Misalud: Reducing Cardiovascular Risk in Primary Care: a Randomized Clinical Trial
Study Details
Study Description
Brief Summary
Cardiovascular disease is a leading cause of death and disease in Chile. It explains 27.6% of the causes of death and 14% of disabled adjusted life years in the Chilean population. Low levels of physical activity and low levels of adherence to pharmacological therapy are major risk factors for cardiovascular disease in at-risk populations. This project will design and test the effectiveness of a mobile application based on gamification theory for improving cardiovascular disease control in a population of 900 primary care patients with moderate or high cardiovascular risk levels. A randomized controlled trial was designed to test the effect of the App in improving 30% of the levels of physical activity and adherence to pharmacological therapy and a significant reduction of 20% in cardiovascular risk levels.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Background:
Cardiovascular disease is still a major cause of death and disease in Chile. It explains 27.6% of the causes of death and 14% of disabled adjusted life years in the Chilean population. According to the Chilean National Health Survey the population with moderate and high cardiovascular risk in Chile is 25.5%.
In Chile, 80% of the population holds public health insurance and are beneficiaries of the public health care network at no co-payment. Chile has a strong primary care network. Most of its population is registered in primary care clinics and receives clinical and preventive services for free.
Control of cardiovascular risk factors such as physical activity, hypertension, and diabetes has been insufficient in Chile. Only 20% of the population with moderate or high cardiovascular risk reported adequate levels of physical activity. In addition, only 50% of the population with hypertension reaches adequate blood pressure levels and only 30% of the population with diabetes is well controlled. These insufficient standards are associated with low adherence to pharmacological therapies that do not reach the level of 50% even though medications are free of cost for this population in primary care.
There is evidence that the use of mobile applications can improve cardiovascular disease control in at-risk patients. However, there is a lack of information on the type of best application models (e.g informative, interactive, gamification-based), and on their applicability and effectiveness in real primary care settings. There is some evidence that gamified-based applications are superior that informative or interactive models. There are no well-designed trials in Latin America testing the effectiveness of gamification-based application in reducing cardiovascular risk in primary care patients.
Hypothesis:
Null hypothesis: The use of a gamification-based mobile application in primary care patients does not improve their level of physical activity and medication adherence compared to standard care.
Alternative hypothesis: The use of a gamification-based mobile application in primary care patients improves their level of physical activity and medication adherence compared to standard care.
General Objective:
This project aims to reduce cardiovascular risk in a population with moderate and high-risk levels by developing a mobile interactive application based on gamification that could integrate self-control with clinical management in primary care.
Specific Objectives:
To improve by 30% the level of physical activity in a population with moderate or high cardiovascular risk patients through the use of a new gamification-based mobile application.
To improve by 30% the level of medication adherence in a population of moderate and high cardiovascular risk patients through the use of a new gamification-based mobile application.
To develop a usable, reliable, and safe gamification-based mobile application for primary care patients.
To achieve at least a 66%% of weekly usability rate of the new gamification-based mobile application.
Procedures:
Data sources The trial will be conducted in three primary care clinics in Santiago (La Pintana), Talca (San Clemente) and Concepción (Chiguayante). Primary baseline data will be obtained from personal interviews conducted to a group of 900 participants selected from a random sample of patients with moderated or high cardiovascular risk registered in each primary care clinic. Clinical baseline data will be obtained from electronic charts from the same group of patients using a standardized instrument. All participants will have a basic panel of lab tests that define their cardiovascular risk and are included in the national cardiovascular program as part of their usual care. Half of the participants will complete a 6-minute walk test (6MWT) to assess their aerobic capacity and exercise tolerance. A final survey, clinical assessment, and 6MWT will be conducted at the end of the trial to the same participants.
Data Dictionary:
Primary outcome:
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Level of physical activity: Intensity and frequency of physical activity measured through the International Physical Activity Questionnaire (IPAQ).
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Medication adherence: The extent to which patients comply with medical indications on drug doses and frequency. It will be estimated using the internationally validated "Adherence to Refills and Medications scale" (ARMS)
Secondary outcomes:
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Cardiovascular risk level: Probability of developing a cardiovascular event ( cerebrovascular, heart, blood vessel disease) during the next five years. According to the Chilean National Guidelines based on the Framingham score.
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High Blood Pressure: An abnormal and persistent elevation of blood pressure defined as systolic levels of 140 mm Hg or higher or diastolic levels of 90 mm Hg or higher.
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Diabetes: A metabolic disorder defined as levels of HbA1c levels >= 6.5%, or fasting plasma glucose >= 126 mg/dl, or an oral glucose tolerance test or random plasma glucose level > = 200 mg/dl
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Lipid disorder: A metabolic disorder defined as a total blood cholesterol level ≥ 200 mg/dL, LDL cholesterol < 130, HDL cholesterol > 50 mg/dl and trygglicerides < 200 mg/dl
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Smoking: current smoker defined as an adult who has smoked 100 cigarettes in his or her lifetime and who currently smokes cigarettes.
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Sedentarism: Sedentary life style defined as a level of physical activity lower that 150 minutes per week of moderate aerobic activity.
Registry Baseline and final information gathered directly from participants, electronic charts and 6MWT will be registered in the Research Electronic Data Capture software (Redcap). Redcap is the licensed institutional metadata EDC software used by the Research Center at PUC for clinical trials. Registration will be conducted by an independent assistant team at PUC and will not be accessible to the research team.
In addition, a process information system will be developed based on a tracking form for registering recruitment, intervention compliance, and final evaluation of the study population.
Quality assurance/data check The Chilean National Research Agency (ANID), which is the funding agency for this project, requires researchers to report regularly all steps of the project and any changes that are needed during the process. To assuring a standard report, ANIS required the Principal Investigator to register the information bi-monthly on a specific platform.
(https://fondefsis.conicyt.cl/cgi-bin/proyectos.php) where all relevant activities, processes, landmarks, and results are described. A tracking financial system is also included in a separate section of the platform. In addition, a research executive supervisor is designated by ANID. She has to meet bi-monthly with the research team to assure the scientific the project is developing as planned. Also, a financial supervisor is designated by ANID for assuring that the expenses of the project are in line with the approved budget and are in the correct timing.
The Institutional Review Board at PUC fully reviewed and approved all instruments and procedures conducted in the study. In addition, the whole protocol had to be reviewed and approved by local IRB local Committees in Santiago (SSMSO), Talca (SSMaule) and Concepción (SSConcepción).
A specific team from the project will be in charge of checking the data provided by the interviewers. The team will be responsible for assuring the appropriate conduction of the informed consent process, the correct application of the questionnaires and clinical chart assessment, and the accurate application and registration of the 6MWT. In addition, a random sample of 5% of the interviews will be re-checked to assure correct application. All interviewers will be checked. In case of detection of false data, all interviews conducted by the particular interviewer will have to be repeated.
Sample size:
The sample size was estimated based on the magnitude of the changes expected to achieve after the intervention in the two primary outcomes of the study i.e. level of physical activity and adherence to medication therapy. The sample size was estimated for each clinic independently.
The level of physical activity was based on information provided by the National Health Survey (2017) and the National Survey on Physical Activity (2018). According to this information, the study considered an improvement of at least 30% (i.e 18% to 25%) in the population physically active when comparing the intervention vs. the control group.
Adherence to medical therapy parameters for the population with moderate to high cardiovascular risk in Chile was based on national studies of primary care patients conducted in Chile. According to this information, the study considered a relative improvement of at least 30% (i.e from 50% to 65%) in the level of adherence to medication therapy in the intervention vs. the control group in each clinic. This level of medication therapy adherence is clinically significant for reducing cardiovascular disease in high-risk populations.
The study was designed to achieve a power of 0.8 (i.e. 20% of type II error) to show significant differences between intervention and control groups in each clinic and with a type I error (alfa level) of 0.05 (two-sided test). Based on these parameters, we estimated a sample size of 127 participants per group to detect significant differences in the level of physical activity and 113 participants in each group for detecting significant differences in levels of medication adherence. We estimated an attrition rate of 10% of the population during the study, and therefore, the final sample size was set at 300 participants percenter (150 participants in each group) Missing data: An intention to treat analysis will be conducted as the primary model of the study analysis. Therefore, the primary analysis will consider no change in study variables among participants with missing data. A single imputation method using the mean substitution technique will also be conducted to test the magnitude of the effect of missing data in the final outcome. Sensitivity analysis of these methods will be conducted.
Statistical analysis The data from the study will be collected and registered in the Research Electronic Data Capture (RedCap) platform. Descriptive and analytic statistics will be conducted using IBM-SPSS software professional version. Univariate and multivariate analysis will be conducted to test the association and potential confounder variables between the intervention model and the primary and secondary outcomes considered. A logistic regression model will be applied to analyze categorical variables such as level of physical activity, level of medication adherence, or level of cardiovascular risk changes pre and post-intervention between groups. The model will adjust for potential confounding variables in case there are significant differences in critical variables (e.g. education level) at baseline. A multiple linear regression model will be used for the analysis of continuous variables such as changes in cardiovascular risk scores or Met-min/week scores between groups before and after the intervention. Results of the study will be reported using the CONSORT criteria.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Health App This group will have access to a gamified App to help them to control their cardiovascular risk factors and to improve their adherence to medication therapy. Half of the participants will be allocated to the App group. They will be stratified by age and cardiovascular risk level according to national standards based on the Framingham risk factors level. |
Other: Health App
The intervention will include training health teams and patients in accessing and using a gamified health App 2-3 times a week. The App is based on a gamified character that improves its health if a patient checks its App, complies with her therapy, does regular exercise, and introduces normal levels of blood pressure, lipids level, and HbA1c levels. On the other hand, the character gets sick if the patient does not comply with her therapy or does not achieve certain levels of physical activity (i.e. 30 min moderate exercise 5 times a week or 2.5 hs a week or more than 9000 steps/day).
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| Active Comparator: Usual Care This group will not have access to the gamified App and will receive their usual care at the primary care clinic. In addition, they will receive extra information on cardiovascular risk factors control. Both groups will have the same access to clinical checks and medications at the clinic. |
Other: Usual Care
In this group, participants will receive their usual cardiovascular care according to the national guidelines. All patients receive free care at the primary care clinics and also receive free medications prescribed according to the national guidelines at the clinics. In addition, participants in this group will receive specific written information to improve their medication compliance, level of physical activity, blood pressure, HbA1c, and lipids level control.
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Outcome Measures
Primary Outcome Measures
- Change in medication adherence [Change from baseline medication adherence at 18 months]
Compliance with pharmacologic therapy estimated using the the Adherence to Refills and Medications Scale (ARMS). Unit of Measure : Scale units (Score 12 to 28 units)
- Change in level of physical activity [Change from baseline in level of physical activity at 18 months]
The level of physical activity (vigorous, moderate, mild) of participants will be estimated based on the International Physical Questionnaire (IPAQ) which expresses the energy expended by individuals in MET/min/week. Unit of Measure: MET-minutes/week
- Change in functional capacity [Change from baseline in functional capacity at 18 months]
The functional capacity of a random sample of 50% (450) of participants will be estimated based on the 6-minute walk test. Unit of Measure: Meters
- Change in fatigue level [Change from baseline in fatigue level at 18 months]
The level of fatigue and dyspnea will be estimated using the Borg Scale, which is a component of the 6-minute walk test. Unit of Measure: Scale units (Score: 0 to 10 units)
Secondary Outcome Measures
- Change in cardiovascular risk level [Change from baseline in cardiovascular risk level at 18 months]
Cardiovascular risk level of the participant population will be estimated according to the National Chilean Guidelines of Cardiovascular Disease for Primary Care that is based on the Framingham studies. Unit of measure: risk percentage at 10 years (% at 10 years)
Eligibility Criteria
Criteria
Inclusion Criteria:
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Adults between 30 and 65 years old
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Included in the population-based registration system of primary care clinics in Santiago (La Pintana-LP), Talca (San Clemente-SC) and Concepción (Giguayante-Ch)
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Individuals with a moderate (10-15%) or high (>15%) cardiovascular risk level according to the National Chilean Guidelines adapted from the Framingham scale.
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Individuals with a personal smartphone or with access to a smartphone from a close family relative identified as caring supporters by them.
Exclusion Criteria:
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Adults not in the year range
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Adults not cognitive competent (e.g not able to answer a personal survey)
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Individuals with low or very low cardiovascular risk -
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Primary Care Clinic Concepción (Chiguayante-Ch) | Chiguayante | Concepción | Chile | 4100000 |
| 2 | Primary Care Clinic, Talca (San Clemente-SC) | San Clemente | Talca | Chile | 3520000 |
| 3 | Primary Care Clinic Santiago (La Pintana-Ch) | Santiago | Chile | 8820000 |
Sponsors and Collaborators
- Pontificia Universidad Catolica de Chile
- National Fund for Research and Development in Health, Chile
Investigators
- Study Director: Klaus Puschel, MD,MPH,MSc, School of Medicine. Pontificia Universidad Católica de Chile
- Principal Investigator: Julian Varas, MD, MSc, School of Medicine. Pontificia Universidad Católica de Chile
Study Documents (Full-Text)
None provided.More Information
Additional Information:
- Chilean National Health Survey, 2017
- Health status indicators, Chile 2021
- Ministerio de Salud de Chile, Departamento de Epidemiología, 2019. Informes Encuestas. Encuesta Nacional de Salud 2.
- Ministerio de Salud, Chile. Orientaciones Técnicas. Programa de Salud Cardiovascular, 2017
Publications
- Alvarado L. [Adherence to treatment in chronic diseases and the patient's experience]. Rev Med Chil. 2016 Feb;144(2):269-70. doi: 10.4067/S0034-98872016000200019. Spanish.
- Bansilal S, Castellano JM, Garrido E, Wei HG, Freeman A, Spettell C, Garcia-Alonso F, Lizano I, Arnold RJ, Rajda J, Steinberg G, Fuster V. Assessing the Impact of Medication Adherence on Long-Term Cardiovascular Outcomes. J Am Coll Cardiol. 2016 Aug 23;68(8):789-801. doi: 10.1016/j.jacc.2016.06.005.
- Boutron I, Altman DG, Moher D, Schulz KF, Ravaud P; CONSORT NPT Group. CONSORT Statement for Randomized Trials of Nonpharmacologic Treatments: A 2017 Update and a CONSORT Extension for Nonpharmacologic Trial Abstracts. Ann Intern Med. 2017 Jul 4;167(1):40-47. doi: 10.7326/M17-0046. Epub 2017 Jun 20.
- Du L, Cheng Z, Zhang Y, Li Y, Mei D. The impact of medication adherence on clinical outcomes of coronary artery disease: A meta-analysis. Eur J Prev Cardiol. 2017 Jun;24(9):962-970. doi: 10.1177/2047487317695628. Epub 2017 Jan 1. Review.
- Fernando L, Pamela S, Alejandra L. Cardiovascular disease in Latin America: the growing epidemic. Prog Cardiovasc Dis. 2014 Nov-Dec;57(3):262-7. doi: 10.1016/j.pcad.2014.07.007. Epub 2014 Aug 4.
- Kripalani S, Risser J, Gatti ME, Jacobson TA. Development and evaluation of the Adherence to Refills and Medications Scale (ARMS) among low-literacy patients with chronic disease. Value Health. 2009 Jan-Feb;12(1):118-23. doi: 10.1111/j.1524-4733.2008.00400.x.
- Momany MC, Martinez-Gutierrez J, Soto M, Capurro D, Ciampi F, Thompson B, Puschel K. Development of mobile technologies for the prevention of cervical cancer in Santiago, Chile study protocol: a randomized controlled trial. BMC Cancer. 2017 Dec 13;17(1):847. doi: 10.1186/s12885-017-3870-8.
- Pérez-Jover V, Sala-González M, Guilabert M, Mira JJ. Mobile Apps for Increasing Treatment Adherence: Systematic Review. J Med Internet Res. 2019 Jun 18;21(6):e12505. doi: 10.2196/12505.
- Serón P, Muñoz S, Lanas F. [Levels of physical activity in an urban population from Temuco, Chile]. Rev Med Chil. 2010 Oct;138(10):1232-9. doi: /S0034-98872010001100004. Epub 2011 Jan 10. Spanish.
- Valencia-Monsalvez F, Mendoza-Parra S, Luengo-Machuca L. [Evaluation of Morisky medication adherence scale (mmas-8) in older adults of a primary health care center in Chile]. Rev Peru Med Exp Salud Publica. 2017 Apr-Jun;34(2):245-249. doi: 10.17843/rpmesp.2017.342.2206. Spanish.
- Varleta P, Akel C, Acevedo M, Salinas C, Pino J, Opazo V, García A, Echegoyen C, Rodríguez D, Gramusset L, León S, Cofré P, Hernández H, Neira P, Retamal R, Petit G, Moya N. [Assessment of adherence to antihypertensive therapy]. Rev Med Chil. 2015 May;143(5):569-76. doi: 10.4067/S0034-98872015000500003. Spanish.
- Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, Brauer M, Kutty VR, Gupta R, Wielgosz A, AlHabib KF, Dans A, Lopez-Jaramillo P, Avezum A, Lanas F, Oguz A, Kruger IM, Diaz R, Yusoff K, Mony P, Chifamba J, Yeates K, Kelishadi R, Yusufali A, Khatib R, Rahman O, Zatonska K, Iqbal R, Wei L, Bo H, Rosengren A, Kaur M, Mohan V, Lear SA, Teo KK, Leong D, O'Donnell M, McKee M, Dagenais G. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020 Mar 7;395(10226):795-808. doi: 10.1016/S0140-6736(19)32008-2. Epub 2019 Sep 3. Erratum in: Lancet. 2020 Mar 7;395(10226):784.
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