mHealth intervention to improve quality of life in patients with chronic diseases during the COVID-19 crisis in Paraguay: A study protocol for a randomized controlled trial

Tamara Escrivá-Martínez, Mª Dolores Vara, Nadia Czeraniuk, Matías Denis, Francisco J Núñez-Benjumea, Luis Fernández-Luque, Alba Jiménez-Díaz, Vicente Traver, Juan José Llull, Antonio Martínez-Millana, Jorge Garcés-Ferrer, Marta Miragall, Rocío Herrero, Analía Enríquez, Verena Schaefer, Sergio Cervera-Torres, Cecilia Villasanti, Carmen V Cabral, Irene Fernández, Rosa Mª Baños, Tamara Escrivá-Martínez, Mª Dolores Vara, Nadia Czeraniuk, Matías Denis, Francisco J Núñez-Benjumea, Luis Fernández-Luque, Alba Jiménez-Díaz, Vicente Traver, Juan José Llull, Antonio Martínez-Millana, Jorge Garcés-Ferrer, Marta Miragall, Rocío Herrero, Analía Enríquez, Verena Schaefer, Sergio Cervera-Torres, Cecilia Villasanti, Carmen V Cabral, Irene Fernández, Rosa Mª Baños

Abstract

Background: Patients with chronic disease represent an at-risk group in the face of the COVID-19 crisis as they need to regularly monitor their lifestyle and emotional management. Coping with the illness becomes a challenge due to supply problems and lack of access to health care facilities. It is expected these limitations, along with lockdown and social distancing measures, have affected the routine disease management of these patients, being more pronounced in low- and middle-income countries with a flawed health care system.

Objectives: The purpose of this study is to describe a protocol for a randomized controlled trial to test the efficacy of the Adhera® MejoraCare Digital Program, an mHealth intervention aimed at improving the quality of life of patients with chronic diseases during the COVID-19 outbreak in Paraguay.

Method: A two-arm randomized controlled trial will be carried out, with repeated measures (baseline, 1-month, 3-month, 6-month, and 12-month) under two conditions: Adhera® MejoraCare Digital Program or waiting list. The primary outcome is a change in the quality of life on the EuroQol 5-Dimensions 3-Levels Questionnaire (EQ-5D-3L). Other secondary outcomes, as the effect on anxiety and health empowerment, will be considered. All participants must be 18 years of age or older and meet the criteria for chronic disease. A total of 96 participants will be recruited (48 per arm).

Conclusions: It is expected that the Adhera® MejoraCare Digital Program will show significant improvements in quality of life and emotional distress compared to the waiting list condition. Additionally, it is hypothesized that this intervention will be positively evaluated by the participants in terms of usability and satisfaction. The findings will provide new insights into the viability and efficacy of mHealth solutions for chronic disease management in developing countries and in times of pandemic.

Trial registration: ClinicalTrials.gov NCT04659746.

Conflict of interest statement

The authors have declared that no competing interests exist.

Copyright: © 2022 Escrivá-Martínez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Figures

Fig 1. SPIRIT flow diagram: Schedule of…
Fig 1. SPIRIT flow diagram: Schedule of enrollment, interventions and assessments.
CFS, Computer Fluency Scale; EQ-5D-3L, EuroQol 5-Dimensions 3-Levels Questionnaire; GAD-2, Generalized Anxiety Disorder Questionnaire-2; PHQ-2, Patient Health Questionnaire-2; PSS-4, Perceived Stress Scale-4; GSES-12, General Self-Efficacy-12; HES, Health Empowerment Scale; SUS, System Usability Scale; TUQ, Telehealth Usability Questionnaire; MAUQ, mHealth App Usability Questionnaire; and CSQ, Client Satisfaction Questionnaire. *This instrument will be administered in the Adhera MejoraCare condition.
Fig 2. Functionalities of the Adhera MejoraCare…
Fig 2. Functionalities of the Adhera MejoraCare solution.
Left: Symptom’s monitoring. Center: Patient empowerment categories in the educational section. Right: Educational units included in the ‘‘How to protect from coronavirus” category.

References

    1. Xiong J, Lipsitz O, Nasri F, Lui LMW, Gill H, Phan L, et al.. Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J. Affect. Disord. 2020;277: 55–64. doi: 10.1016/j.jad.2020.08.001
    1. Torales J, O’Higgins M, Castaldelli-Maia JM, Ventriglio A. The outbreak of COVID-19 coronavirus and its impact on global mental health. I Int. J. Soc. Psychiatry. 2020;66: 317–320. doi: 10.1177/0020764020915212
    1. de Oliveira-Andrade R. Covid-19: Concerns rise as cases expand rapidly in South America. BMJ. 2020;369: m1926. doi: 10.1136/bmj.m1926
    1. Torales J, Ríos-González C, Barrios I, O’Higgins M, González I, García O, et al.. Self-Perceived Stress During the Quarantine of COVID-19 Pandemic in Paraguay: An exploratory survey. Front Psychiatry. 2020;11: 558691. doi: 10.3389/fpsyt.2020.558691
    1. Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with covid-19: Evidence from meta-analysis. Aging. 2020;12: 6049–6057. doi: 10.18632/aging.103000
    1. Kang C, Yang S, Yuan J, Xu L, Zhao X, Yang J. Patients with chronic illness urgently need integrated physical and psychological care during the COVID-19 outbreak. Asian J Psychiatr. 2020; 51: 102081. doi: 10.1016/j.ajp.2020.102081
    1. Cransac-Miet A, Zeller M, Chagué F, Faure AS, Bichat F, Danchin N, et al.. Impact of COVID-19 lockdown on lifestyle adherence in stay-at-home patients with chronic coronary syndromes: Towards a time bomb. Int J Cardiol. 2021;323: 285–287. doi: 10.1016/j.ijcard.2020.08.094
    1. Saqib MAN, Siddiqui S, Qasim M, Jamil MA, Rafique I, Awan UA, et al.. Effect of COVID-19 lockdown on patients with chronic diseases. Diabetes Metab Syndr Clin Res Rev. 2020;14: 1621–1623. doi: 10.1016/j.dsx.2020.08.028
    1. Chudasama Y V., Gillies CL, Zaccardi F, Coles B, Davies MJ, Seidu S, et al.. Impact of COVID-19 on routine care for chronic diseases: A global survey of views from healthcare professionals. Diabetes Metab Syndr Clin Res Rev. 2020;14: 965–967. doi: 10.1016/j.dsx.2020.06.042
    1. Liu N, Huang R, Baldacchino T, Sud A, Sud K, Khadra M, et al.. Telehealth for noncritical patients with chronic diseases during the COVID-19 pandemic. J. Med. Internet Res. 2020;22: e19493. doi: 10.2196/19493
    1. Curioso WH. Building capacity and training for digital health: Challenges and opportunities in Latin America. J. Med. Internet Res. 2019;21: e16513. doi: 10.2196/16513
    1. Kruse C, Betancourt J, Ortiz S, Luna SMV, Bamrah IK, Segovia N. Barriers to the use of mobile health in improving health outcomes in developing countries: Systematic review. J. Med. Internet Res. 2019;21: e13263. doi: 10.2196/13263
    1. Kouroubali A, Koumakis L, Kondylakis H, Katehakis DG. Smart healthcare apps for quality cancer patient support. International Journal of Big Data and Analytics in Healthcare. 2020;5: 28–48. doi: 10.4018/978-1-5225-8021-8.ch003
    1. Triantafyllidis A, Kondylakis H, Votis K, Tzovaras D, Maglaveras N, Rahimi K. Features, outcomes, and challenges in mobile health interventions for patients living with chronic diseases: A review of systematic reviews. Int. J. Med. Inform. 2019; 132: 103984. doi: 10.1016/j.ijmedinf.2019.103984
    1. Maisto M, Diana B, Di Tella S, Matamala-Gomez M, Montana JI, Rossetto F, et al.. Digital interventions for psychological comorbidities in chronic diseases—A systematic review. J Pers Med. 2021;11: 30. doi: 10.3390/jpm11010030
    1. Debon R, Coleone JD, Bellei EA, De Marchi ACB. Mobile health applications for chronic diseases: A systematic review of features for lifestyle improvement. Diabetes Metab Syndr. 2019;13: 2507–2512. doi: 10.1016/j.dsx.2019.07.016
    1. Kristjansdottir OB, Børøsund E, Westeng M, Ruland C, Stenberg U, Zangi HA, et al.. Mobile app to help people with chronic illness reflect on their strengths: Formative evaluation and usability testing. J Med Internet Res. 2020;4: e16831. doi: 10.2196/16831
    1. Parks AC, Williams AL, Kackloudis GM, Stafford JL, Boucher EM, Honomichl RD. The effects of a digital well-being intervention on patients with chronic conditions: Observational study. J Med Internet Res. 2020;22: e16211. doi: 10.2196/16211
    1. Kondylakis H, Katehakis DG, Kouroubali A, Logothetidis F, Triantafyllidis A, Kalamaras I, et al.. COVID-19 Mobile apps: A systematic review of the literature. J. Med. Internet Res. 2020; 22; e23170. doi: 10.2196/23170
    1. Moher D, Schulz KF, Simera I, Altman DG. Guidance for developers of health research reporting guidelines. PLoS Med. 2010;7: e1000217. doi: 10.1371/journal.pmed.1000217
    1. Eysenbach G, Consort-Ehealth Group. Consort-Ehealth: improving and standardising evaluation reports of web-based and mobile health interventions. J J. Med. Internet Res. 2011;13: e126. doi: 10.2196/jmir.1923
    1. Chan AW, Tetzlaff JM, Gøtzsche PC, Altman DG, Mann H, Berlin JA, et al.. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013; 346: e7586. doi: 10.1136/bmj.e7586
    1. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al.. SPIRIT 2013 statement: Defining standard protocol items for clinical trials. Ann. Intern. Med. 2013; 158: 200–207. doi: 10.7326/0003-4819-158-3-201302050-00583
    1. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. In: Behavior Research Methods. 2007; 39: 175–191. doi: 10.3758/bf03193146
    1. Liu WT, Huang CD, Wang CH, Lee KY, Lin SM, Kuo HP. A mobile telephone-based interactive self-care system improves asthma control. Eur Respir J. 2011;37: 310–317. doi: 10.1183/09031936.00000810
    1. Andrews G, Cuijpers P, Craske MG, McEvoy P, Titov N. Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: A meta-analysis. PLoS One. 2010;5: e13196. doi: 10.1371/journal.pone.0013196
    1. Van Ballegooijen W, Cuijpers P, Van Straten A, Karyotaki E, Andersson G, Smit JH, et al.. Adherence to internet-based and face-to-face cognitive behavioural therapy for depression: A meta-analysis. PLoS One. 2014;9: e100674. doi: 10.1371/journal.pone.0100674
    1. Instituto Nacional de Estadística. Proyección de la Población por Sexo y Edad, 2019. Itapúa: INE; 2021. Available from:
    1. Ministerio de Tecnologías de la Información y Comunicación. Dirección General de Encuestas, Estadísticas y Censos 2019. Paraguay: MITIC; 2021. Available from:
    1. Saghaei M. Random allocation software for parallel group randomised trials. BMC Med Res Methodol. 2004;4: 26. doi: 10.1186/1471-2288-4-26
    1. World Medical Association. World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013; 310: 2191–2194. doi: 10.1001/jama.2013.281053
    1. Food Drug Administration. International conference on harmonization, good clinical practice: consolidated guidelines, Federal Register, USA. 1997. Avaliable at:
    1. American Psychological Association. Ethical Principles of Psychologists and Code of Conduct. Am. Psychol. 2002;57, 1060–1073. doi: 10.1037/0003-066X.57.12.1060
    1. World Health Organization. Coronavirus disease (COVID-19) advice for the public. World Health Organization. 2020. Available from:
    1. Ryff CD. Happiness is everything, or is it? Explorations on the meaning of psychological well-being. J Pers Soc Psychol. 1989;57: 1069–1081. doi: 10.1037/0022-3514.57.6.1069
    1. Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: Toward an integrative model of change. J Consult Clin Psychol. 1983;51: 390–395. doi: 10.1037//0022-006x.51.3.390
    1. Hors-Fraile S, Schneider F, Fernandez-Luque L, Luna-Perejon F, Civit A, Spachos D, et al.. Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: A study protocol. BMC Public Health. 2018;18: 698. doi: 10.1186/s12889-018-5612-5
    1. Carrasco-Hernandez L, Jódar-Sánchez F, Núñez-Benjumea F, Conde JM, González MM, Civit-Balcells A, et al.. A mobile health solution complementing psychopharmacology-supported smoking cessation: Randomized controlled trial. JMIR mHealth uHealth. 2020; 8: e17530. doi: 10.2196/17530
    1. Becker EM. Computer fluency, access to technology, and attitudes towards technologically-based therapeutic tools among practicing clinicians—University of Miami; 2012. Available from:
    1. Badia X, Roset M, Montserrat S, Herdman M Segura A. The Spanish version of EuroQol: a description and its applications. European Quality of Life scale. Med Clin. 1999;112: 79–85. Available from:
    1. EuroQol Group. EuroQol—a new facility for the measurement of health-related quality of life. Health Policy. 1990;16: 199–208. Available from: doi: 10.1016/0168-8510(90)90421-9
    1. Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al.. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study. Qual Life Res. 2013;22: 1717–1727. doi: 10.1007/s11136-012-0322-4
    1. Keeley T, Al-Janabi H, Lorgelly P, Coast J. A qualitative assessment of the content validity of the ICECAP-A and EQ-5D-5L and their appropriateness for use in health research. PLoS One. 2013;8: e85287. doi: 10.1371/journal.pone.0085287
    1. Herdman M, Badia X, Berra S. El EuroQol-5D: una alternativa sencilla para la medición de la calidad de vida relacionada con la salud en atención primaria. Aten Primaria. 2001;28: 425–430. doi: 10.1016/s0212-6567(01)70406-4
    1. Kroenke K, Spitzer RL, Williams JBW, Monahan PO, Löwe B. Anxiety disorders in primary care: Prevalence, impairment, comorbidity, and detection. Ann Intern Med. 2007;146: 317–325. doi: 10.7326/0003-4819-146-5-200703060-00004
    1. García-Campayo J, Zamorano E, Ruiz MA, Pérez-Páramo M, López-Gómez V, Rejas J. The assessment of generalised anxiety disorder: psychometric validation of the Spanish version of the self-administered GAD-2 scale in daily medical practice. Health Qual Life Outcomes. 2012;10: 114. doi: 10.1186/1477-7525-10-114
    1. Kroenke K, Spitzer RL, Williams JBW. The Patient Health Questionnaire-2. Med Care. 2003;41: 1284–1292. doi: 10.1097/01.MLR.0000093487.78664.3C
    1. Rodríguez-Muñoz MF, Castelao PC, Olivares ME, Soto C, Izquierdo N, Ferrer FJ, et al.. PHQ-2 como primer instrumento de cribado de la depresión prenatal. Rev Esp Salud Pública. 2017; 91: e201701010. Available from:
    1. Herrero J, Meneses J. Short web-based versions of the Perceived Stress (PSS) and Center for Epidemiological Studies-Depression (CESD) Scales: A comparison to pencil and paper responses among Internet users. Comput Human Behav. 2006;22: 830–846. doi: 10.1016/j.chb.2004.03.007
    1. Vallejo MA, Vallejo-Slocker L, Fernández-Abascal EG, Mañanes G. Determining factors for stress perception assessed with the Perceived Stress Scale (PSS-4) in Spanish and other European samples. Front Psychol. 2018;9: 37. doi: 10.3389/fpsyg.2018.00037
    1. Bosscher R. J., Smit J. H., & Kempen GIJM. Algemene competentieverwachtingen bij ouderen [Global expectations of self-efficacy in the elderly: An investigation of psychometric properties of the General Self-Efficacy Scale]. Ned Tijdschr voor Psychol. 1997;52: 239–248. Available from:
    1. Herrero R, Espinoza M, Molinari G, Etchemendy E, Garcia-Palacios A, Botella C, et al.. Psychometric properties of the General Self Efficacy-12 Scale in Spanish: General and clinical population samples. Compr Psychiatry. 2014;55: 1738–1743. doi: 10.1016/j.comppsych.2014.05.015
    1. Serrani DJL. Escala de empoderamiento sobre la salud para adultos mayores. Adaptación al español y análisis psicométrico. Colombia Médica. 2014; 45: 179–186. Available from: (accessed on 2 February 2021).
    1. Brooke J. SUS: a quick and dirty usability scale. Usability Eval Ind. 1996;189: 4–7. Available from:
    1. Sevilla-Gonzalez MDR, Moreno Loaeza L, Lazaro-Carrera LS, Bourguet Ramirez B, Vázquez Rodríguez A, Peralta-Pedrero ML, et al.. Spanish version of the System Usability Scale for the Assessment of Electronic Tools: Development and Validation. JMIR Hum Factors. 2020;7: e21161. doi: 10.2196/21161
    1. Parmanto B, Lewis AN Jr., Graham KM, Bertolet MH. Development of the Telehealth Usability Questionnaire (TUQ). Int J Telerehabilitation. 2016;8: 3–10. doi: 10.5195/ijt.2016.6196
    1. Torre AC, Bibiloni N, Sommer J, Plazzotta F, Angles MV, Terrasa SA, et al.. Traducción al español y adaptación transcultural de un cuestionario sobre la usabilidad de la telemedicina. Med (Buenos Aires). 2020;80: 134–137. Available from:
    1. Zhou L, Bao J, Setiawan IMA, Saptono A, Parmanto B. The mhealth app usability questionnaire (MAUQ): Development and validation study. JMIR mHealth uHealth. 2019;7: e11500. Available from: doi: 10.2196/11500
    1. Attkisson C, Greenfield TK. The Client Satisfaction Questionnaire (CSQ) scales and the Service Satisfaction Scale-30. Assess Clin Pr. 1996;30: 120–127. Available from:
    1. Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: Development of a general scale. Eval Program Plann. 1979;2: 197–207. doi: 10.1016/0149-7189(79)90094-6
    1. Roberts RE, Atrkisson CC, Mendias RM. Assessing the Client Satisfaction Questionnaire in English and Spanish. Hisp J Behav Sci. 1984;6: 385–396. doi: 10.1177/07399863840064004
    1. Wilcox R. Introduction to robust estimation and hypothesis testing. 3rd ed. Burlington: Elsevier; 2013.
    1. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdate: LEA; 1988.
    1. Algina J, Keselman HJ, Penfield RD. An alternative to Cohen’s standardized mean difference effect size: A robust parameter and confidence interval in the two independent groups case. Psychol. Methods. 2005; 10: 317–328. doi: 10.1037/1082-989X.10.3.317
    1. Budd J, Miller BS, Manning EM, Lampos V, Zhuang M, Edelstein M, et al.. Digital technologies in the public-health response to COVID-19. Nat. Med. 2020; 26; 1183–1192. doi: 10.1038/s41591-020-1011-4
    1. Hoffer-Hawlik MA, Moran AE, Burka D, Kaur P, Cai J, Frieden TR, et al.. Leveraging telemedicine for chronic disease management in low- and middle-income countries during Covid-19. Glob Heart. 2020; 15: 63. doi: 10.5334/gh.852
    1. Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of attrition and dropout in app-based interventions for chronic disease: Systematic review and meta-analysis. J. Med. Internet Res. 2020; 22: e20283. doi: 10.2196/20283

Source: PubMed

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