Salud digital y móvil

To test the feasibility of a smartphone app, BebeApp, that provides evidence-based early childhood development (ECD) guidance in rural Guatemala and pilot procedures for an adequately powered randomised controlled trial. We conducted an individually randomised pilot feasibility trial to compare BebeApp to printed ECD guidance. This trial was conducted in Tecpán, Chimaltenango, a semi-rural community that is 95% Kaqchikel Indigenous Maya. First-time primary caregiver-infant (0-28 days) dyads. BebeApp provides age-dependent, evidence-based caregiver guidance for breastfeeding and complementary feeding, sleep and developmental support. A mixed-methods evaluation of BebeApp's implementation and acceptability using the Reach, Effectiveness, Adoption, Implementation, Maintenance framework. App usability, usefulness and satisfaction were assessed via questionnaires, semi-structured interviews and app interaction data. 41 infant-caregiver dyads were enrolled with 40 completing the study. Engagement was high with caregivers opening BebeApp a median (IQR) 11 (6-21) times per month. Usability was found to be acceptable but no difference was found between pre-measurements and post-measurements. In interviews, caregivers expressed some initial difficulty using BebeApp but were able to gain confidence with a training session. App usefulness and satisfaction responses were positive. Caregivers often noted that BebeApp was their only source of ECD information outside of their family. We found that caregivers in rural Guatemala responded positively to a smartphone ECD app and engaged with it throughout the trial. Given the urgent need for ECD programmes in low- and middle-income settings, smartphone apps may be a method to deliver services directly to caregivers.

BACKGROUND: In Guatemala, childhood vaccination rates, particularly in Indigenous communities, are low due to inaccessible information and mistrust. Using a human-centered design (HCD) process with community partners, we developed CLAVE (Culturally and Linguistically Appropriate Vaccine Education), a video series on routine and human papillomavirus (HPV) immunization in Kaqchikel, K’iche’, and Spanish. Content was distributed via social media and through community health workers (CHWs). This study describes the instructional design process and assesses implementation feasibility through community-level measures of reach and engagement and acceptability among CHWs across 12 communities in the Central Highlands of Guatemala. METHOD: To develop content, we applied an HCD framework and collected iterative feedback from communities through 16 CHW interviews and nine focus group discussions with 42 community members. We implemented CLAVE in 12 communities, with four communities randomly assigned in parallel to each arm: (1) a six-week, geographically targeted social media campaign promoting CLAVE videos; (2) the same social media campaign plus CLAVE videos and complementary digital infographic job aids provided to CHWs; and (3) a control arm with no exposure to CLAVE videos or the CHW intervention. Platform analytics were used to assess the reach and engagement potential on social media, and CHW survey data were used to assess acceptability of content among CHWs. RESULTS: The CLAVE campaign reached 486,594 unique social media platform users, with over 4.1 million impressions and a high overall engagement rate reflecting multiple user interactions with content. Spanish and Kaqchikel versions reached the largest audiences, while K’iche’ content generated proportionally higher engagement and viewing rates, suggesting stronger interaction among smaller language audiences. Vaccine acceptance was high across all CHWs. Amid a high baseline, the intervention was not associated with significant differences in CHWs’ perceptions of the efficacy or importance of routine childhood vaccination or HPV vaccination, nor with knowledge measures. However, CHWs receiving CLAVE content directly were more likely to strongly agree that the HPV vaccine is safe (p < 0.05). CHWs reported high perceived usefulness and frequent utilization of CLAVE content. CONCLUSIONS: This pilot suggests that geographically targeted paid social media distribution of community-engaged, multilingual vaccine education content can achieve broad exposure, and that pairing videos with job aids can support CHW vaccine education efforts. REGISTRY: ClinicalTrials.gov, TRN: NCT06186206, Registration date: 05 January 2024.

To assess human papillomavirus (HPV) vaccine awareness and uptake among caregivers in rural Indigenous communities in Guatemala and to identify sociodemographic predictors of vaccine unawareness and non-uptake. This cross-sectional survey was conducted across 12 rural Indigenous communities in Guatemala's Central Highlands. Using a community-engaged research approach, trained multilingual health workers administered surveys in Spanish, Kaqchikel or K'iche'. Eligible participants were adults who served as primary caregivers to children. The survey assessed HPV vaccine awareness, vaccine attitudes and uptake among those with daughters aged 8 or older. Logistic regression was used to examine predictors of vaccine unawareness and bivariate analysis explored differences in vaccine uptake. Among 602 participants (92.5% identified as Indigenous), 95% expressed willingness to vaccinate a child against cervical cancer, yet only 56% had heard of the HPV vaccine. Of the 175 participants with eligible daughters, only 33.7% reported vaccination. Indigenous identity, older age and illiteracy were significantly associated with HPV vaccine unawareness. Speaking an Indigenous language at home was associated with greater awareness. Departmental differences were significant: participants from Sololá were more likely to be unaware of the vaccine, while those from Sacatepéquez had higher awareness and uptake. Community partners noted that access to information, geographic connectivity and social desirability may influence both awareness and response accuracy. Despite strong willingness to vaccinate, significant knowledge gaps persist among Indigenous caregivers. Tailored, community-informed education strategies-delivered through trusted channels and adapted linguistically and culturally-are urgently needed to increase awareness and uptake of the HPV vaccine in underserved Guatemalan communities.

This study presents a technical framework for real-time fetal Doppler data quality assessment using deep learning and edge-AI, designed to improve data collection and support future clinical studies in low-resource settings. Integrated into a low-cost, edge-computing system co-designed with Indigenous midwives in rural Guatemala, our solution utilizes an Android phone for data acquisition and decision support. Retrospective analysis demonstrates the potential to detect fetal growth restriction, hypertension, and other pregnancy-related conditions using Doppler-based fetal cardiac signals. To ensure accurate assessments and provide immediate feedback, a real-time signal quality metric is essential. We analyzed two fetal Doppler datasets: 191 recordings, captured in rural Guatemala, for training and validation, and five captured in a German hospital (in Leipzig) for testing. The data were segmented into 3.75 s intervals, and categorized into five quality levels: good, poor, radiofrequency interference, talking, and silent. A deep neural network was trained on these segments, achieving a micro F 1 score of 97.4% and a macro F 1 score of 94.2%, with 99.2% accuracy for 'Good' quality in the Guatemala dataset, based on five-fold cross-validation. For the Leipzig dataset, the F 1 score was 93.3% on 'Good' quality segments, demonstrating the model's ability to generalize across different datasets. By implementing the algorithm within an Android decision-support application in an mHealth framework, we have enabled real-time feedback during signal acquisition, improving data quality at the source. This scalable, edge mHealth solution offers significant potential to enhance maternal and fetal health monitoring in the Global South, contributing to global health efforts through the integration of mobile technology, AI, and healthcare.

Neonatal mortality remains a significant equity issue in rural Indigenous communities of Guatemala, where structural barriers and systemic discrimination impede access to quality newborn care. This field report describes a novel community-based initiative implemented by Maya Health Alliance, an Indigenous-lead NGO, to address high neonatal mortality in Maya Kaqchikel communities through a quality improvement (QI) framework. The intervention centers on home-based neonatal care delivered by trained Neonatal Technicians (NTs), supported by a co-designed smartphone application enabling early identification of neonatal danger signs, clinical decision-making, and data collection. The initiative also leverages a culturally responsive referral and patient navigation system to overcome humanistic barriers to care. Designed using QI methodology, the project applies iterative cycles to track key performance indicators such as perinatal and neonatal mortality rates, referral success rates, and the proportion of newborns receiving timely home evaluations. Since launching in 2024, the program has reached 85% of reported newborns, increased referral rates, and engaged local midwives and health staff through ongoing training and co-design efforts. However, challenges have emerged, including high prevalence of low birth weight, limitations in local hospital capacity, and discriminatory care at facilities that discourage families from accepting referrals. The intervention centers Indigenous practices by positioning TMMs at the frontline and adapting protocols to the communities' lived realities. This initiative demonstrates the potential for culturally embedded, digitally supported, and equity-focused QI interventions to improve neonatal outcomes in resource-limited Indigenous settings. Future efforts will focus on expanding staff capacity, deepening community trust, and strengthening health system partnerships. Main findings: A community-based neonatal health program that integrates traditional Maya practices, home visits, and digital decision support in rural Guatemala has improved detection of at-risk newborns and referral rates.Added knowledge: This study highlights the feasibility of combining culturally tailored care, mHealth tools, and accompaniment in Indigenous settings, while documenting significant barriers rooted in structural inequities and cultural distrust.Global health impact for policy and action: Scaling such integrated models may strengthen neonatal care in marginalized communities, but it requires systemic reforms, investment in local health systems, and respect for cultural autonomy.

Cancer is a leading cause of death globally. Accurate cancer burden information is crucial for policy planning, but many countries do not have up-to-date cancer surveillance data. To inform global cancer-control efforts, we used the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework to generate and analyse estimates of cancer burden for 47 cancer types or groupings by age, sex, and 204 countries and territories from 1990 to 2023, cancer burden attributable to selected risk factors from 1990 to 2023, and forecasted cancer burden up to 2050. Cancer estimation in GBD 2023 used data from population-based cancer registration systems, vital registration systems, and verbal autopsies. Cancer mortality was estimated using ensemble models, with incidence informed by mortality estimates and mortality-to-incidence ratios (MIRs). Prevalence estimates were generated from modelled survival estimates, then multiplied by disability weights to estimate years lived with disability (YLDs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the GBD standard life expectancy at the age of death. Disability-adjusted life-years (DALYs) were calculated as the sum of YLLs and YLDs. We used the GBD 2023 comparative risk assessment framework to estimate cancer burden attributable to 44 behavioural, environmental and occupational, and metabolic risk factors. To forecast cancer burden from 2024 to 2050, we used the GBD 2023 forecasting framework, which included forecasts of relevant risk factor exposures and used Socio-demographic Index as a covariate for forecasting the proportion of each cancer not affected by these risk factors. Progress towards the UN Sustainable Development Goal (SDG) target 3.4 aim to reduce non-communicable disease mortality by a third between 2015 and 2030 was estimated for cancer. In 2023, excluding non-melanoma skin cancers, there were 18·5 million (95% uncertainty interval 16·4 to 20·7) incident cases of cancer and 10·4 million (9·65 to 10·9) deaths, contributing to 271 million (255 to 285) DALYs globally. Of these, 57·9% (56·1 to 59·8) of incident cases and 65·8% (64·3 to 67·6) of cancer deaths occurred in low-income to upper-middle-income countries based on World Bank income group classifications. Cancer was the second leading cause of deaths globally in 2023 after cardiovascular diseases. There were 4·33 million (3·85 to 4·78) risk-attributable cancer deaths globally in 2023, comprising 41·7% (37·8 to 45·4) of all cancer deaths. Risk-attributable cancer deaths increased by 72·3% (57·1 to 86·8) from 1990 to 2023, whereas overall global cancer deaths increased by 74·3% (62·2 to 86·2) over the same period. The reference forecasts (the most likely future) estimate that in 2050 there will be 30·5 million (22·9 to 38·9) cases and 18·6 million (15·6 to 21·5) deaths from cancer globally, 60·7% (41·9 to 80·6) and 74·5% (50·1 to 104·2) increases from 2024, respectively. These forecasted increases in deaths are greater in low-income and middle-income countries (90·6% [61·0 to 127·0]) compared with high-income countries (42·8% [28·3 to 58·6]). Most of these increases are likely due to demographic changes, as age-standardised death rates are forecast to change by -5·6% (-12·8 to 4·6) between 2024 and 2050 globally. Between 2015 and 2030, the probability of dying due to cancer between the ages of 30 years and 70 years was forecasted to have a relative decrease of 6·5% (3·2 to 10·3). Cancer is a major contributor to global disease burden, with increasing numbers of cases and deaths forecasted up to 2050 and a disproportionate growth in burden in countries with scarce resources. The decline in age-standardised mortality rates from cancer is encouraging but insufficient to meet the SDG target set for 2030. Effectively and sustainably addressing cancer burden globally will require comprehensive national and international efforts that consider health systems and context in the development and implementation of cancer-control strategies across the continuum of prevention, diagnosis, and treatment. Gates Foundation, St Jude Children's Research Hospital, and St Baldrick's Foundation.

There has been an alarming increase in the incidence of a chronic kidney disease (CKD) of unknown etiology primarily affecting young individuals engaged in agricultural activities in Mesoamerica and South Asia. Despite extensive research over the past 2 decades, causes remain unclear. The disease is characterized by progressive loss of kidney function with the absence of heavy proteinuria and hematuria. The International Prospective Study of CKD of Unknown Etiology in Agricultural Communities (CURE study) aims to do the following: (i) identify factors associated with kidney function decline among individuals with or at risk for CKD of uncertain etiology (CKDu); (ii) better characterize the clinical phenotypes of individuals with CKDu and differentiate them from other forms of CKD; (iii) employ advanced laboratory and data analysis methods to conduct discovery science related to risk factors, biomarkers, and causal mechanisms; and (iv) establish a biorepository for future research. The CURE study is a prospective cohort study of up to 3600 participants from 7 sites in Central America and India aged 18 to 45 years with estimated glomerular filtration rate (eGFR) ≥ 20 ml/min per 1.73 m2, no evidence of diabetes, and no other known causes of CKD. Biological samples and questionnaire data are collected from participants during 4 visits at 8-month intervals. Blood, urine, and hair will be analyzed for kidney function biomarkers, trace elements, pesticides and other contaminants, untargeted metabolomics, and genetic assays. Environmental samples, collected from a subset of study participants, will be analyzed for trace elements, agrochemicals, and burning exposures. This study will provide novel information about CKDu etiology and clinical phenotypes across distinct geographies.

Aflatoxin B1 (AFB1) contamination of food crops pose severe public health risks, particularly in decentralized agricultural systems common in low-resource settings. Effective monitoring tools are critical for mitigating exposure, but their adoption is limited by barriers such as cost, infrastructure, and technical expertise. The objectives of this study were: (1) to evaluate common AFB1 detection methods, including enzyme-linked immunosorbent assays (ELISA) and lateral-flow assays (LFA), validated via high-performance liquid chromatography (HPLC), focusing on their suitability for possible applications in decentralized, low-resource settings; and (2) to conduct a barriers-to-use assessment for commonly available AFB1 detection methods and their applicability in low-resource settings. Among four ELISA kits, the AgraQuant Aflatoxin B1 2/50 ELISA Kit demonstrated the highest accuracy and precision, reliably quantifying AFB1 in maize and tortillas across 5-150 ppb with minimal cross-reactivity. For LFA, a smartphone-based algorithm achieved a high presence/absence accuracy rate of 84% but struggled with concentration prediction. The barriers-to-use analysis highlighted the practicality of low-cost tools like moisture readers for field screening but underscored their qualitative limitations. Advanced methods like HPLC and LC-MS offer greater precision but remain impractical due to their high costs and infrastructure requirements, suggesting a potential role for adapted ELISA or LFA methods as confirmatory approaches. These findings support the development of multi-tiered frameworks integrating affordable field tools with regional or centralized confirmatory testing. Addressing systemic barriers through capacity building, partnerships, and improved logistics will enhance AFB1 monitoring in decentralized systems, protecting public health in vulnerable communities.

This paper introduces a novel approach to address the challenges associated with transferring blood pressure (BP) data obtained from oscillometric devices used in self-measured BP monitoring systems to integrate this data into medical health records or a proxy database accessible by clinicians, particularly in low literacy populations. To this end, we developed an automated image transcription technique to effectively transcribe readings from BP devices, ultimately enhancing the accessibility and usability of BP data for monitoring and managing BP during pregnancy and the postpartum period, particularly in low-resource settings and low-literate populations. In the designed study, the photos of the BP devices were captured as part of perinatal mobile health (mHealth) monitoring programs, conducted in four studies across two countries. The Guatemala Set 1 and Guatemala Set 2 datasets include the data captured by a cohort of 49 lay midwives from 1697 and 584 pregnant women carrying singletons in the second and third trimesters in rural Guatemala during routine screening. Additionally, we designed an mHealth system in Georgia for postpartum women to monitor and report their BP at home with 23 and 49 African American participants contributing to the Georgia I3 and Georgia IMPROVE projects, respectively. We developed a deep learning-based model which operates in two steps: LCD localization using the You Only Look Once (YOLO) object detection model and digit recognition using a convolutional neural network-based model capable of recognizing multiple digits. We applied color correction and thresholding techniques to minimize the impact of reflection and artifacts. Three experiments were conducted based on the devices used for training the digit recognition model. Overall, our results demonstrate that the device-specific model with transfer learning and the device independent model outperformed the device-specific model without transfer learning. The mean absolute error (MAE) of image transcription on held-out test datasets using the device-independent digit recognition were 1.2 and 0.8 mmHg for systolic and diastolic BP in the Georgia IMPROVE and 0.9 and 0.5 mmHg in Guatemala Set 2 datasets. The MAE, far below the FDA recommendation of 5 mmHg, makes the proposed automatic image transcription model suitable for general use when used with appropriate low-error BP devices.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

More than 80% of cervical cancer cases and deaths occur in low- and middle-income countries. Here, we analyze a large geographically extensive cross-sectional data set from the Western rural highlands of Guatemala. Our objective is to better characterize weak points in care along the cervical cancer care continuum and investigate sociodemographic and clinical correlates of loss to follow-up. We conducted a retrospective review of electronic health records data from July 21, 2015, through December 10, 2020 for a cytology-based screening and cervical cancer treatment program. We used a care cascade analysis to characterize the progression of individuals through screening, confirmatory testing, and treatment. We examined demographic and clinical factors correlated with screening and loss to follow-up using multivariate logistic regression. A total of 8,872 individuals were included in the analysis. Five thousand nine hundred thirteen cervical cancer screenings were conducted. 4.1% of all screening tests were abnormal, including 0.61% cervical intraepithelial neoplasia or overt cervical cancer. Care cascade analysis showed that 67% of eligible women accepted screening. Of those requiring confirmatory testing or treatment, 73% completed recommended follow-up. In adjusted multivariable analysis, prior history of sexual transmitted infection, prior experience with cervical cancer screening, older age, and current contraceptive use were associated with accepting screening. Age and contraceptive use were also associated with retention in care after a positive first screen. In a large rural Guatemalan retrospective cohort, a care continuum analysis showed that both declining the opportunity to receive cervical cancer screening as well as declining confirmatory testing after a first positive screen were both important weak points along the care continuum. These data support the need for comprehensive and culturally appropriate initiatives to improve screening uptake and retention in care.

The majority of indigenous Guatemalan women give birth at home with traditional birth attendants (TBAs), and maternal mortality rates are high (Ministerio de Salud, 2017). Our objective was to better understand decision-making around whether to remain in the home or to seek facility-level care for obstetric complications. This study was a qualitative analysis using semi-structured interviews in a Maya population in the Western Highlands of Guatemala who received prenatal care between April 2017 and December 2018. We used qualitative interviews with women who were identified as medically high-risk and needing facility-level care, offered assistance with acquiring such care, and yet declined this option. Women interviewed were connected to a primary care organization called Maya Health Alliance, through care with TBAs involved in a program utilizing a smartphone-based decision support application to identify maternal and neonatal complications of pregnancy. Interviews were analyzed using Dedoose (www.dedoose.com). Deductive and inductive analysis was performed. Barriers to care included a disagreement between the respondent and TBA about indications for facility care, fear of hospital care, concerns about the quality of hospital care, logistical obstacles, and lack of control; and they were more often described by respondents who had previous healthcare experiences. Therapeutic misalignment occurred more with conditions perceived to be less severe. Participants described a balancing of fears and apprehensions against concerns of low quality and disrespectful maternity care, and in the setting of emergent conditions, disregarded barriers that were often described as inhibiting non-urgent obstetric care. The decision to engage in medical care in this population of Maya women involves a weighing of the perception of seriousness of the medical complication against fears of facility level care and concerns of a poor quality of care.

Despite the life-saving work they perform, community health workers (CHWs) have long been subject to global debate about their remuneration. There is now, however, an emerging consensus that CHWs should be paid. As the discussion evolves from whether to financially remunerate CHWs to how to do so, there is an urgent need to better understand the types of CHW payment models and their implications. This study examines the legal framework on CHW compensation in five countries: Brazil, Ghana, Nigeria, Rwanda, and South Africa. In order to map the characteristics of each approach, a review of the regulatory framework governing CHW compensation in each country was undertaken. Law firms in each of the five countries were engaged to support the identification and interpretation of relevant legal documents. To guide the search and aid in the creation of uniform country profiles, a standardized set of questions was developed, covering: (i) legal requirements for CHW compensation, (ii) CHW compensation mechanisms, and (iii) CHW legal protections and benefits. The five countries profiled represent possible archetypes for CHW compensation: Brazil (public), Ghana (volunteer-based), Nigeria (private), Rwanda (cooperatives with performance based incentives) and South Africa (hybrid public/private). Advantages and disadvantages of each model with respect to (i) CHWs, in terms of financial protection, and (ii) the health system, in terms of ease of implementation, are outlined. While a strong legal framework does not necessarily translate into high-quality implementation of compensation practices, it is the first necessary step. Certain approaches to CHW compensation - particularly public-sector or models with public sector wage floors - best institutionalize recommended CHW protections. Political will and long-term financing often remain challenges; removing ecosystem barriers - such as multilateral and bilateral restrictions on the payment of salaries - can help governments institutionalize CHW payment.

We propose that the collection of infant experiential and environmental data using smartphone surveys has the potential to fill a gap in foundational and clinical knowledge. To achieve this, these data need to be collected in a systematic way that is translatable globally. We can then begin to understand differences in child development and physical therapy from a variety of cultures and traditions. An infant's development is shaped by experiences in everyday life, and everyday experiences vary around the world. Hence, it is important to quantify these experiences to better understand variability in developmental trajectories. Recent increase in smartphone access has made the capability of collecting infant experiential data more feasible around the world. We provide examples and suggestions for ways in which experiential and environmental data can be collected for future practice.

There is limited evidence regarding the utility of fetal monitoring during pregnancy, particularly during labor and delivery. Developed countries rely on consensus 'best practices' of obstetrics and gynecology professional societies to guide their protocols and policies. Protocols are often driven by the desire to be as safe as possible and avoid litigation, regardless of the cost of downstream treatment. In high-resource settings, there may be a justification for this approach. In low-resource settings, in particular, interventions can be costly and lead to adverse outcomes in subsequent pregnancies. Therefore, it is essential to consider the evidence and cost of different fetal monitoring approaches, particularly in the context of treatment and care in low-to-middle income countries. This article reviews the standard methods used for fetal monitoring, with particular emphasis on fetal cardiac assessment, which is a reliable indicator of fetal well-being. An overview of fetal monitoring practices in low-to-middle income counties, including perinatal care access challenges, is also presented. Finally, an overview of how mobile technology may help reduce barriers to perinatal care access in low-resource settings is provided.

Cervical cancer screening is not well implemented in many low- and middle-income countries (LMICs). Mobile health (mHealth) refers to utilization of mobile technologies in health promotion and disease management. We aimed to qualitatively synthesize published articles reporting the impact of mHealth on cervical cancer screening-related health behaviors. Three reviewers independently reviewed articles with the following criteria: the exposure or intervention of interest was mHealth, including messages or educational information sent via mobile telephone or e-mail; the comparison was people not using mHealth technology to receive screening-related information, and studies comparing multiple different mHealth interventional strategies were also eligible; the primary outcome was cervical cancer screening uptake, and secondary outcomes included awareness, intention, and knowledge of screening; appropriate research designs included randomized controlled trials and quasi-experimental or observational research; and the study was conducted in an LMIC. Of the 8 selected studies, 5 treated mobile telephone or message reminders as the exposure or intervention, and 3 compared the effects of different messages on screening uptake. The outcomes were diverse, including screening uptake (n = 4); health beliefs regarding the Papanicolaou (Pap) test (n = 1); knowledge of, attitude toward, and adherence to colpocytologic examination (n = 1); interest in receiving messages about Pap test results or appointment (n = 1); and return for Pap test reports (n = 1). Overall, our systematic review suggests that mobile technologies, particularly telephone reminders or messages, lead to increased Pap test uptake; additional work is needed to unequivocally verify whether mhealth interventions can improve knowledge regarding cervical cancer. Our study will inform mHealth-based interventions for cervical cancer screening promotion in LMICs.

[Abstract not available]

Purpose Cervical cancer is an important cause of mortality in low- and middle-income countries. Although screening technologies continue to improve, systems of care remain fragmented. It is important to better understand factors that affect use of screening services and loss to follow-up along the care continuum. Methods We conducted a mixed-methods study of a cytology-based screening program in rural Guatemala. A retrospective electronic chart review was performed on data from all patients from 2013 to 2014. We analyzed progression through care and calculated loss-to-follow-up rates. We also analyzed the prior experiences of patients with cervical cancer screening on the basis of self-reported historical data available in the chart review. Structured interviews with a subset of individuals to explore social supports and barriers to screening and engagement in care were conducted at the time of screening. Results The analysis included 515 women (median age, 36 years). Cytologic screening showed concern for neoplastic changes in 0.83%; half resulted in biopsy-proven cervical intraepithelial neoplasia. An additional 9.9% showed severe inflammation. The rate of loss to follow-up was 11.3%. All losses to follow-up occurred for severe inflammation, not for cervical intraepithelial neoplasia. Historical data showed that 73% of the cohort had previously been screened and had high levels of loss to follow-up (57.4%). Qualitative interviews revealed factors that promoted loss to follow-up; these included cost, lack of social supports, transportation, distrust in public facilities, long turn-around times, and failure to return test results or offer follow-up treatments. Conclusions Taken together, these quantitative and qualitative results highlight the need for cervical cancer screening programs in Guatemala to improve uptake of screening services by eligible women and to improve follow-up after a first abnormal screen.

Guatemala's indigenous Maya population has one of the highest perinatal and maternal mortality rates in Latin America. In this population most births are delivered at home by traditional birth attendants (TBAs), who have limited support and linkages to public hospitals. The goal of this study was to characterize the detection of maternal and perinatal complications and rates of facility-level referral by TBAs, and to evaluate the impact of a mHealth decision support system on these rates. A pragmatic one-year feasibility trial of an mHealth decisions support system was conducted in rural Maya communities in collaboration with TBAs. TBAs were individually randomized in an unblinded fashion to either early-access or later-access to the mHealth system. TBAs in the early-access arm used the mHealth system throughout the study. TBAs in the later-access arm provided usual care until crossing over uni-directionally to the mHealth system at the study midpoint. The primary study outcome was the monthly rate of referral to facility-level care, adjusted for birth volume. Forty-four TBAs were randomized, 23 to the early-access arm and 21 to the later-access arm. Outcomes were analyzed for 799 pregnancies (early-access 425, later-access 374). Monthly referral rates to facility-level care were significantly higher among the early-access arm (median 33 referrals per 100 births, IQR 22-58) compared to the later-access arm (median 20 per 100, IQR 0-30) (p = 0.03). At the study midpoint, the later-access arm began using the mHealth platform and its referral rates increased (median 34 referrals per 100 births, IQR 5-50) with no significant difference from the early-access arm (p = 0.58). Rates of complications were similar in both arms, except for hypertensive disorders of pregnancy, which were significantly higher among TBAs in the early-access arm (RR 3.3, 95% CI 1.10-9.86). Referral rates were higher when TBAs had access to the mHealth platform. The introduction of mHealth supportive technologies for TBAs is feasible and can improve detection of complications and timely referral to facility-care within challenging healthcare delivery contexts. Clinicaltrials.gov NCT02348840 .

Technology provides the potential to empower frontline healthcare workers with low levels of training and literacy, particularly in low- and middle-income countries. An obvious platform for achieving this aim is the smartphone, a low cost, almost ubiquitous device with good supply chain infrastructure and a general cultural acceptance for its use. In particular, the smartphone offers the opportunity to provide augmented or procedural information through active audiovisual aids to illiterate or untrained users, as described in this article. In this article, the process of refinement and iterative design of a smartphone application prototype to support perinatal surveillance in rural Guatemala for indigenous Maya lay midwives with low levels of literacy and technology exposure is described. Following on from a pilot to investigate the feasibility of this system, a two-year project to develop a robust in-field system was initiated, culminating in a randomized controlled trial of the system, which is ongoing. The development required an agile approach, with the development team working both remotely and in country to identify and solve key technical and cultural issues in close collaboration with the midwife end-users. This article describes this process and intermediate results. The application prototype was refined in two phases, with expanding numbers of end-users. Some of the key weaknesses identified in the system during the development cycles were user error when inserting and assembling cables and interacting with the 1-D ultrasound-recording interface, as well as unexpectedly poor bandwidth for data uploads in the central healthcare facility. Safety nets for these issues were developed and the resultant system was well accepted and highly utilized by the end-users. To evaluate the effectiveness of the system after full field deployment, data quality, and corruption over time, as well as general usage of the system and the volume of application support for end-users required by the in-country team was analyzed. Through iterative review of data quality and consistent use of user feedback, the volume and percentage of high quality recordings was increased monthly. Final analysis of the impact of the system on obstetrical referral volume and maternal and neonatal clinical outcomes is pending conclusion of the ongoing clinical trial.

Limited funding for medical technology, low levels of education and poor infrastructure for delivering and maintaining technology severely limit medical decision support in low- and middle-income countries. Perinatal and maternal mortality is of particular concern with millions dying every year from potentially treatable conditions. Guatemala has one of the worst maternal mortality ratios, the highest incidence of intra-uterine growth restriction (IUGR), and one of the lowest gross national incomes per capita within Latin America. To address the lack of decision support in rural Guatemala, a smartphone-based system is proposed including peripheral sensors, such as a handheld Doppler for the identification of foetal compromise. Designed for use by illiterate birth attendants, the system uses pictograms, audio guidance, local and cloud processing, SMS alerts and voice calling. The initial prototype was evaluated on 22 women in highland Guatemala. Results were fed back into the refinement of the system, currently undergoing RCT evaluation.