In in low-and middle-income countries (LMIC), where there are very few trained physicians and nurses, community health workers (CHWs) are often the only providers of healthcare to millions of people. Such LMIC are countries that are classified, based on their geographic region and Gross National Income (GNI), as low-middle income by the World Bank Group, the worlds largest development bank. Research has shown digital health tools to be an effective strategy to improve the performance of frontline line health workers. The aim of this review was to systematically examine the literature on digital health tools that are used for decision support in LMIC and describe what we can learn from studies that have used these tools. As part of a larger parent study the following databases were searched: PubMed, Embase, Scopus, CINAHL, Global Health Ovid, Cochrane and Global Idex Medicus, to find ariticles in the following domains: training tools, decision support, data capture, commodity tracking, provider to provider communication, provider to patient communication and alerts, reminders, health information content. These domains were selected based on the World Health Organisation (WHO) framework for classifying digital health interventions. Content from all seven of these domains informed a series of reviews however this review focuses on how digital tools are used to provide decision support to FLHWs. Included studies were conducted in LMIC in Africa, Asia, North America and South America with the most common users of the tools being CHWs. Most tools for FLHW decision-support used in the interventions described in included articles were in either the pilot or prototype phases, and offered maternal and child health care services. Although decision support was the primary digital health function of all these studies, there was considerable variation in the number of digital health functions of each tool with most studies reporting decision support and data capture as their primary and secondary functions respectively. All the studies found their intervention to have beneficial effects on one or more of the following outcomes: beneficiary engagement, provider engagement, health effects and process/outputs. These findings show great potential for the use of decision support digital health tools as a means of improving the outcomes of health systems through; reducing the work load of FLHWs, reducing the costs of health care, improving the efficiency of service delivery and/or improving the overall quality of care.

Ett folkhälsoarbete inriktas på hälsofrämjande- eller förebyggande insatser vilket kan ske på lokal nivå mot den enskilde individen. Missbruks- och beroendevården ansvarar för att ge stöd och behandling till personer som har ett missbruk eller beroende av ohälsosamma levnadsvanor. De ansvarar även för att förbättra och utveckla sina metoder och verktyg. Med utvecklingen av välfärdsteknik, har behandlare inom missbruks- och beroendevården börjat använda e-hälsoverktyg i allt större utsträckning i behandlingsarbete. Det anknyter till vision e-hälsa 2015 som bland annat fokuserar på ett arbete inom vård-och omsorgssektorn på individnivå. Digitala arbetsmiljön ämnar underlätta det vardagliga arbetet som stödjer de processer personalen medverkar i, som i slutänden kan bidra till att individen erbjuds digitala stödverktyg för att förbättra sin hälsa samt öka sin delaktighet. Syftet med studien var att undersöka behandlares erfarenheter av att använda välfärdsteknik i form av e-hälsoverktyg i deras behandlingsarbete. Metoden var kvalitativ med induktiv ansats där det målstyrda urvalet kompletterats med snöbollsurval. Intervjuerna genomfördes i semistrukturerad form och analyserades utifrån en manifest kvalitativ innehållsanalys. Studiens teoretiska perspektiv utgörs av Antonovskys teori KASAM, känslan av sammanhang.  Resultatet utgörs av två kategorier med fyra underkategorier och visar behandlares erfarenheter av att e-hälsoverktyg i behandlingsarbete bidrar till ökade möjligheter som underlättat för motivationsarbetet samt till utökad samverkan med enheten barn-och familj, behandlingshem och företagshälsovården. Resultatet visar även behandlares erfarenheter av att e-hälsoverktyg i behandlingsarbete skapar tillkommande utmaningar i form av ytterligare arbetsuppgifter samt en ökad situationsanpassad användning utefter exempelvis klientens psykiska ohälsa. / A public health work is focused on health promotion or prevention efforts, which can be done at the local level towards the individual. Addiction units is responsible for providing support and treatment to people who have an addiction or dependence on unhealthy lifestyles. They are also responsible for improving and developing their methods and tools. However, With the development of welfare technology, Social workers in addiction units, have increasingly begun to use e-health tools in treatment work. It is related to vision-health 2015, which among other things, focuses on work in the health and care sector at the individual level. The digital work environment aims to facilitate everyday work that supports the processes in which social workers participate, which can ultimately contribute to the individual being offered digital support tools to improve their health and increase their participation. The aim of this study was to investigate social workers’ experiences using welfare technology in the form of “e-health tools” in their work. The method was qualitative with an inductive approach where the purposeful sampling was supplemented with snowball sampling. The interviews were conducted in semi-structured form and analyzed based on a manifest qualitative content analysis. The theoretical perspective of the study consists of Antonovsky’s theory SOC, sense of coherence. The analysis resulted in two categories with four subcategories and shows social worker’s experiences that e-health tools in treatment work contribute to increased opportunities that have facilitated motivational work and such as increased collaboration with the unit for children and families, treatment homes and occupational health care. The results also show social worker’s experiences that e-health tools in treatment work create additional challenges in the form of additional tasks and an increased situation-adapted use according to, for example, the client's mental illness.

Mortality rates in the United States are higher for men than they are for women as a result of chronic diseases such as heart disease, cancer, and diabetes. Despite these disproportionate rates, few health interventions are targeted to men, and limited knowledge exists regarding the specific components needed to design technology health tools to appeal to men. The purpose of this quantitative study was to examine the relationship between the use of technology health tools and the role of self-efficacy in men and the influence on participation in healthy lifestyle behaviors. A quasi-experimental design was used to analyze data collected from the Health Information National Trends Survey (N = 990). A group of men (n = 323) who used technology health tools were compared to a control group of men (n = 667) who did not use technology health tools. Results from the regression analysis indicated that the use of technology health tools for self-management of health behavior had a significant effect on participation in healthy lifestyle behavior (p = .026). Self-efficacy was also found to mediate the relationship between technology health tools and participation in healthy lifestyle behavior (p = .018). This study supports the United States federal government's Healthy People 2020 objective to increase the proportion of people who use Internet health management tools. The implications for positive social change include knowledge for developing targeted technology health interventions to increase the participation of men in healthy lifestyle behavior, reduce the number of men with chronic diseases, improve chronic disease management, and reduce healthcare costs in the United States.