Abstract
Background
Black and Hispanic cancer survivors exposed to cardiotoxic therapies are at higher risk for cardiovascular events than non-Hispanic White survivors, attributed to greater cardiovascular risk factors and lower physical activity.
Objectives
This study sought to determine the effect of a remotely delivered and behaviorally designed gamification intervention vs attention control on physical activity in Black and Hispanic cancer survivors with cardiovascular risk factors.
Methods
Between May 2022 and February 2025, Black and Hispanic breast and prostate cancer survivors who had received cardiotoxic cancer therapy and had ≥1 cardiovascular risk factor were enrolled in a randomized clinical trial with a 24-week intervention and 12-week postintervention period. Participants received a wearable device to track daily steps, established a baseline, selected a step goal increase, and were assigned to attention control (n = 76) or gamification (n = 74). The primary outcome was change in mean daily steps from baseline through the intervention period.
Results
Mean participant age was 64 years; 81% women, 64% Black, and 35% Hispanic. Gamification arm participants had a greater change from baseline in mean daily steps than control participants during the intervention period (+759; 95% CI: 209-1,309; P = 0.007) and follow-up (+581; 95% CI: −47 to 1,208; P = 0.070), and a greater increase in weekly minutes of moderate-vigorous physical activity during intervention (+16; 95% CI: 4-29; P = 0.010) and follow-up (+11; 95% CI: 0-22; P = 0.048).
Conclusions
Gamification increased physical activity compared with attention control in Black and Hispanic cancer survivors, and represents a scalable intervention to reduce cardiovascular risk in this high-risk population (RCT of Strategies to Augment Physical Activity in Black and Hispanic Breast and Prostate Cancer Survivors [ALLSTAR]; NCT05176756)
Key Words: behavioral economics, behavioral risk factors, breast cancer, cancer survivorship, cardio-oncology, cardiovascular diseases, exercise, exercise oncology, gamification, health behavior, lifestyle risk factors, prevention, prostate cancer, randomized trial
Central Illustration
Improvements in cancer treatment strategies have resulted in a growing number of long-term survivors who are expected to live well beyond their cancer diagnosis.1 In these survivors, the burden of de novo cardiovascular disease is substantial, affecting both the quality and quantity of survival.2,3 Survivors of breast and prostate cancer, the most common noncutaneous cancers, may be at especially high risk of cardiovascular disease because of treatments that increase downstream risk of cardiovascular disease.4,5 In observational studies of cancer survivors, there are inverse dose-dependent associations between physical activity levels and the risk of major adverse cardiovascular events and cancer mortality.6,7 However, the majority of breast and prostate cancer survivors are less physically active than recommended by consensus guidelines.8 Compared with non-Hispanic White cancer survivors, Black and Hispanic cancer survivors have significantly higher risk of cardiovascular mortality,9 are more likely to report greater physical function limitations and poor health-related quality life,10 and are even more likely to be physically inactive.11,12
Behavioral economics is a scientific field of inquiry that uses principles from economics and psychology to understand and influence how individuals make decisions.13 Concepts from behavioral economics have been used to design gamification interventions, which apply game features like points and levels to the real world, that substantially increase physical activity in people at high risk for cardiovascular events.14,15 These successful gamification interventions did not require participants to use a separate application but were delivered entirely through automated text messages, facilitating long-term engagement and increasing scalability for clinical entities (health systems or health insurers) seeking to increase physical activity in their populations. Although these interventions have been successful, breast and prostate cancer survivors face barriers to engaging in physical activity that may change how they respond to a gamification intervention, including reduced levels of fitness, stamina, and strength related to prolonged inactivity during cancer treatment and the toxic effects of chemotherapy; the psychosocial stresses of cancer diagnosis, treatment, and recovery; and individual (eg, economic resources) and structural (eg, access to physical fitness facilities) social determinants of health.16 Adverse social determinants of health may be particularly pronounced among Black and Hispanic breast and prostate cancer survivors.17,18
We therefore tested the efficacy of a gamification intervention informed by behavioral economic theory, compared with an attention control that received messaging at a similar frequency, to increase physical activity in Black and Hispanic breast and prostate cancer survivors at increased risk for cardiovascular events.
Methods
ALLSTAR (Randomized Controlled Trial of Strategies to Augment Physical Activity in Black and Hispanic Breast and Prostate Cancer Survivors) was a randomized clinical trial conducted from May 2022 through February 2025, consisting of a 2-week run-in period, a 24-week intervention period, and a 12-week follow-up period. Details of the study design have been described elsewhere.19 The trial protocol (Supplemental Methods) was approved by the University of Pennsylvania and City of Hope Institutional Review Boards. The study was conducted using Way to Health, a research technology platform at the University of Pennsylvania.20
The data that support the findings of this study are available from the corresponding authors upon reasonable request. Drs. Fanaroff and Armenian had full access to all the data in the study and take responsibility for the study’s integrity and the data analysis.
Participants
Recruitment occurred at 2 sites in southeastern Pennsylvania and Southern California. Participants were eligible if the following applied: 1) they identified as Black or Hispanic; 2) they were diagnosed with breast or prostate cancer ≥2 years prior; 3) they were treated with cardiotoxic therapy; 4) they had ≥1 risk factor for cardiovascular disease; 5) they owned a smartphone or tablet running the Android or iOS operating system; and 6) they were able to read English or Spanish. We excluded participants with active malignancy or ongoing treatment with chemotherapy. Patients being treated with long-term suppressive hormonal therapy, such as aromatase inhibitors or androgen deprivation therapy, were eligible for inclusion. For complete inclusion and exclusion criteria, see Supplemental Table 1. Eligible participants were contacted by e-mail, physical mail, text message, phone, or in-person and offered enrollment. Participants visited the study website on the Way to Health platform to create an account, provide informed consent, and complete baseline survey assessments. Eligible participants were mailed a wrist-worn wearable device (Fitbit Charge 5 or 6), linked to the Way to Health platform for remote data collection.
Run-in period and randomization
The participants entered a 2-week run-in period, during which a baseline step count was estimated using the second week of data.14 Participants who did not complete the run-in phase or had baseline counts <1,000 or >7,500 steps/d were excluded from the trial. After the run-in period, each participant was informed of their baseline step count and asked to set a goal step increase of 1,500 to 3,000 steps greater than their baseline. This approach was selected to allow participants personalized goal setting,14 while nudging them to choose an ambitious but achievable target.
Participants were then randomized 1:1 to attention control or behaviorally designed gamification, stratified by site and baseline step count (<4,000, 4,000-5,999, 6,000-7,500 steps), using an electronic number generator and block sizes of 2 through the Way to Health platform. Allocation was concealed, and treatment assignment was done automatically by the Way to Health platform when participants reached the end of the baseline period, preventing recruiter influence. Treatment assignment was open-label, but patients were not explicitly informed about other treatment arms. Investigators, statisticians, and data analysts were blinded to arm assignments until the study and analysis were completed.
Interventions
Participants in the gamification arm were entered into a game that leverages insights from behavioral economics to address barriers to behavior change, and that has increased physical activity in several prior studies (Figure 1).14,15 After 24 weeks, participants no longer participated in the game but continued to receive a daily text message noting their step count the day prior for an additional 12 weeks. Screenshots of text messages sent to study participants are included in Supplemental Figure 1.
Figure 1.
Features of the Gamification Intervention
Participants randomized to gamification were awarded 70 points each week and lost 10 points each day that they did not meet their step count goal. At the end of each week, participants with ≥40 points moved up a level and those with <40 points moved down a level.
Participants randomized to attention control received a text message each day for 36 weeks telling them their step count from the prior day.
Outcome measures
The primary outcome was change in daily steps from baseline through the 24-week intervention period. Secondary outcomes included change in mean daily steps from baseline through the 12-week postintervention follow-up period; change in mean weekly minutes of moderate to vigorous physical activity (MVPA) from baseline through the intervention and follow-up periods; and change in physical function (as measured by the PROMIS [Patient-Reported Outcomes Measurement Information System] physical function 6b scale), cancer fatigue (as measured by the PROMIS cancer fatigue short form), and quality of life (as measured by EQ-5D-5L and visual analogue scale) from baseline through 24- and 36-week follow-up. Step data was captured by the wearable devices, automatically transferred to participants’ internet-connected devices via Bluetooth, and then automatically uploaded to the Penn Way to Health platform. Consistent with the 2018 Physical Activity Guidelines for Americans, MVPA was defined as any minute during which a participant took at least 100 steps.21 Surveys were completed by participants on the Way to Health platform at baseline, 24-week follow-up, and 36-week follow-up.
Statistical analysis
Baseline characteristics are presented as mean (SD), median with 25th to 75th percentiles (Q1-Q3), or count (percentage) dependent on the data distribution.
With 150 participants, we estimated 90% power to detect a difference between arms of 1,000 steps, assuming that the control arm had mean daily steps of 5,000, an SD of the difference between intervention and control arms of 2,000 steps,15 and a 10% dropout rate. All randomly assigned patients were included in the intention-to-treat analysis.
Data were missing for any day that the participant did not use the wearable device or upload data. Before conducting any analyses, we prespecified that the primary analysis would use multivariable imputation by chained equations for days with missing step values or values <1,000 steps/d, as in prior work, because daily step values <1,000 may not reflect full data capture.22,23 The following determinants were included in the imputation model: study arm, calendar month (fitted as a nominal variable), week of study, baseline daily steps, age, diagnosis (breast vs prostate cancer), site of enrollment, race/ethnicity, educational level, marital status, household income level, and self-reported health. We performed 20 sets of imputations and combined results using Rubin’s standard rules.24 In addition to the primary analysis, we performed 2 sensitivity analyses using collected data without imputation (days with missing step count or step count <1,000 are excluded); in the first sensitivity analysis, only days with missing step counts were excluded, and in the second we excluded days with missing step count or step count <1,000. As multiple imputation assumes that missingness is at random (ie, that days with missing step count or step count <1,000 are otherwise the same as days that the fitness tracker was worn), we performed a set of sensitivity analyses using a pattern-mixture framework, a method of accounting for informative missingness by assuming that participants’ physical activity was lower on days where step count was missing or <1,000.25 In this set of sensitivity analyses, we performed the following: 1) reduced imputed step counts by 25%, 50%, and 75% (setting any resulting values <1,000 to 1,000); 2) set step count at 1,000 for any day with step count missing; and 3) set step count at 0 for any day with step count missing.
The primary analysis fit generalized linear mixed-effects regression models to compare changes in daily steps and weekly minutes of MVPA between treatment arms, adjusting for each participant’s baseline measure, time from study start (as a continuous measure), calendar month, and participant random effects to account for repeated measures. We assumed that the relationship between time from study start and change from baseline in daily steps was approximately linear based on results from prior studies15 and visual inspection of step count data plotted against study week. As a sensitivity analysis, we produced fully adjusted models, adding age, diagnosis, site of enrollment, race, education, marital status, income, self-reported health, body mass index, and a month/site interaction term to the main adjusted model. For change from baseline in steps, we confirmed that these parameters were normally distributed by visual inspection of histograms and Q-Q plots, and obtained the difference in change from baseline step count between treatment arms for the intervention and follow-up periods as least squared means (LS-means). Model results are presented as the LS-mean difference with 95% CI. We report the effectiveness of the intervention for the primary outcome overall and key subgroups. For patient-reported outcomes, we used mixed-effects models, adjusting for each participant’s baseline measure, time from study start, and participant random effects.
Statistical analyses were performed using SAS version 9.4 (SAS Institute, Inc) in February 2025.
Results
Of 1,427 patients contacted and offered enrollment, 222 completed the informed consent process and all baseline surveys were mailed a wearable fitness tracker, and registered it on the Way to Health platform. Of these 222, 150 completed the baseline run-in period with step count >1,000 but <7,500, and were randomized to attention control (n = 76) or gamification (n = 74) (Figure 2). Demographics and clinical characteristics were similar between the groups (Table 1). The mean age of the cohort was 64.0 ± 9.6 years, 81.3% were women, 64.0% were Black, and 34.7% were Hispanic. Mean baseline daily step count was 4,675 ± 1,624 and mean goal step count increase was 1,743 ± 463.
Figure 2.
CONSORT Diagram
We attempted to contact 1,427 potentially eligible participants, of whom 222 were eligible, completed the informed consent process and all baseline questionnaires, and started the baseline period. Of these, 150 ultimately enrolled in the trial and 136 completed the intervention and follow-up periods.
Table 1.
Baseline Characteristics by Arm
| Control (n = 76) | Gamification (n = 74) | Overall (N = 150) | |
|---|---|---|---|
| Age, y | 63.8 ± 10 | 64.3 ± 9.3 | 64 ± 9.6 |
| Female | 59 (77.6) | 63 (85.1) | 122 (81.3) |
| Race/ethnicity | |||
| Black non-Hispanic | 47 (61.8) | 49 (66.2) | 96 (64) |
| Hispanic | 28 (36.8) | 24 (32.4) | 52 (34.7) |
| Black and Hispanic | 1 (1.3) | 0 (0) | 1 (0.7) |
| Other | 0 (0) | 1 (1.4) | 1 (0.7) |
| Education | |||
| Some high school or less | 4 (5.3) | 4 (5.4) | 8 (5.3) |
| High school graduate | 9 (11.8) | 11 (14.9) | 20 (13.3) |
| Some college or specialized training | 27 (35.5) | 23 (31.1) | 50 (33.3) |
| College graduate | 36 (47.4) | 36 (48.6) | 72 (48) |
| Marital status | |||
| Single | 21 (27.6) | 18 (24.3) | 39 (26) |
| Married | 36 (47.4) | 38 (51.4) | 74 (49.3) |
| Other | 19 (25) | 18 (24.3) | 37 (24.7) |
| Annual household income | |||
| <$50,000 | 34 (44.7) | 29 (39.2) | 63 (42) |
| $50,000-100,000 | 26 (34.2) | 21 (28.4) | 47 (31.3) |
| >$100,000 | 16 (21.1) | 24 (32.4) | 40 (26.7) |
| Language used for study communication | |||
| English | 71 (93.4) | 69 (93.2) | 140 (93.3) |
| Spanish | 5 (6.6) | 5 (6.8) | 10 (6.7) |
| Area Deprivation Index score | |||
| 0-25 (least deprived) | 27 (35.5) | 33 (44.6) | 60 (40) |
| 26-50 | 17 (22.4) | 19 (25.7) | 36 (24) |
| 51-75 | 13 (17.1) | 11 (14.9) | 24 (16) |
| 76-100 (most deprived) | 19 (25) | 11 (14.9) | 30 (20) |
| Self-reported health status | |||
| Excellent | 6 (7.9) | 1 (1.4) | 7 (4.7) |
| Very good | 17 (22.4) | 24 (32.4) | 41 (27.3) |
| Good | 39 (51.3) | 34 (45.9) | 73 (48.7) |
| Fair | 12 (15.8) | 14 (18.9) | 26 (17.3) |
| Poor | 2 (2.6) | 1 (1.4) | 3 (2) |
| Experience with wireless technology health tracking | |||
| None | 10 (13.2) | 8 (10.8) | 18 (12) |
| Little experience | 17 (22.4) | 18 (24.3) | 35 (23.3) |
| Moderate experience | 32 (42.1) | 31 (41.9) | 63 (42) |
| Very experienced | 17 (22.4) | 17 (23) | 34 (22.7) |
| BMI, kg/m2 | 32.5 ± 7.9 | 32.2 ± 6.4 | 32.4 ± 7.2 |
| Obesitya | 33 (43.4) | 33 (44.6) | 66 (44) |
| Diabetes | 22 (28.9) | 20 (27) | 42 (28) |
| Hyperlipidemia | 38 (50) | 38 (51.4) | 76 (50.7) |
| Hypertension | 44 (57.9) | 46 (62.2) | 90 (60) |
| Current smoking | 2 (2.6) | 3 (4.1) | 5 (3.3) |
| Prior myocardial infarction | 1 (1.3) | 2 (2.7) | 3 (2) |
| Coronary artery disease | 2 (2.6) | 2 (2.7) | 4 (2.7) |
| Prior stroke | 2 (2.6) | 0 (0) | 2 (1.3) |
| Heart failure | 1 (1.3) | 5 (6.8) | 6 (4) |
| Chronic obstructive pulmonary disease | 1 (1.3) | 3 (4.1) | 4 (2.7) |
| Chronic kidney disease | 3 (3.9) | 2 (2.7) | 5 (3.3) |
| Type of cancer | |||
| Breast | 60 (78.9) | 63 (85.1) | 123 (82) |
| Prostate | 16 (21.1) | 11 (14.9) | 27 (18) |
| Years from diagnosis to enrollment | 6.9 ± 4.6 | 8.7 ± 5.1 | 7.8 ± 4.9 |
| Treatment for breast cancer | |||
| Surgery | 59 (98.3) | 62 (98.4) | 121 (98.4) |
| Radiation | 50 (83.3) | 57 (90.5) | 107 (87) |
| Systemic therapies | |||
| Anthracyclines | 23 (38.3) | 29 (46) | 52 (42.3) |
| HER2-targed therapies | 13 (21.7) | 13 (20.6) | 26 (21.1) |
| Active cancer therapy at enrollmentb | 32 (53.3) | 21 (33.3) | 53 (43.1) |
| Years from last cancer therapy to enrollment | 3 ± 4.1 | 4.2 ± 4.9 | 3.6 ± 4.5 |
| Treatment for prostate cancer | |||
| Surgery | 9 (56.3) | 7 (63.6) | 16 (59.3) |
| Nonsurgical local therapy | |||
| External beam radiation | 11 (68.8) | 10 (90.9) | 21 (77.8) |
| Local therapy | 4 (25.1) | 0 (0) | 4 (14.8) |
| None | 2 (12.5) | 1 (9.1) | 3 (11.1) |
| Androgen deprivation therapy | 16 (100) | 11 (100) | 27 (100) |
| Active cancer therapy at enrollmentb | 3 (18.8) | 2 (18.2) | 5 (18.5) |
| Years from last cancer therapy to enrollment | 2.9 ± 3.3 | 2.4 ± 3 | 2.7 ± 3.1 |
| Baseline daily steps | 4,718 ± 1,521 | 4,630 ± 1,733 | 4,675 ± 1,624 |
| Baseline daily steps | 4,750 (3,450-5,950) | 4,550 (3,200-5,900) | 4,700 (3,400-5,900) |
| Step goal increase from baseline | 1,753 ± 458 | 1,732 ± 471 | 1,743 ± 463 |
| Step goal increase from baseline | 1,500 (1,500-1,900) | 1,500 (1,500-1,900) | 1,500 (1,500-1,900) |
Values are mean ± SD, n (%), or median (Q1-Q3).
Obesity defined as body mass index (BMI) >30 kg/m2.
Active cancer therapy included hormone therapy for breast-cancer survivors and androgen deprivation therapy for prostate cancer survivors.
During the intervention and follow-up periods, step data were missing or <1,000 on 18.6% of participant-days, similar to previous physical activity interventions (Supplemental Table 2). A total of 136 participants (90.7%) completed the entire 36-week study. Of 74 gamification arm participants, 71 (95.9%) were able to select a support partner and 67 (90.5%) participant-partner dyads completed a 3-way call with study staff at the start of the study. Overall, there were 13 adverse events in 13 participants, including 1 serious adverse event, an orthopedic injury in a gamification arm participant (Supplemental Table 3). No adverse reactions related to the interventions were reported throughout the entire trial.
Daily steps
Unadjusted mean daily step counts by week and study arm are shown in Figure 3A. Participants in the gamification arm took more steps per day and had a greater change from baseline than those in attention control throughout the entire trial. The mean increase in steps from baseline through 24-week follow-up was 993 ± 1,520 in the control arm and 1,756 ± 1,919 in the gamification arm. Through 12-week postintervention follow-up, the mean increase in steps from baseline was 752 ± 1,744 in the control arm and 1,344 ± 2,185 in the gamification arm. Gamification arm participants met their step goal on 56.2% of participant-days during the intervention period and 40.3% of participant-days during the intervention period (vs 33.8% and 28.0% of participant-days, respectively, in the control arm); they retained ≥40 points in 60.7% of participant-weeks during the intervention period, and 39 (52.7%) finished the intervention period in the gold or platinum level.
Figure 3.
Physical Activity Outcomes
(A) Change in mean daily steps by arm over the 36-week study period; (B) mean weekly minutes of moderate to vigorous physical activity. Shaded areas around each line represent the SEM. Participants in the gamification and attention control arms each had a large increase in physical activity measures between the baseline and intervention period, with a larger increase in the gamification arm which was maintained throughout the post-intervention follow-up period.
In the main adjusted model, there was a significantly greater difference in change from baseline in mean daily steps between gamification and control arms during the intervention period (+759; 95% CI: 209-1,309; P = 0.007), and a nonsignificantly greater difference during follow-up (+581; 95% CI: −47 to 1,208; P = 0.070) (Table 2). Results were similar in the fully adjusted model, although there was a statistically significant difference between gamification and control in both the intervention and follow-up periods. In sensitivity analyses that used collected data without multiple imputation, differences in mean daily steps between the control and gamification arms were larger and statistically significant over both the intervention and follow-up periods (Supplemental Tables 4 and 5). In pattern mixture sensitivity analyses, differences in change from baseline daily step count between the gamification and control arm were attenuated when participants were assumed to be less active on days with missing step count, but the difference between gamification and attention control over the intervention period remained statistically significant even when step count was set to 0 on days with missing step count, the most extreme possible assumption (Supplemental Table 6). Treatment effect for key subgroups are shown for the intervention and postintervention follow-up periods in Supplemental Figures 2 and 3; in these underpowered exploratory analyses, there were no significant treatment effect by subgroup interactions.
Table 2.
Daily Step Outcomes
| Control | Gamification | |
|---|---|---|
| Mean steps/d | 4,718 ± 1,521 | 4,630 ± 1,733 |
| Mean steps/d, wks 1-24 (intervention period) | 5,712 ± 2,159 | 6,386 ± 2,613 |
| Unadjusted mean change from baseline, steps/d, wks 1-24 (intervention period) | 993 ± 1,520 | 1,756 ± 1,919 |
| Main adjusted model | ||
| LS-mean difference vs control (95% CI) | — | 759 (209-1,309) |
| P value | — | 0.007 |
| Fully adjusted model | ||
| LS-mean difference vs control | — | 792 (260-1,323) |
| P value | — | 0.004 |
| Mean steps/d, wks 25-36 (postintervention follow-up period) | 5,470 ± 2,221 | 5,974 ± 2,741 |
| Unadjusted mean change from baseline, steps/d, wks 25-36 (postintervention follow-up period) | 752 ± 1,744 | 1,344 ± 2,185 |
| Main adjusted model | ||
| LS-mean difference vs control | — | 580 (−47 to 1,209) |
| P value | — | 0.070 |
| Fully adjusted model | ||
| LS-mean difference vs control | — | 647 (50-1,244) |
| P value | — | 0.034 |
Values are mean ± SD or 95% CI, unless otherwise indicated. Covariates in the main adjusted model included baseline measure, time, calendar-month fixed effects (fitted as a nominal variable), and participant random effects to account for repeated measures. Fully adjusted models included all elements of the main adjusted model, plus age, cancer type, site, race, education, marital status, income, self-reported health, body mass index, site, and a month/site interaction term.
LS-mean = least squares mean.
Weekly minutes of moderate to vigorous physical activity
Unadjusted mean weekly minutes of MVPA by week and study arm are shown in Figure 3B. The mean increase in weekly minutes of MVPA from baseline through the 24-week intervention period was 17 ± 36 in the control arm and 34 ± 45 in the gamification arm. Through 12-week postintervention follow-up, the mean increase in weekly minutes of MVPA from baseline was 7 ± 39 in the control arm and 19 ± 42 in the gamification arm. In the main adjusted model, gamification participants had a significantly greater increase in weekly minutes of MVPA than control participants during both the intervention (+16; 95% CI: 4-29; P = 0.010) and follow-up (+11; 95% CI: 0-22; P = 0.048) periods (Table 3). Results were similar in the fully adjusted model.
Table 3.
Weekly Minutes Moderate to Vigorous Physical Activity
| Control | Gamification | |
|---|---|---|
| Mean MVPA/wk, baseline | 30.6 ± 45.5 | 28.7 ± 46.8 |
| Mean MVPA/wk, wks 1-24 (intervention period) | 47.7 ± 44 | 62.4 ± 60.6 |
| Unadjusted mean change from baseline, MVPA/wk, wks 1-24 (intervention period) | 17.1 ± 35.7 | 33.7 ± 45.1 |
| Main adjusted model | ||
| LS-mean difference vs control (95% CI) | — | 16.4 (3.9-28.9) |
| P value | — | 0.010 |
| Fully adjusted model | ||
| LS-mean difference vs control (95% CI) | — | 15.6 (3.9-27.4) |
| P value | — | 0.009 |
| Mean MVPA/wk, wks 25-36 (post-intervention follow-up period) | 37.7 ± 34.8 | 47.6 ± 46.9 |
| Unadjusted mean change from baseline, MVPA/wk, wks 25-36 (postintervention follow-up period) | 7.1 ± 39 | 18.9 ± 42.3 |
| Main adjusted model | ||
| LS-mean difference vs control (95% CI) | — | 11.0 (0.1-21.9) |
| P value | — | 0.048 |
| Fully adjusted model | ||
| LS-mean difference vs control (95% CI) | — | 10.9 (0.5-21.2) |
| P value | — | 0.040 |
Values are mean ± SD or 95% CI, unless otherwise indicated. Covariates in the main adjusted model included baseline measure, time, calendar-month fixed effects (fitted as a nominal variable), and participant random effects to account for repeated measures. Fully adjusted models included all elements of the main adjusted model, plus age, cancer type, site, race, education, marital status, income, self-reported health, body mass index, site, and a month/site interaction term.
LS-mean = least squares mean; MVPA = moderate to vigorous physical activity.
At baseline, 2.6% of participants in the control arm (n = 2) and 2.7% in the gamification arm (n = 2) performed ≥150 min/wk of MVPA. During the 24-week intervention period, control participants achieved ≥150 min/wk of MVPA in 5.3% of participant-weeks vs 11.3% in the gamification arm (+6.0%; 95% CI: 4.9%-7.0%; P = 0.028). During 12-week follow-up, control participants achieved ≥150 min/wk of MVPA in 2.1% of participant-weeks vs 7.2% in the gamification arm (+5.1%, 95% CI: 4.3%-5.9%; P = 0.008).
Patient-reported outcomes
Unadjusted scores on patient-reported outcome measures are shown in Supplemental Figure 4. There were no significant differences between arms on change from baseline through the end of the intervention or follow-up periods on any measure (Supplemental Table 7).
Discussion
In this randomized controlled trial enrolling 150 Black or Hispanic breast and prostate cancer survivors at increased cardiovascular risk, behaviorally designed gamification significantly increased physical activity compared with attention control over a 24-week intervention period (Central Illustration). This effect was attenuated over 12-week postintervention follow-up, but the participants randomized to gamification continued to have a higher mean daily step count, although this effect was not statistically significant. Importantly, there was also a significantly greater increase in mean weekly minutes of MVPA in the gamification arm compared with the control arm during the intervention period that persisted through follow-up. Combined with results from previous trials of similar interventions,14,15 these findings suggest that behaviorally designed gamification may be an effective strategy for increasing physical activity in Black and Hispanic breast and prostate cancer survivors.
Central Illustration.
Effect of Behaviorally Designed Gamification on Physical Activity in Black and Hispanic Breast and Prostate Cancer Survivors
In this randomized controlled trial of 150 Black and Hispanic breast and prostate cancer survivors, behaviorally designed gamification significantly and meaningfully increased daily step count and weekly minutes of moderate to vigorous physical activity more than attention control.
Guidelines from the American Cancer Society recommend that cancer survivors should accumulate 150 to 300 minutes of moderate intensity or 75 to 150 minutes of vigorous physical activity each week.26,27 However, there is a continuous, inverse association between physical activity and risk of adverse clinical outcomes, and guidelines also acknowledge that any amount of physical activity is beneficial. In our study, the low average weekly minutes of MVPA and proportion of study participants meeting the weekly 150-minute MVPA threshold at baseline highlight the infeasibility of these recommendations and the value of counseling patients to set achievable, personalized targets. In the United States, just 16% of cancer survivors meet physical activity goals,8 and American Cancer Society guidelines reference barriers to achieving these goals, including barriers faced by all adults (challenges with behavior change, lack of resources and facilities to support physical activity, and built environment that discourages physical activity), those specific to cancer survivors (including the economic burden of cancer survivorship and residual symptoms related to cancer treatment), and those specific to Black and Hispanic cancer survivors (including lower financial well-being and the effects of structural and systemic racism on the built environment).28,29
The gamification intervention tested here directly addresses many of these barriers, providing evidence of the feasibility and efficacy of behaviorally designed and remotely delivered gamification to increase physical activity specifically in a population of cancer survivors from a historically marginalized community. By leveraging principles from behavioral economics, including precommitment, status quo bias, the endowment effect, goal gradients, the fresh start effect, and social accountability, the intervention addresses common barriers to behavior change.30, 31, 32 Allowing participants to set their own achievable goals, rather than striving for unachievable guideline-recommended targets, helps makes the intervention broadly applicable.14 As a fully home-based intervention not requiring clinical personnel, the intervention helps overcome challenges related to lack of resources and facilities to support physical activity. Notably, participants in this study had baseline health-related quality of life scores similar to U.S. population averages,33 which are themselves similar to health-related quality of life scores in breast cancer survivors seen in routine clinical practice,34 so the trial did not assess the efficacy of the intervention specifically in a population of patients with residual symptoms related to cancer treatment. The intervention’s lack of effect on quality of life measures may reflect the fact that participants did not perceive themselves to be limited in physical function at baseline and therefore had limited room to improve from a symptomatic standpoint by increasing physical activity. Quality of life may be a more relevant marker for populations of patients with baseline impairment in physical function.
ALLSTAR is the fourth randomized controlled trial to test this gamification intervention among adults at high risk for major adverse cardiovascular events.14,15,35 The effect on daily steps observed in ALLSTAR is consistent with previous trials: The gamification intervention immediately increased mean daily step count by >2,000 steps above participants’ own baseline, with a gradual decline over the course of the intervention period. When the gamification interventions were withdrawn at the end of the scheduled intervention period, the difference in change from baseline mean daily steps between the gamification and control arms decreased by approximately 150 steps, showing partial maintenance of behavior change. The marginal cost for continuing gamification indefinitely is small, and the decay in intervention effectiveness might be mitigated by not stopping the intervention at all or refreshing it periodically. Importantly, in all of these trials, including ALLSTAR, the increase in physical activity with gamification was achieved in comparison to attention control, which involved goal-setting and daily text message reminders, and was itself associated with substantially increased physical activity, and so the results may underestimate the true efficacy of gamification vs usual care.
These increases in physical activity may be clinically meaningful on the population level. Much of the considerable literature on the association between physical activity and outcomes in cancer survivors is based on self-report, and there are limited data on the association between daily step count and outcomes specifically in cancer survivors. In general, however, the limited data demonstrate an inverse association between daily step count and all-cause, cardiovascular, and cancer-specific mortality in cancer survivors,36 consistent with the relationship in the general population. Using data derived from observational studies in the general population, a long-term increase in daily steps by ∼15% from a baseline of 4,600 per day, as observed in gamification vs control, would be associated with a 9% lower risk of all-cause and cancer mortality and a 15% lower risk of cardiovascular mortality.37 In the recent CHALLENGE (Colon Health and Lifelong Exercise Change) trial, an intensive and structured physical activity intervention reduced the hazard of the composite of all-cause death, cancer recurrence, or new cancer diagnosis in colon cancer survivors by 28%,38 although whether an unsupervised, unstructured intervention designed to increase physical activity in the course of daily physical activity would have a similar effect is uncertain and must be tested in adequately powered clinical trials. The step gains achieved in our trial’s gamification arm are potentially achievable on a population level because of the scalability and sustainability of the gamification intervention. Using the Way to Health platform, the intervention is delivered automatically with no need for participant engagement beyond striving to achieve daily step goals and no need for clinically trained personnel. Limited personnel needs enhance scalability, lower cost, and increase cost-effectiveness.39 No economic analysis was performed for ALLSTAR, but total costs for delivery of a similar intervention were <$1,000 per participant with incremental cost-effectiveness ratio <$50,000 per life-year gained under all assumptions.39 The wearable fitness tracker used in this study costs $160, and many of the other costs related to intervention delivery are fixed, with limited marginal costs to enroll additional participants. Costs could be further reduced to <$100 per participant through economies of scale and by tracking step counts using the integrated functionality of smartphones rather than providing participants with wearable fitness trackers.
Study limitations
First, a minority of patients contacted and offered enrollment ultimately enrolled in the trial. Although all clinical trials enroll a selected cohort, and the low consent rate in this trial partially reflects a low-touch approach to recruitment by text message and e-mail rather than in person contact,40 the results of this study are most applicable to the cohort of patients who volunteer to participate in a study designed to test ways to increase physical activity. Trial participants had higher self-reported income and a greater likelihood of completing college than the U.S. population averages, for example. Moreover, patients who speak neither English nor Spanish, who represent an even more vulnerable population, were excluded. Second, the trial enrolled relatively few patients with prostate cancer, and the outcomes were assessed in combined population of breast and prostate cancer. Although there was no significant treatment effect by subgroup interaction for cancer type, breast and prostate cancer survivors differ in important ways, and we cannot rule out a differential effect in breast and prostate cancer survivors. Third, we only enrolled breast and prostate cancer survivors, and it is uncertain whether these findings will generalize to patients with hematologic malignancies or lung cancer. Fourth, this study was conducted in 2 health systems, and findings may not generalize to the broader population of breast and prostate cancer survivors. Last, although more physical activity is strongly associated with a lower rate of clinical outcomes,6,7 it is not certain whether increasing daily step count will improve clinical outcomes. It will be important for the results from this study to be validated in a multicenter study and in patients with other types of cancer, and to determine whether effects on daily step count translate to clinical outcomes.
Conclusions
In this trial enrolling Black and Hispanic breast and prostate cancer survivors at elevated risk of cardiovascular events, a behaviorally-designed gamification intervention increased mean daily step count compared with attention control over a 24-week intervention period. This scalable and sustainable intervention could be a useful component of strategies to reduce cardiovascular risk in cancer survivors.
Perspectives.
COMPETENCY IN MEDICAL KNOWLEDGE: In Black and Hispanic breast and prostate cancer survivors, a gamification intervention incorporating principles from behavioral economic theory meaningfully increases physical activity compared with attention control over a 6-month intervention period.
TRANSLATIONAL OUTLOOK: Further research is needed to determine whether increases in routine daily physical activity reduce the incidence of cardiovascular events in this high risk population.
Funding Support and Author Disclosures
ALLSTAR was funded by a grant from the American Heart Association Strategically Focused Research Network Award in Cardio-Oncology (869104) to Drs. Fanaroff and Armenian and (849569) to Dr Ky. The funding source had no role in the design, execution, or analyses of the study, interpretation of the data, or decision to submit results. Dr Volpp is a co-owner of a behavioral economics consulting firm, VAL Health, and a member of the Scientific Advisory Board of THRIVE Global. Neither organization has any involvement in this study. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Footnotes
Ronald Witteles, MD, Deputy Editor, served as Acting Editor-in-Chief for this paper.
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.
Appendix
For supplemental tables and figures, please see the online version of this paper.
Appendix
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