Promosi kesehatan menggunakan gambar dan teks dalam aplikasi WhatsApp pada kader posbindu

PurposeThis study aimed to determine the effectiveness of educational programs through WhatsApp media on the level of knowledge and satisfaction of learning of Posbindu health workers.Methods This study was an experimental research on 1 group that consisted of 33 respondents. Two stages of intervention were done with sending an educational text message about diabetes in the first week and picture messages in the second week. The instruments of this study consisted of a knowledge questionnaire and a learning satisfaction questionnaire. The study was conducted on Posbindu health workers with message delivery interventions through WhatsApp.ResultsThere was a significant change between the mean pre-test and post intervention of text messaging and educational images on knowledge of type 2 diabetes variables, while the delivery of picture messages had the highest mean value of learning satisfaction.Conclusions Promotion and health education programs through message delivery on WhatsApp effectively can improve the knowledge and satisfaction of learning about type 2 diabetes mellitus.Tujuan: Penelitian ini bertujuan untuk mengetahui efektifitas program edukasi tentang diabetes tipe 2 melalui media WhatsApp pada tingkat pengetahuan dan kepuasan belajar kader Posbindu.Metode: Penelitian eksperimental ini dilakukan pada 1 grup dengan 33 responden. Intervensi terdiri dari 2 tahap, yakni: pengiriman pesan teks edukasi tentang diabetes pada minggu pertama dan pesan bergambar pada minggu kedua. Instrumen penelitian ini terdiri dari kuesioner pengetahuan dan kuesioner kepuasan belajar. Penelitian dilakukan pada kader Posbindu dengan intervensi pengiriman pesan melalui WhatsApp.Hasil: Terdapat perubahan signifikan antara rerata nilai pre test , post intervensi pengriman pesan teks dan post intervensi pengiriman gambar edukasi pada variabel tentang pengetahuan diabetes tipe 2. Sedangkan pengiriman pesan bergambar memiliki rerata nilai kepuasan belajar paling tinggi.Implikasi Praktis: Penelitian ini menyarankan program promosi dan edukasi kesehatan melalui pengiriman pesan bergambar pada aplikasi WhatsApp efektif meningkatkan pengetahuan dan kepuasan belajar.Keaslian: Penelitian ini menyatakan bahwa WhatsApp adalah media pendidikan potensial karena merupakan media interaktif antara pengirim dan penerima pesan

Multimorbidity Patterns of Chronic Diseases among Indonesians: Insights from Indonesian National Health Insurance (INHI) Sample Data

Given the increasing burden of chronic diseases in Indonesia, characteristics of chronic multimorbidities have not been comprehensively explored. Therefore, this research evaluated chronic multimorbidity patterns among Indonesians using Indonesian National Health Insurance (INHI) sample data. We included 46 chronic diseases and analyzed their distributions using population-weighted variables provided in the datasets. Results showed that chronic disease patients accounted for 39.7% of total patients who attended secondary health care in 2015-2016. In addition, 43.1% of those were identified as having chronic multimorbidities. Findings also showed that multimorbidities were strongly correlated with an advanced age, with large numbers of patients and visits in all provinces, beyond those on Java island. Furthermore, hypertension was the leading disease, and the most common comorbidities were diabetes mellitus, cerebral ischemia/chronic stroke, and chronic ischemic heart disease. In addition, disease proportions for certain disease dyads differed according to age group and gender. Compared to survey methods, claims data are more economically efficient and are not influenced by recall bias. Claims data can be a promising data source in the next few years as increasing percentages of Indonesians utilize health insurance coverage. Nevertheless, some adjustments in the data structure are accordingly needed to utilize claims data for disease control and surveillance purposes

Validating maps of land cover and land degradation with citizen science and mobile gaming

Peatland comprises around 24% of South Sumatra, a province on the island of Sumatra in Indonesia. Following catastrophic fires in 2015, peat restoration has become a priority for this area. To identify candidate areas for restoration, both land cover over time and land degradation have been mapped using optical and radar remote sensing. Limited field data have been used to help validate these maps but more validation data are still needed. One way to fill this gap is to tap into the power of citizen science, which has become an emerging area of interest. In citizen science, any member of the public can take part in scientific research, whether this is through data collection, analysis of the data or hypothesis generation. Here we present the results from a citizen science campaign using the Urundata mobile gaming application, which has been developed as part of the Restore+ project. Urundata has two main components: a rapid image assessment tool that allows users to classify satellite imagery by the type of land cover/land use visible or to examine pairs of images for detection of change over time (developed from an application called Picture Pile). The second component sends users to specific locations on the ground via a mobile device and asks for information related to land cover and evidence of land degradation (developed from an application called FotoQuest Go). Together these two components have been used to help validate land cover and land degradation maps of South Sumatra through citizen science

Building up local knowledge on restoration: lessons learnt from organizing a set of crowdsourcing campaigns

Restoration of degraded land is an important national goal to achieve Indonesia’s environmental targets. To map both land cover and land degradation, Indonesia needs timely, high quality data and the necessary tools. We have addressed this issue by running a sequence of crowdsourcing campaigns. Our aim is not only to collect the data but to also potentially present a way for citizens to contribute to larger environmental policies and strategies. Focusing on land cover identification and tree cover change, we planned and ran a set of pilot crowdsourcing campaigns in two provinces in Indonesia. We analysed the data from these pilot campaigns, and then used the insights obtained in the subsequent crowdsourcing campaign on land cover identification, upscaled to national level, which is currently ongoing. The campaigns were run using a mobile application developed as part of the RESTORE+ project. Through this application, we presented volunteers with simple microtasks by showing them satellite images and asking a simple yes/no question as to whether the image shows a particular land cover class. The application implemented a scoring system, which additionally performs a quality control of the data contributed by the crowd, and users competed with each other to classify the satellite images displayed by the application. 692 volunteers have actively engaged in the pilot crowdsourcing campaigns and have contributed more than 2.5 million satellite image interpretations. Based on the insights from the pilot campaigns, as well as an expert consultation session in Indonesia, the crowdsourcing application was modified to ensure, first, a uniform number of interpretations across the images, and secondly, higher quality data by allowing users to focus on geographical areas familiar to them, as well as to see the larger area surrounding the target sample. We analyzed the data collected and will present issues regarding data quality, comparing the accuracy of the contributions from the volunteers with the accuracy of the data collected by a set of experts. We show that a citizen science approach is promising and can complement scientific analyses and can provide potential inputs to policies on landscape restoration. A crowdsourcing approach to image interpretation can also help to shorten the time needed for data collection, making the process more cost-effective. In addition, the collective ownership of the results ensures their legitimacy and increases the chances of data acceptance. We also focus on transparency and the importance of open data. We present how we have made data generated by the crowd accessible in order to empower citizens in exploring and process the data further, thereby actively participating in environmental decision making

Increasing Demand for Natural Rubber Necessitates a Robust Sustainability Initiative to Mitigate Impacts on Tropical Biodiversity

© 2015 Wiley Periodicals, Inc.Strong international demand for natural rubber is driving expansion of industrial-scale and smallholder monoculture plantations, with >2 million ha established during the last decade. Mainland Southeast Asia and Southwest China represent the epicenter of rapid rubber expansion; here we review impacts on forest ecosystems and biodiversity. We estimate that 4.3-8.5 million ha of additional rubber plantations are required to meet projected demand by 2024, threatening significant areas of Asian forest, including many protected areas. Uncertainties concern the potential for yield intensification of existing cultivation to mitigate demand for new rubber area, versus potential displacement of rubber by more profitable oil palm. Our review of available studies indicates that conversion of forests or swidden agriculture to monoculture rubber negatively impacts bird, bat and invertebrate biodiversity. However, rubber agroforests in some areas of Southeast Asia support a subset of forest biodiversity in landscapes that retain little natural forest. Work is urgently needed to: improve understanding of whether land-sparing or land-sharing rubber cultivation will best serve biodiversity conservation, investigate the potential to accommodate biodiversity within existing rubber-dominated landscapes while maintaining yields, and ensure rigorous biodiversity and social standards via the development of a sustainability initiative

Detecting industrial oil palm plantations on Landsat images with Google Earth Engine

Oil palm plantations are rapidly expanding in the tropics, which leads to deforestation and other associated damages to biodiversity and ecosystem services. Forest researchers and practitioners in developing nations are in need of a low-cost, accessible and user-friendly tool for detecting the establishment of industrial oil palm plantations. Google Earth Engine (GEE) is a cloud computing platform which hosts publicly available satellite images and allows for land cover classification using inbuilt algorithms. These algorithms conduct pixel-based classification via supervised learning. We demonstrate the use of GEE for the detection of industrial oil palm plantations in Tripa, Aceh, Indonesia. We performed land cover classification using different spectral bands (RGB, NIR, SWIR, TIR, all bands) from our Landsat 8 image to distinguish the following land cover classes: immature oil palm, mature oil palm, non-forest non-oil palm, forest, water, and clouds. The overall accuracy and Kappa coefficient were the highest using all bands for land cover classification, followed by RGB, SWIR, TIR, and NIR. Classification and Regression Trees (CART) and Random Forests (RFT) algorithms produced classified land cover maps which had higher overall accuracies and Kappa coefficients than the Minimum Distance (MD) algorithm. Object-based classification and using a combination of radar- and optic-based imagery are some ways in which oil palm detection can be improved within GEE. Despite its limitations, GEE does have the potential to be developed further into an accessible and low-cost tool for independent bodies to detect and monitor the expansion of oil palm plantations in the tropics

Understanding and Integrating Local Perceptions of Trees and Forests into Incentives for Sustainable Landscape Management

We examine five forested landscapes in Africa (Cameroon, Madagascar, and Tanzania) and Asia (Indonesia and Laos) at different stages of landscape change. In all five areas, forest cover (outside of protected areas) continues to decrease despite local people’s recognition of the importance of forest products and services. After forest conversion, agroforestry systems and fallows provide multiple functions and valued products, and retain significant biodiversity. But there are indications that such land use is transitory, with gradual simplification and loss of complex agroforests and fallows as land use becomes increasingly individualistic and profit driven. In Indonesia and Tanzania, farmers favor monocultures (rubber and oil palm, and sugarcane, respectively) for their high financial returns, with these systems replacing existing complex agroforests. In the study sites in Madagascar and Laos, investments in agroforests and new crops remain rare, despite government attempts to eradicate swidden systems and their multifunctional fallows. We discuss approaches to assessing local values related to landscape cover and associated goods and services. We highlight discrepancies between individual and collective responses in characterizing land use tendencies, and discuss the effects of accessibility on land management. We conclude that a combination of social, economic, and spatially explicit assessment methods is necessary to inform land use planning. Furthermore, any efforts to modify current trends will require clear incentives, such as through carbon finance. We speculate on the nature of such incentive schemes and the possibility of rewarding the provision of ecosystem services at a landscape scale and in a socially equitable manner

Global, regional, and national age-specific progress towards the 2020 milestones of the WHO End TB Strategy: a systematic analysis for the Global Burden of Disease Study 2021

Background Global evaluations of the progress towards the WHO End TB Strategy 2020 interim milestones on mortality (35% reduction) and incidence (20% reduction) have not been age specific. We aimed to assess global, regional, and national-level burdens of and trends in tuberculosis and its risk factors across five separate age groups, from 1990 to 2021, and to report on age-specific progress between 2015 and 2020. Methods We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021) analytical framework to compute age-specific tuberculosis mortality and incidence estimates for 204 countries and territories (1990–2021 inclusive). We quantified tuberculosis mortality among individuals without HIV co-infection using 22 603 site-years of vital registration data, 1718 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, 680 site-years of mortality surveillance data, and 9 site-years of minimally invasive tissue sample (MITS) diagnoses data as inputs into the Cause of Death Ensemble modelling platform. Age-specific HIV and tuberculosis deaths were established with a population attributable fraction approach. We analysed all available population-based data sources, including prevalence surveys, annual case notifications, tuberculin surveys, and tuberculosis mortality, in DisMod-MR 2.1 to produce internally consistent age-specific estimates of tuberculosis incidence, prevalence, and mortality. We also estimated age-specific tuberculosis mortality without HIV co-infection that is attributable to the independent and combined effects of three risk factors (smoking, alcohol use, and diabetes). As a secondary analysis, we examined the potential impact of the COVID-19 pandemic on tuberculosis mortality without HIV co-infection by comparing expected tuberculosis deaths, modelled with trends in tuberculosis deaths from 2015 to 2019 in vital registration data, with observed tuberculosis deaths in 2020 and 2021 for countries with available cause-specific mortality data. Findings We estimated 9·40 million (95% uncertainty interval [UI] 8·36 to 10·5) tuberculosis incident cases and 1·35 million (1·23 to 1·52) deaths due to tuberculosis in 2021. At the global level, the all-age tuberculosis incidence rate declined by 6·26% (5·27 to 7·25) between 2015 and 2020 (the WHO End TB strategy evaluation period). 15 of 204 countries achieved a 20% decrease in all-age tuberculosis incidence between 2015 and 2020, eight of which were in western sub-Saharan Africa. When stratified by age, global tuberculosis incidence rates decreased by 16·5% (14·8 to 18·4) in children younger than 5 years, 16·2% (14·2 to 17·9) in those aged 5–14 years, 6·29% (5·05 to 7·70) in those aged 15–49 years, 5·72% (4·02 to 7·39) in those aged 50–69 years, and 8·48% (6·74 to 10·4) in those aged 70 years and older, from 2015 to 2020. Global tuberculosis deaths decreased by 11·9% (5·77 to 17·0) from 2015 to 2020. 17 countries attained a 35% reduction in deaths due to tuberculosis between 2015 and 2020, most of which were in eastern Europe (six countries) and central Europe (four countries). There was variable progress by age: a 35·3% (26·7 to 41·7) decrease in tuberculosis deaths in children younger than 5 years, a 29·5% (25·5 to 34·1) decrease in those aged 5–14 years, a 15·2% (10·0 to 20·2) decrease in those aged 15–49 years, a 7·97% (0·472 to 14·1) decrease in those aged 50–69 years, and a 3·29% (–5·56 to 9·07) decrease in those aged 70 years and older. Removing the combined effects of the three attributable risk factors would have reduced the number of all-age tuberculosis deaths from 1·39 million (1·28 to 1·54) to 1·00 million (0·703 to 1·23) in 2020, representing a 36·5% (21·5 to 54·8) reduction in tuberculosis deaths compared to those observed in 2015. 41 countries were included in our analysis of the impact of the COVID-19 pandemic on tuberculosis deaths without HIV co-infection in 2020, and 20 countries were included in the analysis for 2021. In 2020, 50 900 (95% CI 49 700 to 52 400) deaths were expected across all ages, compared to an observed 45 500 deaths, corresponding to 5340 (4070 to 6920) fewer deaths; in 2021, 39 600 (38 300 to 41 100) deaths were expected across all ages compared to an observed 39 000 deaths, corresponding to 657 (–713 to 2180) fewer deaths. Interpretation Despite accelerated progress in reducing the global burden of tuberculosis in the past decade, the world did not attain the first interim milestones of the WHO End TB Strategy in 2020. The pace of decline has been unequal with respect to age, with older adults (ie, those aged >50 years) having the slowest progress. As countries refine their national tuberculosis programmes and recalibrate for achieving the 2035 targets, they could consider learning from the strategies of countries that achieved the 2020 milestones, as well as consider targeted interventions to improve outcomes in older age groups