Messages For Your Health: A Cancer Screening Prevention Study
NCT ID: NCT02376023
Last Updated: 2017-02-09
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
UNKNOWN
Clinical Phase
NA
Total Enrollment
400 participants
Study Classification
INTERVENTIONAL
Study Start Date
2016-02-22
Study Completion Date
2017-12-31
Brief Summary
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The purpose of this study is to evaluate the implementation and effectiveness of text messages as a means for improving adherence to cervical cancer screening.
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Detailed Description
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1. Problem Outline, Theoretical Framework and Project Justification
The problem: Cervical Cancer
Cervical cancer is a serious public health problem. Worldwide, it is the third leading cause of death of women. An estimated 270,000 women die every year due to cervical cancer, and more than 85% of these deaths take place in developing countries (1).
Chile´s national cervical cancer program was created in 1987. Since then, and with the systematic implementation of cervical cancer screening through Papanicolau (Pap) smears, cervical cancer mortality rates have dropped significantly (2,3).
In spite of all efforts, cervical cancer continues to cause the mortality of more than 500 women each year in Chile. Across the nation, only 59 percent of the population is up-to-date with their Pap, a figure that has not changed significantly in the last 10 years (2). In the Metropolitan Region, this percentage is as low as 56 percent. The distribution of cervical cancer, like that of other cancers, follows a pattern of inequality in that women of lowest socioeconomic status are those most affected (4).
Closing the Gap: Mobile Health (mHealth)
Mobile technologies have had an exponential increase in the last few years.
In 2014, the penetration of mobile phones will reach 90% in developing countries compared to 121% in developed countries. (5, 6).
This same trend can also be seen in access to mobile broadband technologies, which will have an estimated penetration of 32% by the end of 2014.
The number of internet users worldwide follows this same trend as well. By the end of 2014, there will be more than 3 billion users, with more than 2/3 of these in developing countries.
According to a survey by the Deputy Minister of Telecommunications in Chile (7), access to a mobile or fixed internet connection was 39.4% by the end of 2009. This increased to over 60% by 2012.
This coverage is distributed unequally according to socioeconomic class, with more than 81% of penetration in richer homes and less than 30% in poorer strata (21.4% and 9.8% respectively).
On the other hand, mobile telephones reached more than 90% of homes in 2009, of both rural and urban survey respondents interviewed by the Deputy Minister of Telecommunications. While inequalities remain in this area as well, they are much less profound than with other technologies: the mobile telephone can be found widely distributed in all socioeconomic levels, and varies between 97% in richer strata and 82.8% in poor SES (7).
By the end of 2013, the percentage of mobile telephone subscribers per 100 inhabitants was almost 40% for mobile phones with a contract and more than 94% for phones with prepaid plans.
The Solution: Using mobile health technology (mHealth)
Mobile health (mHealth) has been defined by the WHO (World Health Organization) as "medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices" (9).
Given the explosion of the use of these technologies in the world and particularly in developing countries, the potential for mobile health in health issues is huge.
The overall interest in mobile health is widespread (11). According to the WHO´s report on mHealth in 2011 (9), mobile health strategies exist in at least 75% of the countries that belong to the WHO in each region. 100% of the countries in the Southeast Asian region reported some mobile health initiative at different stages of development, and the Americas region reported that more than 90% of its countries had some form of mobile health initiative (Chile was not included in these statistics).
According to the World Bank, high-income countries reported more initiatives than low-income countries.
Some examples of mobile health initiatives in Latin America are the following: Mexico reported a mobile health program called MedicalHome in which a million mobile telephone subscribers have access to health professional support by telephone for $5 per month, which is charged directly to the cell phone account. Columbia reported a program for treatment adherence reminders using voice messages and Peru reported a RCT (Randomized Controlled Trial) that was done to assess treatment adherence using text messaging in patients with HIV/AIDS (9).
One of the most relevant problems regarding the use of these technologies is that there isn´t sufficient evidence of its effectiveness in prevention (12). Because of this, it is imperative to invest in rigorous and systematic evaluations of these interventions so that they can be applied at the population level.
While some evidence exists that shows that mobile health is an effective strategy for treatment adherence for prenatal care and those with HIV and TB (13,14,15), the potential use of mobile health technologies in cancer prevention has not been fully explored. Given the widespread existence of mobile telephones in Chile, investigators intend with this study to deliver a simple, replicable, and scalable intervention to improve the rates of morbidity and mortality due to cervical cancer that afflict Chile´s population.
2. Research Questions
1\. Do mobile technologies have a preventive benefit in women with greater risk of getting cervical cancer as compared to usual care? 2. In women with greater risk of getting cervical cancer, what are the barriers and facilitators to implementing this kind of technological intervention?
3\. Research Hypotheses
1. Null Hypothesis: The proposed intervention does not increase Pap adherence rates in the studied health centers.
Alternative Hypothesis: The proposed intervention increases Pap adherence rates in the studied health centers.
2. Null Hypothesis: An intervention using mobile technology cannot be feasibly implemented in this population.
Alternative Hypothesis: It is possible to implement an intervention using mobile technology in this population.
4\. Study Objectives General Objective: Evaluate the implementation and effectiveness of a mobile health intervention to increase cervical cancer screening adherence.
Specific Objectives:
1. Evaluate the effect that a text message intervention has on Pap adherence rates.
2. Evaluate the implementation and usability of a cellphone mobile health intervention in three health centers of the Southeast Metropolitan Health District of Santiago.
5\. Methodology Design:
1. Quantitative phase:
1. Target Population:
Target population will be women between 25 and 64 years of age who use cell phones and do not have an up-to-date Pap test (no Pap in the last three years). They must also be registered at one of the following health clinics: CESFAM (Centro de Salud Familiar) El Roble or CESFAM Juan Pablo II.
A randomized controlled trial will be carried out to evaluate the effectiveness of text message intervention in improving Pap adherence. Socio-demographic variables associated with its effectiveness will also be analyzed.
Selection methodology: Using the database of medical records in each clinic, women will be identified that meet the inclusion criteria. They will be invited to participate in the study, and if they choose to accept, informed consent will be obtained.
Before randomization, the participants will be asked to complete a questionnaire with simple demographic questions and questions regarding their beliefs and attitudes about cellphone use and cervical cancer.
2. Randomization:
Participants will be randomized into either the intervention group or the control group using a randomization software that keeps the randomization sequence hidden. The control group will receive their usual care in each health center, which consists of different interventions depending on the health center they attend. Examples of usual care include periodic midwife visits, education by health personnel and cervical cancer health campaigns.
c) Intervention: Women randomized to the intervention group will receive text and voice messages (designed with input from previous qualitative phase) sent to their cellphones that remind them to get a Pap smear, send them information about cervical cancer, and inform them of health clinic location and hours where they could get a Pap smear.
2. Qualitative phase:
The implementation of a mHealth intervention could fail for many reasons. Some of the previously described barriers for this and other types of mobile interventions are: restrictions in the number of characters in the text message, illiteracy, poor signal coverage and quality, and confidentiality and pertinence in families where cellphones are shared.
However, there may be many other factors that hinder or facilitate its effectiveness: lack of funds to keep credit on a cellphone throughout the entire month, losing the phone, little use of text messaging in the elderly, among others.
Investigators will carry out focus groups with women who receive care at the participating centers in order to define barriers and facilitators to a text message intervention that will promote Pap adherence.
Focus Groups Participants:
Women between 25 and 64 years old that meet the inclusion criteria for the study.
Midwives at the health care centers.
Investigators will carry out nine (9) focus groups in total. Women will let us know about barriers and facilitators to the use of this technology and midwives will help investigators to characterize the usual care that women receive and better inform text message content as well as barriers to their use.
Every community member that attends a focus group will receive an incentive of 5,000 Chilean pesos (8 USD) for their time and information. Each health professional that attends a focus group will receive 10,000 Chilean pesos (16 USD).
Data Encoding The focus groups will be led by individuals expert in qualitative methods and assisted by the Principal Investigator and a student assistant who will serve as a note-taker. The focus groups will be recorded for analysis.
The audio of the focus groups will be transcribed and coded using the software Atlas.ti version 6.2
Analysis Information will be analyzed using a qualitative content analysis process\* by two or more investigators who will extract relevant themes regarding usage patterns, barriers, and facilitators to this type of intervention. Investigators will use the conceptual framework called PRECEDE-PROCEED in order to carry out the analysis\*. Investigators will use it to identify predisposing factors that reinforce and enable the use of mobile technologies to improve Pap adherence.
The collected information will contribute to the design of the intervention, and from there the quantitative phase of the study will begin.
d) Sample size Previous studies have shown that without an intervention, around 30% of women who are not up-to-date with their Pap test will get a Pap within the following 6-12 months. Looking at literature regarding similar interventions for other pathologies, investigators anticipate seeing an absolute increase of 15% in adherence rate. With this difference in proportions, and alpha errors of 5% and beta errors of 20%, the estimated sample size is 176 per arm. Considering a loss of 10%, investigators will recruit an estimated 200 patients per arm.
e) Statistical Analysis Investigators will use descriptive statistics to characterize demographic variables of the included patients in the same manner as charactering the indicators of implementation.
For the primary outcome (proportion of women with an up-to-date Pap), investigators will use a chi-squared test to test differences in proportions.
For the multivariate analysis, investigators will use logistic regression and Poisson regression.
For the categorical variables, investigators will use a chi-squared test.
The problem: Cervical Cancer
Cervical cancer is a serious public health problem. Worldwide, it is the third leading cause of death of women. An estimated 270,000 women die every year due to cervical cancer, and more than 85% of these deaths take place in developing countries (1).
Chile´s national cervical cancer program was created in 1987. Since then, and with the systematic implementation of cervical cancer screening through Papanicolau (Pap) smears, cervical cancer mortality rates have dropped significantly (2,3).
In spite of all efforts, cervical cancer continues to cause the mortality of more than 500 women each year in Chile. Across the nation, only 59 percent of the population is up-to-date with their Pap, a figure that has not changed significantly in the last 10 years (2). In the Metropolitan Region, this percentage is as low as 56 percent. The distribution of cervical cancer, like that of other cancers, follows a pattern of inequality in that women of lowest socioeconomic status are those most affected (4).
Closing the Gap: Mobile Health (mHealth)
Mobile technologies have had an exponential increase in the last few years.
In 2014, the penetration of mobile phones will reach 90% in developing countries compared to 121% in developed countries. (5, 6).
This same trend can also be seen in access to mobile broadband technologies, which will have an estimated penetration of 32% by the end of 2014.
The number of internet users worldwide follows this same trend as well. By the end of 2014, there will be more than 3 billion users, with more than 2/3 of these in developing countries.
According to a survey by the Deputy Minister of Telecommunications in Chile (7), access to a mobile or fixed internet connection was 39.4% by the end of 2009. This increased to over 60% by 2012.
This coverage is distributed unequally according to socioeconomic class, with more than 81% of penetration in richer homes and less than 30% in poorer strata (21.4% and 9.8% respectively).
On the other hand, mobile telephones reached more than 90% of homes in 2009, of both rural and urban survey respondents interviewed by the Deputy Minister of Telecommunications. While inequalities remain in this area as well, they are much less profound than with other technologies: the mobile telephone can be found widely distributed in all socioeconomic levels, and varies between 97% in richer strata and 82.8% in poor SES (7).
By the end of 2013, the percentage of mobile telephone subscribers per 100 inhabitants was almost 40% for mobile phones with a contract and more than 94% for phones with prepaid plans.
The Solution: Using mobile health technology (mHealth)
Mobile health (mHealth) has been defined by the WHO (World Health Organization) as "medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices" (9).
Given the explosion of the use of these technologies in the world and particularly in developing countries, the potential for mobile health in health issues is huge.
The overall interest in mobile health is widespread (11). According to the WHO´s report on mHealth in 2011 (9), mobile health strategies exist in at least 75% of the countries that belong to the WHO in each region. 100% of the countries in the Southeast Asian region reported some mobile health initiative at different stages of development, and the Americas region reported that more than 90% of its countries had some form of mobile health initiative (Chile was not included in these statistics).
According to the World Bank, high-income countries reported more initiatives than low-income countries.
Some examples of mobile health initiatives in Latin America are the following: Mexico reported a mobile health program called MedicalHome in which a million mobile telephone subscribers have access to health professional support by telephone for $5 per month, which is charged directly to the cell phone account. Columbia reported a program for treatment adherence reminders using voice messages and Peru reported a RCT (Randomized Controlled Trial) that was done to assess treatment adherence using text messaging in patients with HIV/AIDS (9).
One of the most relevant problems regarding the use of these technologies is that there isn´t sufficient evidence of its effectiveness in prevention (12). Because of this, it is imperative to invest in rigorous and systematic evaluations of these interventions so that they can be applied at the population level.
While some evidence exists that shows that mobile health is an effective strategy for treatment adherence for prenatal care and those with HIV and TB (13,14,15), the potential use of mobile health technologies in cancer prevention has not been fully explored. Given the widespread existence of mobile telephones in Chile, investigators intend with this study to deliver a simple, replicable, and scalable intervention to improve the rates of morbidity and mortality due to cervical cancer that afflict Chile´s population.
2. Research Questions
1\. Do mobile technologies have a preventive benefit in women with greater risk of getting cervical cancer as compared to usual care? 2. In women with greater risk of getting cervical cancer, what are the barriers and facilitators to implementing this kind of technological intervention?
3\. Research Hypotheses
1. Null Hypothesis: The proposed intervention does not increase Pap adherence rates in the studied health centers.
Alternative Hypothesis: The proposed intervention increases Pap adherence rates in the studied health centers.
2. Null Hypothesis: An intervention using mobile technology cannot be feasibly implemented in this population.
Alternative Hypothesis: It is possible to implement an intervention using mobile technology in this population.
4\. Study Objectives General Objective: Evaluate the implementation and effectiveness of a mobile health intervention to increase cervical cancer screening adherence.
Specific Objectives:
1. Evaluate the effect that a text message intervention has on Pap adherence rates.
2. Evaluate the implementation and usability of a cellphone mobile health intervention in three health centers of the Southeast Metropolitan Health District of Santiago.
5\. Methodology Design:
1. Quantitative phase:
1. Target Population:
Target population will be women between 25 and 64 years of age who use cell phones and do not have an up-to-date Pap test (no Pap in the last three years). They must also be registered at one of the following health clinics: CESFAM (Centro de Salud Familiar) El Roble or CESFAM Juan Pablo II.
A randomized controlled trial will be carried out to evaluate the effectiveness of text message intervention in improving Pap adherence. Socio-demographic variables associated with its effectiveness will also be analyzed.
Selection methodology: Using the database of medical records in each clinic, women will be identified that meet the inclusion criteria. They will be invited to participate in the study, and if they choose to accept, informed consent will be obtained.
Before randomization, the participants will be asked to complete a questionnaire with simple demographic questions and questions regarding their beliefs and attitudes about cellphone use and cervical cancer.
2. Randomization:
Participants will be randomized into either the intervention group or the control group using a randomization software that keeps the randomization sequence hidden. The control group will receive their usual care in each health center, which consists of different interventions depending on the health center they attend. Examples of usual care include periodic midwife visits, education by health personnel and cervical cancer health campaigns.
c) Intervention: Women randomized to the intervention group will receive text and voice messages (designed with input from previous qualitative phase) sent to their cellphones that remind them to get a Pap smear, send them information about cervical cancer, and inform them of health clinic location and hours where they could get a Pap smear.
2. Qualitative phase:
The implementation of a mHealth intervention could fail for many reasons. Some of the previously described barriers for this and other types of mobile interventions are: restrictions in the number of characters in the text message, illiteracy, poor signal coverage and quality, and confidentiality and pertinence in families where cellphones are shared.
However, there may be many other factors that hinder or facilitate its effectiveness: lack of funds to keep credit on a cellphone throughout the entire month, losing the phone, little use of text messaging in the elderly, among others.
Investigators will carry out focus groups with women who receive care at the participating centers in order to define barriers and facilitators to a text message intervention that will promote Pap adherence.
Focus Groups Participants:
Women between 25 and 64 years old that meet the inclusion criteria for the study.
Midwives at the health care centers.
Investigators will carry out nine (9) focus groups in total. Women will let us know about barriers and facilitators to the use of this technology and midwives will help investigators to characterize the usual care that women receive and better inform text message content as well as barriers to their use.
Every community member that attends a focus group will receive an incentive of 5,000 Chilean pesos (8 USD) for their time and information. Each health professional that attends a focus group will receive 10,000 Chilean pesos (16 USD).
Data Encoding The focus groups will be led by individuals expert in qualitative methods and assisted by the Principal Investigator and a student assistant who will serve as a note-taker. The focus groups will be recorded for analysis.
The audio of the focus groups will be transcribed and coded using the software Atlas.ti version 6.2
Analysis Information will be analyzed using a qualitative content analysis process\* by two or more investigators who will extract relevant themes regarding usage patterns, barriers, and facilitators to this type of intervention. Investigators will use the conceptual framework called PRECEDE-PROCEED in order to carry out the analysis\*. Investigators will use it to identify predisposing factors that reinforce and enable the use of mobile technologies to improve Pap adherence.
The collected information will contribute to the design of the intervention, and from there the quantitative phase of the study will begin.
d) Sample size Previous studies have shown that without an intervention, around 30% of women who are not up-to-date with their Pap test will get a Pap within the following 6-12 months. Looking at literature regarding similar interventions for other pathologies, investigators anticipate seeing an absolute increase of 15% in adherence rate. With this difference in proportions, and alpha errors of 5% and beta errors of 20%, the estimated sample size is 176 per arm. Considering a loss of 10%, investigators will recruit an estimated 200 patients per arm.
e) Statistical Analysis Investigators will use descriptive statistics to characterize demographic variables of the included patients in the same manner as charactering the indicators of implementation.
For the primary outcome (proportion of women with an up-to-date Pap), investigators will use a chi-squared test to test differences in proportions.
For the multivariate analysis, investigators will use logistic regression and Poisson regression.
For the categorical variables, investigators will use a chi-squared test.
Conditions
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Cervical Cancer
Study Design
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Allocation Method
RANDOMIZED
Intervention Model
PARALLEL
Primary Study Purpose
PREVENTION
Blinding Strategy
TRIPLE
Caregivers
Investigators
Outcome Assessors
Study Groups
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mHealth
Women in the mHealth group will receive text and voice messages, in addition to their habitual care from the health clinic they attend. The messages will remind them to schedule a PAP smear, and will be sent for 1 year following enrollment in the study.
Group Type
EXPERIMENTAL
mHealth
Intervention Type
OTHER
Text and voice messages sent to study participants reminding them to schedule a PAP smear.
No mHealth
Women in the No mHealth group will not receive any text messages, and will only receive their habitual care from the health clinic they attend.
Group Type
NO_INTERVENTION
No interventions assigned to this group
Interventions
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mHealth
Text and voice messages sent to study participants reminding them to schedule a PAP smear.
Intervention Type
OTHER
Eligibility Criteria
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Inclusion Criteria
* Must have and use a mobile phone
* Enrolled at one of the following clinics: CESFAM El Roble or CESFAM Juan Pablo II.
* Must not have had a Pap test within 3 years or more from recruitment
* Enrolled at one of the following clinics: CESFAM El Roble or CESFAM Juan Pablo II.
* Must not have had a Pap test within 3 years or more from recruitment
Exclusion Criteria
* Women who have ever had the diagnosis of cervical cancer.
* Women with a mental or physical disability that inhibits them from understanding the implications of the study or being able to reach the health clinic for an exam.
* Women that are considering relocating within the next year.
* Women with a mental or physical disability that inhibits them from understanding the implications of the study or being able to reach the health clinic for an exam.
* Women that are considering relocating within the next year.
Minimum Eligible Age
25 Years
Maximum Eligible Age
64 Years
Eligible Sex
FEMALE
Accepts Healthy Volunteers
No
Sponsors
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Centro de Salud Familiar El Roble
UNKNOWN
Sponsor Role
collaborator
Pontificia Universidad Catolica de Chile
OTHER
Sponsor Role
lead
Responsible Party
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Javiera Martínez
Javiera Martínez MD, MPH
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
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Carmen Huerta
Role: STUDY_CHAIR
Comisión Nacional de Investigación Científica y Tecnológica
Locations
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CESFAM El Roble
Santiago, RM, Chile
Site Status
RECRUITING
CESFAM Juan Pablo II
Santiago, RM, Chile
Site Status
RECRUITING
Countries
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Chile
Central Contacts
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Facility Contacts
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References
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Human papillomavirus (HPV) and cervical cancer. (Updated 2014, November). Retrieved June 4, 2014, from http://www.who.int/mediacentre/factsheets/fs380
Reference Type
BACKGROUND
Defunciones y mortalidad por causas. (n.d.). Retrieved June 4, 2014, from http://www.deis.cl/?p=2541
Reference Type
BACKGROUND
Fica A. [Cancer of cervix in Chile. Too much vaccine amid a neglected Papanicolau]. Rev Chilena Infectol. 2014 Apr;31(2):196-203. doi: 10.4067/S0716-10182014000200010. Spanish.
Reference Type
BACKGROUND
Martínez-Bejarano, R & Martínez-Salgado, C. La mortalidad por cáncer cérvico uterino y de mamá en Colombia y Mexico como expresión de las desigualdades socio-económicas y de genero. III Congreso de la Asociación Latinoamericana de Población, ALAP, Córdoba -Argentina, from 24-26 of September 2008. Retrieved June 4, 2014, from http://www.alapop.org/2009/images/DOCSFINAIS_PDF/ALAP _2008_FINAL_155.pdf
Reference Type
BACKGROUND
Aylward, D., Leão, B., Curioso, W., & Cruz, F. (2010). Can You Heal Me Now? Potential (and Pitfalls) of mHealth. Americas Quarterly, 4(3), 88-95. Retrieved June 4, 2014, from http://www.americasquarterly.org/node/1699
Reference Type
BACKGROUND
The World in 2014. ICT Facts and Figures. ITU World Telecommunications. Retrieved June 4, 2014, from http://www.itu.int/en/ITU-D/Statistics/Pages/facts/default.aspx
Reference Type
BACKGROUND
Encuesta Nacional de Consumidores de Servicios de Telecomunicaciones. Subsecretaria de Telecomunicaciones 2014. http://www.subtel.gob.cl/component/search/?searchword=Encuesta%20Nacional&searchphrase=all&Itemid=101
Reference Type
BACKGROUND
Abonados Móviles [Mobile Subscribers]. (2015, January 9). Retrieved June 4, 2014, from http://www.subtel.gob.cl/informacion-estadistica-actualizada-e-historica4/informacion-estadistica4
Reference Type
BACKGROUND
MHealth: New Horizons for Health through Mobile Technologies. (2011). Global Observatory for EHealth Series, 3. Retrieved June 4, 2014, from http://www.who.int/goe/publications/goe_mhealth_web.pdf
Reference Type
BACKGROUND
Green paper on mobile health (mHealth). (2010). European Commission. Retrieved June 4, 2014, from http://ec.europa.eu/digital-agenda/en/news/green-paper-mobile-health-mhealth
Reference Type
BACKGROUND
Curioso WH, Mechael PN. Enhancing 'M-health' with south-to-south collaborations. Health Aff (Millwood). 2010 Feb;29(2):264-7. doi: 10.1377/hlthaff.2009.1057.
Reference Type
BACKGROUND
Vodopivec-Jamsek V, de Jongh T, Gurol-Urganci I, Atun R, Car J. Mobile phone messaging for preventive health care. Cochrane Database Syst Rev. 2012 Dec 12;12(12):CD007457. doi: 10.1002/14651858.CD007457.pub2.
Reference Type
BACKGROUND
Curioso WH, Kepka D, Cabello R, Segura P, Kurth AE. Understanding the facilitators and barriers of antiretroviral adherence in Peru: a qualitative study. BMC Public Health. 2010 Jan 13;10:13. doi: 10.1186/1471-2458-10-13.
Reference Type
BACKGROUND
Curioso, W., Gozzer, E., Valderrama, M., Rodriguez-Abad, J., Villena, J., Villena, A. Understanding the potential role of cell phones and the Internet to support care for diabetic patients and caregivers in Peru. AMIA 2009 Symposium Proceedings Page, 805. Retrieved June 4, 2014, from http://faculty.washington.edu/wcurioso/Curioso_Understanding_AMIA_2009.pdf
Reference Type
BACKGROUND
Curioso, W., Gozzer, E., Valderrama, M., Rodriguez-Abad, J., Villena, J., Villena, A. (2009). Uso y percepciones hacia las tecnologías de información y comunicación en pacientes con diabetes en un hospital público del Perú. [Use and perceptions towards information and communication technologies in patients with diabetes in a Peruvian public hospital]. Rev Per Med Exp Sal Pub, 26(2), 161-67.
Reference Type
BACKGROUND
Palmer MJ, Henschke N, Villanueva G, Maayan N, Bergman H, Glenton C, Lewin S, Fonhus MS, Tamrat T, Mehl GL, Free C. Targeted client communication via mobile devices for improving sexual and reproductive health. Cochrane Database Syst Rev. 2020 Jul 14;8(8):CD013680. doi: 10.1002/14651858.CD013680.
Reference Type
DERIVED
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.
Reference Type
DERIVED
Other Identifiers
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FONIS ProyectoSA14ID0072
Identifier Type: OTHER_GRANT
Identifier Source: secondary_id
CEC Med UC 14-213
Identifier Type: -
Identifier Source: org_study_id
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