Leveraging Family Dynamics to Increase the Effectiveness of Incentives for Physical Activity: The FIT-FAM Randomized Controlled Trial

doi:10.21203/rs.3.rs-21239/v1

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Leveraging Family Dynamics to Increase the Effectiveness of Incentives for Physical Activity: The FIT-FAM Randomized Controlled Trial

https://doi.org/10.21203/rs.3.rs-21239/v1

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published 10 Sep, 2020

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Background In Singapore, 37% of adults are insufficiently active despite widespread opportunities for physical activity (PA). Research shows that PA can be increased by use of group-based extrinsic incentives. This study evaluates whether a novel incentive design linking children’s incentives to both their own and their parent’s PA (measured via pedometers) can increase parents’ PA without compromising children’s PA.

Methods We conducted a two-arm, parallel, open-labelled randomized controlled trial where parent-child dyads were randomly assigned to either (1) rewards to the child contingent on child’s PA (child-based) or (2) rewards to the child contingent on both child’s and parent’s PA (family-based). Parents had to be English-speaking, computer-literate, non-pregnant, full-time employees, aged 25–65 years, and with a participating child aged 7–11 years. Parent-child dyads were randomized within strata (self-reported low vs high weekly PA) into study arms in a 1:1 ratio. Participants were given pedometers to assess daily steps. The primary outcome was the between-arm difference in the change from baseline in parent’s mean steps/day measured by accelerometry at months 6 and 12.

Results 159 and 157 parent-child dyads were randomized to the child-based or family-based arms, respectively, and all with outcomes evaluated an intent-to-treat perspective. At month 6, there was a statistically significant 613 steps/day (95% CI: 54–1171) differential in favour of family-based parents. At month 12, the differential was reduced to 369 steps/day (95% CI: -88–1114) and no longer statistically significant.

Conclusions Our findings provide evidence that family-based incentive strategies have the potential to improve outcomes at no additional cost but also indicate that more research is needed to identify strategies that encourage long-term behavior change for both parents and children.

Physical Medicine & Rehab

Nutrition & Dietetics

Physical activity

incentives

rewards

randomized controlled trial

activity tracker

accelerometer

parents

children

steps

There is strong evidence that sustained physical activity (PA) reduces risks for non-communicable diseases, increases longevity, and reduces medical costs [1, 2]. In Singapore, the setting of this study, 37% of adults [3] and at least 59% of primary school children [4] are insufficiently active (i.e., engaging in less than 150 min/week of moderate-to-vigorous intensity PA) despite Singapore being a highly walkable city with numerous subsidized community-based PA programs.

Singapore has a multi-pronged approach to confronting physical inactivity [5]. One component includes the use of financial rewards (termed “incentives”) in the National Steps Challenge™, a program that is run by the Health Promotion Board and open to all residents [6]. Although this program has not been independently evaluated, financial incentives to increase PA have demonstrated effectiveness both in adults and children [7, 8].

Research from behavioural economics and psychology suggests that the effectiveness of incentives of any given magnitude can be increased through careful attention to incentive design [9]. One promising strategy is group-based incentives, where the reward is contingent on the behavior of all of the individuals in the group [10]. Under this scheme, people are expected to work harder to reach the goal due to the social desirability of not wanting to let down the group [11]. This approach is likely to be more effective when the groups are smaller and more closely aligned, such as within families, as this increases accountability and the social ‘costs’ of not meeting the goal.

In this study, we tested whether a novel incentive design that linked children’s incentives to both their own and their parent’s PA (measured via activity trackers) could increase parents’ PA without compromising children’s PA. We predicted that parents in the linked scheme (termed “family-based”) would work harder to increase their PA because they have an additional “cost” of not meeting the goal, in the form of disappointing their child. We further expected that the children in this arm would motivate their parents to increase PA in efforts to gain the reward. Financial incentives targeting children are especially appealing as they have been shown to be effective at low monetary values. For example, in one randomized controlled trial conducted with youths in Singapore, an incentive valued at S$30 (≈ US$21.60) per month tied to reaching a daily step goal resulted in greater average steps/day in every month over a 9-month period [12].

We tested our hypotheses using a two-arm, parallel, open-labelled randomized controlled trial. For the same step targets and incentive level, we hypothesized that the family-based incentive scheme would be more effective at increasing step activity at months 6 and 12 (hypothesis (H) 1) and other measures of PA and health outcomes (H2) among parents without reducing children’s PA (H3) relative to a scheme that incentivizes children based on their own PA alone (termed “child-based”). We also hypothesized that parents in the family-based incentive scheme would be more likely to achieve the weekly step targets (goal attainment) over the course of the study (H4). We explored several potential moderators of effectiveness, including parent’s and child’s gender, family dynamics, and parent’s social support for and enjoyment of PA.

Study design and participant characteristics

FIT-FAM (Financial Incentive Trial targeting FAMilies) was a 12-month (48-week), open-labelled randomized controlled trial conducted in Singapore comparing two parallel arms (1:1 allocation ratio): (1) activity tracker plus child-based incentive, and (2) activity tracker plus family-based incentive. This manuscript conforms to CONSORT reporting guidelines (Additional file 1, CONSORT checklist).

Participants were recruited from 11 worksites and through newspaper advertisements. To be eligible, parents had to be English-speaking, computer-literate, non-pregnant, full-time employees, aged 25–65 years upon enrolment, have a child aged 7–11 years who was willing to participate, and provide adequate baseline accelerometer data (for themselves and their child). We focused on parents who were full-time employees as this is a particularly inactive group in Singapore [13]. Both parent and child had to be willing to wear a wireless activity tracker throughout the study and an accelerometer for 7 days each at months 6 and 12, and able to climb ≥ 10 stair steps without stopping.

Eligible parents wishing to participate signed an informed consent form, assented to their child’s participation, and paid a non-refundable enrolment fee of S$25 (≈ US$18.00). Those who answered ‘Yes’ to any Physical Activity Readiness Questionnaire question [14], had a body mass index (BMI) of > 40 kg/m², asthma, chronic obstructive pulmonary disease, diabetes mellitus, hypertension, lipid disorders, stroke, or personal or familial history of cardiovascular conditions were required to obtain written approval from a physician prior to enrolment.

Outcomes and assessments

Step-tracking and awarding of incentives were based on Fitbit activity trackers (Fitbit Flex® for parents and Fitbit Zip® for children) provided upon enrolment, with documentation of validity and reliability summarized elsewhere [15]. However, to ensure higher quality data and to minimize missingness, the primary outcome was the between-arm difference in the change in parents’ steps/day at months 6 and 12 relative to baseline measured using waist-worn triaxial GT3X + or wGT3X-BT ActiGraph accelerometers. Accelerometry was also used to measure the following secondary outcomes: steps/day (children), moderate-to-vigorous PA (MVPA), MVPA bouts, sedentary duration, light, moderate, and vigorous activity, and total volume of PA (sum of light, moderate, and vigorous activity [16]) presented in average minutes/day. Accelerometer data were expressed as average counts per minute (cpm). Tri-axial vector magnitude (VM) cut-points classified time in sedentary (0–199 cpm) [17], light (200–2689 cpm), moderate (2690–6166 cpm), and vigorous (≥ 6167 cpm) minutes/day [16]. MVPA was defined as VM ≥ 2690 cpm. MVPA bout minutes were defined as a total of 10 or more consecutive minutes above the MVPA VM cut-point with allowance for interruptions of 1 or 2 minutes below the cut-point [18]. The Choi et al. algorithm was used to identify adherent days [19].

Participants were encouraged to wear the accelerometer on their waist for 7 days during waking hours at each assessment period, regardless of whether they wore their activity tracker during follow-up. Data were considered adherent if ≥ 3 weekdays and 1 weekend day were provided for ≥ 600 min/day of wear time during each assessment period. All data were processed with R (version 3.5.1).

Secondary health outcomes for parents include BMI (Seca 217 Portable Stadiometer and Seca 869 Floor Scale), systolic blood pressure (Welch Allyn Spot Vital Signs Blood Pressure monitor), estimated cardiorespiratory fitness [maximum oxygen consumption (VO_2max) approximated based on age, gender, BMI, resting heart rate (Welch Allyn Spot Vital Signs Blood Pressure monitor), and a non-exercise test (NET-F) for cardiorespiratory fitness; termed NET-F VO_2max] [20, 21], and health-related quality of life (EQ-5D-5L) using the Thailand EQ-5D-5L value set as no Singapore value set was available [22]). Covariates (age, gender, and ethnicity) were captured at baseline and potential moderators were captured at baseline and both follow-up assessments using online questionnaires. For moderators, family dynamics were measured using the Family Adaptability and Cohesion Scale (FACES IV) [23], and parents’ social support for and enjoyment of PA were measured by the Physical Activity and Social Support scale (PASS) [24, 25] and the Physical Activity Enjoyment Scale (PACES), respectively [26]. To encourage attendance and survey completion, parents were compensated S$20 (≈ US$14.40) per completed follow-up assessment.

Randomization

After enrolment and completing the baseline assessment, parent-child dyads were randomized with equal probability into one of two arms (Fig. 1, CONSORT flow diagram) within strata using a computer algorithm with strata defined by low or high amounts of weekly self-reported PA. Those who self-reported less than 60 min/week of MVPA were classified as low PA participants. A statistician generated the randomization list and did not disclose the allocation sequence to the study team members (research assistants/associates) who enrolled and revealed the arm allocation to participants and administered the interventions. For allocation concealment, sequentially numbered, opaque, and sealed randomization envelopes was used for the randomization assignment for all participants.

Intervention

Upon enrolment, all participants were provided with booklets covering the benefits of and strategies for increasing PA, encouraged to achieve ≥ 10,000 steps/day (step target), and issued an activity tracker (Fitbit Zip® for children and a Fitbit Flex® for parents). The child’s activity tracker could be upgraded to a Fitbit Flex® for an additional S$20 (≈ US$14.40). Participants also had access to all features available on the Fitbit app and website.

Child-based incentive arm

Child-based children were awarded S$5 (≈ US$3.60) each week that they achieved the target through logging their steps on the activity tracker according to the following schedule: ≥10,000 steps/day on ≥ 4, ≥5, and ≥ 6 days each week in months 1–3, 4–6, and 7–12, respectively, and their participating parent logged ≥ 2,000 steps/day on ≥ 4 days in the same week. Although all participants were given the same ≥ 10,000 steps/day target, a minimum of 2,000 tracked steps/day was prescribed for incentive awarding to motivate child-based parents to wear the activity tracker. Child-based children could also earn a S$5 (≈ US$3.60) monthly bonus if they and their parents met their respective step targets in all 4 weeks in the month. If either child or parent did not reach their goal (≥ 10,000 steps/day target) or minimum wear (≥ 2,000 steps/day), respectively, in any particular week, the child earned no incentive for that week.

Family-based incentive arm

Family-based children were awarded S$5 (≈ US$3.60) each week that they and their participating parent achieved the same step target schedule presented to child-based children through logging their steps on their activity trackers. Family-based children were also eligible to earn the monthly bonus.

We chose a ≥ 10,000 steps/day target for simplicity because this is an often-recommended target [27] and our prior research revealed that achieving this goal significantly increases PA for both adults and children [12, 28]. The incremental number of target days during each incentive period further encourages participants to strive to increase PA throughout the study. The maximum pay-out possible per child (in either arm) was valued at S$300 (≈ US$216) over 12 months (48 weeks). Pay-outs were disbursed as child-friendly gift vouchers (e.g., Toys"R"Us).

Statistical analysis

The study was powered to detect a medium effect size (r) of 0.3 between family-based and child-based parents at month 12. Using this effect size, an alpha of 0.05, power of 0.8, and assuming 20% attrition at month 12, we needed 158 parent-child dyads per arm.

We used a mixed effects linear difference-in-differences regression of the following form to test our primary hypothesis (H1) on parents:

where steps/day is the number of daily steps recorded for person i on day j as measured by the accelerometer during each assessment. Independent variables include time and treatment (family-based participants) dummies and their interactions, controls for age, gender, and ethnicity, worksite k fixed effects and random effects for individual participants, which adjusts the standard errors for clustering within individuals across days. Tests of our hypotheses were the sign and significance of the interaction terms, which allowed for testing whether step changes from baseline at months 6 and 12 were greater for family-based than child-based parents.

Analogous regressions were run for secondary hypotheses with the exception of H4. This hypothesis was tested with separate mixed effects logistic regression models for each incentive period where the dependent variable is an indicator variable for whether the ≥ 10,000 steps/day target was achieved and the key independent variable is a dummy for family-based participants. This variable allowed for testing whether those in the family-based arm were more likely to achieve the ≥ 10,000 steps/day targets in each incentive period. The logistic regressions included the same controls, and fixed and random effects as the linear model. Finally, we also explored several potential moderators of effectiveness as described in Additional file 2. All analyses were from the intent-to-treat (ITT) perspective and conducted in Stata (version 14.2).

Participant characteristics

Overall, 316 dyads were recruited from January 2016 to July 2017, of which 159 were randomly assigned to the child-based arm and 157 to the family-based arm (Fig. 1, CONSORT flow diagram). Parents were on average 42 years old and 57.0% were male (Table 1). The majority were Chinese (75.3%), college graduates or postgraduates (85.4%), and, among those who declared, had monthly household incomes of ≥S$10,000 (≈US$7,198) (31.1%). Children were on average 9 years old and 54.8% were male. Baseline levels of all parents’ measures are shown in Table 2. Differences between arms for all parents’ characteristics and levels of parents’ measures were not statistically significant at baseline.

Table 1. Participants’ mean (SD) baseline characteristics by study arm.

Participant characteristics	All Participants (n=316)	Child-Based Incentive (n=159)	Family-Based Incentive (n=157)
Parents’ age, years, mean (SD)	42.0 (4.4)	42.0 (4.4)	42.1 (4.5)
Children’s age, years, mean (SD)	9.0 (1.4)	9.0 (1.4)	9.0 (1.4)
Parents’ sex, no. (%)
Male	180 (57.0)	92 (57.9)	88 (56.1)
Children’s sex, no. (%)
Male	173 (54.8)	94 (59.1)	79 (50.3)
Parents’ ethnicity, no. (%)
Chinese	238 (75.3)	120 (75.5)	118 (75.2)
Malay	4 (1.3)	3 (1.9)	1 (0.6)
Indian	62 (19.6)	31 (19.5)	31 (19.8)
Other	12 (3.8)	5 (3.1)	7 (4.5)
Parents’ education, no. (%)
High school or lower	3 (1.0)	0 (0.0)	3 (1.9)
Diploma or professional qualification	43 (13.7)	15 (9.4)	28 (17.8)
College graduate or higher	269 (85.4)	143 (89.9)	126 (80.3)
Monthly household income, no. (%)
<S$5,000	35 (11.1)	17 (10.7)	18 (11.5)
S$5,000–S$9,999	94 (29.8)	52 (32.7)	42 (26.8)
≥S$10,000	98 (31.1)	47 (29.6)	51 (32.5)
Don’t know	3 (1.0)	0 (0.0)	3 (1.9)
Prefer not to say	85 (27.0)	42 (26.4)	43 (27.4)

Table 2. Parents’ mean (SD) baseline measures by study arm.

All Participants

(n=316)

Child-Based Incentive

(n=159)

Family-Based Incentive

(n=157)

Average Baseline Levels of Accelerometry Measures

Steps/day

8338

(2693.0)

8425

(2807.1)

8250

(2564.9)

MVPA^a min/day

44.8

(24.5)

45.6

(24.4)

43.9

(24.5)

MVPA^a bout min/ day

16.9

(18.6)

17.7

(18.7)

16.2

(18.4)

Sedentary activity min/day

526.4

(108.4)

523.0

(107.4)

529.8

(109.2)

Light activity min/day

302.6

(82.4)

303.6

(88.2)

301.7

(75.9)

Moderate activity min/day

42.0

(22.7)

42.8

(22.2)

41.3

(23.2)

Vigorous activity min/day

2.7

(5.1)

2.8

(5.6)

2.6

(4.7)

Total volume of physical activity^b min/day

347.3

(86.3)

349.2

(93.5)

345.6

(78.3)

Average Baseline Levels of Health Measures

Body mass index (kg/m²)

24.4

(3.6)

24.2

(3.7)

24.5

(3.5)

Systolic blood pressure (mm Hg)

115.1

(17.0)

115.5

(17.7)

114.7

(16.2)

NET-F VO_2max^c

30.7

(3.6)

31.0

(3.6)

30.5

(3.5)

EQ-5D Index^d

0.95

(0.09)

0.96

(0.08)

0.95

(0.10)

^a MVPA is moderate-to-vigorous physical activity

^b Total volume of physical activity is the sum of light, moderate, and vigorous activity minutes

^c NET-F VO_2max is a measure of cardiorespiratory fitness assessed without lab-based exercise

^d EQ-5D is a standardized means of measuring health-related quality of life

Six (3.8 %) parents in the child-based and 12 (7.7 %) in the family-based arm were lost to follow-up at month 6. Twenty (12.6 %) parents in the child-based and 17 (10.8 %) in the family-based arms were lost to follow-up at month 12 (Fig. 1).

Steps logged and goal attainment as measured by the activity tracker

Figs. 2A and 2B show average steps/day logged on the activity tracker by week over 48 weeks for parents and children, respectively, for days when ≥500 steps (indicating more than minimal wear) were taken. Child-based parents and family-based parents logged on average 8,955 steps/day, and 10,645 steps/day, respectively. Child-based and family-based children logged similar average steps/day of 10,772 and 10,793, respectively.

Figs. 2C and 2D show the percentage of parents and children meeting the step targets according to the ≥10,000 steps/day schedule by week over 48 weeks. Child-based parents met the target for 37%, 23%, and 21% of the possible weeks in months 1–3, 4–6, and 7–12, respectively. These percentages were higher (79%, 67%, and 55%, respectively) for parents in the family-based arm. Logistic regression results indicate statistically significant differences across all three incentive periods (Additional file 3), consistent with H4. Child-based children met the target for 75%, 65%, and 55% of the possible weeks in months 1–3, 4–6, and 7–12, respectively. These figures were similar to those of children in the family based arm at 77%, 67%, and 57%, respectively. Logistic regression results revealed no statistically significant differences (Additional file 4).

On average, children in the child-based and family-based arm earned S$11.51 (≈US$8.29) and S$11.30 (≈US$8.13) per month, respectively, over the 12-month incentive period.

Parents’ outcomes

The primary outcome regression results based on the accelerometer worn at each assessment period are shown in Table 3. Wear time was not statistically different across arms (Additional file 5). At month 6, family-based parents increased their steps/day by 234 steps (95% CI: -157–624) relative to baseline, whereas child-based parents decreased their steps/day by 379 steps (95% CI: -778–19). Consistent with H1, family-based parents had a positive and statistically significant step differential of 613 steps/day (95% CI: 54–1171) compared to child-based parents at month 6. Adjusting for wear time did not change the direction or significance of this result.

Table 3. Difference (95% CI) in parents’ accelerometer-derived outcomes at months 6 and 12^a.

Difference from Baseline,

by Study Arm

Between-arm Comparisons

Child-Based Incentive

(n=159)

Family-Based Incentive

(n=157)

Family-Based Incentive vs Child-Based Incentive

MONTH 6

Steps/day

-379

(-778, 19)

234

(-157, 624)

613*

(54, 1171)

MVPA^b, min/day

-0.2

(-4.4, 3.9)

2.8

(-0.7, 6.2)

3.0

(-2.4, 8.4)

MVPA^b bouts, min/day

0.0

(-3.2, 3.1)

3.5*

(0.5, 6.5)

3.5

(-0.8, 7.9)

Sedentary activity, min/day

8.6

(-7.7, 25.0)

12.9

(-4.1, 29.8)

4.2

(-19.3, 27.7)

Light activity, min/day

-12.9

(-27.4, 1.7)

-15.8**

(-27.2, -4.3)

-2.9

(-21.4, 15.6)

Moderate activity, min/day

0.2

(-3.5, 4.0)

2.4

(-0.8, 5.5)

2.1

(-2.8, 7.0)

Vigorous activity, min/day

-0.5

(-1.3, 0.4)

0.4

(-0.7, 1.5)

0.9

(-0.5, 2.2)

Total volume of physical activity^c, min/day

-13.1

(-28.9, 2.7)

-13.0*

(-25.1, -0.9)

-0.1

(-19.8, 20.0)

MONTH 12

Steps/day

-208

(-620, 203)

160

(-219, 539)

369

(-191, 928)

MVPA^b, min/ day

0.7

(-3.6, 5.1)

2.9

(-0.5, 6.3)

2.2

(-3.4, 7.7)

MVPA^b bouts, min/day

0.6

(-2.6, 3.8)

2.4

(-0.3, 5.2)

1.8

(-2.4, 6.1)

Sedentary activity, min/day

11.8

(-6.6, 30.3)

13.2

(-6.7, 33.2)

1.4

(-25.7, 28.5)

Light activity, min/ day

-14.5*

(-28.7, -0.2)

-16.5**

(-28.8, -4.3)

-2.1

(-20.9, 16.7)

Moderate activity, min/day

0.8

(-3.1, 4.7)

2.1

(-1.0, 5.2)

1.3

(-3.7, 6.3)

Vigorous activity, min/day

0.01

(-1.0, 1.0)

0.8

(-0.1, 1.6)

0.8

(-0.5, 2.1)

Total volume of physical activity^c, min/day

-13.7

(-28.4, 1.1)

-13.6*

(-26.5, -0.8)

0.0

(-19.6, 19.6)

^a Unadjusted for wear time since wear time was comparable across arms

^b MVPA is moderate-to-vigorous physical activity

^c Total volume of physical activity is the sum of light, moderate, and vigorous activity minutes

Note: * p<0.05, ** p<0.01, *** p<0.001

At month 12, family-based parents increased their steps/day by 160 steps (95% CI: -219–539) relative to baseline whereas child-based parents decreased their steps/day by 208 steps (95% CI: -620–203). However, the differential of 369 steps/day (95% CI: -191–928) was no longer statistically significant, inconsistent with H1. None of the secondary accelerometry-based measures (Table 3) nor any of the health outcomes (Table 4) were statistically different across arms at months 6 or 12, inconsistent with H2.

Table 4. Difference (95% CI) in parent’s health outcomes at months 6 and 12.

Difference from Baseline,

by Study Arm

Between-arm Comparisons

Child-Based Incentive

(n=159)

Family-Based Incentive

(n=157)

Family-Based Incentive vs Child-Based Incentive

MONTH 6

Body mass index (kg/m²)

0.0

(-0.1, 0.1)

0.0

(-0.1, 0.1)

0.0

(-0.1, 0.2)

Systolic blood pressure (mm Hg)

-1.1

(-2.7, 0.4)

-1.7*

(-3.1, -0.3)

-0.6

(-2.6, 1.5)

NET-F VO_2max^a

-0.1

(-0.2, 0.1)

-0.1*

(-0.2, 0.0)

0.0

(-0.2, 0.1)

Change in EQ-5D Index^b

0.016*

(0.002, 0.031)

0.001

(-0.015, 0.018)

-0.015

(-0.037, 0.007)

MONTH 12

Body mass index (kg/m²)

0.2*

(0.0, 0.3)

0.2**

(0.0, 0.3)

0.0

(-0.2, 0.2)

Systolic blood pressure (mm Hg)

-1.1

(-2.9, 0.7)

-0.7

(-2.3, 0.9)

0.4

(-2.0, 2.8)

NET-F VO_2max^a

-0.2***

(-0.3, -0.1)

-0.2**

(-0.3, -0.1)

0.0

(-0.1, 0.2)

Change in EQ-5D Index^b

-0.009

(-0.025, 0.008)

-0.011

(-0.026, 0.005)

-0.002

(-0.024, 0.021)

^a NET-F VO_2max is a measure of cardiorespiratory fitness assessed without lab-based exercise

^b EQ-5D is a standardized means of measuring health-related quality of life

Note: * p<0.05, ** p<0.01, *** p<0.001

Children’s outcomes

Additional file 6 presents children’s accelerometer results. At month 6, relative to baseline, family-based children achieved a statistically significant increase of 464 steps/day (95% CI: 34–895), whereas child-based children logged a decrease of 8 steps/day (95% CI: -445–428), resulting in a statistically non-significant differential of 473 steps/day (95% CI: -139–1085) between the two arms.

At month 12, relative to baseline, family-based children logged an increase of 315 steps/day (95% CI: -131–761), while child-based children logged an increase of 254 steps/day (CI: -184–693), for a non-statistically significant differential of 61 steps/day (95% CI: -565–686). Results for other children’s outcomes were also not statistically different across arms (Additional file 6). Hence, consistent with H3, the family-based incentive did not negatively affect the PA of children in the family-base arm.

Potential moderators

Neither gender, social support for PA, family dynamics, nor enjoyment of PA appeared to moderate the effectiveness of the family-based incentives on steps (Additional file 7).

Given that financial incentives are commonly used to motivate both children and adults to increase PA [7, 8], identifying optimal strategies for leveraging incentives is needed. Linking children’s financial incentives to both their own and their parents’ behavior represents a novel strategy not previously studied.

Findings confirmed our primary hypothesis that the family-based incentive scheme would increase parent’s steps relative to child-only incentives. Results were in the expected direction at both months 6 and 12 but only statistically significant at month 6. Parents in the family-based incentive scheme also increased goal attainment (≥ 10,000 steps/day) over the course of the study (H4) and without negatively affecting children’s PA (H3). In fact, family-based children logged significantly more steps at month 6 compared to baseline and more steps than child-based children at both months 6 and 12 although these differences were not statistically significant (Additional file 6).

Several factors may explain the lack of statistically significant results at month 12. First, we were underpowered to detect step differences of this magnitude. Second, it is possible that the more challenging ≥ 10,000 steps/day threshold on ≥ 6 days a week from months 7–12 was simply too high to be sustained, leading to fewer participants striving to meet the target. Had we kept the target unchanged between months 6 and months 12 (i.e., ≥ 10,000 steps/day on ≥ 5 days/week), it is possible that the month 6 results would have been sustained. However, waning effectiveness of incentives over time is not unique to this study [29]. Nevertheless, despite the lack of statistical significance at month 12, family-based parents exhibited increases in PA compared to child-based parents for all relevant PA outcomes (i.e., steps, MVPA, MVPA bouts, moderate activity, and vigorous activity), suggesting that the family-based incentive may have had some effect on parents’ behavior at month 12.

The lack of differential effectiveness in health outcomes is not surprising given the relatively small differences in steps/day observed across arms. It is possible that if the month 6 step results were maintained, health improvements could have materialized. However, it is also possible that for increased steps to translate to real health improvements, a specific duration and intensity of PA would need to be incentivized. Future studies should consider incentivizing MVPA bout minutes as that may increase the likelihood of sustained health improvements. Without this evidence, it will be difficult to justify the value of any incentive-based program to funders.

Strengths and Limitations

The strengths of this study include its novel intervention design, the randomized nature of the intervention, the 12-month duration, the focus on both PA-based and health outcomes, and the use of accelerometry, a gold standard for measuring PA. The primary limitation concerns the generalizability of these results as we recruited a convenience sample of participants in Singapore. Although the majority of the resident population are fully employed (75% of 25–64 year olds) and English literate [about 84% of the 35–54 years age group (of which 97% of the study’s parent participants fall under)] [30, 31], our sample of parents are highly educated with 99% holding post-secondary qualifications compared to approximately 76% and 50% of Singapore residents for those in age groups 35–44 and 45–54 years, respectively [31], potentially reducing the generalizability of the results both within and beyond Singapore. Hence, whether or not these results are generalizable is unknown.

There is growing interest in identifying optimal incentive strategies aimed to reduce risk factors for chronic disease. Our findings provide evidence that family-based incentives may be a promising strategy. However, more research is needed to identify cost-effective strategies that encourage long-term behavior change of both parents and children.

BMI

body mass index

cpm

counts per minute

EQ-5D-5L

health-related quality of life

FACES IV

Family Adaptability and Cohesion Scale

ITT

intent-to-treat

MVPA

moderate-to-vigorous physical activity

physical activity

PACES

Physical Activity Enjoyment Scale

PASS

Physical Activity and Social Support scale

NET-F

non-exercise test for fitness

vector magnitude

VO_2max

maximum oxygen consumption

WHO

World Health Organization

Ethics approval and consent to participate

Ethics approval was granted by the National University of Singapore Institutional Review Board (Approval Number: NUS 2592). All parents signed informed consent and assented to their child’s participation.

Consent for publication

Not applicable.

Availability of data and materials

De-identified data will be made available upon reasonable request to the corresponding author. An investigator who proposes to use the data must have approval from an Institutional Review Board, Independent Ethics Committee, or Research Ethics Board, as applicable, and execute a data use/sharing agreement with Duke-NUS Medical School.

Competing interests

We declare no competing interests.

Funding

This study was supported by a Health Services Research Competitive Research Grant (HSRG/0048/2015) from the National Medical Research Council, Ministry of Health, Singapore. The study did not involve any partnership with Fitbit.

Authors' contributions

EAF was the principal investigator and conceived the study. EAF, DSW, and KRE designed the study. RLSM was involved in study implementation and data acquisition. EAF, RLSM, DSW, and KRE contributed to the interpretation of the results and critically read and edited several drafts of the manuscript before submission. All authors read and approved the submitted version.

Acknowledgements

We thank Yubing Tian for data analysis and for preparing the initial manuscript drafts.

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Leveraging Family Dynamics to Increase the Effectiveness of Incentives for Physical Activity: The FIT-FAM Randomized Controlled Trial

Status:

Journal Publication

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Abstract

Figures

Background

Methods

Study design and participant characteristics

Outcomes and assessments

Randomization

Intervention

Statistical analysis

Results

Participant characteristics

Steps logged and goal attainment as measured by the activity tracker

Parents’ outcomes

Children’s outcomes

Potential moderators

Discussion

Strengths and Limitations

Conclusions

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors' contributions

Acknowledgements

References

Supplementary Files

Status:

Journal Publication

Version 1