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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.
Full 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:
Secondary outcomes:
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.
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900 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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