  Severe impairment278 (9.0)8 (2.2)9 (1.1)14 (1.2)
Memory
Short-term Free Recall <0.0001
  No impairment 160 (53.7)259 (71.2)551 (70.0)956 (79.5)
  Mild impairment39 (13.1)38 (10.4)97 (12.3)113 (9.4)
  Moderate impairment26 (8.7)26 (7.1)60 (7.6)57 (4.7)
  Severe impairment73 (24.5)41 (11.3)79 (10.0)77 (6.4)
Long-term Free Recall <0.0001
  No impairment145 (48.8)234 (64.3)497 (63.2)885 (73.6)
  Mild impairment35 (11.8)53 (14.6)126 (16.0)159 (13.2)
  Moderate impairment33 (11.1)35 (9.6)87 (11.1)74 (6.2)
  Severe impairment84 (28.3)42 (11.5)76 (9.7)85 (7.1)
Executive Function
Working Memory <0.0001
  No impairment198 (65.8)288 (78.7)642 (81.1)1005 (83.2)
  Mild impairment 52 (17.3)54 (14.8)100 (12.6)148 (12.3)
  Moderate impairment24 (8.0)16 (4.4)41 (5.2)41 (3.4)
  Severe impairment27 (9.0)8 (2.2)9 (1.1)14 (1.2)
Cognitive Initiation
  No impairment156 (52.2)252 (68.9)513 (64.9)890 (73.7)
  Mild impairment62 (20.7)74 (20.2)157 (19.9)219 (18.1)
  Moderate impairment16 (5.4)12 (3.3)42 (5.3)38 (3.2)
  Severe impairment65 (21.7)28 (7.7)79 (10.0)61 (5.1)
Cognitive Flexibility
  No impairment157 (53.4)268 (73.6)554 (70.8)935 (77.7)
  Mild impairment15 (5.1)18 (5.0)45 (5.8)79 (6.6)
  Moderate impairment19 (6.4)18 (4.9)46 (5.9)50 (4.2)
  Severe impairment105 (35.5)60 (16.5)138 (17.6)139 (11.6)
Visuospatial Organization
Planning/Organization <0.0001
  No impairment97 (36.7)161 (51.1)353 (49.9)564 (53.0)
  Mild impairment24 (9.1)29 (9.2)75 (10.6)104 (9.8)
  Moderate impairment20 (7.6)19 (6.0)64 (9.0)95 (8.9)
  Severe impairment123 (46.6)106 (33.7)216 (30.5)302 (28.4)
Table 4. Distribution of survivor health behaviors across patient activation levels.
Table 4. Distribution of survivor health behaviors across patient activation levels.
Health BehaviorLevel 1Level 2Level 3Level 4p Value
No. (%)No (%)No (%)No. (%)
Meeting CDC Physical Activity Guidelines 1 <0.0001
  Yes129 (43.7)182 (49.6)465 (58.8)813 (67.6)
  No166 (56.3)185 (50.4)326 (41.2)389 (32.4)
Smoking 2 0.004
  Never212 (71.9)253 (68.8)554 (70.1)915 (76.0)
  Current53 (18.0)64 (17.4)142 (18.0)147 (12.2)
  Former30 (10.2)51 (13.9)94 (11.9)142 (11.8)
Risky drinking 3 0.0002
  Yes67 (23.2)117 (32.3)272 (35.0)433 (36.6)
  No222 (76.8)245 (67.7)505 (65.0)749 (63.4)
Sleep disturbance 4 0.42
  None to slight122 (40.5)128 (34.8)290 (36.6)476 (39.4)
  Mild151 (50.2)198 (53.8)432 (54.5)614 (50.8)
  Moderate or Severe28 (9.3)42 (11.4)70 (8.8)118 (9.8)
Healthy Eating Index score 5 <0.0001
  <51 (poor diet)93 (30.6)102 (27.5)198 (24.8)213 (17.5)
  50–80 (needs improvement)208 (68.4)263 (70.9)590 (73.8)979 (80.2)
  >80 (good)3 (1.0)6 (1.6)12 (1.5)28 (2.3)
1 CDC PA guidelines: endorsing 150 min of moderate or 75 min of vigorous PA per week. 2 Current smoking: within the past 30 days; former smoking: smoking outside of a 30-day period.3 Risky drinking: >3 per day or >7 per week (females) >4 per day or >14 per week (males). 4 PROMIS sleep disturbance 8a t-score <25 (none to slight), 25> and ≤30 (mild), and >30 (moderate to severe). 5 Healthy Eating Index score <51 (poor diet), 50–80 (needs improvement), and >80 (good).
Table 5. Distribution of survivor psychological factors across patient activation levels.
Table 5. Distribution of survivor psychological factors across patient activation levels.
Psychological Factors Level 1 Level 2 Level 3 Level 4 p Value
No. (%)No (%)No (%)No. (%)
Depression symptoms 1 <0.0001
  Yes85 (28.2)59 (16.0)68 (8.5)94 (7.7)
  No216 (71.8)310 (84.0)728 (91.5)1122 (92.3)
Anxiety symptoms 2 <0.0001
  Yes71 (23.6)43 (11.7)67 (8.4)83 (6.8)
  No230 (76.4)326 (88.3)730 (91.6)1132 (93.2)
Somatization symptoms 3 <0.0001
  Yes88 (29.3)56 (15.2)83 (10.4)103 (8.5)
  No212 (70.7)313 (84.8)713 (89.6)1112 (91.5)
Cancer-Related Worry 4
  General fear <0.0001
  Yes126 (41.9)142 (38.5)263 (33.0)349 (28.7)
  No175 (58.1)227 (61.5)534 (67.0)868 (71.3)
Body-focused <0.0001
  Yes125 (41.5)105 (28.4)138 (17.3)189 (15.5)
  No176 (58.5)265 (71.6)659 (82.7)1028 (84.5)
Health-related quality of life 5
Poor physical-health-related quality of life <0.0001
  Yes113 (40.2)79 (22.1)119 (15.5)114 (9.7)
  No168 (59.8)278 (77.9)648 (84.5)1058 (90.3)
Poor mental-health-related quality of life <0.0001
  Yes113 (40.4)102 (28.7)145 (18.9)173 (14.8)
  No167 (59.6)253 (71.3)622 (81.1)999 (85.2)
1 Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile) (endorsing depression symptoms). 2 Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile) (endorsing anxiety symptoms). 3 Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile) (endorsing somatization symptoms). 4 Cancer-related worry (CRW) factor score <3 (not endorsing CRW) and ≥3 (endorsing CRW). 5 Short-Form Health Survey (SF-36) t-score score ≤ 40 (endorsing poor health-related quality of life).
Table 6. Multivariable logistic regression of physical activity level 1.
Table 6. Multivariable logistic regression of physical activity level 1.
Independent VariablesOdds Ratio (OR)95% CI
Patient Activation Level
  2 vs. 1
  3 vs. 1
  4 vs. 1
1.14
1.53
2.07
0.80–1.62
1.13–2.09
1.53–2.80
Age at assessment0.980.97–0.99
Age at diagnosis0.990.97–1.01
Gender
  Male vs. Female
1.37
1.15–1.63
Diagnosis Group
  Lymphoma vs. Leukemia
  Sarcoma vs. Leukemia
  CNS Tumor vs. Leukemia
  Embryonal Tumor vs. Leukemia
  Other vs. Leukemia
0.90
0.75
0.69
0.79
0.86
0.68–1.18
0.56–1.00
0.51–0.92
0.58–1.06
0.61–1.22
Race
  NH Black vs. NH White
  Other vs. NH White
0.90
0.90
0.69–1.18
0.58–1.39
Educational Attainment
  Some post-high school vs. high school or less
  College graduate vs. high school or less
1.18
1.29
0.93–1.50
1.01–1.65
Intelligence
  Mild vs. no impairment
  Moderate vs. no impairment
  Severe vs. no impairment
0.91
0.61
0.59
0.64–1.28
0.38–1.00
0.37–0.95
Auditory condition grade 3+ at assessment
  Yes vs. No
0.97
0.74–1.26
Cardiovascular condition grade 3+ at assessment
  Yes vs. No
0.80
0.59–1.09
Endocrine condition grade 3+ at assessment
  Yes vs. No
0.78
0.65–0.93
Hematological condition grade 3+ at assessment
  Yes vs. No
0.32
0.06–1.69
Neurological condition grade 3+ at assessment
  Yes vs. No
0.52
0.35–0.76
Pulmonary condition grade 3+ at assessment
  Yes vs. No
0.66
0.47–0.93
Renal condition grade 3+ at assessment
  Yes vs. No
0.70
0.31–1.61
1 modeling probability of meeting CDC PA guidelines (150 min of moderate or 75 min of vigorous PA per week).
Table 7. Multivariable ordinal logistic regression of patient activation level 1.
Table 7. Multivariable ordinal logistic regression of patient activation level 1.
Psychological PredictorNumber (%) of Total Sample95% CI
Depression Symptoms 22682 (99.04%)2.37 (1.87–2.99)
Anxiety Symptoms 32682 (99.04%)2.21 (1.73–2.83)
Somatization Symptoms 42682 (99.04%)1.99 (1.59–2.50)
Cancer-Related Worry
  General Fear 52684 (99.11%)1.45 (1.23–1.71)
  Body-Focused 62685 (99.15%)2.21 (1.83–2.66)
Health-Related Quality of Life
  Physical Component 72577 (95.16%)2.57 (2.06–3.20)
  Mental Component 82574 (95.05%)2.08 (1.72–2.52)
1 Modeling probability of endorsing higher ordered levels of patient activation; models adjusted for age at survey, age at diagnosis, race, educational attainment, gender, diagnosis, insurance status, perceived instrumental support, CTCAE grade 3+ auditory, cardiovascular, endocrine, immunologic, neurological, and pulmonary conditions. 2 Not endorsing depression symptoms (Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile)). 3 Not endorsing anxiety symptoms (Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile)). 4 Not endorsing somatization symptoms (Brief Symptom Inventory (BSI) t-score ≥63 (top 10th percentile)). 5 Not endorsing body-focused cancer-related worry (factor score ≥3). 6 Not endorsing body-focused cancer-related worry (factor score ≥3). 7 Not endorsing suboptimal physical health-related quality of life (Short-Form Health Survey (SF-36) t-score score ≤40)). 8 Not endorsing suboptimal mental health-related quality of life (Short-Form Health Survey (SF-36) t-score score ≤40).
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Ware, M.E.; De La Cruz, A.; Dong, Q.; Shelton, K.; Brinkman, T.M.; Huang, I.-C.; Webster, R.; Potter, B.; Krull, K.; Mirzaei, S.; et al. Characterization of Patient Activation among Childhood Cancer Survivors in the St. Jude Lifetime Cohort Study (SJLIFE). Cancers 2024, 16, 3220. https://doi.org/10.3390/cancers16183220

AMA Style

Ware ME, De La Cruz A, Dong Q, Shelton K, Brinkman TM, Huang I-C, Webster R, Potter B, Krull K, Mirzaei S, et al. Characterization of Patient Activation among Childhood Cancer Survivors in the St. Jude Lifetime Cohort Study (SJLIFE). Cancers. 2024; 16(18):3220. https://doi.org/10.3390/cancers16183220

Chicago/Turabian Style

Ware, Megan E., Angelica De La Cruz, Qian Dong, Kyla Shelton, Tara M. Brinkman, I-Chan Huang, Rachel Webster, Brian Potter, Kevin Krull, Sedigheh Mirzaei, and et al. 2024. "Characterization of Patient Activation among Childhood Cancer Survivors in the St. Jude Lifetime Cohort Study (SJLIFE)" Cancers 16, no. 18: 3220. https://doi.org/10.3390/cancers16183220

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