Obesity in adolescence is a serious worldwide problem. According to the World Health Organization, adolescents are aged 10–19 years, but the Ministry of Health of the Republic of Indonesia, classifies early adolescents as those aged 12–16 years, and late adolescents as those aged 17–25 years old. The report on the health examination of freshmen students of Universitas Indonesia in 2017–2019, stated that about 30% of the freshmen were obese.[3-5]
The design and implementation of conventional programs for the management of obesity are flawed. Conventional management done by means of one-way communication that only occurs during patient visits, which though easier and more practical to implement, often fails to get patients to their targets owing to health workers’ lack of training, insufficient time, and lack of concern for interventions.
A self-empowerment-based patient-centered service with a coaching approach has recently been introduced in the management of the obese, including university students. The concept of a health promotion being developed in universities includes that of self-empowerment for students, an approach that involves the competence of individuals, in this case students, in self-confidence, skill development, and participatory behavior. Patient-centered methods involve a two-way communication during which there is deep intense communication between health workers and patients.
The coaching process can be affected when a person wants to maximize their potential or wants to achieve certain goals in the future. Coaching is given to assist a client called a coachee to enable him to optimize his potential of adopting a positive attitude, a strong mentality, and a healthier lifestyle. In growing and developing self-capacity, coaching focuses more on the effort to improve self-awareness for change. To the knowledge of the researcher’s team, no research that has identified the success of patient-centered services based on self-empowerment with a coaching approach for obese students in Indonesia. This study’s aim was to analyze the applicability and effectiveness of self-empowerment-based patient-centered coaching for the weight loss program model for obese students.
Materials and Methods
The research design was a randomized controlled trial in two groups of obese students in Universitas Indonesia. Ethical approval was obtained from Institutional Review Board vide letter No KET-1361/UN2.F1/ETIK/PPM.00.02/2020 dated 16/11/2020, and written informed consent was taken from all participants in the study.
The study was conducted from August to December 2021 at the university clinic of Universitas Indonesia. Educational and coaching interventions for both groups were carried out online using a zoom platform.
The inclusion criteria in this study were students of Universitas Indonesia, aged not more than 24 years, with a body mass index of 25 kg/m2 or more, and willing to participate in research and sign an informed consent. Excluded were any students with co-morbidities or health problems that could interfere with the condition when the intervention was given (which could be proven by a letter from the treating doctor). The sample size was calculated using the sample size estimation formula for the mean difference in the two independent groups. The level of significance was 1.96 and the power was 0.84. The target population was obese students at the Universitas Indonesia. A total of 60 students met the criteria. The subjects were randomly assigned to two groups using the SPSS software program and the results are found in Figure 1 based on consort 2010. A total of 41 obese students, 23 students in the intervention group, and 18 students in the control group completed the study. A total of 19 students were lost to follow-up [Figure 1].
In the intervention group, students had training sessions plus a patient-centered care intervention program based on self-empowerment with the coaching approach. This program was called “From Fat to Fit with SMART Program.” It is modified from the BSMARTR coaching model with a patent certificate number EC 00202122414 from the Ministry of Law and Human Rights of the Republic of Indonesia. Each coaching session lasting 30–90 min consisted of bonding, setting goals, meaningfulness, agreement, resources, time frame planning, and responsibility. The students also had online sessions on obesity, nutrition, and physical activity from internist experts, clinical nutrition specialists, and sports medicine specialists. Education sessions were held two times (at the beginning of the program and in the middle of the program). There were 8 health coaches comprising family medicine specialists, internists, sports medicine specialists, general practitioners and experienced sports coaches. An internist instructed the students on obesity and its impact on health and a proper diet, and a clinical nutrition specialist instructed them on how to record it, and a sports medicine specialist on the regiment of exercises and how to record it. The intervention group had coaching from health coaches who had been trained by an internationally certified coach. One health coach assisted 4 obese students. The coaching sessions were conducted online in six meetings every 2 weeks through zoom. The successive themes of the coaching sessions were the development of the habit of healthy behavior, vision strategy, body self-image, timeline perspective/state line exercise, happiness model, and healthy behavior habit/vision board. In the control group, only educational sessions were given.
This program comprised measurements of anthropometry, body composition, self-monitored food intake, self-monitored physical activity, subjective well-being, and healthy behavior habits. Anthropometric measurements and body composition measurements were carried out by the research team who had no knowledge of the subjects’ group of origin. Weight was measured using a scale in kilograms, and height was taken with a height-measuring device in centimeters. Body mass index (BMI) was calculated by dividing weight (kilograms) by the square of height (meters) and BMI ≥25 kg/m2 was categorized as obese. The circumference of the waist and hip, as well as waist-to-hip ratio, were taken using a tape in centimeters. The measurement of body composition was done (fat-free mass, total body fat, and muscle mass) using a bioelectrical impedance analysis (BIA) tool named Inbody. Food intake was recorded using a self-monitored food record form. Bouchard Activity Record was used to measure physical activity. A subjective well-being questionnaire consisting of 36 questions that reflected self-esteem components, self-efficacy components, and psychological well-being components was used to measure subjective well-being. Each question had to be answered with really disagree, disagree, neutral, agree, and really agree with the score of 1–5. The cutoff was calculated using formula: total questions x highest score for each question × 80% = 36 × 5 × 80% = 144. The total score ≥144 was categorized as a positive value and the total score <144 was categorized as a negative value.[14-17] The habit of healthy behavior was measured with the healthy behavior habit wheel consisting of eight aspects of healthy behavior habits namely hobby/passion, creative innovation, movement exercise, food nourishment, sleep rest, relational, emotional, and spiritual. The students had to indicate on a scale of 1 (not satisfied) to 10 (very satisfied) showing how satisfied they were in each aspect.[18-21]
Descriptive analysis included computing mean and standard deviation for continuous variable while frequency and percentages for categorical variables. Paired t-test or Mann-Whitney test, as appropriate, were used to compare the average anthropometric measurements (weight, body mass index, waist circumference, and waist-to-hip ratio), body composition (fat-free mass, muscle mass, and total body fat), and self empowerment (subjective well-being,[14-17] healthy behavior habit,[18-21] food intake, and physical activity with self-empowerement-based patient-centered care using the coaching approach between the intervention group and the control group.
The study participants consisted of 41 obese Indonesian students aged 18–22 years (divided into two groups) studying at Universitas Indonesia. There was no significant difference in the proportion of gender characteristics and faculty origin in the two groups [Table 1]. There was no difference in the mean or median value on the characteristics of age, anthropometric status (weight, BMI, waist circumference, hip circumference, waist-to-hip ratio), or body composition (fat-free mass, total body fat, and muscle mass) in the two groups before intervention [Table 2]. Healthy behavior habits in the control group had a significantly higher value than in the intervention group (44.2 ± 10.79 vs. 52.2 ± 9.46, P = 0.02) [Table 2]. However, there was no significant difference between the two groups on subjective well-being, food intake, and physical activity of the subjects before the intervention [Table 2]. Data obtained from previous surveys regarding behavioral changes theory stated that obese students at Universitas Indonesia’s clinic were at the stage of contemplation and action using the s-weight indicator.
After the intervention, no difference in the average value of the measurement of self-empowerment (subjective well-being and healthy behavior habit) in the two groups was seen [Table 3]. With regard to the measurement of food intake, the intervention group had a statistically significant greater value than the control group (1334.7 [874–2252.7] vs. 1124.4 [850.6–1987.2], P = 0.04), while the value of physical activity in the intervention group was statistically significantly lower than in control group (1.8 ± 0.29 vs. 2.2 ± 0.49, P = 0.01), both of which had significant differences [Table 3].
The value of changes in the intervention group was statistically significantly greater than in the control group as regards the component of total body fat (−0.9 [−12.9, 0.70] vs. 0.0 [−6.9, 3.50], P = 0.02) and healthy behavior habit (13.5 ± 11.85 vs. 7.5 ± 8.08, P = 0.04). The value of changes between the intervention group and control group with regard to body weight (−1 [−15.50, 5.40] vs. 0.15 [−9.80, 5], P = 0.08), body mass index (−0.8 [−6, 2.20] vs. 0.0 [−4, 6], P = 0.14), waist circumference (−1.7 ± 5.36 vs. 0.87 ± 4.11, P = 0.18), hip circumference (−2.8 ± 5.67 vs. −1.1 ± 3.11, P = 0.40), waist-to-hip ratio (0.01 ± 0.04 vs. 0.02 ± 0.03, P = 0.44), fat-free mass (0.00 [−10, 1] vs. 0.85 [13.8, 23], P = 0.28), and muscle mass (0.25 ± 1.27 vs. −0.04 ± 1.10, P = 0.67) were clinically positive although not statistically significant (P > 0.05) [Table 4].
No significant difference was found in the measurement of food intake, although the intervention group had a higher score than the control group (112.2 ± 467.85 vs. −1.85 ± 396.36, P = 0.40) [Table 4]. There was a statistically significant difference in physical activity, with higher scores for the control group than the intervention group (0.0 [−0.6, 0.3] vs. 0.1 [−0.6, 1.1], P = 0.04) [Table 4].
For the satisfaction scale of healthy behavior habits, there was no statistically significant difference between the intervention group and the control group before the intervention [Table 5]. However, there were significant differences after the intervention in the hobby component (P = 0.02), movement exercise (P = 0.029), and sleep rest (P = 0.008) [Table 6]. The changes in the satisfaction scale of the habit of healthy behavior was significantly greater in value in the control group with regard to hobby/passion (2 [−4.6] vs. 1 [−2.2], P = 0.02), movement exercise (2.3 ± 2.11 vs. 1.2 ± 1.93, P = 0.03), sleep rest (2 [−6.5] vs. 1 [−3.2], P = 0.01), and the spiritual (1 [0.6] vs. 0 [−1.3], P = 0.00). No significant difference was found in the subjective well-being aspects of respondents (1.61 ± 12.68 vs. 4.78 ± 11.82, P = 0.5) [Table 7].
Reduction of total body fat and improvement in healthy behavior in the intervention group was significantly greater than in the control group. Although not statistically significant, there were reductions in body weight, waist circumference, hip circumference, waist-to-hip ratio, as well as fat free mass, and muscle mass improvement in the intervention group. Reduction in body mass index and waist circumference was associated with reduced risk of metabolic syndrome diseases. Waist circumference is an accurate indicator of cardiovascular risk because it represents central obesity and visceral fat.[25,26] Improvement of fat-free mass, which is the main factor affecting the basal metabolism of the body, was higher in the intervention group in the final measurement than in the control group. A good weight loss program can maintain or prevent the loss of fat-free mass in order not to disturb total energy balance. Effective physical activity can produce stable fat-free mass. The reduction of body weight was greater in the intervention group than in the control group. Body weight loss is a complex process. The body naturally has adaptive thermogenesis regulation during which basal energy expenditure is reduced with any reduction in calorie intake and a decrease in the activity of the hormone leptin in the body. This produces a response in the body in which an anabolic process of fat storage is created and weight gain can occur again. The measurement of weight is also strongly influenced by the pattern of food consumed in the last 12 h from the time of measurement of the subject with the BIA tool. The use of food records or recall and food weighing pre-BIA measurement could be done to ensure a more accurate food intake pre-measurement of subjects, which can affect the later measurement results. Physical activity in the control group was significantly higher than in the intervention group with a lower food intake. In this study, the control group might have indeed reduced their food intake and increased physical activity than the intervention group, but this physical activity did not prevent a decrease in fat-free mass. In the intervention group where the intake was higher than the control group, there was an increase in muscle mass and fat-free mass. Weight loss that is dominated by a decrease in muscle mass tends to result in a posture that looks unfit. This shows that the food intake and the physical activity had an impact on the energy balance in the intervention group.
This study did not only measure body composition but also the respondent’s healthy behavior habits that enable the achievement of a healthy lifestyle and an ideal body weight.[31,32] In this study, the initial value of healthy behavior habits in individuals who underwent health coaching was significantly lower than in those who had no health coaching. At the end of the study, however, the change in the value of healthy behavior habits was greater in the intervention group than in the control group. This shows that health coaching can produce a significant improvement in the subject’s healthy behavior habits. A healthy behavior habit that is developed in line with the theory of a change in one’s behavior is an essential component of a weight loss program.
Reduction in body weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio in the intervention group at the end of the study was better than in the control group although not significant. This is an indication of the positive effect health coaching has on these obesity management indicators.
The reduction in total body fat in the intervention group was significantly greater than in the control group. This is good since the target of obesity treatment is not only to lose weight but also to reduce total body fat.[34-36]
The reduction in total body fat in a weight loss program is a great achievement. A greater increase in the healthy behavior habit of subjects in the intervention group also showed the benefits of health coaching. Other clinically positive results (greater reductions in body weight, BMI, waist circumference, hip circumference, and waist-to-hip ratio) were also observed in the intervention group.
This study had several weaknesses because of the small number of subjects together with the high number of participants who dropped out before the end of the study. There were fewer participants at the end of the study than had started the study. The 3 months of research might have been too long to keep subjects interested and focused from start to the end. There is often a plateau phase in weight loss programs.[37,38] In this case, it might also have been influenced by the fact that adolescents are naturally more reactive and emotionally volatile. Besides, owing to the ongoing pandemic in Indonesia and around the world, social restrictions were imposed to prevent the spread of the SARS-COV2 virus.[40,41] From a mental health perspective, Masgon et al. in 2020 found that policies and restrictions related to COVID-19 led to increased anxiety and reduced life satisfaction in adolescents. With the restrictions, students found it difficult to participate in this research activity, some of which had to be carried out face-to-face, especially as regards anthropometric measurements and body composition. The reduced time allowed for movement on account of the restrictions is likely to affect body weight if improperly handled. Follow-up for participants in this study was done via phone and by text message. Sessions done on an online platform because of the COVID-19 pandemic might also have affected the retention of the study subjects[40,41] resulting in possible attrition bias.
However, there were no significant differences in the changes in the three months of study in anthropometric status, body composition, and self-empowerment in the intervention group compared to the control group. Further research on a larger scale is required to obtain compelling results and determine the ideal duration of intervention necessary for a change of behavior in individuals.
A model weight loss program for obese students was obtained through patient-centered services based on self-empowerment with the coaching approach. This weight loss program model for obese students has proven effective in creating changes in anthropometric status indicators (weight, body mass index, waist circumference, hip circumference, waist-to-hip ratio), body composition (fat-free mass ratio, muscle mass, total body fat), self-empowerment (healthy behavior habits), food intake, and physical activity.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
This study was supported by grants from the Ministry of Research, Technology and Higher Education of the Republic of Indonesia through SEAMEO RECFON for data collection (Grant number: 056a/RECFON-SK/X/2020 and 086j/RECFON-SK/VI/2021) and Indonesian Hydration Working Group. We would like to acknowledge SEAMEO RECFON - PKGR Universitas Indonesia, IHWG, educators, health coaches, Nutrition Science Doctoral Study Program Faculty of Medicine Universitas Indonesia, and all the research team include nurse, dietitian, sports medicine resident, and Universitas Indonesia’s Satellite Clinic. We would also thank the participants of this study for their contribution.
1. Grossman DC, Bibbins-Domingo K, Curry SJ, Barry MJ, Davidson KW, et alUS Preventive Services Task Force. Screening for obesity in children and adolescents:US preventive services task force recommendation statement. JAMA 2017;317:2417–26.
2. Ministry of Health Republic of Indonesia. Manual of National Standards for Youth Care Health Services. Jakarta: Ministry of the Health Republic of Indonesia; 2013.
3. Universitas Indonesia. Universitas Indonesia Freshman Health Examination Results Report Final. Depok: Makara Clinic; 2017.
4. Universitas Indonesia. Universitas Indonesia Freshman Student Health Examination Results Report Final. Depok: Makara Clinic; 2018.
5. Universitas Indonesia. Universitas Indonesia Freshman Student Health Examination Results Report Final. Depok: Makara Clinic; 2019.
7. Rueda-Clausen CF, Benterud E, Bond T, Olszowka R, Vallis MT, Sharma AM. Effect of implementing the 5As of obesity management framework on provider-patient interactions in primary care. Clin Obes 2014;4:39–44.
8. Cochran J. Empowerment in adolescent obesity state of the science. Online J Rural Nurs Health Care 2008;8:63–73.
9. Vanaya Coaching. Health Coaching Changing Behavior. Jakarta: Vanaya Coaching International; 2017.
10. Moher D, Schulz KF, Altman DG. The CONSORT statement:Revised recommendations for improving the quality of reports of parallel-group andomized trials. Lancet 2001;357:1191–4.
11. Munoz N, Bernstein M Nutrition Assessment Clinical and Research Applications. United States: Jones and Bartlet Learning; 2019.
12. Lukaski HC. Requirements for clinical use of bioelectrical impedance analysis (BIA). Ann N Y Acad Sci 1999;873:72–6.
13. Bouchard C, Tremblay A, Leblanc C, Lortie G, Savard R, Thériault G. A method to assess energy expenditure in children and adults. Am J Clin Nutr 1983;37:461–7.
14. Rosenberg M. Society and the Adolescent Self-Imzage. Princeton NJ: Princeton University Press; 1965.
15. Chen G, Gully SM, Eden D. Validation of a new general self-efficacy scale. Organ Res Methods 2001;4:62–83.
16. Ryff CD, Keyes CL. The structure of psychological well-being revisited. J Pers Soc Psychol 1995;69:719–27.
17. Sirigatti S, Stefanile C, Giannetti E, Iani L, Penzo I, Mazzeschi A. Assessment of factor structure of Ryff's Psychological Well-Being Scales in Italian adolescents. Boll Psicol Appl 2009;259:30–50.
18. Atkinson M, Chois RT. Art &Science of Coaching:Step-by-step Coaching. Canada: Exalon Pub; 2010.
19. Atkinson M, Chois RT. Art &Science of Coaching:Inner Dynamics. Canada: Exalon Pub; 2007.
20. Atkinson M, Chois RT. Art &Science of Coaching:Flow, the Core of Coaching. Canada: Exalon Pub; 2011.
21. VHCCP. Wheel of Health. USA: Vanderbilt University Medical Center; 2015.
22. Dutton GR, Lewis CE, Cherrington A, Pisu M, Richman J, Turner T, et al. A weight loss intervention delivered by peer coaches in primary care:Rationale and study design of the PROMISE trial. Contemp Clin Trials 2018;72:53–61.
23. Andrés A, Saldaña C, Beeken RJ. Assessment of processes of change for weight management in a UK sample. Obes Facts 2015;8:43–53.
24. NIH. Managing Overweight and Obesity in Adults. Systematic Evidence Review from the Obesity Expert Panel. UnitedPS.t 4a 4t -e 7s:., U. S. Department of Health and Human Services; 2013:44–7.
25. Zhu S, Wang Z, Heshka S, Heo M, Faith MS, Heymsfield SB. Waist circumference and obesity-associated risk factors among whites in the third National health and nutrition examination survey:Clinical action thresholds. Am J Clin Nutr 2002;76:743–9.
26. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79:379–84.
27. Dayan PH, Sforzo G, Boisseau N, Pereira-Lancha LO, Lancha AH Jr. A new clinical perspective:Treating obesity with nutritional coaching versus energy-restricted diets. Nutrition 2019;60:147–51.
28. Hwaung P, Bosy-Westphal A, Muller MJ, Geisler C, Heo M, Thomas DM, et al. Obesity tissue:Composition, energy expenditure, and energy content in adult humans. Obesity (Silver Spring) 2019;27:1472–81.
29. Walter-Kroker A, Kroker A, Mattiucci-Guehlke M, Glaab T. A practical guide to bioelectrical impedance analysis using the example of chronic obstructive pulmonary disease. Nutr J 2011;10:35.
30. Sirajuddin S, Surmita S, Astuti T. Food Consumption Survey Indonesia. Jakarta: Ministry of Health Republic of Indonesia; 2018.
31. Johnson SS, Paiva AL, Cummins CO, Johnson JL, Dyment SJ, Wright JA, et al. Transtheoretical model-based multiple behavior intervention for weight management:Effectiveness on a population basis. Prev Med 2008;46:238–46.
32. Manchaiah VK. Health behavior change in hearing healthcare:A discussion paper. Audiol Res 2012;2:e4.
34. Forbes GB. Longitudinal changes in adult fat-free mass:Influence of body weight. Am J Clin Nutr 1999;70:1025–31.
35. Stern L, Iqbal N, Seshadri P, Chicano KL, Daily DA, McGrory J, et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults:One-year follow-up of a randomized trial. Ann Intern Med 2004;140:778–85.
36. Willoughby D, Hewlings S, Kalman D. Body composition changes in weight loss:Strategies and supplementation for maintaining lean body mass, a brief review. Nutrients 2018;10:E1876.
37. Rojo-Tirado MA, Benito PJ, Atienza D, Rincón E, Calderón FJ. Effects of age, sex, and treatment on weight-loss dynamics in overweight people. Appl Physiol Nutr Metab 2013;38:967–76.
38. Rojo-Tirado MA, Benito PJ, Ruiz JR, Ortega FB, Romero-Moraleda B, Butragueño J, et al. Body composition changes after a weight loss intervention:A 3-Year follow-up study. Nutrients 2021;13:E164.
39. Somerville LH, Jones RM, Casey BJ. A time of change:behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain Cogn 2010;72:124–33.
40. World Health Organization. Indonesia: WHO Coronavirus Disease (COVID-19) dashboard; 2021. Available from: https://covid19.who.int/region/searo/country/id
. Last accessed on 2022 Jun 06.
41. Djalante R, Lassa J, Setiamarga D, Sudjatma A, Indrawan M, Haryanto B, et al. Review and analysis of current responses to COVID-19 in Indonesia:Period of January to March 2020. Prog Disaster Sci 2020;6:100091.
42. Magson NR, Freeman JY, Rapee RM, Richardson CE, Oar EL, Fardouly J. Risk and protective factors for prospective changes in adolescent mental health during the COVID-19 pandemic. J Youth Adolesc 2021;50:44–57.