Aamir Raoof Memon  ( Institute of Physiotherapy and Rehabilitation Sciences, Peoples University of Medical & Health Sciences for Women, Nawabshah, Sindh, Pakistan. )
Tahir Masood  ( Isra Institute of Rehabilitation Sciences, Isra University, Islamabad Campus )
Waqar Ahmed Awan  ( Isra Institute of Rehabilitation Sciences, Isra University, Islamabad Campus )
Ahmed Waqas  ( CMH Lahore, Medical College & Institute of Dentistry, Lahore Cantt, Pakistan )

Objective: To determine the efficacy of an incentive-based approach combined with a smartphone application in promoting physical activity and weight-loss among female medical students, and to explore among them psychological effects pertaining to self-esteem, guilt, body-shaming, and perception of physical beauty.
Methods: The pilot, randomised controlled trial was conducted at the Peoples University of Medical and Health Sciences for Women, Nawabshah, Pakistan, from March to May 2017, and comprised female students who were randomly allocated to either the incentivized or the non-incentivized group. The incentivized group was given a weekly financial incentive based on the required level of physical activity, measured each week for five weeks using Moves application. All subjects completed several questionnaires covering secondary outcomes at the end of the trial. SPSS 20 was used for data analysis.
Results: Of the 56 subjects, there were 28(50%) in each of the two groups. The use of financial incentives combined with the smartphone application did not result in a significant increase in physical activity (p>0.05). However, within-group weight-loss at the end of intervention was significant for both the groups (p<0.05). There was no significant change in the number of steps in the control group during the course of intervention (p>0.05), but there was a significant decline in the number of steps in intervention group from weeks 4 and 5 compared to the baseline physical activity (p<0.05).
Conclusion: Financial incentives combined with a smartphone app designed to track physical activity did not promote physical activity or decrease obesity.
Keywords: Financial incentive, Obesity, Physical activity, Smartphone, Student. (JPMA 68: 1438; 2018)

Introduction

Physical activity (PA) is considered beneficial in reducing the risk of several diseases, and a lack of it in the early years of life may lead to health problems later.^1,2 PA among university students tends to be lower than the general population, with most of them unable to achieve recommended levels.¹ Female students are particularly vulnerable to physical inactivity (PI) and sedentary behaviour.^3,4 Statistics from Western countries show that PI in university students ranges from 23-59%, compared to 44% in the developing countries.^5,6 A recent large-scale study of university students in 23 countries in all of the world\\\'s major geographical regions found that average PI ranged 37.1-50.5%. In South Asia, the highest PI prevalence was found in Pakistan (80.6%).⁷ At the same time, it should be noted that obesity affects all socioeconomic groups irrespective of their age, gender and ethnicity. The younger population is also vulnerable, which makes it an immediate public health concern.^8,9 A further worry is that for all weight groups, weight-based harassment and bullying have been associated with anxiety about weight, sedentary and bulimic behaviours, lower body satisfaction, lower self-esteem, depressive symptoms and suicidal ideation. ^10,11 Mounting evidence highlights the importance of financial incentives in stimulating healthy behaviours such as weight-loss, improved diet, gym attendance, and smoking cessation.^12-20 Although several studies have focussed on different financial incentives to promote healthy behaviours in many countries, the evidence from Asian countries, especially Pakistan, is non-existent.^19,21-23 At the same time, several studies have looked at the use of smartphone applications to promote PA and weight-loss.^24-26 However, the results of several systemic reviews and meta-analyses are mixed, suggesting that the issue should be explored further.^24,25,27 More specifically, several studies have used the Moves application, and it has been validated as an accurate measure of PA tracking.^28-30 Given the lack of data from developing countries, particularly Pakistan, on the topic, the current study was planned to evaluate the efficacy of the Active Student Trial, and to assess its psychological effects on self-esteem, guilt, body shaming, and the perception of physical beauty among medical students. The current study (ActiveStudent trial) combines an incentive-based approach and a smartphone application, and was designed to promote PA and weight-loss among female university students.

Subjects and Methods

The pilot, randomised controlled trial was conducted at the Peoples University of Medical and Health Sciences for Women (PUMHSW), Nawabshah, Pakistan, from March to May 2017. Due to the absence of a trial registry in Pakistan, approval was obtained from the institutional ethics review committee (Letter No: PUMHS/SBA/VC/511).
The study comprised female undergraduate medical students who were overweight or obese, measured by the Asian body mass index (BMI) cut-off values,31 aged 18-25 years, and active Android/IPhone/Windows smartphone users. Those with known cases of asthma, diabetes mellitus, cardiovascular disease, cancer, physical disability or mental illness were excluded, and so were pregnant and lactating women or those intending to become pregnant within the following two months. Those who were already part of any other PA study, and those who were unable or unwilling to install the Moves application on their smartphone were also excluded.  The selected subjects were randomly allocated to either the incentivized group or the non-incentivized group through a computer-generated randomised table with an allocation ratio of 1:1. The incentivized group was given a weekly financial incentive based on the following schedule: a) PKR100 (0.95 American dollar [USD]) for logging 7500-9999 steps for >4 days per week; b) PKR200 (1.9 USD) for logging >10000 steps for >4 days per week; and c) PKR300 (2.85 USD) for logging >12000 steps for >4 days per week. On the other hand, the control group was not given any incentives. PA, in the form of step count, was measured each week for five weeks by the Moves application (ProtoGeoOy Inc., Helsinki, Finland).³² The tool has been validated as accurate for this purpose.^28,30 Participants were instructed to download the application and leave it running in the background with their smartphones switched on. They were told to carry their phones with them at all times, either in a pocket or on a belt clip. Demographic and general information was obtained through a questionnaire. BMI was measured at the beginning and at the end of the trial. Participants also completed several questionnaires covering secondary outcomes at the end of the trial [see Supplementary material]. Prior to the inclusion in the study, all subjects signed an informed consent form. All the participants were given a detailed description of the study, and their anonymity and data confidentiality was guaranteed. Data was analyzed using SPSS 20. Categorical variables were presented as frequencies and percentages, while continuous variables were presented as mean ± standard deviation. Differences between the groups were assessed using the independent t-test. The significance level was set at p<0.05. Variation in number of steps taken by study participants across six time points and between the groups were estimated using mixed-design analysis of variance (ANOVA) which had repeated measures with a between-subject factor. Mauchly\\\'s test was run to ensure that the assumption of sphericity was met prior to running the mixed-design ANOVA. Post-hoc pairwise comparisons were conducted using Tukey\\\'s test corrected with Bonferroni method.

Results

A total of 268 participants were assessed and 56(21%) who met the inclusion criteria were randomly allocated to the two groups of 28(50%) each (Figure-1).



Of the total, 27(48.2%) subjects were pursuing a Doctorate in Physical Therapy, followed by 23(41%) studying for a Bachelor\\\'s degree in Medicine and Surgery (MBBS). Overall, 49(87.5%) subjects were using android-based smartphones and 45(80.4%) reported a family history of non-communicable diseases, including diabetes and obesity. Although 31(55.4%) subjects reported being active, 53(94.66%) were uninterested in participating in any future PA programme (Table-1).



Within-group weight-loss at the end of intervention was significant for both groups (p<0.05). Although participants in the intervention group took more steps and weighed less than the controls, the effect was not statistically significant (Table-2).



The intervention group started with relatively higher number of steps than the control group which was noted throughout the study, but there was a steep decline in the number of steps for both the groups (Figure-2).



A significant decline in physical activity was observed across the six time points (p<0.001). There was no significant main effect of the type of intervention and mean number of steps taken during the intervention (p=0.331). There was no significant interaction between time and type of intervention (p=0.284). There were no significant differences between the number of steps taken from to week 4 (p>0.05). However, compared to the baseline, a significant decline in physical activity was observed at week 4 (p<0.001) and week 5 (p<0.001) in the intervention group.
There were no significant differences between the groups when measured on several scales and inventories (p>0.05 each) (Table-3).



Discussion

This study found that a programme of financial incentives did not result in a significant inter-group difference measured as PA (number of steps), body weight, or secondary outcomes (p>0.05). Although the incentivized group took more steps than the control group throughout the duration of the study, the difference was not statistically significant (p>0.05). However, five weeks after the intervention, within-group weight-loss was significant for both the intervention (p<0.001) and the control group (p<0.05). There were no differences in number of steps taken by the intervention and control group. However, during the intervention, both groups experienced progressive decline in number of steps taken.Although smartphone applications are increasingly used in interventions that promote PA and weight-loss,^24-26 several reviews have reported mixed results.^24,25,27 Patel et al. used a combination of the Moves smartphone application and financial incentives in a sample of university employees, and found it effective in promoting PA in obese and overweight individuals.30 However, the incentives they provided were much higher than those in the current study. Several studies have demonstrated the short-term (4-12 week) efficacy of financial incentives in stimulating weight-loss.^12,19,33 and, overall, the evidence suggests that monetary incentives do result in goal attainment.^15,34 Although they appear to be effective in sustaining adherence to an exercise programme for more than one year, their potential for promoting exercise maintenance is questionable.^21,35 Additionally, several underlying theories and mechanisms, such as operant conditioning and behavioural economics, have been claimed to be responsible for the effectiveness of financial incentives in influencing behaviour. ^36,37 The use of smartphone applications in health interventions (especially PA research) is widespread, but their psychometric validity remains to be established,^24,29 particularly as a decline in adherence to smartphone-based interventions has been reported.^27,38 Hence, it is essential to include behavioural change techniques in research on PA applications to improve participant motivation.³⁹ It has been found that weight status, weather conditions, socioeconomic characteristics and seasonal change influence the efficacy of incentivized PA and weight-loss programmes.^40,41 Although mixed findings have been reported regarding the potential of incentives to improve the uptake of walking programmes and completion rates, some authors argue that factors such as the schedule, size and other contextual factors may alter the efficacy of monetary incentives.^34,40,42,43 It is likely that these factors apply to the population in the current study as the trial was conducted during the summer-time exam season, which may explain the decline in PA during the study. Another potential explanation lies in the Hawthorne effect,⁴⁴ as baseline PA was initially considerably higher in both groups at the beginning compared to the end of the study. The step count fell to almost half of baseline for both the intervention (12865.36±9364.03 vs 6697.00±6339.61) and control group (9029.82±6346.24 vs 6130.29±4698.69). It is possible that meagre amount of monetary incentives did not extrinsically motivate the incentivized group in improving the physical activity level (PKR 100 for logging 7500-9999 steps for >4 days per week). Future research utilising higher amount of financial incentive as a motivator to improve physical activity is needed. The findings of the current study reflect that the participants were sedentary on the basis of number of steps taken during the study period. Additionally, 55.4% believed that they were physically active, but 94.66% of them were not interested in participating in any future PA programme. This shows that the participants were intrinsically not motivated to participate in physical activity. Moreover, an incorrect perception of physical activity may suggest participants\\\' lack of understanding of physical activity. The most likely reasons for this include highly demanding study schedules and commitments and lack of integration of PA and emphasis on its importance in undergraduate curricula. Furthermore, previous studies have recommended adopting a randomised control design with a larger sample size over a longer duration.45,46 The current study is a first step in this direction in the context of developing countries where the consequences of obesity and PI can be a costly public health burden. Simple, cost-effective preventive measures may help to address the enormous direct and indirect costs associated with PI and obesity. To the best of our knowledge, this is the first study in South Asia (particularly Pakistan), on the combined use of financial incentives and smartphone technology to improve PA and reduce body weight in overweight and obese subjects. However, it has a few limitations. As mentioned earlier, due to the absence of a trial registry in Pakistan, approval was obtained from PUMHSW, Nawabshah. Based on our findings, we recommend that future studies should recruit a larger sample from more diverse settings, divided equally into intervention and control groups, with incentives that are designed to optimally motivate participants. Our study did not include a pre-intervention assessment of secondary outcomes, and future work should include pre- and post-intervention assessments. A further consideration is that this intervention was limited to female participants. We recommend that future studies should also assess efficacy in males. The study used self-reporting measures, which can increase recall bias in the assessment of outcomes. Finally, the combined use of financial incentives and rigorously designed smartphone technology for tracking PA, along with dietary and cognitive behavioural interventions are recommended as a way to improve PA and reduce body weight.

Conclusion

Although there was a noticeable reduction in body weight in both the groups after the five-week intervention, the combination of financial incentives and smartphone applications were not found to be effective in promoting PA and in decreasing obesity.

Acknowledgements: The authors would like to acknowledge Farsam Lutfi (Doctor of Physical Therapy Student) for her help in the data collection. We thank Elaine Seery (AuthorAID in the Eastern Mediterranean) for improving the use of English in the manuscript.
Conflict of Interest: None.
Disclosure: This study was part of corresponding author\\\'s thesis required for the partial fulfilment of Master of Philosophy (M.Phil) in Health, Physical Education & Sports Sciences.
Source of Funding: PUMHSW, Nawabshah, partially funded the study.

References

1. Dabrowska-Galas M, Plinta R, Dabrowska J, Skrzypulec-Plinta V. Physical activity in students of the Medical University of Silesia in Poland. Phys Ther. 2013; 93:384-92.
2. Reiner M, Niermann C, Jekauc D, Woll A. Long-term health benefits of physical activity-a systematic review of longitudinal studies. BMC Public Health. 2013; 13:813.
3. Radu L-E, F?g?ra? S-P, Vanvu G. Physical Activity Index of Female University Students. Procedia Soc Behav Sci. 2015; 191:1763-6.
4. El-Gilany A, Badawi K, El-Khawaga G, Awadalla N. Physical activity profile of students in Mansoura University. East Mediterr Health J. 2011; 17:694-702.
5. Haase A, Steptoe A, Sallis JF, Wardle J. Leisure-time physical activity in university students from 23 countries: associations with health beliefs, risk awareness, and national economic development. Prev Med. 2004; 39:182-90.
6. Keating XD, Guan J, Piñero JC, Bridges DM. A meta-analysis of college students\\\' physical activity behaviors. J Am Coll Health. 2005; 54:116-25.
7. Pengpid S, Peltzer K, Kassean HK, Tsala JPT, Sychareun V, Müller-Riemenschneider F. Physical inactivity and associated factors among university students in 23 low-, middle-and high-income countries. Int J Public Health. 2015; 60:539-49.
8. Hingorjo MR, Syed S, Qureshi MA. Overweight and obesity in students of a dental college of Karachi: lifestyle influence and measurement by an appropriate anthropometric index. J Pak Med Assoc. 2009; 59:528-32.
9. Anand T, Grover S, Tanwar S, Kumar R, Meena GS, Ingle GK. Accuracy of body weight perceptions among students in a medical school in Central Delhi, India. Educ Health (Abingdon). 2015; 28:96-100.
10. Eisenberg ME, Neumark-Sztainer D, Story M. Associations of weight-based teasing and emotional well-being among adolescents. Arch Pediatr Adolesc Med. 2003; 157:733-8.
11. Hayden-Wade HA, Stein RI, Ghaderi A, Saelens BE, Zabinski MF, Wilfley DE. Prevalence, characteristics, and correlates of teasing experiences among overweight children vs. non?overweight peers. Obes Res. 2005; 13:1381-92.
12. Gneezy U, Meier S, Rey-Biel P. When and why incentives (don\\\'t) work to modify behavior. J Econ Perspect. 2011; 25:191-209.
13. Dallery J, Glenn IM. Effects of an Internet?based voucher reinforcement program for smoking abstinence: A feasibility study. J Appl Behav Anal. 2005; 38:349-57.
14. Giné X, Karlan D, Zinman J. Put Your Money Where Your Butt Is: A Commitment Contract for Smoking Cessation. Am Econ J Appl Econ. 2010; 2:213-35.
15. Charness G, Gneezy U. Incentives to exercise. Econometrica. 2009; 77:909-31.
16. Paloyo AR, Reichert AR, Reinermann H, Tauchmann H. The Causal Link Between Financial Incentives and Weight Loss: An Evidence?Based Survey of the Literature. J Econ Surv. 2014; 28:401-20.
17. Finkelstein EA, Hoerger TJ. Can fiscal approaches help to reduce obesity risk?. In: Crawford D, Jeffery RW, Ball K, Brug J, eds. Obesity Epidemiology: From Aetiology to Public Health. USA: Oxford University Press, 2010; pp 368-79.
18. Cahill K, Perera R. Competitions and incentives for smoking cessation. Cochrane Database Syst Rev. 2011; 4:CD004307.
19. Paul-Ebhohimhen V, Avenell A. Systematic review of the use of financial incentives in treatments for obesity and overweight. Obes Rev. 2008; 9:355-67.
20. Wall J, Mhurchu CN, Blakely T, Rodgers A, Wilton J. Effectiveness of monetary incentives in modifying dietary behavior: a review of randomized, controlled trials. Nutr Rev. 2006; 64:518-31.
21. Mitchell MS, Goodman JM, Alter DA, John LK, Oh PI, Pakosh MT, et al. Financial incentives for exercise adherence in adults: systematic review and meta-analysis. Am J Prev Med. 2013; 45:658-67.
22. Finkelstein EA, Linnan LA, Tate DF, Birken BE. A pilot study testing the effect of different levels of financial incentives on weight loss among overweight employees. J Occup Environ Med. 2007; 49:981-9.
23. Volpp KG, John LK, Troxel AB, Norton L, Fassbender J, Loewenstein G. Financial incentive-based approaches for weight loss: a randomized trial. JAMA. 2008; 300:2631-7.
24. Jee H. Review of researches on smartphone applications for physical activity promotion in healthy adults. J Exerc Rehabil. 2017; 13:3-11.
25. Bert F, Giacometti M, Gualano MR, Siliquini R. Smartphones and health promotion: a review of the evidence. J Med Syst. 2014; 38:9995.
26. Bort-Roig J, Gilson ND, Puig-Ribera A, Contreras RS, Trost SG. Measuring and influencing physical activity with smartphone technology: a systematic review. Sports Med. 2014; 44:671-86.
27. Shin DW, Yun JM, Shin JH, Kwon H, Min HY, Joh HK, et al. Enhancing physical activity and reducing obesity through smartcare and financial incentives: a pilot randomized trial. Obesity (Silver Spring). 2017; 25:302-10.
28. Evenson KR, Furberg RD. Moves app: a digital diary to track physical activity and location. Br J Sports Med. 2017; 51:1169-70.
29. Case MA, Burwick HA, Volpp KG, Patel MS. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA. 2015; 313:625-6.
30. Patel MS, Asch DA, Rosin R, Small DS, Bellamy SL, Heuer J, et al. Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults: A Randomized, Controlled Trial. Ann Intern Med. 2016; 164:385-94.
31. WHO EC. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363: 157-63.
32. Moves app [Online] [Cited 2017 Dec 24]. Available from: URL: http://moves-app.com/.
33. Finkelstein EA, Brown DS, Brown DR, Buchner DM. A randomized study of financial incentives to increase physical activity among sedentary older adults. Prev Med. 2008; 47:182-7.
34. Jeffery RW. Financial incentives and weight control. Prev Med. 2012; 55:S61-7.
35. Jeffery RW, Wing RR, Thorson C, Burton LR. Use of personal trainers and financial incentives to increase exercise in a behavioral weight-loss program. J Consult Clin Psychol. 1998; 66:777-83.
36. King D, Greaves F, Vlaev I, Darzi A. Approaches based on behavioral economics could help nudge patients and providers toward lower health spending growth. Health Aff (Millwood). 2013; 32:661-8.
37. Strohacker K, Galarraga O, Williams DM. The impact of incentives on exercise behavior: a systematic review of randomized controlled trials. Ann Behav Med. 2014; 48:92-9.
38. Duncan M, Vandelanotte C, Kolt GS, Rosenkranz RR, Caperchione CM, George ES, et al. Effectiveness of a web- and mobile phone-based intervention to promote physical activity and healthy eating in middle-aged males: randomized controlled trial of the ManUp study.J Med Internet Res.
2014; 16:e136.
39. Conroy DE, Yang CH, Maher JP. Behavior change techniques in top-ranked mobile apps for physical activity. Am J Prev Med. 2014; 46:649-52.
40. Martin E, Abreu D, Winters F. Money and motive: effects of incentives on panel attrition in the survey of income and program participation. J Off Stat. 2001; 17:267-84.
41. Tucker P, Gilliland J. The effect of season and weather on physical activity: a systematic review. Public Health. 2007; 121:909-22.
42. Gingerich SB, Anderson DR, Koland H. Impact of financial incentives on behavior change program participation and risk reduction in worksite health promotion. Am J Health Promot. 2012; 27:119-22.
43. Farooqui MA, Tan YT, Bilger M, Finkelstein EA. Effects of financial incentives on motivating physical activity among older adults: results from a discrete choice experiment. BMC Public Health. 2014; 14:141.
44. McCambridge J, Witton J, Elbourne DR. Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. J Clin Epidemiol. 2014; 67:267-77.
45. Glynn LG, Hayes PS, Casey M, Glynn F, Alvarez-Iglesias A, Newell J, et al. SMART MOVE- a smartphone-based intervention to promote physical activity in primary care: study protocol for a randomized controlled trial. Trials. 2013; 14:157.
46. Knight E, Stuckey MI, Prapavessis H, Petrella RJ. Public health guidelines for physical activity: is there an app for that? A review of android and apple app stores. JMIR Mhealth Uhealth. 2015; 3:e43.