Abstract
Purpose
Assess feasibility, acceptability, and preliminary efficacy of an integrated symptom management and lifestyle intervention (SMLI) to improve adherence to the American Cancer Society’s (ACS) Guidelines on Nutrition and Physical Activity in Latina cancer survivors and their informal caregivers (dyads).
Methods
Forty-five dyads were randomized to a 12-week telephone-delivered intervention or attention control. Intervention effects on nutrition, physical activity, symptom burden, and self-efficacy for symptom management were estimated using Cohen’s ds.
Results
Mean age was 64 for survivors and 53 for caregivers. Feasibility was demonstrated by the 63% consent rate out of approached dyads. The SMLI was acceptable for 98% of dyads. Among survivors, medium-to-large effect sizes were found for increased servings of total fruits and vegetables (d = 0.55), vegetables (d = 0.72), and decreased sugar intake (d = − 0.51) and medium clinically significant effect sizes for total minutes of physical activity per week (d = 0.42) and grams of fiber intake per day (d = 0.40) for intervention versus attention control. Additionally, medium-to-large intervention effects were found for the reduction of symptom burden (d = 0.74). For caregivers, medium-to-large intervention effects were found for reduced total sugar intake (d = − 0.60) and sugar intake from sugar-sweetened beverages (d = − 0.65); vegetable intake was increased with a medium effect size (d = 0.41).
Conclusion
SMLI was feasible and acceptable for both dyadic members. A larger, well-powered trial is needed to formally evaluate SMLI effectiveness.
Implications for Cancer Survivors
Integrating symptom management with lifestyle behavior interventions may increase adherence to the ACS guidelines on nutrition and physical activity to prevent new and recurrent cancers.
Keywords: Cancer survivors, Caregivers, Diet, Physical activity, Symptom management, Lifestyle behaviors, Latinas
Background
Latinx (term used for people of Latino or Hispanic origin) are the youngest and largest minority group in the USA, comprising approximately 18% of the population [1]. In 2018, there were 81,700 new cases of cancer diagnosed in Latinas, who are diagnosed at younger ages and later stages compared to non-Hispanic whites [2]. Cancer is the leading cause of death among Latinas, accounting for 21% of deaths [2]. The rate of cancer diagnoses for Latinx people under 50 years of age (25%) is more than double that of non-Hispanic whites (12%) [2]. Cancer is often comorbid with obesity, and obesity is an independent risk factor for 13 different types of cancer (breast, thyroid, colon/rectum, meningioma, adenocarcinoma of the esophagus, liver, multiple myeloma, kidneys, gallbladder, uterus, upper stomach, pancreas, and ovaries) [2, 3]. Obesity is highly prevalent among Latinx with a rate of 47%, compared to 38% among non-Hispanic whites [4].
An estimated 42% of cancer cases and 45% of cancer deaths across all ethnicities in the USA could be prevented through the adoption of healthier lifestyles [5, 6]. Modifying lifestyle behaviors such as diet and physical activity plays a key role in cancer prevention and control. For both the general and cancer survivor population (defined as individuals from cancer diagnosis to end of life), there is strong evidence that following the American Cancer Society (ACS) guidelines on nutrition and physical activity can assist with weight management [7, 8], reduce risk of recurrent or new cancers [7], improve quality of life (QOL) [8–12], and reduce mortality [9, 13]. Despite robust evidence, few cancer survivors adhere to these guidelines. Specifically, less than 30–70% of cancer survivors meet the ACS guidelines of 2.5 cups of vegetables and fruit per day and less than 66% meet the 150 min of moderate physical activity each week [10, 12, 14]. Among Latina cancer survivors, adherence to these guidelines is the lowest among all racial and ethnic groups with less than 15% meeting all of the guidelines [15]. Of note, a more recent randomized controlled trial of supervised resistance and aerobic training among a predominantly Latina breast cancer survivor group [16] found Latina survivors to have poorer metabolic health and body composition and to be less physically active at baseline compared to non-Hispanic white survivors participating in the intervention [17]. However, the Latina breast cancer survivors participating in this trial were not only adherent to the intervention but ethnicity appeared to moderate the effects of the intervention on most indicators of metabolic syndrome suggesting high potential for lifestyle interventions to improve outcomes in this population [17].
Interventions directed solely at lifestyle behaviors among cancer survivors have had some success; however, the majority of these have been predominantly among non-Hispanic whites [18–20]. In the majority of trials, even when these health behaviors were improved during the intervention, they were not sustained in longer-term follow-up [20]. One potential reason for survivors not enacting healthy lifestyle behaviors and meeting the guidelines could be the burden of multiple symptoms experienced during and following cancer treatment [21–25]. Many symptoms last up to 10 years after completion of cancer treatment [26, 27]. The end of chemotherapy was rated as moderately to extremely stressful by 48% of breast cancer survivors [28, 29]; more than 60% of breast cancer survivors report significant problems with fatigue and sleep [30]. Clinically significant depressive symptoms were reported by 67% of cancer survivors [31].
Latinas with cancer often report higher numbers of symptoms and greater psychological distress associated with symptoms than non-Hispanic whites [32]. These symptoms may interfere with information processing and reduce motivation and ability to engage in healthy lifestyle behaviors. Yet, survivors may be motivated to enact lifestyle behavior changes by seeing the immediate benefit of symptom reduction. For example, the most prevalent and debilitating symptom of fatigue can be managed with physical activity [33–36]. Relief of fatigue is the immediate benefit that can motivate the survivor to adopt physical activity behavior, while the long-term benefit of sustaining physical activity is illness prevention. Similarly, moderate physical activity can be beneficial in the management of sleep disturbance [34, 37, 38] and depression and anxiety [39–41]. Dietary changes may help with gastrointestinal symptoms [42, 43] and fatigue [44]. This stronger evidence for physical activity and more limited evidence for dietary changes to potentially mitigate symptoms was the rationale for developing and testing the integrated symptom management and lifestyle behavior coaching intervention for Latina cancer survivors in this study.
Another avenue by which we attempted to improve enactment of healthy lifestyle behaviors was the involvement of informal caregivers of cancer survivors. Informal caregivers are people within the survivor’s social network, related by blood or social attachment, who provide emotional, informational, and/or instrumental support [45]. Behavioral interventions that include a family member or caregiver demonstrate greater success with improving outcomes when the intervention is focused on the dyad versus the individual survivor only [46–49]. For caregivers, Beesley and colleagues reported that more than 50% of caregivers for women with ovarian cancer did not meet the ACS physical activity guideline of 150 min of moderate physical activity each week, 71% were overweight or obese, 40% ate fewer than 2 servings of fruit per day, and 80% ate fewer than 5 servings of vegetables per day [50]. Despite these suboptimal adherence rates, survivors and caregivers express interest in participating in programs to promote healthy lifestyles behaviors with high motivation [51, 52]. In a qualitative study among lung cancer survivors and their informal caregivers, the behaviors that survivors and caregivers were most interested in learning more about were exercise, stress management, and diet [53]. Caregivers who engage in healthy lifestyle behaviors can facilitate survivors’ enactment of such behaviors.
Lifestyle interventions may help alleviate symptoms (e.g., fatigue, sleep impairment) experienced by Latina cancer survivors and their caregivers and could prevent cancer by helping them meet the ACS guidelines on nutrition and physical activity. Therefore, in this pilot randomized controlled trial (NCT04314479) called Nuestra Salud (For Your Health), we evaluated the feasibility, acceptability, and preliminary efficacy of a novel integrated symptom management and lifestyle intervention (SMLI) which was culturally and linguistically tailored to Latina cancer survivors and their informal caregivers.
Methods
The Nuestra Salud study received approval from the Institutional Review Board at the University of Arizona. Informal caregivers, family members, or friends were designated as caregivers by the cancer survivors. Cancer survivors and their caregivers were enrolled as dyads, and both members provided signed informed consent. We recruited 45 Latinas who had completed primary treatment for solid tumor cancers and reported at least one of five symptoms (fatigue, depression, anxiety, pain, disrupted sleep) at a severity of 4 or greater on a 0–10 scale, the threshold for the need of symptom management is based upon the National Comprehensive Cancer Network Guidelines [54]. Latina cancer survivors were recruited from the southern Arizona community, University of Arizona Cancer Center, and a support group in the Arizona, US-Sonora, Mexico border region. Informal caregivers did not have to live with or near the survivor, but had to be willing to sign and mail the informed consent form and participate by telephone. Informal caregivers were therefore from a variety of locations including Arizona, California, and Sonora, Mexico.
Dyads N = 45 (90 people) were randomized in a 2:1 ratio to either a telephone-based (a) 12-week SMLI (N = 28 dyads) or (b) attention control condition of 12 weekly symptom assessments (N = 17 dyads). The rationale for approximate 2:1 randomization to SMLI versus control was based on the need to evaluate the completion of SMLI sessions and feedback about the intervention based on a larger group of survivors and caregivers, as compared to 1:1 randomization.
The primary outcomes of the trial were diet and physical activity, and secondary outcomes were severity of symptoms and self-efficacy for symptom management outcomes. Blinded data collectors from the University of Arizona Cancer Center Behavioral Measurement and Interventions Shared Resource administered telephone interviews in either English or Spanish to collect assessments at baseline and week 13. After completion of the baseline and week 13 assessments, survivors and caregivers received a $25 gift card to thank them for their time.
Symptom management and lifestyle behavior intervention (SMLI)
Social cognitive theory [55] provided the theoretical underpinnings for the intervention. The integrated SMLI was designed to deliver symptom management and lifestyle behavior change coaching concurrently to address symptoms and improve diet and physical activity. Using an individualized approach, the SMLI was intended to improve motivation and increase self-efficacy [56–58]. Social cognitive theory posits that an individual with given information, attitude, beliefs, and needs functioning in a given social and physical environment will engage in behavior in pursuit of positive outcomes. The perceived self-efficacy of each participant influences the acquisition of new behaviors, including the inhibition and disinhibition of behaviors and the amount of time and effort an individual is willing to put towards changing a behavior. Finally, self-efficacy impacts psychosocial elements to include anxiety, distress, and thought patterns around behavior change. For the SMLI arm of the study only, self-efficacy for lifestyle behavior goals was used as a process variable on most coaching calls to help participants achieve the lifestyle goals. Because no two individuals are the same, a patient-centered approach allows the coach to help guide participants through their individual journey in meeting the lifestyle goals while addressing symptoms. On each call, participants were coached to explore barriers and facilitators of enacting healthy diet and physical activity behaviors, resulting in tailored behavior change.
The intervention consisted of 12 private, 20- to 30-min coaching sessions with trained bicultural health coach in either English or Spanish. Health coaches had more than 4 years of health coaching experience for changing lifestyle behaviors and specific experience with cancer survivors. Coaching sessions were delivered using the electronic health and intervention platform (eHIP) [59]. The eHIP provided a secure, HIPAA-compliant study platform which delivered short message series texts for participant communication and recorded phone calls for fidelity and protocol monitoring. Data collection and management, including coaching notes, was facilitated through the use of REDCap electronic data capture tools hosted at University of Arizona. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies [60, 61]. Dyads randomized to the SMLI received 12 weekly coaching sessions, printed materials from the Symptom Management and Survivorship Handbook (SMSH) developed by the authors (TB, AS, TC) and a Fitbit® as a strategy for self-monitoring. Calls began with a symptom assessment using the General Symptom Distress Scale (GSDS) and reference to the SMSH for strategies to manage elevated symptoms identified by the GSDS, including lifestyle behavior changes as a method for managing symptoms. Motivational interviewing (MI) served as the basis for the behavior change strategy in the coaching sessions. Coaches and participants worked together to establish goals aimed at building self-efficacy by setting Specific, Measurable, Attainable, Relevant, and Timely (SMART) goals. SMART goals, when achieved (or not achieved, allowing for the identification of barriers), increased motivation for the attainment of other lifestyle behavior goals congruent with the ACS guidelines on nutrition and physical activity for cancer prevention [7]. These goals included increasing the number of steps per day (daily activity); servings of vegetables, fruit, or whole grains per day; reduction of calories from added sugars, fat, and processed and red meat; and reduction in alcohol consumption. Nuestra Salud participants set one to two small, achievable goals on each coaching call, and self-efficacy for achieving each goal was assessed.
If the participant chose to wear the Fitbit®, information from the Fitbit® such as daily steps or active minutes was used by the coach to tailor the intervention sessions with regard to physical activity and setting realistic goals. Individual coaching calls were placed to the survivor and caregiver, not the dyad together unless indicated as preferred by both members of the dyad. The intervention is intended to work at the individual level with the caregiver supporting the survivor’s behavior change and the caregiver also engaging in the healthy behaviors themselves. The survivors and caregivers were encouraged to engage each other in enacting the healthy lifestyle behaviors.
Attention control
Dyads in the attention control received 12 weekly phone calls in either English or Spanish by trained research assistants to assess symptoms only. Phone call assessments allowed for tracking the process of change in symptoms and lasted approximately 5 min. After the 12 weekly symptom assessment calls and the week 13 telephone interview was completed, participants in the attention control received the SMSH printed materials, one call with the intervention health coach, and a Fitbit®.
Assessments
At baseline, all participants completed a questionnaire that included demographic, cancer stage (survivor), caregiver relationship information, and the 18-item United States Department of Agriculture Food Security Questionnaire [62] that has been used in diverse populations [63] and translated into Spanish.
Primary outcomes
Dietary intake was assessed by the NCI Dietary Screener Questionnaire [64], a 19-item dietary screener which asks about the frequency of consumption over the past 30 days of selected foods and drinks. The NCI Dietary Screener Questionnaire (DSQ) captures intakes of fruits and vegetables, dairy/calcium, added sugars, whole grains/fiber, and red and processed meat. The 19 items were selected based on the relationship to one or more dietary factors of interest in the dietary guidelines and relation to cancer prevention dietary guidelines. The scoring algorithm for the NCI DSQ has been validated and tested against 24-h dietary recall estimates with < 2% difference in mean intakes and < 16% difference in prevalence of food groups consumed. The NCI DSQ has been translated to Spanish with good reliability and validity [65].
Physical Activity was assessed by the Women’s Health Initiative (WHI) Physical Activity Questionnaire [66] which consists of nine questions and collects usual frequency, duration, and pace of recreational walking; frequency and duration of other recreational activities or exercises (mild, moderate, and strenuous); and household and yard activities over the last 7 days. The WHI physical activity questionnaire was designed to capture daily activity and has been translated into Spanish with good reliability and validity.
Secondary outcomes
General Symptom Distress Scale (GSDS) [67] is a brief instrument for a rapid assessment of 15 symptoms: shortness of breath, pain, sleep difficulties, bowel problems, nausea, vomiting, numbness or tingling, swelling in hands and feet, skin rashes or sores, difficulty concentrating, poor appetite, depression, anxiety, fatigue, and cough. Respondents indicate presence of each symptom (yes/no) and rate its severity on the scale from 1 to 10. The GSDS has been used in both English and Spanish [67]. The 0–10 ratings of 15 symptoms were summed into an index at baseline, weeks 1–12, and in week 13 assessments. Since the GSDS is a collection of symptom items summarized in an index and not a scale, internal consistency and reliability are not applicable.
Self-efficacy for symptom management was assessed by the Patient Reported Outcomes Measurement Information System (PROMIS) [68], an eight-item short form administered by interview. PROMIS responses are represented as t-scores with a mean of 50 and standard deviation 10, with higher scores indicating greater self-efficacy.
Feasibility was assessed by the percent of consented dyads out of those approached and percent of intervention dyads completing at least 8 of 12 intervention sessions. The benchmark to demonstrate feasibility was at least 50% consent rate, which is relatively high for dyadic studies where two people have to consent [69]. The benchmark for completion of intervention sessions was set at 80% of individual coaching sessions for both members of the dyad [70]. Acceptability was evaluated by qualitatively summarizing responses to open-ended questions in the week 13 satisfaction survey.
Acceptability of the intervention was assessed via a set of open-ended questions at week 13. Participants were asked what they liked and disliked about the intervention and about the perceived benefits of, and challenges to, participating. The benchmark was 80% of dyads deeming the intervention helpful.
Self-efficacy for health behaviors process variable (intervention arm only): Based on Bandura’s social cognitive theory [71], mastery of a skill is a critical construct in building self-efficacy. On most intervention coaching calls, participants were asked on scale of 1 (0% achievement) to 5 (100% achievement) whether or not they achieved the previous week’s goal. A score of 3 or greater, representing at least a partial achievement of their previous goal, was considered meaningful in building self-efficacy.
Analysis
To assess preliminary efficacy, primary and secondary outcomes at week 13 (one outcome at a time) were related to trial arm while adjusting for baseline value using general linear modeling. The least square (LS) means by trial arm were output from the model, and differences between them were evaluated. Due to the nature of pilot trials, the focus was not on statistical significance, but on estimating the effect sizes as differences between LS means by trial arm, divided by the adjusted standard deviation (square root of the mean square error). Cohen’s classification for effect sizes is 0.2 (small), 0.5 (medium), and 0.8 (large), with effect sizes of 0.33 or greater often deemed as clinically significant for patient-reported outcomes [72, 73].
Sample size considerations for this pilot study were not based on formal hypotheses. The effect size estimates from this study will be used to formally power a larger definitive trial of SMLI. The total sample size was determined based on study duration and available resources to complete this pilot.
Results
Latina survivors who completed baseline interview were 64 years old on average, and 100% were Hispanic with the majority indicating Mexican ethnic origin. Over 75% of survivors chose Spanish for assessments and coaching. Caregivers had a mean age of 53 years; 70% were Hispanic with one-third indicating Mexican for their ethnicity and over 50% opting to participate in coaching calls using Spanish as their primary language (Table 1). Survivors were, on average, 10 years post-diagnosis, and the majority (68%) had breast cancer. Most of the caregivers were either a spouse/partner, daughter/son, or friend. More than 50% of the survivors indicated moderate-to-severe food insecurity and a household income of less than $50,000 per year with an average of 4.3 people living in the home. Even though one symptom at or above the NCCN threshold of four on a 0–10 scale was required in the inclusion criteria for survivors, the mean number of symptoms above this threshold was 5.27 (SD 2.80) for survivors. For the caregivers, the mean was 2.94 (SD 3.29). The prevalence of symptoms at or above the NCCN threshold of four among survivors and caregivers is depicted in Fig. 1.
Table 1.
Characteristics of survivors and caregivers and their outcomes at baseline by study group
| Characteristic | Survivors |
Caregivers |
||
|---|---|---|---|---|
| Intervention N = 23 Mean (StDev) or N (%) |
Control N = 14 Mean (StDev) or N (%) |
Intervention N = 21 Mean (StDev) or N (%) |
Control N = 13 Mean (StDev) or N (%) |
|
|
| ||||
| Age | 64.35 (8.44) | 57.36 (12.13) | 57.67 (17.34) | 46.62 (19.01) |
| Number of comorbid conditions | 6.46 (2.54) | 4.29 (2.13) | 3.40 (2.41) | 2.64 (2.01) |
| BMI | 31.34 (6.38) | 27.08 (3.72) | 29.64 (8,67) | 28.66 (5.24) |
| Spanish language preference | 18 (78%) | 11 (79%) | 12 (57%) | 7 (54%) |
| Mexican ethnic origin | 20 (90%) | 11 (85%) | 8 (38%) | 4 (31%) |
| Marital status* | ||||
| Married | 8 (35%) | 7 (50%) | 9 (43%) | 9 (82%) |
| Divorced/separated | 5 (22%) | 2 (14%) | 1 (5%) | 1 (9%) |
| Widowed | 4 (17%) | 2 (14%) | 3 (14%) | 0 (0%) |
| Single | 6 (26%) | 2 (14%) | 8 (38%) | 3 (23%) |
| Never smoker | 19 (83%) | 13 (93%) | 11 (52%) | 10 (77%) |
| Caregiver is Spouse/partner | 6 (26%) | 4 (29%) | ||
| Sibling | 3 (13%) | 1 (7%) | ||
| Daughter or son | 7 (30%) | 4 (29%) | ||
| Mother/parent | 1 (4%) | 1 (7%) | ||
| Friend | 5 (22$) | 4 (29%) | ||
| Other | 1 (4%) | 0 (0%) | ||
| Education | ||||
| Less than high school | 3 (50%) | 1 (17%) | 0 (0%) | 2 (40%) |
| High school/GED | 1 (17%) | 2 (33%) | 2 (50%) | 0 (0%) |
| Vocational/technical/community college | 0 (0%) | 3 (50%) | 0 (0%) | 2 (40%) |
| 4-year college | 1 (17%) | 0 (0%) | 1 (25%) | 1 (20%) |
| Post graduate or professional | 1 (17%) | 0 (0%) | 1 (25%) | 0 (0%) |
| Employment | ||||
| Full time | 2 (9%) | 4 (29%) | 6 (29%) | 7 (58%) |
| Part time | 2 (9%) | 1 (7%) | 3 (14%) | 1 (8%) |
| Retired | 6 (26%) | 4 (29%) | 6 (29%) | 1 (8%) |
| Stay at home | 7 (30%) | 4 (29%) | 4 (19%) | 2 (17%) |
| Disabled | 6 (26%) | 1 (7%) | 2 (10%) | 0 (0%) |
| Annual income | ||||
| $10,000 or less | 9 (53%) | 2 (18%) | 4 (25%) | 0 (0%) |
| $10,001–$30,000 | 4 (24%) | 2 (18%) | 5 (31%) | 3 (43%) |
| $30,001–$50,000 | 2 (12%) | 5 (45%) | 2 (13%) | 3 (43%) |
| $50,001–$75,000 | 1 (6%) | 1 (9%) | 2 (13%) | 0 (0%) |
| $75,001–$100,000 | 0 (0%) | 1 (9%) | 1 (6%) | 0 (0%) |
| More than $100,000 | 1 (6%) | 0 (0%) | 2 (13%) | 1 (14%) |
| Site of cancer | ||||
| Head or neck | 1 (4%) | 0 (0%) | ||
| Liver | 0 (0%) | 1 (7%) | ||
| Breast | 19 (83%) | 11 (79%) | ||
| Colon | 1 (4%) | 0 (0%) | ||
| Kidney | 0 (0%) | 1 (7%) | ||
| Lymphoma | 1 (4%) | 0 (0%) | ||
| Other | 2 (9%) missing specifics | 1 (7%) uterine | ||
| Currently on treatment | 4 (17%) | 2 (14%) | ||
| Radiation | 2 (9%) | 0 (0%) | ||
| Other | 3 (13%) | 2 (14%) | ||
| Years since diagnosis | 9.02 (6.67), Range 0.6–22.3 | 11.91 (7.27), Range 1.2–23.4 | ||
| Food security | ||||
| 0 | 6 (32%) | 10 (67%) | 17 (74%) | 11 (73%) |
| 1 | 4 (21%) | 1 (7%) | 1 (4%) | 0 (0%) |
| 2 | 3 (16%) | 2 (13%) | 2 (9%) | 2 (13%) |
| 3 | 2 (11%) | 1 (7%) | 2 (9%) | 1 (7%) |
| ≥ 4 | 4 (22%) | 1 (7%) | 1 (4%) | 1 (7%) |
| Fiber intake (g/day) | 16.01 (2.65) | 16.25 (3.41) | 16.69 (4.59) | 16.59 (3.08) |
| Sugar (g/day) | 12.65 (3.17) | 14.12 (4.51) | 15.71 (5.69) | 16.18 (4.82) |
| Sugar from sugar-sweetened beverages (g/day) | 4.97 (2.71) | 5.94 (3.84) | 7.05 (4.78) | 7.41 (4.15) |
| Fruit and vegetable intake** (cup equivalents/day) | 2.49 (0.67) | 2.62 (0.62) | 2.53 (0.81) | 2.70 (1.10) |
| Vegetable intake (cup equivalents/day) | 1.52 (0.39) | 1.57 (0.39) | 1.60 (0.51) | 1.56 (0.47) |
| Fruit intake (cup equivalents/day) | 0.98 (0.43) | 1.04 (0.33) | 0.92 (0.41) | 1.18 (0.86) |
| Meets PA guidelines | 1 (4%) | 4 (27%) | 10 (48%) | 7 (54%) |
| Physical Activity (min/week) | 45.22 (51.53) | 146.5 (203.8) | 193.8 (212.9) | 201.5 (169.2) |
| Summed severity index | 40.87 (18.61) | 32.93 (20.43) | 22.57 (21.27) | 18.15 (19.46) |
| Global symptom distress | 5.48 (2.63) | 4.62 (2.60) | 3.60 (2.58) | 3.62 (2.57) |
| Self-efficacy for symptom management (PROMIS) | 51.23 (6.84) | 49.86 (6.69) | 53.27 (8.08) | 52.35 (7.80) |
Marital status missing for one survivor in the control group
Education data only available for N = 12 (6 + 6)
Income data available for N = 28 (17+ 11)
Three caregivers in the intervention arm self-identified as non-Hispanic
Three caregivers (2 + 1) identified other language preference
Fruit and vegetable intake included legumes and excluded French fries
Fig. 1.

Baseline symptom prevalence for survivors and caregivers at a grade of 4 or higher (out of 10)
Feasibility
Of 115 Latina cancer survivors approached for participation, 43 were ineligible (21 failed symptom screening and 22 could not identify a partner). Twenty-seven survivors refused to participate either because they were not interested (n = 10), did not return the baseline assessment forms (n = 10), or were too sick (n = 7) (Fig. 2). The consent rate of 45 out of 72 eligible dyads (63%) exceeded the planned 50% benchmark for the dyadic consent rate. After consenting to participate in the study, 45 dyads were randomized: 28 dyads to the intervention and 17 dyads to the control group (Fig. 2). In the intervention arm, five dyads attrited prior to completing baseline forms and 11 dyads after baseline. Most common reasons for attrition included family members becoming ill and no longer being interested. Of the survivors who completed the intervention, more than 80% completed all coaching sessions. For the control condition, four dyads did not complete the post-interview, most commonly citing no longer being interested in participating (Fig. 2).
Fig. 2.

CONSORT
Physical activity, diet, and symptoms at baseline
At baseline, mean minutes per week of physical activity was 85 for survivors and 197 for caregivers. The mean for survivors was markedly below the recommended 150 min per week. Average fiber, vegetable, and fruit intake was suboptimal at 16 g, < 1.6 cups, and < 1.2 cups per day, respectively, for both survivors and caregivers, well below the recommended amounts of 25–30 g, 2–3 cups, and 1.5–2 cups per day, respectively [74]. Global symptom distress for survivors was five on a 1–10 scale, reflecting bothersome symptom burden in the posttreatment period (Table 2).
Table 2.
Post-intervention outcomes by study group. Effect sizes of 1/3 or higher are bolded (differences between LS means of at least 1/3 of the adjusted standard deviation)
| Outcome | Survivors |
Caregivers |
||||
|---|---|---|---|---|---|---|
| Intervention, LS mean (SE) | Control, LS mean (SE) | P value Adj. effect size | Intervention, LS mean (SE) | Control, LS mean (SE) | P value Adj. effect size | |
|
| ||||||
| Fiber intake (g/day) | 17.87 (0.66) | 16.95 (0.73) | 0.36 0.40 |
16.57 (1.28) | 17.26 (1.21) | 0.71 0.18 |
| Sugar (g/day) | 11.36 (0.38) | 12.03 (0.41) | 0.25 0.51 |
12.41 (0.74) | 13.82 (0.71) | 0.19 0.60 |
| Sugar from sugar-sweetened beverages (g/day) | 4.14 (0.22) | 4.23 (0.24) | 0.76 0.13 |
4.94 (0.38) | 5.73 (0.36) | 0.15 0.65 |
| Fruit and Vegetable intake (cup equivalents/day) | 2.99 (0.16) | 2.69 (0.17) | 0.22 0.55 |
2.41 (0.18) | 2.59 (0.17) | 0.48 0.32 |
| Vegetable intake (cup equivalents/day) | 1.79 (0.09) | 1.56 (0.10) | 0.11 0.72 |
1.52 (0.09) | 1.63 (0.08) | 0.36 0.41 |
| Fruit intake (cup equivalents/day) | 1.15 (0.07) | 1.08 (0.07) | 0.52 0.28 |
0.90 (0.12) | 0.94 (0.12) | 0.85 0.09 |
| Physical activity (min/week) | 205.79 (56.91) | 124.30 (62.60) | 0.36 0.42 |
167.39 (49.36) | 237.83 (46.94) | 0.33 −0.46 |
| Summed severity index | 14.53 (3.60) | 23.46 (3.96) | 0.12 0.74 |
13.05 (3.55) | 10.40 (3.38) | 0.61 0.24 |
| Global symptom distress | 3.07 (0.85) | 3.53 (0.90) | 0.73 0.17 |
2.96 (0.56) | 2.64 (0.53) | 0.69 0.19 |
| Self-efficacy for symptom management (PROMIS) | 55.37 (2.35) | 55.37 (2.46) | 0.99 0.01 |
55.15 (2.29) | 54.11 (2.07) | 0.74 0.15 |
Meets PA guidelines post-intervention
Survivors: intervention 5 out 12 (42%), control 3/10 (30%)
Caregivers: intervention 6 out of 10 (60%), control 6/11 (55%)
Lifestyle behavior goal attainment (intervention arm only)
From the first intervention call to the last intervention call, mean scores for goal attainment of lifestyle behaviors improved from 4.0 (SD 0.8) to 4.5 (SD 0.8) for survivors and from 4.2 (SD 1.3) to 4.4 (SD 1.3) for caregivers on a scale from 1 (did not attain goal) to 5 (goal attainment).
Acceptability
The majority of dyads were satisfied with the program, and of the 23 dyads that started the intervention, 86% (n = 20) completed at least 75% of sessions. The average number of coaching sessions among dyads who completed the program were 9.3 (SD 3.2) and 9.0 (SD 4.3) for survivors and caregivers, respectively. The sessions were completed over 12 weeks on average with a maximum of 15 weeks. In exit interviews, both survivors and caregivers expressed satisfaction with the intervention and praised the health coaches who were perceived as knowledgeable and understanding of their needs. Participants indicated they appreciated the convenience of the phone-based intervention and the ability to converse with their coaches and receive materials in English or Spanish. Some survivors did voice frustration with getting the Fitbit® device setup on the internet and required some additional help by study staff.
Preliminary efficacy
For survivors, medium-to-large effect sizes were observed post-intervention for a number of the lifestyle goals, including servings of total fruit and vegetables (d = 0.55), vegetables (d = 0.72), and sugar intake (d = 0.51). Medium, clinically significant effect sizes were found for total minutes of physical activity per week and grams of fiber intake per day, d = 0.42 and d = 0.40, respectively. Medium-to-large intervention effects were found for improved summed symptom severity for survivors (d = 0.74); however the effects for the global symptom distress and self-efficacy for managing symptoms were small, d = 0.17 and 0.01, respectively.
For caregivers, no intervention effect was found for any of the symptom measures. Medium-to-large intervention effects were observed for both total sugar intake (d = − 0.60) and sugar intake from sugar-sweetened beverages (d = − 0.65) and a medium intervention effect for vegetable intake (d = 0.41).
Discussion
This pilot study of 45 Latina cancer survivor and caregiver dyads yielded important information on feasibility, acceptability, and preliminary effects of a 12-week integrated symptom management and lifestyle intervention to improve several vital survivor outcomes. The prevalence of symptoms requiring intervention per NCCN guidelines was relatively high, supporting the need to integrate strategies for symptom management and lifestyle behaviors. Most notably, symptom severity improved as well as physical activity, total consumption of fruits and vegetables, and consumption of vegetables, fiber, and sugar in survivors; all are important in promoting overall well-being in this particularly vulnerable population. Caregivers also experienced a benefit of improved diet.
Average fruit, vegetable, and fiber daily intakes and minutes of physical activity were significantly lower than recommended values at baseline, with no participants meeting both the diet and physical activity guidelines. Our results are similar to others who have reported low intake of fruits and vegetables and low physical activity in Latinx cancer survivors. Nayak et al. reported that among Latinx cancer survivors, less than 20% were meeting the ACS guidelines on nutrition and physical activity [73]. In our study, the average minutes of physical activity per week for survivors at baseline was 85. These values are more than double that of baseline values of a 16-week exercise intervention for Mexican American and Puerto Rican breast cancer survivors who reported on average 34.5 min of exercise per day [75]. These differences may be attributed to differences in geographic regions, Texas and Puerto Rico versus Southern Arizona and Northern Mexico, and a difference in assessment tools. Noteworthy, at baseline, the caregivers participating in this study reported above the recommended levels of 150 min of moderate to vigorous physical activity per week (Table 1); this may explain the lack of change observed in the intervention arm.
In this study, survivors and caregivers were experiencing high levels of commonly co-occurring symptoms, most prevalently sleep disturbance, pain, anxiety, depression, and energy/fatigue, also known as the SPADE symptoms. [76] These SPADE symptoms are all barriers to information processing and, thus as we hypothesize, barriers to the adoption and long-term engagement with healthy lifestyle behaviors. While the SMLI intervention addressed all symptoms, self-management strategies need to be enacted to begin reducing these SPADE symptoms. Lifestyle components of the intervention specifically addressed sleep, because management of sleep is associated with intervention success for other symptoms such as pain [77]. Pain, depression, and anxiety co-occur [78, 79], and when pain is addressed together with mood within an intervention, larger improvements are observed [80].
Although overall symptom severity and lifestyle behaviors improved for women randomized to the intervention and goal attainment for these lifestyle behaviors continued to improve, self-efficacy for symptom management remained unchanged. The SMLI sessions were led by lifestyle behavior intervention health coaches whose training was predominantly focused on diet and physical activity. Although the strategies from the symptom management handbook were discussed when symptoms were elevated, the actual SMART goals were set around the lifestyle behaviors and not symptom management. Because the focus of the intervention was on the attainment of these cancer-preventive lifestyle behaviors, in hindsight, it is not surprising that self-efficacy for symptom management did not change.
Importantly in this study, Latina survivors in the intervention experienced improvement in symptom severity and substantial improvements in both dietary and activity behaviors. These results are supported by secondary analyses of other lifestyle interventions for cancer survivors where in moderate physical activity was found to be beneficial in the management of sleep disturbance [34, 36, 38], depression, and anxiety [39–41], and dietary changes were associated with improved gastrointestinal symptoms [42, 43]. Although not directly tested in this intervention, there is a dose response between the number of cancer prevention lifestyle guidelines met and quality of life [8, 13]. Thus, there is reason to expect quality of life to also improve with an integrated symptom management and lifestyle behavior intervention such as the SMLI delivered in Nuestra Salud.
Caregivers become involved in complex care activities [81] for an average of 14 months from the time of diagnosis [82, 83]. Unique to this study population, the cultural values of familism (priority of family obligation) and collectivism (group over individual goals) are expressed by the high value and expectations that Latinx people place on support from their social networks during illness [84, 85]. Hispanics rely on family support more than non-Hispanic whites, have lower friend support, and experience greater obligation to provide assistance during illness than non-Hispanic whites [79, 86, 87]. For these reasons, involvement of caregivers of Latinx cancer survivors is particularly significant.
Integration of symptom management with lifestyle coaching can have significant positive synergy. Survivors can be motivated to enact lifestyle changes to see the immediate benefit of symptom reduction. While adherence to the ACS guidelines on nutrition and physical activity for cancer prevention [7] may reduce the risk of cancer recurrence and co-morbid chronic conditions such as obesity and type II diabetes, these are long-term targets. In contrast, symptom relief is an immediate benefit that can motivate survivors to change their diet and/or increase physical activity. This uniquely positions these symptoms as an important immediate target that survivors can address by enacting healthy lifestyle behaviors.
The study was not without limitations. Although our sample size was adequate to evaluate feasibility and acceptability, it was not able to test the effectiveness of the SMLI intervention. In addition, attrition was high prior to the start of and throughout the intervention, with caregivers posing more of a challenge to maintain on study than survivors. In this study, the mean time since diagnosis ranged from 9 to 11 years, and caregivers may no longer have identified as a support person in the same way as they had closer to the time of initial diagnosis and treatment. Fitbits® were provided to both members of the dyad participating in the intervention: While these activity monitors were useful in helping to recruit participants, there was restricted uptake of use, particularly by survivors, limiting the ability to evaluate their use as an additional measure of physical activity and sleep. Latinas in this study indicated that complicated setup of the device and lack of smart devices to load the Fitbit® application prohibited their use. The study recruited from areas along the US-Mexico border and this provided a few challenges as some members of the dyad resided in Northern Mexico. Specifically, in one scenario, participant materials had to be mailed to a friend residing in the USA and then transported to the participant in Mexico. On two separate occasions, in an effort to meet the needs of the participants, study staff attended support groups along the US-Mexico border to collect forms, troubleshoot Fitbits®, and deliver gift cards. Some of the sessions were completed using the WhatsApp instant messenger platform instead of the eHIP platform because of the high use of WhatsApp within this population. The Nuestra Salud study was designed specifically for Latina cancer survivors and their caregivers; however, the majority of participants were from Southern Arizona and Northern Mexico, and these results may not generalize to others in the Latinx community from different geographical areas. Self-selection bias may also have occurred with participants being potentially more favorably predisposed to receiving and acting on this information than those who refused.
Even with these limitations, this project tested the Nuestra Salud intervention with a rigorous study design, enrolled a vulnerable, minority population of survivors and their caregivers, and established the potential of an integrated symptom management and lifestyle behavior intervention designed to reduce symptoms and improve cancer-preventive behaviors. Future studies need to address the issue of attrition within this population and work to not only tailor the intervention both linguistically and culturally but to develop appropriate retention strategies. Bernard-Davila et al. identified factors among Hispanic breast cancer survivors, including employment status, perception of research being costly to participate in, and only speaking/reading Spanish, as reasons for not participating in clinical trials [88]. These factors should be considered when designing the study and training recruiters and study personnel.
Studies such as Nuestra Salud that include the caregiver as part of a dyadic lifestyle intervention are needed and hold promise for improving health behaviors of survivors and their informal caregivers. Using the telephone for delivery of the intervention reduces costs and increases reach and scalability. Given these preliminary results, the effectiveness of this telephone-based intervention with high potential for dissemination should be demonstrated in adequately powered studies. Larger studies are needed wherein the interdependence between members of the dyad and enactment of lifestyle behaviors can be evaluated. Results will provide specific guidance on how a telephone-based, integrated symptom management and lifestyle behavior intervention can address and promote adherence to healthy lifestyle behaviors for both survivors and caregivers.
Funding
This work was supported by the American Cancer Society Institutional Research Grant (128749-IRG-16-124-37-IRG) (Crane) and Behavioral Measurement and Interventions Shared Resource at the University of Arizona Cancer Center Support Grant National Cancer Institute (P30 CA023074).
Footnotes
Conflict of interest The authors declare that they have no conflict of interest.
Ethical approval All procedures performed in the study involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent Informed consent was obtained from all individual participants included in the study.
References
- 1.Noe-Bustamante LL, Lopez MH, Krogstad JM. U.S. Hispanic population surpassed 60 million in 2019, but growth has slowed. Pew Research Center. https://www.pewresearch.org/fact-tank/2020/07/07/u-s-hispanic-population-surpassed-60-million-in-2019-but-growth-has-slowed/. Published 2020, July 7. Accessed Aug 8, 2020. [Google Scholar]
- 2.Society AC. Cancer Facts & Figures for Hispanics/Latinos 2018–2020. Atlanta: American Cancer Society, Inc.; 2018. [Google Scholar]
- 3.Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. [DOI] [PubMed] [Google Scholar]
- 4.Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015–2016. NCHS Data Brief 2017(288):1–8. [PubMed] [Google Scholar]
- 5.Islami F, Goding Sauer A, Miller KD, Siegel RL, Fedewa SA, Jacobs EJ, et al. Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States. CA Cancer J Clin. 2018;68(1):31–54. [DOI] [PubMed] [Google Scholar]
- 6.Song M, Giovannucci E. Preventable incidence and mortality of carcinoma associated with lifestyle factors among white adults in the United States. JAMA Oncol. 2016; 2(9):1154–61 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kushi LH, Doyle C, McCullough M, Rock CL, Demark-Wahnefried W, Bandera EV, et al. American Cancer Society guidelines on nutrition and physical activity for cancer prevention. CA Cancer J Clin. 2012;62(1):30–67. [DOI] [PubMed] [Google Scholar]
- 8.Blanchard CM, Courneya KS, Stein K. Cancer survivors’ adherence to lifestyle behavior recommendations and associations with health-related quality of life: results from the American Cancer Society’s SCS-II. J Clin Oncol. 2008;26(13):2198–204. [DOI] [PubMed] [Google Scholar]
- 9.Inoue-Choi M, Robien K, Lazovich D. Adherence to the WCRF/AICR guidelines for cancer prevention is associated with lower mortality among older female cancer survivors. Cancer Epidemiol Prev Biomarkers. 2013;22(5):792–802. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kohler LN, Garcia DO, Harris RB, Oren E, Roe DJ, Jacobs ET. Adherence to diet and physical activity cancer prevention guidelines and cancer outcomes: a systematic review. Cancer Epidemiol Biomark Prev. 2016;25(7):1018–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kohler LN, Harris RB, Oren E, Roe DJ, Lance P, Jacobs ET. Adherence to nutrition and physical activity cancer prevention guidelines and development of colorectal adenoma. Nutrients. 2018;10(8): [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Park SH, Knobf MT, Kerstetter J, Jeon S. Adherence to American Cancer Society guidelines on nutrition and physical activity in female cancer survivors: results from a randomized controlled trial (Yale Fitness Intervention Trial). Cancer Nurs. 2019;42(3):242–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Thomson CA, McCullough ML, Wertheim BC, et al. Nutrition and physical activity cancer prevention guidelines, cancer risk, and mortality in the women’s health initiative. Cancer Prev Res (Phila). 2014;7(1):42–53 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Greenlee H, Molmenti CL, Crew KD, et al. Survivorship care plans and adherence to lifestyle recommendations among breast cancer survivors. J Cancer Surviv. 2016;10(6):956–63. [DOI] [PubMed] [Google Scholar]
- 15.Byrd DA, Agurs-Collins T, Berrigan D, Lee R, Thompson FE. Racial and ethnic differences in dietary intake, physical activity, and body mass index (BMI) among cancer survivors: 2005 and 2010 National Health Interview Surveys (NHIS). J Racial Ethn Health Disparities. 2017;4(6):1138–46. [DOI] [PubMed] [Google Scholar]
- 16.Dieli-Conwright CM, Courneya KS, Demark-Wahnefried W, et al. Effects of aerobic and resistance exercise on metabolic syndrome, sarcopenic obesity, and circulating biomarkers in overweight or obese survivors of breast cancer: a randomized controlled trial. J Clin Oncol. 2018;36(9):875–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Dieli-Conwright CM, Sweeney FC, Courneya KS, et al. Hispanic ethnicity as a moderator of the effects of aerobic and resistance exercise in survivors of breast cancer. Cancer. 2019;125(6):910–20 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Morey MC, Snyder DC, Sloane R, Cohen HJ, Peterson B, Hartman TJ, et al. Effects of home-based diet and exercise on functional outcomes among older, Overweight Long-term Cancer Survivors. JAMA. 2009;301(18):1883–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pierce JP, Natarajan L, Caan BJ, Parker BA, Greenberg ER, Flatt SW, et al. Influence of a diet very high in vegetables, fruit, and fiber and low in fat on prognosis following treatment for breast cancer. JAMA. 2007;298(3):289–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Spark LC, Reeves MM, Fjeldsoe BS, Eakin EG. Physical activity and/or dietary interventions in breast cancer survivors: a systematic review of the maintenance of outcomes. J Cancer Surviv. 2013;7(1):74–82. [DOI] [PubMed] [Google Scholar]
- 21.Cleeland CS, Zhao F, Chang VT, et al. The symptom burden of cancer: evidence for a core set of cancer-related and treatment-related symptoms from the Eastern Cooperative Oncology Group Symptom Outcomes and Practice Patterns study. Cancer. 2013;119(24):4333–40 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Mendoza TR, Wang XS, Lu C, et al. Measuring the symptom burden of lung cancer: the validity and utility of the lung cancer module of the M. D. Anderson Symptom Inventory. Oncologist. 2011;16(2):217–27 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Alfano CM, Smith AW, Irwin ML, et al. Physical activity, long-term symptoms, and physical health-related quality of life among breast cancer survivors: a prospective analysis. J Cancer Surviv. 2007;1(2):116–28 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Cho MH, Dodd MJ, Cooper BA, Miaskowski C. Comparisons of exercise dose and symptom severity between exercisers and nonexercisers in women during and after cancer treatment. J Pain Symptom Manag. 2012;43(5):842–54 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Hardcastle SJ, Maxwell-Smith C, Kamarova S, Lamb S, Millar L, Cohen PA. Factors influencing non-participation in an exercise program and attitudes towards physical activity amongst cancer survivors. Support Care Cancer. 2018;26(4):1289–95. [DOI] [PubMed] [Google Scholar]
- 26.Stanton AL, Bernaards CA, Ganz PA. The BCPT symptom scales: a measure of physical symptoms for women diagnosed with or at risk for breast cancer. J Natl Cancer Inst. 2005;97(6):448–56. [DOI] [PubMed] [Google Scholar]
- 27.Howard-Anderson J, Ganz PA, Bower JE, Stanton AL. Quality of life, fertility concerns, and behavioral health outcomes in younger breast cancer survivors: a systematic review. J Natl Cancer Inst. 2012;104(5):386–405. [DOI] [PubMed] [Google Scholar]
- 28.Ganz PA, Kwan L, Stanton AL, Krupnick JL, Rowland JH, Meyerowitz BE, et al. Quality of life at the end of primary treatment of breast cancer: first results from the moving beyond cancer randomized trial. J Natl Cancer Inst. 2004;96(5):376–87. [DOI] [PubMed] [Google Scholar]
- 29.Stanton AL, Ganz PA, Kwan L, Meyerowitz BE, Bower JE, Krupnick JL, et al. Outcomes from the moving beyond cancer psychoeducational, randomized, controlled trial with breast cancer patients. J Clin Oncol. 2005;23(25):6009–18. [DOI] [PubMed] [Google Scholar]
- 30.Bower JE, Ganz PA, Irwin MR, Kwan L, Breen EC, Cole SW. Inflammation and behavioral symptoms after breast cancer treatment: do fatigue, depression, and sleep disturbance share a common underlying mechanism? J Clin Oncol. 2011;29(26):3517–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Owen JE, O’Carroll Bantum E, Pagano IS, Stanton A. Randomized trial of a social networking intervention for cancer-related distress. Ann Behav Med. 2017;51(5):661–72 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Badger TA, Segrin C, Hepworth JT, Pasvogel A, Weihs K, Lopez AM. Telephone-delivered health education and interpersonal counseling improve quality of life for Latinas with breast cancer and their supportive partners. Psycho-Oncology. 2013;22(5):1035–42. [DOI] [PubMed] [Google Scholar]
- 33.Baruth M, Wilcox S, Ananian CD, Heiney S. Effects of home-based walking on quality of life and fatigue outcomes in early stage breast cancer survivors: a 12-week pilot study. J Phys Act Health. 2015;12(s1):S110–8. [DOI] [PubMed] [Google Scholar]
- 34.Cheville AL, Kollasch J, Vandenberg J, Shen T, Grothey A, Gamble G, et al. A home-based exercise program to improve function, fatigue, and sleep quality in patients with stage IV lung and colorectal cancer: a randomized controlled trial. J Pain Symptom Manag. 2013;45(5):811–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kampshoff CS, Chinapaw MJ, Brug J, et al. Randomized controlled trial of the effects of high intensity and low-to-moderate intensity exercise on physical fitness and fatigue in cancer survivors: results of the Resistance and Endurance exercise After ChemoTherapy (REACT) study. BMC Med. 2015;13(1):275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Velthuis M, Agasi-Idenburg S, Aufdemkampe G, Wittink H. The effect of physical exercise on cancer-related fatigue during cancer treatment: a meta-analysis of randomised controlled trials. Clin Oncol. 2010;22(3):208–21. [DOI] [PubMed] [Google Scholar]
- 37.Kwiatkowski F, Mouret-Reynier M, Duclos M, Leger-Enreille A, Bridon F, Hahn T, et al. Long term improved quality of life by a 2-week group physical and educational intervention shortly after breast cancer chemotherapy completion. Results of the ‘Programme of Accompanying women after breast Cancer treatment completion in Thermal resorts’(PACThe) randomised clinical trial of 251 patients. Eur J Cancer. 2013;49(7):1530–8. [DOI] [PubMed] [Google Scholar]
- 38.Stevinson C, Steed H, Faught W, Tonkin K, Vallance JK, Ladha AB, et al. Physical activity in ovarian cancer survivors: associations with fatigue, sleep, and psychosocial functioning. Int J Gynecol Cancer. 2009;19(1):73–8. [DOI] [PubMed] [Google Scholar]
- 39.Cramer H, Pokhrel B, Fester C, Meier B, Gass F, Lauche R, et al. A randomized controlled bicenter trial of yoga for patients with colorectal cancer. Psycho-Oncology. 2016;25(4):412–20. [DOI] [PubMed] [Google Scholar]
- 40.Rao MR, Raghuram N, Nagendra H, et al. Anxiolytic effects of a yoga program in early breast cancer patients undergoing conventional treatment: a randomized controlled trial. Complement Ther Med. 2009;17(1):1–8. [DOI] [PubMed] [Google Scholar]
- 41.Courneya KS, McKenzie D, Gelmon KA, et al. A multicenter randomized trial of the effects of exercise dose and type on psychosocial distress in breast cancer patients undergoing chemotherapy. Cancer Epidemiol Prev Biomarkers. 2014:cebp. 1163.2013. [DOI] [PubMed] [Google Scholar]
- 42.Sun V, Grant M, McMullen CK, et al. Surviving colorectal cancer: long-term, persistent ostomy-specific concerns and adaptations. J Wound Ostomy Continence Nurs. 2013;40(1):61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Ravasco P, Monteiro-Grillo I, Camilo M. Individualized nutrition intervention is of major benefit to colorectal cancer patients: long-term follow-up of a randomized controlled trial of nutritional therapy. Am J Clin Nutr. 2012;96(6):1346–53. [DOI] [PubMed] [Google Scholar]
- 44.Zick SM, Colacino J, Cornellier M, Khabir T, Surnow K, Djuric Z. Fatigue reduction diet in breast cancer survivors: a pilot randomized clinical trial. Breast Cancer Res Treat. 2017;161(2):299–310. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Harding R, Epiphaniou E, Hamilton D, Bridger S, Robinson V, George R, et al. What are the perceived needs and challenges of informal caregivers in home cancer palliative care? Qualitative data to construct a feasible psycho-educational intervention. Support Care Cancer. 2012;20(9):1975–82. [DOI] [PubMed] [Google Scholar]
- 46.Hartmann M, Bäzner E, Wild B, Eisler I, Herzog W. Effects of interventions involving the family in the treatment of adult patients with chronic physical diseases: a meta-analysis. Psychother Psychosom. 2010;79(3):136–48. [DOI] [PubMed] [Google Scholar]
- 47.Martire LM, Lustig AP, Schulz R, Miller GE, Helgeson VS. Is it beneficial to involve a family member? A meta-analysis of psychosocial interventions for chronic illness. Health Psychol. 2004;23(6):599–611. [DOI] [PubMed] [Google Scholar]
- 48.Martire LM, Helgeson VS. Close relationships and the management of chronic illness: associations and interventions. Am Psychol. 2017;72(6):601–12 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Shields CG, Finley MA, Chawla N, Meadors WP. Couple and family interventions in health problems. J Marital Fam Ther. 2012;38(1):265–80. [DOI] [PubMed] [Google Scholar]
- 50.Beesley VL, Janda M, Eakin EG, Auster JF, Chambers SK, Aitken JF, et al. Gynecological cancer survivors and community support services: referral, awareness, utilization and satisfaction. Psycho-Oncology. 2010;19(1):54–61. [DOI] [PubMed] [Google Scholar]
- 51.Demark-Wahnefried W, Aziz NM, Rowland JH, Pinto BM. Riding the crest of the teachable moment: promoting long-term health after the diagnosis of cancer. J Clin Oncol. 2005;23(24):5814–30 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Ganz PA. A teachable moment for oncologists: cancer survivors, 10 million strong and growing! J Clin Oncol. 2005;23(24):5458–60. [DOI] [PubMed] [Google Scholar]
- 53.Chandrasekar D, Tribett E, Ramchandran K. Integrated palliative care and oncologic care in non-small-cell lung cancer. Curr Treat Options in Oncol. 2016;17(5):23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.NCCN Clinical practice guidelines in oncology. Palliative Care. National Comprehensive Cancer Network;2020. [DOI] [PubMed] [Google Scholar]
- 55.Bandura AJEC NJ. Social foundations of thought and action. 1986;1986. [Google Scholar]
- 56.Loprinzi PD, Cardinal BJ. Self-efficacy mediates the relationship between behavioral processes of change and physical activity in older breast cancer survivors. Breast Cancer. 2013;20(1):47–52. [DOI] [PubMed] [Google Scholar]
- 57.Stacey FG, James EL, Chapman K, Courneya KS, Lubans DR. A systematic review and meta-analysis of social cognitive theory-based physical activity and/or nutrition behavior change interventions for cancer survivors. J Cancer Surviv. 2015;9(2):305–38 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Packel LB, Prehn AW, Anderson CL, Fisher PL. Factors influencing physical activity behaviors in colorectal cancer survivors. Am J Health Promot. 2015;30(2):85–92. [DOI] [PubMed] [Google Scholar]
- 59.Crane TE, Parizek D, Eddy N, et al. Ehealth and intervention platform. In: Google Patents; 2018. [Google Scholar]
- 60.Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Frongillo EA Jr. Validation of measures of food insecurity and hunger. J Nutr. 1999;129(2S Suppl):506s–9s. [DOI] [PubMed] [Google Scholar]
- 63.Gany F, Lee T, Ramirez J, et al. Do our patients have enough to eat?: food insecurity among urban low-income cancer patients. J Health Care Poor Underserved. 2014;25(3):1153–68 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Thompson FE, Subar AF, Smith AF, et al. Fruit and vegetable assessment: performance of 2 new short instruments and a food frequency questionnaire. J Am Diet Assoc. 2002;102(12):1764–72. [DOI] [PubMed] [Google Scholar]
- 65.Wakimoto P, Block G, Mandel S, Medina N. Development and reliability of brief dietary assessment tools for Hispanics. Prev Chronic Dis. 2006;3(3):A95. [PMC free article] [PubMed] [Google Scholar]
- 66.Meyer AM, Evenson KR, Morimoto L, Siscovick D, White E. Test-retest reliability of the Women’s Health Initiative physical activity questionnaire. Med Sci Sports Exerc. 2009;41(3):530–8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Badger TA, Segrin C, Meek P. Development and validation of an instrument for rapidly assessing symptoms: the general symptom distress scale. J Pain Symptom Manag. 2011;41(3):535–48 3062688. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Correia H Spanish translations of PROMIS instruments. Northwestern University, Dept of Medical Social Sciences. 2011. [Google Scholar]
- 69.Holmstrom AJ, Wyatt GK, Sikorskii A, Musatics C, Stolz E, Havener N. Dyadic recruitment in complementary therapy studies: experience from a clinical trial of caregiver-delivered reflexology. Appl Nurs Res. 2016;29:136–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Voils CI, King HA, Maciejewski ML, Allen KD, Yancy WS Jr, Shaffer JA. Approaches for informing optimal dose of behavioral interventions. Ann Behav Med. 2014;48(3):392–401 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Bandura A, Freeman W, Lightsey R. Self-efficacy: the exercise of control. In: Springer; 1999. [Google Scholar]
- 72.Sloan JA, Cella D, Hays RD. Clinical significance of patient-reported questionnaire data: another step toward consensus. J Clin Epidemiol. 2005;58(12):1217–9. [DOI] [PubMed] [Google Scholar]
- 73.Nayak P, Paxton RJ, Holmes H, Nguyen HT, Elting LS. Racial and ethnic differences in health behaviors among cancer survivors. Am J Prev Med. 2015;48(6):729–36. [DOI] [PubMed] [Google Scholar]
- 74.U.S. Department of Health and Human Services USDoA. 2015–2020 Dietary Guidelines for Americans 2015. [Google Scholar]
- 75.Mama SK, Song J, Ortiz A, et al. Longitudinal social cognitive influences on physical activity and sedentary time in Hispanic breast cancer survivors. Psychooncology. 2017;26(2):214–21 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Kroenke K Studying symptoms: sampling and measurement issues. Ann Intern Med. 2001;134(9 Pt 2):844–53. [DOI] [PubMed] [Google Scholar]
- 77.Koffel E, Kats AM, Kroenke K, et al. Sleep disturbance predicts less improvement in pain outcomes: secondary analysis of the SPACE randomized clinical trial. Pain Med. 2020;21(6):1162–7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Crane TE, Badger TA, Sikorskii A, Segrin C, Hsu CH, Rosenfeld AG. Trajectories of depression and anxiety in Latina breast cancer survivors. Oncol N urs Forum. 2019;46(2):217–27 [DOI] [PubMed] [Google Scholar]
- 79.Badger TA, Segrin C, Sikorskii A, et al. Randomized controlled trial of supportive care interventions to manage psychological distress and symptoms in Latinas with breast cancer and their informal caregivers. Psychol Health. 2020;35(1):87–106 [DOI] [PubMed] [Google Scholar]
- 80.Kroenke K, Baye F, Lourens SG, et al. Automated self-management (ASM) vs. ASM-enhanced collaborative care for chronic pain and mood symptoms: the CAMMPS randomized clinical trial. J Gen Intern Med. 2019;34(9):1806–14 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Fletcher BS, Miaskowski C, Given B, Schumacher K. The cancer family caregiving experience: an updated and expanded conceptual model. Eur J Oncol Nurs. 2012;16(4):387–98 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.American Cancer Society. Family Caregivers. 2011. [Google Scholar]
- 83.Yabroff KR, Kim Y. Time costs associated with informal caregiving for cancer survivors. Cancer. 2009;115(18 Suppl):4362–73. [DOI] [PubMed] [Google Scholar]
- 84.Gaugler JE, Kane RL, Kane RA, Newcomer R. Predictors of institutionalization in Latinos with dementia. J Cross Cult Gerontol. 2006;21(3–4):139–55. [DOI] [PubMed] [Google Scholar]
- 85.Marquez JA, Ramírez García JI. Family caregivers’ narratives of mental health treatment usage processes by their Latino adult relatives with serious and persistent mental illness. J Fam Psychol. 2013;27(3):398–408. [DOI] [PubMed] [Google Scholar]
- 86.John R, Resendiz R, De Vargas LW. Beyond familism?: familism as explicit motive for eldercare among Mexican American caregivers. J Cross Cult Gerontol. 1997;12(2):145–62. [DOI] [PubMed] [Google Scholar]
- 87.Jutagir DR, Gudenkauf LM, Stagl JM, et al. Ethnic differences in types of social support from multiple sources after breast cancer surgery. Ethn Health. 2016;21(5):411–25 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Bernard-Davila B, Aycinena AC, Richardson J, et al. Barriers and facilitators to recruitment to a culturally-based dietary intervention among urban Hispanic breast cancer survivors. J Racial Ethn Health Disparities. 2015;2(2):244–55 [DOI] [PMC free article] [PubMed] [Google Scholar]
