Medical technology intervention in improving the quality of life among the type 2 diabetes mellitus patients

INTRODUCTION

T2DM is a chronic disease characterized by high blood glucose levels, caused by a combination of genetic and lifestyle factors such as obesity and physical inactivity, which contributes to insulin resistance or decreased insulin output over time.¹ Diabetes impairs people’s functional capacities and quality of life, resulting in significant morbidity and premature death. These trends have been blamed on increased consumption of unhealthy diets and sedentary lifestyles, which result in elevated body mass index (BMI) and fasting plasma glucose.²

According to the International diabetes federation 2019, there are around 463 million people worldwide living with diabetes and this number is expected to reach 700 million by 2045.³ India is referred to as the diabetic capital of the world. It was discovered in 2017 that India had the second-largest diabetic population, after China, with 73 million diabetic patients and by 2045, this figure is expected to be doubled to 134 million.⁴ Diabetes is a psychologically difficult medical condition for both patients and caregivers. Living successfully with diabetes necessitates lifelong discipline and commitment, which can be very stressful and depressing.⁵

Patient education increases diabetic patients’ QOL and metabolic regulation while also lower the rate of acute complications.6 Several studies have shown that behaviour change is more effective than basic disease education in enhancing diabetes regulation. Still the patients must have a basic understanding of the pathophysiology, complications and treatment of their disease, for controlling the metabolic parameters of diabetes mellitus. Usually, blood glucose levels has been used as an indicator of physiological control for assessing the impact of teaching programs. But recently other indicators like QOL or patient satisfaction have been proposed by educators.⁷

The WHO defined QOL as an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standard and concerns.⁸ When comparing chronically ill people to healthy adults or childbearing women, it was apparent that chronically ill people have lower mean QOL domain ratings.9 There were mixed findings when it came to the connection between QOL and glycaemic regulation and while some studies had clearly shown such a link, others had not.¹⁰ Recent advancements in the fields of patient outcome analysis and health technology assessment have fueled an explosion in the use of QOL evaluation as a clinical research technique. More emphasis is now being placed on assessing the quality of health care and the economic value of new interventions.¹¹

The role of mobile health technologies in improving self-efficacy in the management of chronic diseases is gaining popularity. In the coming years, the integration of mHealth into public health practice as a strategy for chronic disease surveillance will be critical as health costs rise due to an aging population and rising prevalence of chronic disease and co-morbidity.¹² Developers have created effective and user-friendly apps, which an increasing number of smartphone users have downloaded and used to aid in the management of chronic diseases.¹

With the above background the present study was conducted to assess the effect of educational intervention on QOL among the T2DM patients attending the urban health centre, Bannimantap, Mysuru.

METHODS

Study design and population source

A quasi-experimental study was conducted in urban primary health centre, Bannimantap, Mysuru over a period of 6 months (November 2019 to May 2020) among T2DM patients who were regularly attending the non-communicable diseases unit at urban primary health centre. T2DM patients aged 18-65 years having more than 1 year of history of disease were selected for the study. Subjects who owned an android smartphone and received education up to 7th standard and above were included in the study. Patients with severe complications like gangrene, nephropathy, retinopathy, pregnant ladies, patients who were not capable of using smartphone application and illiterates were excluded from the study. The study was approved by the institutional ethics committee and oral informed consent was obtained from the participants after explaining the purpose and procedure of the study.

Sample size

Assuming a mean change of 4 mmol/l and 6 mmol/l in blood sugar of group A and group B and an alpha error of 5% with a power of 80%, at least 46 subjects needed to be studied in each group.^13,14

Sampling technique

T2DM patients who came for treatment at the urban health centre were noted and random number generation was done online. Using simple random sampling technique, the number of T2DM patients were allotted to each group for the study. After the participants were allotted into groups, group A was educational intervention using smartphone application, group B was given intervention with handouts regarding diet and physical exercise and group C was the control group. The patients were assessed for QOL before and 3 months after educational intervention.

Study tool

The study tools used in this study were QOL questionnaire of WHO (WHO-QOL-BREF) and the pre-tested semi-structured questionnaire to assess socio demographic characteristics. WHO-QOL-BREF questionnaire includes total 26 questions, out of 26 questions, 24 questions covered the domains which were classified into 4 domains such as physical health domain, psychological health domain, social functions domain and environmental domain and two questions pertaining to base on the satisfaction of overall health of that person. Each answer to the question was measured through Likert scale from 1-5 score, later each domain score was calculated which had got a set of domain score and was converted to a scale ranging from 0-20, with minimum possible score of 20 and then this score was multiplied with 5 final score which ranged from 0-100 and it was calculated for each domain and the mean domain score of all domains together gave the QOL score in the range of 0-100. Higher the scores, better the QOL.

Statistical analysis

The data collected was entered in Microsoft excel 2019 spreadsheet followed by analysis using SPSS version 23 (licensed to JSS AHER). Qualitative variables like gender, religion, place of residence were represented using proportions. Quantitative data such as scores showing non-parametric distribution were expressed as median and interquartile range. The comparison between the educational interventional and control group was done using Chi-square test and McNemer test. P value <0.05 was considered statistically significant.

RESULTS

In the present study, out of the 138 study participants, around 50 (36.2%) participants belonged to the age group 51-60 years while 48 (34.8%) of them belonged to the age group 41-50 years. Majority of the study participants were females (77.5%) and 31 (22.5%) were males. Around 34 (24.6%) participants were illiterates while another 34 (24.6%) participants had primary school education. Majority of the study participants were homemakers (69.5%). 63% of the subjects belonged to lower middle class of modified Kuppuswamy scale. Around 101 (73.2%) participants belonged to joint family (73.2%) and more than half (57.2%) of the study participants had family history of T2DM. Around 50% of the patients had duration of diseases between 6-10 years and 39.1% between 0-5 years. Around 95 (68.8%) of the participants were on mixed diet and 105 (76.1%) of them were on oral hypoglycaemic drugs (Table 2).

*significant p value.

McNemer test.

Table 2 shows that duration of T2DM and glycaemic status of the patients were found to be statistically significant with a p value of less than 0.05.

On assessing the QOL score across all the four domains, the overall mean score of QOL improved from 81.72±8.572 to 86.43±6.322. After educational intervention, the mean score of physical health (domain 1) increased from 89.77±6.227 to 93.68±5.611, psychological health (domain 2) from 79.94±7.956 to 83.83±7.866, social relationship (domain 3) from 42.93±5.949 to 48.64±5.805 and that of environmental (domain 4) score from 114.35±15.104 to 117.48±13.91.

The QOL scores converted into categorical variable after getting the mean score and dividing the group into above the mean and below the mean score. Then they labelled as good and poor QOL. It was observed that after educational intervention, the total quality of life score was good for around 68 (49.27%) participants while 70 (50.72%) participants had poor QOL score. The physical QOL score was good for 29 (63.1%) out of the 46 group A participants when compared group B and C which had 21 (45.7%) and 20 (43.5%) participants with good QOL. The psychological and social QOL score after educational intervention score was also seen higher in group A, 25 (54.4%) and 28 (60.8%) when compared to group B and C. Majority of the participants in all the three groups had poor environmental QOL score. Group B and C had 25 each participants with poor QOL score while 24 participants in group A had poor environmental QOL score.

In the current study, the association of QOL of study subjects with that of educational intervention was compared using McNemers test and it was found that educational intervention using smartphone app (group A) was significant when compared to group B and group C with a statistical significance of p value <0.05 (Table 3).

DISCUSSION

The present study showed that educational intervention using smartphone application showed more effective results in the management of diabetes mellitus and overall quality of life when compared to handouts and control groups. This was found to be similar to a study conducted by Kumar et al in Mysuru, Karnataka which showed that an intervention using a mobile application had better effect in managing the outcome of T2DM patients.¹⁵ Similar conclusion was also seen in a study conducted in Cairo university of Egypt showed that the educational intervention was an effective tool and had a positive impact on the health of the diabetic patients.¹⁶ Systematic review and meta-analysis study conducted in Beijing, China showed that smartphone apps offered moderate benefits for T2DM self-management which was similar to our study.¹³ Another study conducted in China on mobile based intervention in the management of diabetes (systematic review of randomized control trial) also showed that the use of mobile based intervention yielded a clinically significant HbA1c reduction among adult outpatients with DM.¹⁷

The present study showed improvement in QOL after educational intervention which was similar to another study done by Kumar et al in Mysore, Karnataka which also showed an improvement in QOL after using an android mobile application.¹² Aghamolaei et al in Iran also showed significant improvement in HbA1c and QOL when compared to the control group.¹⁸ Similar study using mobile application was conducted on type 1 diabetes patients by Berndt et al which showed an increase in the QOL of the subjects.¹⁹

However, many studies did not show any significant improvement in QOL as a result of the intervention. Mccarrol et al did a web based interventional study which showed no change in QOL of the subjects.²⁰ Klee et al three-month randomized double-crossover analysis also found that the mobile intervention had no impact on QOL.²¹

According to the findings of our research, educational intervention had a direct effect on the physical and mental health of T2DM patients. The educational intervention aided in the self-care management of diabetic patients so as to handle any complications that arose as a result of T2DM.¹⁴ The boon of easy accessibility and affordability of cell phones in modern life had aided in the success of educational interventions using smart phone applications (group A). In the case of handouts (group B), these benefits were lost. In addition, older diabetic patients with vision problems may be unable to read the instructions on the handouts. As a result, the efficacy of educational intervention in group A was statistically significant with a p<0.05 when compared to the other two groups, group B and C.

CONCLUSION

Educational intervention using smartphone app for the management of T2DM showed a better improvement in quality of life when compared to other two groups, handouts and control group. All the four domains, physical, psychological, social and environmental scores showed improvements after the intervention. Educational interventions, especially technological approaches can be critical in the management of non-communicable diseases so as to improve the overall health and QOL of the patients.

ACKNOWLEDGEMENTS

The authors take this opportunity to thank the study participants for their cooperation. We also thank the medical officer and lab technicians of the urban primary health centre, Bannimantap. We also thank the JSS medical college, Mysuru for allowing us to conduct this study.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

REFERENCES

1. 1. Doddaiah SK, Prakash B, Chandra BS, Kadkol PS, Arun V, Mohandas A, et al. Effectiveness of smartphone-based intervention on the perceptions of type 2 diabetes mellitus patients in Mysuru, Karnataka, India. Obesity Med. 2020;20:100295.
2. 2. Khan MA, Hashim MJ, King JK, Govender RD, Mustafa H, AlKaabi J. Epidemiology of type 2 diabetes-global burden of disease and forecasted trends. J Epidemiol Glob Health. 2020;10(1):107-11.
3. 3. International Diabetes Federation. Fact sheet: Diabetes Atlas, 2020. Available at: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas/159-idf-diabetes-atlas-ninth-edition-2019.html. Accessed on 12 April 2021.
4. 4. Oberoi S, Kansra P. Economic menace of diabetes in India: a systematic review. Int J Diabetes Dev Ctries. 2020:1-12.
5. 5. Ratnesh KS, Kannan S, Khadilkar KS, Sravani GV, Raju R. Identifying the burden and predictors of diabetes distress among adult type 2 diabetes mellitus patients. Indian J Commun Med. 2020;45(4):497.
6. 6. Tankova T, Dakovska G, Koev D. Education of diabetic patients-a one year experience. Patient Educ Couns. 2001;43(2):139-45.
7. 7. Aghamolaei T, Eftekhar H, Mohammad K, Nakhjavani M, Shojaeizadeh D, Ghofranipour F, et al. Effects of a health education program on behavior, HbA1c and health-related quality of life in diabetic patients. Acta Medica Iranica. 2005;43(2):89-94.
8. 8. WHOQOL. Fact sheet: Measuring quality of life, 2020. Available at: https://www.who.int/toolkits/whoqol. Accessed on 12 April 2021.
9. 9. Martínez YV, Prado-Aguilar CA, Rascón-Pacheco RA, Valdivia-Martínez JJ. Quality of life associated with treatment adherence in patients with type 2 diabetes: a cross-sectional study. BMC Health Serv Res. 2008;8(1):1-10.
10. 10. Testa MA, Simonson DC. Health economic benefits and quality of life during improved glycemic control in patients with type 2 diabetes mellitus: a randomized, controlled, double-blind trial. JAMA. 1998;280(17):1490-6.
11. 11. Rubin RR, Peyrot M. Quality of life and diabetes. Diabetes Metab Res Rev. 1999;15(3):205-18.
12. 12. Kumar DS, Prakash B, Chandra BS, Kadkol PS, Arun V, Thomas JJ. An android smartphone-based randomized intervention improves the quality of life in patients with type 2 diabetes in Mysore, Karnataka, India. Diabetes Metab Syndr.2020;14(5):1327-32.
13. 13. Cui M, Wu X, Mao J, Wang X, Nie M. Type 2 Diabetes Mellitus self- management via smart phone applications: a systematic review and meta-analysis. PLoS One. 2016;11(11):0166718.
14. 14. Chen L, Pei J, Kuang J, Chen H, Chen Z, Li Z, et al. Effect of lifestyle intervention in patients with type 2 diabetes: a meta-analysis. Metabolism. 2015;64(2):338-47.
15. 15. Kumar DS, Prakash B, Chandra BS, Kadkol PS, Arun V, Thomas JJ, et al. Technological innovations to improve health outcome in type 2 diabetes mellitus: a randomized controlled study. Clinic Epidemiol Glob Health. 2021;9:53-6.
16. 16. Ahmed MM, Degwy HME, Ali MI, Hegazy NH. The effect of educational intervention on knowledge, attitude and glycemic control in patients with type 2 diabetes mellitus. Indian J Commun Med Pub Health. 2015;2(3).
17. 17. Wu Y, Yao X, Vespasiani G, Nicolucci A, Dong Y, Kwong J, et al. Mobile app-based interventions to support diabetes self-management: a systematic review of randomized controlled trials to identify functions associated with glycemic efficacy. JMIR Mhealth Uhealth. 2017;5(3):35.
18. 18. Aghamolaei T, Eftekhar H, Mohammad K, Nakhjavani M, Shojaeizadeh D, Ghofranipour F, et al. Effects of a health education program on behavior, HbA1c and health-related quality of life in diabetic patients. Acta Medica Iranica. 2005;43(2):89-94.
19. 19. Berndt RD, Takenga C, Preik P, Kuehn S, Berndt L, Mayer H, et al. Impact of information technology on the therapy of type-1 diabetes: a case study of children and adolescents in Germany. J Personal Med. 2014;4(2):200-17.
20. 20. McCarroll ML, Armbruster S, Pohle-Krauza RJ, Lyzen AM, Min S, Nash DW, et al. Feasibility of a lifestyle intervention for overweight/obese endometrial and breast cancer survivors using an interactive mobile application. Gynecolog Oncol. 2015;137(3):508-15.
21. 21. Klee P, Bussien C, Castellsague M, Combescure C, Dirlewanger M, Girardin C, et al. An intervention by a patient-designed do-it-yourself mobile device app reduces HbA1c in children and adolescents with type 1 diabetes: a randomized double-crossover study. Diabetes Technol Therapeut. 2018;20(12):797-805.