Patient Directed Financial Incentives (P4P4P) to change health related-behaviours

Financial incentives for patients or pay-for-performance-for-patients (P4P4P), is a controversial method that aims to support behavior change by giving the patient rewards for achieved goals. The intervention is used for example to reduce smoking, obesity and a sedentary lifestyle.

Question

What systematic reviews are there on patient directed financial incentives to change health related-behaviours?

Identified literature

Table 1. Systematic reviews with low/medium risk of bias.

CI = Confidence interval; FI = Financial incentives; MD = Mean difference; NCD = Noncommunicable diseases; OR = Odds ratio; PA = Physical activity; PDI = Poly Dispersity Index; RCT = Randomized controlled trial; RR = Risk ratio; SMD = Standardized mean difference; WL = Weight loss; WMD = Weighted mean difference
Included studies Population/Intervention Outcome
Luong et al 2020 [4]
Domain: Physical activity, costs
Studies: 51 RCTs
39 studies included in meta-analysis
Setting: Workplaces, schools, communities and health care.
Risk of bias: Cochrane risk of bias tool. The methodological domain most classified at high risk of bias in individual studies was blinding of participants and personnel.
Inclusion criteria: Adults (>18)
Included population:
Adults aged 18 to 81 (n=17773)
Female: 61%
Intervention: Financial incentives to increase physical activity (PA).
Any material reward or penalty, including, but not limited to cash rewards, deposit contracts, and vouchers that could be exchanged for goods.
Leisure time PA
SMD: 0.46 (95% CI, 0.28 to 0.63). n=15 studies
Leisure time PA at longest follow-up
SMD: 0.10 (95% CI, 0.02 to 0.19). n=6 studies.
Walking behavior (steps)
SMD: 0.25 (95% CI, 0.13 to 0.36). n=20 studies.
MD: 754 steps.
Walking behavior at longest follow-up
SMD: 0.11 (95% CI, 0.00 to 0.22). n=14 studies. MD: 459 steps.
Total time PA
SMD: 0.52 (95% CI, –0.09 to 1.12). n=6 studies.
Total time PA at longest follow-up
SMD: 0.09 (95% CI, –0.33 to 0.51). n=not known.
Estimated cost:
USD 5.60 per MET-hour per person
Authors' conclusion:
“There is moderate quality evidence that financial incentives improved leisure time PA and walking behaviour at the end of the intervention period and moderate-to-high quality evidence of small, sustained effects at the longest follow-up after the incentive had been withdrawn.”

“This review highlights the potential role of financial incentives to promote and maintain PA in adults across diverse settings and populations, with the most robust evidence supporting the use of financial incentives to increase walking behaviour in the short term. There are preliminary data to suggest financial incentives can promote PA maintenance; however, more research is needed to examine the conditions under which financial incentives are likely to drive long-term, post incentive adherence to PA”
Mitchell et al 2019 [6]
Domain: Physical activity
Studies: 23 RCTs.
12 included in meta-analysis.
Setting: 19 of 23 from USA.
Risk of bias: Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for quantitative
Inclusion criteria: Adults (>18).
Included population:
Adults (n=2631)
Mean age: 41 years.
Female: 64.5%
Intervention: Financial incentives, which were defined as any cash or non-cash reward with a monetary value, not including gifts of negligible or symbolic value. Incentives rewarding multiple health behaviours were included if at least part of the incentive was allocated to a physical activity behaviour or outcome.
Daily step counts during intervention:
MD: 607.1 steps (95% CI, 422.1 to 792.1). n=not known.
Daily step counts after intervention (average follow-up: 17.5 weeks):
MD: 513.8 steps (95% CI, 312.7 to 714.9). n=not known
Number of studies with positive effect
20 of 22 studies.
Authors' conclusion:
“That incentives increased physical activity for interventions of short and long durations and after incentives were removed, though the count of studies with positive post-intervention effects was modest. Nonetheless, and contrary to what has been suggested for years, a short-term incentive ‘dose’ may promote sustained physical activity post-intervention.”
Gong et al 2018 [9]
Domain: Physical activity, weight management
Studies: 11 RCTs
Two studies focused on physical activity; nine studies focused on weight loss.
Risk of bias: 5 studies with Jaded Score 5; 1 study scored 4; 5 studies with Jadad Score 3.
Inclusion criteria population: Adults >18 with a chronic health condition or sedentary lifestyle.
Included population: Total population 3524 adults. Obese adults 9 studies, 3282 participants; sedentary lifestyle 1 study, 40 participants; knee replacement for osteoarthritis 1 study, 202 participants. Median sample size n=132 (n=40 to n=1790)
Interventions: Interventions promoting physical activity or weight loss lasting at least 12 weeks. 19 intervention arms.
Deposit contracts, 6 studies; gain incentive, 8 studies; loss incentives, 2 studies; lottery, 2 studies; mixed gain incentive and lottery, 1 study.
Maximum total expected payouts USD 172 to USD 1645.
Combined:
SMD 0.395 (95% CI, 0.243 to 0.546). n=11 studies.
Physical activity:
SMD 0.392 (95% CI, –0.027 to 0.811)
940 steps (95% CI, 306 to 1574)
n=2 studies.
Weight loss:
SMD 0.395 (95% CI, 0.209 to 0.581)
–2.32 kg (95% CI, 1.76 to 2.88)
n=9 studies
Authors' conclusion:
“Our results suggest that FI are moderately effective in improving PA and WL in adults with sedentary lifestyles or comorbidities, increasing steps per day by 940 steps and weight loss by 2.3 kilograms compared to control participants. […]
We found a smaller difference between the control arm and the intervention arm when the control group had more frequent interactions with a health coach. Control participants who receive coaching may be more motivated to participate in healthy behaviors, likely causing a smaller difference seen between control and intervention groups in those studies. […]
We found that longer intervention duration is associated with an attenuated intervention effect. […] When designing FI interventions, habit formation should be emphasized over rewards.”
Purnell et al 2014 [10]
Domain: Weight management
Studies: RCTs (n=3), randomized study (n=1), observational studies (n=2), simulation studies (n=3), quasi-experimental (n=3).
Risk of bias: 6 studies with small sample size and selection bias. 3 studies with possible reporting bias. Only two studies accounted for effects of high attrition.
Population: Adults >18. US-based. Community-based.
Intervention: Financial interventions (monetary or non-monetary) for dietary behavior change.
Financial incentives including: Taxation (simulation studies); Vouchers and re-imbursements (quasi-experimental studies, observation study); deposit contracts (observation study, RCTs); Cash incentives (observation study, randomized study and RCTs); Lottery (observation study, RCTs)
Cash, deposit contract and lottery interventions:
Moderate to large short-term weight-loss. Nonsignificant long-term effects or no long-term difference between intervention and control.
Authors' conclusion:
“Results from a diverse set of studies suggest that certain types of financial incentives for dietary behavior change can be appropriate for addressing the epidemic of obesity and healthful dietary behavior when properly administered, but the issue of behavioral maintenance persists as an unresolved weakness of this approach.”
Paul-Ebhohimhen et al 2008 [11]
Domain: Weight management
Studies: 9 RCTs
8 US-based studies, 1 based in Canada. No included studies conducted after year 2000.

Risk of bias: All studies missing blinding of outcome assessors. Underreporting of random allocation procedure and dropouts in 7 and 6 studies respectively.
Population: Adults ≥18 with BMI ≥28 (allowance made for ethnic groups with lower BMI cut-offs).
Included population: Mean age in studies from 35.7–52.8.
Mean BMI 29.3–31.8.

Interventions: Financial incentives in behavioral obesity treatments with minimum 1 year follow-up.
Incentives in form of cash or cash from participants’ deposited money.
Maximum reward 0.2% of personal disposable income to 10,2%, median at 1.2%
Weight change, WMD
No significant effect
12 months, n=5 studies:
–0.4 kg (95% CI, –1.6 to 0.8 kg)
18 months, n=2 studies:
–0.7 kg (95% CI, –2.5 to 1.1 kg)
30 months, n=1 study:
1.1 kg (95% CI, –1.3 to 3.4)
Weight change for incentives less than 1.2% of PDI, WMD
12 months n=3 studies:
0.0 kg (95% CI, –1.5 to 1.6 kg)
Weight change for incentives above 1.2% of PDI, WMD
12 months, n=2 studies:
–1.1 kg (95% CI, –3.1 to 0.9 kg)
18 months, n=1 study:
–0.7 kg (95% CI, –2.5 to 1.1 kg)
Authors' conclusion:
“Results from meta‐analysis showed no significant effect of use of financial incentives on weight loss or maintenance at 12 months and 18 months. Further sub‐analysis by mode of delivery and amount of incentives although also non‐statistically significant were suggestive of very weak trends in favour of use of amounts greater than 1.2% personal disposable income, rewards for behaviour change rather than for weight, rewards based on group performance rather than for individual performance and rewards delivered by non‐psychologists rather than delivered by psychologists.”
Notley et al 2019 [5]
Domain: Smoking
Studies: 43 RCTs or cluster RCTs
Setting:
33 mixed population studies; 10 studies on pregnant women
Risk of bias:
8 studies were judged as low risk of bias, and 10 to be at high risk of bias, with the rest at unclear risk.
Inclusion criteria: Adults (<18) smokers in any setting. Results is presented separately for pregnant women.
Included population: Adults, mixed population (n=21600); pregnant women (n=2571)

Intervention: Financial incentives to reduce smoking, including cash payments or vouchers for goods and groceries, offered directly or online, valued at 45 USD–1185 USD; or self-deposits.
Incentive schemes to reward participants also included prize draws alongside other guaranteed incentives, but studies which offer only non‐guaranteed rewards (e.g. raffle only) were excluded.
Smoking cessation at 6 to 24 months in mixed population: RR: 1.49 (95% CI, 1.28 to 1.73). n=30 studies. GRADE: High
Smoking cessation at 10 to 24 weeks post-partum
RR: 2.38 (95% CI, 1.54 to 3.69). n=9 studies. GRADE: Moderate
The systematic review also contains descriptive data on costs and adverse effects
Authors' conclusion:
“There is high‐certainty evidence that incentives boost long‐term cessation rates (six months or more) in mixed‐population studies. This effect appears to persist following their discontinuation, suggesting that even a short-incentivised intervention may have long‐term benefits. There is moderate‐certainty evidence that incentives also boost the long‐term cessation rates of pregnant women who smoke, which continues post‐partum.”

“Low‐ to moderate‐value incentives appear to achieve sustained success rates beyond the end of the reward schedule, suggesting that even modest incentive schemes may be effective at encouraging long‐term smoking abstinence. Deposit‐refund trials may be prone to low rates of uptake compared to reward‐based programs; however, people who do sign up and contribute their own money achieve comparable or higher quit rates than reward‐only participants.”
Wilson et al 2018 [8]
Domain: Smoking<br/ > Studies: 22 RCTs
22 studies included in the meta analysis 16 studies on psychotherapy interventions (n=5457), 6 on contingency management (n=1124).
Risk of bias: No studies assessed as high risk of bias. 8 studies had moderate risk of bias, proportionate to intervention type. 14 studies were low risk of bias.
Inclusion criteria: Women smoking tobacco; pregnant during the intervention
Included population:
Pregnant women (n=6581)
Intervention: Contingency management (6 studies, 1124 participants) vs. psychotherapy (16 studies, 5457 participants). Financial incentives: 250 USD–1180 USD. Psychotherapy time: 48 min–600 min.
Smoking cessation at late pregnancy
OR: 3.67 (p<0.001). n=not known.
Smoking cessation at early postpartum
OR: 2.86 (p<0.01). n=not known.
Smoking cessation at late postpartum
OR: 3.96 (p<0.001). n=not known.
Authors' conclusion:
“The findings from the present meta-analysis indicate that contingency management is an efficacious treatment for promoting smoking abstinence at each of the three time points examined. In contrast, psychotherapy-based interventions had nonsignificant effects at each time point.”
Finkelstein et al 2019 [7]
Domain: Physical activity, weight management, smoking, costs.
Studies: 48 RCTs including 70 contrasts (intervention arms)
Risk of bias: Cochrane Risk of Bias Assessment tool. All studies, regardless of risk of bias, included in narrative synthesis.
Included population: Majority of studies on adult populations in high income countries primarily US (68 and 60 contrasts respectively). Specific target population dependent on health domain.
Interventions: Financial incentive interventions for NCD prevention. Trials lasting at least 4 weeks, median 16 weeks (4–78 weeks).
Contrasts targeting diet (n=3), fitness session attendance (n=12), physical activity (n=11), weight loss (n=20) or smoking cessation (n=24); financial incentives in form of cash (n=23), deposit contracts (n=8), lotteries (n=8), non-cash rewards (n=19) or combination of incentive types (n=12).
Narrative analysis
Percentage of contrast with statistically significant effects
All contrasts
48 of 70 (69%) Per domain type
Weight loss
13 of 20 (65%)
Physical Activity
5 of 11 (45%)
Fitness session attendance
10 of 12 (83%)
Healthy food purchases
1 of 3 (33%)
Smoking cessation
19 of 24 (79%)
Per incentive type
Cash-based
18 of 23 (78%)
Deposit contracts
6 of 8 (75%)
Non-cash incentives
Combined financial incentives
10 of 12 (83%)
Lotteries
1 of 8 (13%)
Authors' conclusion:
“Our primary finding is that although the overwhelming majority of contrasts reviewed (69%) find a statistically significant intervention effect, the existing evidence base does not provide a strong case for incentives as a tool for NCD prevention in any of the included domains [due to proxy measures and bias in diet and physical activity domains; unclear cost-effectiveness in weight loss and smoking cessation domains]. […]
The review suggests that multi-pronged incentive strategies may be most likely to be effective. This includes strategies that target both participation and outcomes or those that tie incentives to both shorter and longer term behaviours and outcomes. Effectiveness may be more likely by offering more frequent opportunities to earn incentives and by targeting lower income populations. […] This review further suggests strategies that appear least compelling. This includes pure-cash based lotteries […] and deposit contracts.”
Barte et al 2017 [12]
Domain: Physical activity, weight management
Studies: 12 RCTs
Risk of bias: The studies mainly had an unclear risk of bias. A few points with a high risk of bias were assessed. These were mainly in the domain of blinding participants, personnel, and outcome assessments.
Population: Mixed populations, both adults/children and overweight /sedentary individuals.
Interventions: Financial incentives given to an individual to increase physical activity.
Physical activity attendance: 3 of 6 studies showed a positive effect.
Physical activity subjective: 0 of 6 studies showed a positive effect.
Physical activity objective: 3 of 3 studies showed a positive effect.
Fitness: 0 of 2 studies showed a positive effect.
Weight: 1 of 7 studies showed a positive effect
Authors’ conclusion:
“Our study suggests that unconditional incentives (ie, an intervention with only free activity) did not affect physical activity or the other selected outcomes. For studies investigating the effect of a reward, more promising results were found and especially for studies with a reward for physical activity behaviour. For rewards on attendance, three out of five studies showed a positive effect on attendance, which is in line with a previous systematic review.15 However, this kind of reward did not result in other physical-activity, fitness, or weight effects. Therefore, it remains questionable whether these rewards for attending exercise sessions have positive health effects, because an increase in exercise sessions does not have to lead to a better total physical activity pattern.”

References

  1. Luong M-LN, Hall M, Bennell KL, Kasza J, Harris A, Hinman RS. The Impact of Financial Incentives on Physical Activity: A Systematic Review and Meta-Analysis. American journal of health promotion : AJHP 2020:890117120940133.
  2. Mitchell MS, Orstad SL, Biswas A, Oh PI, Jay M, Pakosh MT, et al. Financial incentives for physical activity in adults: systematic review and meta-analysis. British journal of sports medicine 2019.
  3. Gong Y, Trentadue TP, Shrestha S, Losina E, Collins JE. Financial incentives for objectively-measured physical activity or weight loss in adults with chronic health conditions: A meta-analysis. PloS one 2018;13:e0203939.
  4. Purnell JQ, Gernes R, Stein R, Sherraden MS, Knoblock-Hahn A. A systematic review of financial incentives for dietary behavior change. Journal of the Academy of Nutrition and Dietetics 2014;114:1023-35.
  5. Paul-Ebhohimhen V, Avenell A. Systematic review of the use of financial incentives in treatments for obesity and overweight. Obesity reviews : an official journal of the International Association for the Study of Obesity 2008;9:355-67.
  6. Notley C, Gentry S, Livingstone-Banks J, Bauld L, Perera R, Hartmann-Boyce J. Incentives for smoking cessation. The Cochrane database of systematic reviews 2019;7:CD004307.
  7. Wilson SM, Newins AR, Medenblik AM, Kimbrel NA, Dedert EA, Hicks TA, et al. Contingency Management Versus Psychotherapy for Prenatal Smoking Cessation: A Meta-Analysis of Randomized Controlled Trials. Women's health issues : official publication of the Jacobs Institute of Women's Health 2018;28:514-523.
  8. Finkelstein EA, Bilger M, Baid D. Effectiveness and cost-effectiveness of incentives as a tool for prevention of non-communicable diseases: A systematic review. Social Science and Medicine 2019;232:340-350.
  9. Barte JCM, Wendel-Vos GCW. A Systematic Review of Financial Incentives for Physical Activity: The Effects on Physical Activity and Related Outcomes. Behavioral Medicine 2017;43:79-90.

SBU Enquiry Service Consists of structured literature searches to highlight studies that can address questions received by the SBU Enquiry Service from Swedish healthcare or social service providers. We assess the risk of bias in systematic reviews and when needed also quality and transferability of results in health economic studies. Relevant references are compiled by an SBU staff member, in consultation with an external expert when needed.

Published: 1/26/2021
Report no: ut202103
Registration no: SBU2020/815