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Cancer survivorship in Ireland is increasing in both frequency and longevity. However, a significant proportion of cancer survivors do not reach the recommended physical activity levels and have overweight. This has implications for both physical and psychological health, including an increased risk of subsequent and secondary cancers. Mobile health (mHealth) interventions demonstrate potential for positive health behavior change, but there is little evidence for the efficacy of mobile technology in improving health outcomes in cancer survivors with overweight or obesity.
This study aims to investigate whether a personalized mHealth behavior change intervention improves physical and psychological health outcomes in cancer survivors with overweight or obesity.
A sample of 123 cancer survivors (BMI≥25 kg/m2) was randomly assigned to the standard care control (n=61) or intervention (n=62) condition. Group allocation was unblinded. The intervention group attended a 4-hour tailored lifestyle education and information session with physiotherapists, a dietician, and a clinical psychologist to support self-management of health behavior. Over the following 12 weeks, participants engaged in personalized goal setting to incrementally increase physical activity (with feedback and review of goals through SMS text messaging contact with the research team). Direct measures of physical activity were collected using a Fitbit accelerometer. Data on anthropometric, functional exercise capacity, dietary behavior, and psychological measures were collected at face-to-face assessments in a single hospital site at baseline (T0), 12 weeks (T1; intervention end), and 24 weeks (T2; follow-up).
The rate of attrition was 21% (13/61) for the control condition and 14% (9/62) for the intervention condition. Using intent-to-treat analysis, significant reductions in BMI (
The results demonstrate that for cancer survivors with a BMI≥25 kg/m2, lifestyle education and personalized goal setting using mobile technology can yield significant changes in clinically relevant health indicators. Further research is needed to elucidate the mechanisms of behavior change and explore the capacity for mHealth interventions to improve broader health and well-being outcomes in the growing population of cancer survivors.
ISRCTN Registry ISRCTN18676721; https://www.isrctn.com/ISRCTN18676721
RR2-10.2196/13214
There is an average of 35,000 new cases of cancer diagnosed each year in Ireland, representing a doubling of cases in the past 25 years [
There is consistent evidence of a positive association between overweight, obesity, and all-cause morbidity and mortality [
Health behavior change interventions can improve physical health outcomes, such as weight and BMI, as well as health behavior (eg, physical activity) and psychological health (eg, quality of life and well-being) in both the general population [
Systematic review evidence suggests that the use of relevant BCTs significantly increased the success of weight loss programs [
Studies have found that both mHealth tools and relevant BCTs can lead to positive health behavior changes and weight loss; therefore, the delivery of BCTs through mHealth tools may be particularly effective. Digital interventions that included a greater number of BCTs were found to have larger effects on health behavior change than interventions with fewer BCTs [
mHealth interventions incorporating relevant BCTs have the potential to improve health and well-being outcomes. However, there are a limited number of mHealth interventions for cancer survivors that describe content in terms of BCTs. A recent systematic review identified 15 digital health behavior change interventions for cancer survivors, concluding that digital interventions may improve physical activity and reduce BMI; however, findings regarding dietary behavior and well-being outcomes are mixed [
The aim of this study is to investigate the impact of a personalized mHealth behavior change intervention on physical and psychological health outcomes in a group of cancer survivors with overweight or obesity. More specifically, this project examined the impact of lifestyle education and personalized goal setting, compared with standard medical care, on physical activity (step count) as well as other behavioral, clinical, and psychological outcomes.
The full methodological details of the trial, including a detailed description of the development of the intervention, are reported in the study protocol [
A 2-arm, parallel, open-label RCT design was used to investigate the impact of the intervention versus standard care on clinical, psychological, and health behavior outcomes.
The statistical program G*Power was used to conduct power analysis. With 2 groups (intervention and control), 3 measurements (baseline, time 1, and time 2), an assumed correlation among repeated measures of 0.3, a small-medium effect size, and a power of 0.8, the recommended sample size for repeated measures analysis of variance (ANOVA) was 102. A final sample size of 123 was calculated based on an attrition rate of 20%, as observed in similar studies using mobile technology interventions with cancer survivors [
Participants were randomized to either the intervention or the standard care control condition using a computerized random number generator (enrollment was carried out by MGK and JR, and randomization and group allocation was carried out by JG). The study was not blinded, but step count, one of the main outcome measures, was recorded directly using the Fitbit device (Healthy Metrics Research, Inc).
Recruitment took place offline (by phone), and assessments were carried out face-to-face in a single hospital site, Letterkenny University Hospital, County Donegal, Ireland. Assessments were performed before randomization (T0; baseline), at 12 weeks (T1; intervention end), and at 24 weeks (T2; follow-up).
The design of this study was approved by the Research Ethics Committee of the National University of Ireland, Galway, on September 12, 2017 (Ref: 17/MAY/20) and by the Research Ethics Committee at Letterkenny University Hospital on May 2, 2017.
Adults aged 18-70 years, with a calculated BMI≥25 kg/m2, with a solid cancer and who had completed active cancer treatment (those continuing on endocrine therapy were permitted inclusion), who attended Oncology Services in Letterkenny University Hospital during the recruitment phase (December 2017 to January 2018), and who were willing to use mobile technology were eligible to participate.
Participants were recruited from the Oncology Services of Letterkenny University Hospital. A total of 159 eligible participants (aged 18-70 years, BMI≥25, and active cancer treatment completed) were identified sequentially from the oncology outpatient waiting list (N=347) by the clinical team. The clinical team contacted these participants by telephone, described the aims and design of the study, and asked if they were willing to use mobile technology. Prospective participants who expressed interest in the study were sent a participant information sheet and consent form (
CONSORT (Consolidated Standards of Reporting Trials) diagram showing the flow of participants through each stage of the randomized controlled trial.
This complex intervention was delivered through mHealth technology and included BCTs that aimed to improve clinical, psychological, and health behavior outcomes. The full details are described in the study protocol [
A 4-hour lifestyle education and information session (week 1) was delivered by health care professionals (3 physiotherapists, 1 dietician, and 1 clinical psychologist). Physiotherapists demonstrated a series of daily strengthening exercises and recommended schedules for moderate-intensity physical activity. The dietician delivered a comprehensive overview on healthy eating; answered numerous questions that clarified misinformation on nutrition; and specifically advised participants to reduce their caloric intake and reduce the intake of red meat, processed meat, salt, and sugar and increase fruit, vegetable, and fiber intake. The clinical psychologist offered practical strategies for problem solving, identifying barriers to change, and preventing relapse. The BCTs included in this session and the corresponding code from the BCT Taxonomy V1 [
An 8-week goal-setting intervention (weeks 4-12) was delivered using mobile technology (ie, Fitbit Alta accelerometer plus SMS text messaging contact). Participants received weekly text messages with feedback on their average daily step count and a goal of increasing their step count by 10% in the following week. The BCTs included in the personalized goal-setting intervention were
Participants randomized to the control condition received standard care and were also provided with a Fitbit Flex 2 to measure physical activity for the 24 weeks of the study. As such, a number of BCTs were also present in the control condition in this study. On being enrolled in the study for meeting eligibility criteria (BMI≥25 kg/m2), all participants were encouraged to maintain a healthy weight (
Goal setting (outcome; 1.3): “set or agree on a goal defined in terms of a positive outcome of the wanted behavior.”
Provide information on the consequences of behavior to the individual (5.1): “provide information (eg, written, verbal, and visual) about health consequences of performing the behavior.”
Demonstration of the behavior (6.1): “provide an observable sample of the performance of the behavior.”
Provide instruction on how to perform the behavior (4.1): “advise or agree on how to perform the behavior.”
Problem solving (1.2): “analyze, or prompt the person to analyze, factors influencing the behavior and generate or select strategies that include overcoming barriers and/or increasing facilitators.”
Goal setting (behavior; 1.1): “set or agree on a goal defined in terms of the behavior to be achieved.”
Action planning (1.4): “prompt detailed planning of performance of the behavior, must include at least one of context, frequency, duration, and intensity.”
Self-monitoring of behavior (2.3): “establish a method for the person to monitor and record their behavior(s) as part of a behavior change strategy.”
Feedback on behavior (2.2): “monitor and provide informative or evaluative feedback on performance of the behavior and must include one of form, frequency, duration, and intensity.”
Goal setting (behavior; 1.1): “set or agree on a goal defined in terms of the behavior to be achieved.”
Graded tasks (8.7): “set easy-to-perform tasks, making them increasingly difficult, but achievable, until behavior is performed.”
Social reward (10.4): “arrange verbal or nonverbal reward if and only if there has been effort and/or progress in performing the behavior (includes
Review behavior goal(s) (1.5): “review behavior goal(s) jointly with the person and consider modifying the goal(s) or behavior change strategy in light of achievement.”
Goal setting (outcome) (1.3): “set or agree on a goal defined in terms of a positive outcome of the wanted behavior.”
Provide information on consequences of behavior to the individual (5.1): “provide information (eg, written, verbal, and visual) about health consequences of performing the behavior.”
Self-monitoring of behavior (2.3): “establish a method for the person to monitor and record their behavior(s) as part of a behavior change strategy.”
All participants were provided with a Fitbit activity tracker for the duration of the study. Each participant was registered with a Fitbit user account. Accounts were set up using a centralized email address corresponding to their study ID number and a randomly generated alphanumeric password. The Fitbit was set up and paired with the participants’ mobile devices (ie, smartphone or tablet). The participants were also given an information sheet with instructions on how to synchronize their Fitbit device and app and asked to perform this weekly to prevent loss of data. This sheet also contained the contact details of the research team should they encounter any technical issues or wish to discuss any concerns with their health care providers. A computer program was developed by the Insight Centre for Data Analytics at the National University of Ireland, Galway, to allow participants’ physical activity data to be extracted from the Fitbit server. A member of the research team (JG) logged in to each participant’s user account and authorized this third-party program to access their data from Fitbit. The anonymized data for all participants were exported to Excel for analysis.
To facilitate the goal-setting intervention, a weighted average for daily step count was calculated for participants with at least five observations per week. Participants who showed no activity for more than 2 days a week were contacted to verify that there were no technical issues. There were a number of possible reasons for someone to have 0 steps on a given day (eg, the participant did not wear the monitor or the Fitbit failed to record). These reasons were not recorded, and self-reported adherence to monitor wear was not measured. Within 2 weeks of receipt, a number of participants reported challenges using their Fitbit. As a result, all participants were invited to attend 1 of the 2 technical support sessions. A total of 12 participants attended a session and received hands-on support and troubleshooting advice regarding their device from the research team (JG and MGK). Following the implementation of the European Union General Data Protection Regulation (May 2018), participants were automatically logged out of their Fitbit app. However, this was possible to fix at a distance over the phone or via a text message.
Anthropometric measurements included weight in kilograms, BMI, and waist circumference in centimeters.
The 6-minute walk test measures the distance walked in 6 minutes on a hard, flat surface. Systolic blood pressure, diastolic blood pressure, heart rate, blood oxygen saturation, subjective fatigue, and dyspnea were measured pretest (ie, resting), posttest, and 4 minutes later (ie, recovery).
Health-related quality of life was measured using the Medical Outcomes Survey Short Form (RAND-36) [
Self-reported physical activity was measured using the Godin Leisure-Time Exercise Questionnaire [
All outcomes were measured at baseline (T0), 12 weeks (T1; intervention end), and 24 weeks (T2; follow-up). The measures are described in full in the trial protocol [
To maximize power and conform to intent-to-treat analysis, missing data were handled using the expectation-maximization (EM) algorithm. A nonsignificant MCAR test [
A series of 3 (time: baseline [T0], 12 weeks [T1], and 24 weeks [T2])×2 (group: control and intervention) mixed ANOVAs were performed to determine the effect of the intervention on clinical, psychological, and health behavior outcomes. In the case of a significant interaction effect, follow-up two-tailed independent sample
A flow diagram of the progress through each phase of this 2-group parallel randomized trial is shown in
Participants’ characteristics are described in
Participants’ characteristics at baseline assessment (N=123).
Characteristics | Control (n=61) | Intervention (n=62) | |
Age (years), mean (SD) | 59.24 (7.65) | 55.61 (8.05) | |
Weight (kg), mean (SD) | 87.10 (16.32) | 84.18 (13.98) | |
BMI (kg/m2), mean (SD) | 32.64 (5.41) | 30.33 (3.99) | |
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Female | 49 | 42 |
|
Male | 4 | 12 |
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|
Breast | 49 (80) | 50 (81) |
|
Prostate | 1 (2) | 1 (2) |
|
Lung | 0 (0) | 1 (2) |
|
Colorectal | 9 (15) | 8 (13) |
|
Testicular | 2 (3) | 2 (3) |
|
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|
Angina | 1 (2) | 2 (4) |
|
Heart attack | 3 (6) | 1 (2) |
|
High blood pressure | 19 (36) | 18 (33) |
|
Stroke | 3 (6) | 1 (2) |
|
Diabetes | 5 (9) | 6 (11) |
|
High cholesterol | 21 (40) | 20 (37) |
|
Depression | 12 (23) | 9 (17) |
|
Anxiety | 12 (23) | 12 (22) |
Means and SDs for all anthropometric measurements are presented in
Anthropometric measurements.
Outcome | Weight, mean (SD) | BMI, mean (SD) | Waist circumference, mean (SD) | |||||||
|
T0a | T1b | T2c | T0 | T1 | T2 | T0 | T1 | T2 | |
Control | 86.9 (15.2) | 85.99 (14.94) | 86.16 (14.76) | 32.44 (5.07) | 32.26 (5.02) | 32.33 (5.03) | 103.35 (9.28) | 101.82 (9.41) | 101.53 (9.38) | |
Intervention | 84.17 (13.11) | 82.11 (13.41) | 82.59 (13.69) | 30.47 (3.74) | 29.78 (4.04) | 29.95 (4.12) | 101.15 (11.07) | 98.43 (11.72) | 98.13 (11.69) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
There was no significant interaction effect on weight (
There was a significant interaction between group and time (
Results of 3×2 mixed analysis of variance showing a significant reduction in BMI for the intervention group only. T0: time 1, baseline; T1: time 1, intervention end (12 weeks); T2: time 2, follow-up (24 weeks).
There was a significant interaction effect for waist circumference (
Results of 3×2 mixed analysis of variance showing a significant reduction in waist circumference that was maintained at follow-up in both conditions, with a larger reduction in the intervention group. T0: time 1, baseline; T1: time 1, intervention end (12 weeks); T2: time 2, follow-up (24 weeks).
There was no significant interaction effect for distance walked; systolic blood pressure; diastolic blood pressure; heart rate; subjective fatigue; or dyspnea measured before, after, or 3 minutes after the 6-minute walk test (the full set of results are presented in
Measures of the 6-minute walk test.
Outcomes | Control, mean (SD) | Intervention, mean (SD) | ||||
|
T0a | T1b | T2c | T0 | T1 | T2 |
Distance walked | 515.99 (67.9) | 551.25 (62.44) | 566.29 (71.79) | 532.57 (69.8) | 571.72 (61.68) | 590.28 (87.78) |
Resting SBPd | 144.12 (19.57) | 135.3 (16.16) | 139.45 (13.24) | 139.95 (21.04) | 129.97 (16.27) | 139.99 (33.52) |
Posttest SBP | 154.48 (20.83) | 151.03 (19.18) | 150.66 (17.33) | 151.67 (23.43) | 145.1 (21.07) | 152.97 (38.02) |
Recovery SBP | 142.32 (17.66) | 134.31 (17.25) | 135.08 (14.74) | 138.01 (18.2) | 129.38 (15.96) | 132.81 (19.19) |
Resting DBPe | 80.89 (7.86) | 76.76 (9.2) | 80.67 (8.25) | 79.56 (9.79) | 76.11 (9.12) | 77.54 (11.06) |
Posttest DBP | 82.15 (8.94) | 81.78 (12.17) | 81.89 (11.66) | 81.27 (12.45) | 77.39 (10.75) | 80.28 (10.83) |
Recovery DBP | 80.27 (8.06) | 77.54 (9) | 78.31 (7.45) | 78.83 (10.62) | 76.35 (9.32) | 78.28 (9.74) |
Resting HRf | 79.01 (10.28) | 77.36 (8.56) | 77.4 (9.27) | 78.73 (11.4) | 77.56 (15.17) | 74.09 (13.30) |
Posttest HR | 111.67 (17.39) | 103.51 (17.94) | 113.45 (17.61) | 127.06 (143.76) | 105.89 (24.44) | 113.53 (50.21) |
Recovery HR | 85.49 (11.88) | 82.07 (10.77) | 83.5 (10.75) | 85.13 (13.32) | 82.31 (12.45) | 83.02 (15.57) |
Resting fatigue | 6.39 (0.9) | 6.22 (0.91) | 5.96 (1.06) | 6.35 (0.79) | 6.17 (1.03) | 6.05 (1.39) |
Posttest fatigue | 9.83 (2.36) | 10.73 (1.98) | 10.35 (2.72) | 9.9 (2.41) | 10.54 (2.45) | 10.2 (3.19) |
Recovery fatigue | 6.93 (1.6) | 6.4 (0.98) | 6.09 (1.42) | 6.88 (1.23) | 6.56 (1.38) | 6.08 (2.71) |
Resting dyspnea | 1.24 (0.73) | 1.12 (0.42) | 1.58 (1.19) | 1.19 (0.65) | 1.15 (0.67) | 1.35 (0.97) |
Posttest dyspnea | 4.02 (1.67) | 3.74 (1.47) | 5.06 (4.61) | 3.5 (1.33) | 4.04 (1.75) | 4.25 (2.4) |
Recovery dyspnea | 1.81 (0.97) | 1.24 (0.47) | 1.88 (1.88) | 1.64 (0.94) | 1.40 (0.87) | 1.45 (1.51) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
dSBP: systolic blood pressure.
eDBP: diastolic blood pressure.
fHR: heart rate.
No significant interaction effects were observed for health-related quality of life (measured by the RAND36 Medical Outcomes Survey). Means and SDs are presented in
Subscales of RAND-36 Medical Outcomes Survey.
Outcome | Control, mean (SD) | Intervention, mean (SD) | |||||
|
T0a | T1b | T2c | T0 | T1 | T2 | |
Physical functioning | 77.87 (17.06) | 81.81 (14.52) | 81.15 (17.28) | 73.87 (20.33) | 80.08 (17.28) | 77.66 (19.83) | |
Role limitations: physical health | 69.67 (39.82) | 78.28 (29.39) | 77.05 (35.15) | 69.76 (37.64) | 85.89 (30.57) | 79.03 (33.63) | |
Role limitations: emotional health | 83.06 (33.12) | 89.62 (23.99) | 83.06 (32.56) | 72.58 (40.72) | 87.37 (29.37) | 83.33 (31.22) | |
Pain | 73.24 (21.85) | 78.11 (21.65) | 74.22 (23.63) | 73.47 (23.16) | 79.28 (19.62) | 75.57 (21.52) | |
Emotional well-being | 77.38 (17.57) | 81.77 (13.59) | 83.74 (13.28) | 73.03 (18.66) | 79.87 (16.32) | 78.77 (18.04) | |
Social functioning | 78.48 (23.4) | 91.8 (15.79) | 88.31 (18.8) | 78.63 (23.01) | 89.31 (17.8) | 85.88 (20.69) | |
Energy | 61.39 (20.21) | 70.99 (16.38) | 68.69 (19.68) | 53.39 (21.27) | 67.02 (17.15) | 63.06 (18.07) | |
General health | 51.73 (20.17) | 57.6 (15.87) | 55.87 (16.4) | 49.5 (16.54) | 56.98 (12.94) | 53.04 (15.74) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
There were also no significant interaction effects for loneliness, self-efficacy, exercise self-efficacy, or exercise social support (full results, including nonsignificant findings, are presented in
Psychological outcome measures.
Outcomes | Control, mean (SD) | Intervention, mean (SD) | |||||
|
T0a | T1b | T2c | T0 | T1 | T2 | |
Loneliness | 4.23 (1.64) | 4.1 (1.57) | 4.34 (1.63) | 3.63 (1.02) | 3.69 (0.9) | 3.74 (1.01) | |
Fatigue (global) | 35.47 (20.47) | 25.18 (20.79) | 31.05 (20.3) | 23.36 (19.42) | 20 (16.45) | 21.49 (15.95) | |
Fatigue severity | 9.77 (4.92) | 8.05 (4.88) | 8.9 (4.59) | 6.92 (3.89) | 6.38 (3.55) | 6.90 (3.47) | |
Fatigue interference | 20.63 (14.43) | 13.28 (14.64) | 17.76 (14.21) | 13.1 (13.47) | 10.53 (11.33) | 11.48 (10.99) | |
Self-efficacy | 20.56 (4.45) | 22.27 (4.26) | 21.96 (4.62) | 21.69 (4.19) | 22.16 (3.92) | 22.01 (4.02) | |
Exercise: self-efficacy | 22.33 (4.14) | 21.93 (4.56) | 21.08 (4.98) | 23.14 (2.49) | 22.69 (3.85) | 22.41 (3.63) | |
Exercise: social support | 12.36 (5.39) | 13.39 (4.39) | 12.45 (4.8) | 12.33 (4.92) | 13.03 (4.31) | 12.1 (5.01) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
As shown in
Results of a 3×2 mixed analysis of variance showing a significant reduction in fatigue at 12 weeks and a nonsignificant increase at 24 weeks in the control group only. T0: time 1, baseline; T1: time 1, intervention end (12 weeks); T2: time 2, follow-up (24 weeks).
Dietary data were collected using the European Prospective Investigation into Cancer and Nutrition Norfolk Food Frequency Questionnaire 45. There were no significant interaction effects for any of the 10 food groups assessed (
Dietary behavior.
Outcomes | Control, mean (SD) | Intervention, mean (SD) | |||||
|
T0a | T1b | T2c | T0 | T1 | T2 | |
Fiber | 16.25 (4.06) | 16.33 (4.78) | 16.64 (4.14) | 17.63 (6.62) | 17.45 (5.32) | 18.6 (6.18) | |
Kilocalorie | 1846.14 (538.65) | 1681.15 (562.66) | 1687.54 (455.96) | 2030.77 (664.09) | 1760.36 (569.79) | 1828.44 (687.56) | |
Sodium | 2940.68 (891.54) | 2547.2 (785.47) | 2685.03 (759.71) | 3131.63 (1021.24) | 2586.32 (834.46) | 2840.5 (1075.67) | |
Saturated fats | 29.06 (13.26) | 24.91 (10.35) | 26.30 (10.29) | 31.95 (14.17) | 24.80 (13.1) | 27.52 (15.98) | |
Fruit | 243.29 (138.28) | 291.02 (153.8) | 269.74 (160.84) | 259.69 (179.98) | 310.94 (214.98) | 312.33 (329.19) | |
Meat | 126.40 (54.37) | 103.33 (48.28) | 119.18 (49.56) | 125.58 (62.87) | 106.49 (78.39) | 120.22 (59.21) | |
Sugar | 48.65 (45.42) | 31.84 (28.06) | 35.55 (28.4) | 55.51 (57.16) | 31.09 (22.25) | 36.89 (36.42) | |
Vegetables | 231.91 (101.65) | 244.62 (95.77) | 263.57 (105.37) | 248.9 (127.94) | 264.88 (106.22) | 303 (130.75) | |
Alcohol | 2.02 (2.67) | 1.75 (2.46) | 2.15 (2.6) | 3.62 (9.97) | 2.80 (7.23) | 3.28 (7.95) | |
Alcoholic beverages | 22.53 (27.63) | 20.67 (28.95) | 27.79 (39.86) | 44.97 (132.53) | 31.81 (91.21) | 40.67 (108.43) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
There was no significant main effect of time (
Scores on the Godin Leisure-Time Exercise Questionnaire.
Outcome | Control, mean (SD) | Intervention, mean (SD) | |||||
|
T0a | T1b | T2c | T0 | T1 | T2 | |
Weekly leisure activity | 31.03 (17.25) | 34.68 (26.12) | 33.03 (29.39) | 31.14 (20.52) | 34.75 (18.34) | 30.38 (16.71) |
aT0: time 0 (baseline).
bT1: time 1 (intervention end; 12 weeks).
cT2: time 2 (follow-up; 24 weeks).
The step count data were collected continuously using Fitbit. Daily step count totals were summed, and an average daily step count was calculated for each week of the 24-week study. Means and SDs are presented in
An analysis of the personalized goal-setting intervention demonstrated that 69% (37/54) of participants in the intervention group met at least 50% (4/8) of their step count goals. However, the goal success rate was not significantly correlated with any of the study outcome variables. A further analysis of prescribed step count goals within the context of goal achievement indicates that success was highest in the earlier stages of the goal-setting intervention when step count goals were below 10,000 steps (
Average daily step count for weeks 1-24 (N=107).
Group | Control, mean (SD) | Intervention, mean (SD) | ||
Week 1 | 8792.11 (3990.17) | 8775.34 (8946.51) | 0.012 (105) | .99 |
Week 2 | 8434.01 (4135.28) | 8978.65 (6063.41) | −0.542 (105) | .59 |
Week 3 | 8622.72 (3126.16) | 10,401.04 (3659.81) | −2.7 (105) | .01 |
Week 4 (SMS 1) | 8638.9 (3768.52) | 9833.51 (3737.18) | −1.646 (105) | .10 |
Week 5 (SMS 2) | 8359.62 (3414.64) | 10,621.07 (4020.28) | −3.133 (105) | <.001 |
Week 6 (SMS 3) | 8308.83 (3523.38) | 10,265.19 (4345.32) | −2.555 (105) | .01 |
Week 7 (SMS 4) | 8519.34 (3318.01) | 10,982.03 (4708.59) | −3.122 (105) | <.001 |
Week 8 (SMS 5) | 9940.19 (4317.15) | 12,247.11 (5842.16) | −2.319 (105) | .02 |
Week 9 (SMS 6) | 8819.53 (4088.03) | 10,744.1 (4681.16) | −2.263 (105) | .03 |
Week 10 (SMS 7) | 9065.88 (3755.52) | 10,262.84 (4780.74) | −1.438 (105) | .15 |
Week 11 (SMS 8) | 8576.29 (3865.43) | 10,610.33 (5441.93) | −2.225 (105) | .03 |
Week 12 | 9067.76 (3838.9) | 10,915.87 (4804.31) | −2.196 (105) | .03 |
Week 13 | 9883.54 (3462.85) | 11,080.53 (5621.11) | −2.113 (105) | .19 |
Week 14 | 9219.04 (3711.7) | 10,908.43 (4703.33) | −2.06 (105) | .04 |
Week 15 | 9185.22 (3715.93) | 11,260.69 (4871.56) | −2.474 (105) | .01 |
Week 16 | 7750.5 (3536.26) | 9553.78 (5119.87) | −2.116 (105) | .04 |
Week 17 | 8726.35 (3938.05) | 10,513.67 (4666.4) | −2.139 (105) | .04 |
Week 18 | 9020.32 (3487.54) | 10,255.48 (3446.08) | −1.843 (105) | .07 |
Week 19 | 9480.41 (3820.46) | 10,901.42 (4965.92) | −1.657 (105) | .10 |
Week 20 | 8624.73 (3426.48) | 10,108.47 (4817.34) | −1.833 (105) | .07 |
Week 21 | 7700.75 (4584.27) | 10,201.34 (4386.2) | −2.883 (105) | <.001 |
Week 22 | 7520.26 (11826.73) | 10,171.88 (7265.27) | −1.4 (105) | .16 |
Week 23 | 8224.2 (5145.45) | 9481.54 (5442.37) | −1.228 (105) | .22 |
Week 24 | 8483.63 (4808.37) | 9700.24 (5860.72) | −1.173 (105) | .24 |
Average daily step count goal for each week and participants’ rate of success in achieving step count goals in weeks 5-12 (n=54).
Time | Goal 1: week 5 | Goal 2: week 6 | Goal 3: week 7 | Goal 4: week 8 | Goal 5: week 9 | Goal 6: week 10 | Goal 7: week 11 | Goal 8: week 12 |
Step count goal, mean (SD) | 7541.75 (4046.05) | 7907.88 (5186.28) | 10,601.11 (4874.16) | 11,598.83 (5337.32) | 9396.26 (5745.74) | 10,922.66 (6074.49) | 11,145.08 (5479.19) | 11,294.56 (6039.08) |
Did achieve goal, n (%) | 41 (76) | 39 (72) | 25 (46) | 35 (65) | 35 (65) | 18 (33) | 17 (32) | 24 (44) |
Did not achieve goal, n (%) | 13 (24) | 15 (28) | 29 (54) | 19 (35) | 19 (35) | 36 (67) | 37 (68) | 30 (56) |
The aim of this trial is to examine the impact of a personalized mHealth behavior change intervention on clinical, psychological, and health behavior outcomes among a group of cancer survivors with overweight or obesity. The results show that the intervention yielded several significant benefits over and above that shown in the standard care control group. The intervention group had a significantly greater reduction in BMI than the control group. This reduction in BMI was maintained at the 24-week follow-up. Relative to the control group, there was a significantly greater reduction in waist circumference in the intervention group. At follow-up, there was a modest reduction in BMI (0.52) and waist circumference (3.02 cm) with small to medium effect sizes. In relation to behavioral outcomes, participants in the intervention group had significantly higher physical activity during both the intervention phase (8 out of the 12 weeks) and the follow-up phase (5 out of the 12 weeks) than those in the control group. Participants in the intervention averaged approximately 2000 extra steps per day (the equivalent of 1 mile or 20 minutes of physical activity [
The design of this intervention is aligned with the National Institute for Health and Care Excellence guidelines for weight management in people with obesity [
A key element of this intervention was the use of personalized goals delivered through mobile technology (ie, Fitbit and SMS text messaging contact). This aimed to enhance participants’ motivation to increase their overall levels of physical activity. In addition to significant increases in physical activity (step count), the results show a good level of goal achievement, suggesting that goal-setting intervention did influence participants’ motivation to increase activity. Although goals were personalized (ie, increase daily step count by 10% per week), goal attainment was highest in the initial stages when step count targets were lower, suggesting there may be a threshold after which increasing step count become unattainable. This is not surprising, and recent evidence suggests that significant health benefits are achievable at much lower levels of physical activity (ie, 4400-7500 steps per day) [
Although the results did not demonstrate any significant improvements in dietary behavior, it is clear that changes in lifestyle (primarily increased physical activity) contributed to significantly greater benefits in key clinical outcomes for the intervention group. An emerging body of research with cancer survivors suggests that digital interventions have positive effects on BMI and physical activity, but the findings are less consistent for diet [
This intervention had 2 behavioral targets (increase physical activity and improve diet) to improve health and well-being outcomes. Systematic review evidence has found that health behavior change interventions focusing on physical outcomes improve well-being in the general population [
Although the effect sizes were small to medium, the large sample size and high retention rate means that the study was adequately powered to detect such effects. Participants were randomized to conditions to reduce selection bias, and the use of intention-to-treat analysis limited the impact of attrition bias. However, it was not possible to blind participants or outcome assessors in this study, a limitation common to many digital health interventions [
A notable strength of this study is the use of a direct measure of physical activity (ie, Fitbit accelerometer). In a review of 15 digital health behavior change interventions with cancer survivors [
Cancer survivors who have overweight or obesity require additional support to self-manage their health behaviors. mHealth technology may provide a cost-effective solution within modern oncology care. mHealth has enormous potential for improved health care delivery, but evidence from this group currently lacks a strong base [
Participant information sheet and consent form.
Results of 3×2 analysis of variance on measures of the 6-minute walk test.
Results of 3×2 analysis of variance on subscales of the RAND-36 Medical Outcomes Survey: Short Form.
Results of 3×2 analysis of variance on other psychological outcomes.
Results of 3×2 analysis of variance on dietary behavior.
CONSORT-eHEALTH checklist (V 1.6.1).
analysis of variance
behavior change technique
Consolidated Standards of Reporting Trials
expectation-maximization
mean difference
mobile health
mode of delivery
randomized controlled trial
The authors would like to acknowledge the support of the nursing staff Tereze Toby, Mary McCollum, Noreen Rodgers, and Caroline Nee; physiotherapists Tommy Kerr, Aoife O’Donnell, and Eimear Masterson; dietician Nina Singaroyan at Letterkenny University Hospital; clinical psychologist Charlene Haughey at Cancer Care West and Letterkenny University Hospital; the Irish Cancer Society Daffodil Centre at Letterkenny University Hospital; the Insight Center for Data Analytics at the National University of Ireland, Galway; and all the participants for their time. This research was funded by a grant awarded to JR and JCW by the Irish Cancer Society with support from Relay for Life Donegal.
None declared.