This systematic review provides a chronological overview of how mhealth research has evolved with changes in mobile technologies. The review involved a PubMed search complemented by manual searching of all issues of the Journal of Medical Internet Research and Telemedicine Journal and eHealth, from inception to January 2015. Articles reporting the evaluation of mhealth interventions in any patient group for any health-related outcomes were analysed without restrictions on the study design. A total of 3476 publications were obtained from the PubMed search and manual searching of eHealth journals. Analysis was based on an abstract review of 515 (14.8%) original research articles, which fulfilled preset inclusion criteria. Three distinct time periods were identified on the basis of mobile devices used in mhealth research. Personal digital assistants (PDAs) dominated mhealth research in the years before 2007 (17 of 33 articles, 51.5%). Basic and feature phones were the main methods of mhealth intervention from 2007 to 2012 (95 of 193 articles, 49.2%). After 2012, smart devices (smartphones, tablet PCs and iPod touches) were highly used in mhealth research (173 of 289 articles, 59.9%). Despite a growing focus on infectious diseases and maternal and child health in the most recent years, non-communicable conditions continued to overshadow the trend of mhealth research. Overall, mHealth research has evolved over the past decade in terms of the mobile devices employed, health conditions addressed and its purpose. While chronic medical conditions have clearly been the focus of mhealth research, a shift in trends is expected as the application of mhealth interventions spreads to other under-studied areas. Future research should continue to leverage on the advancements and ubiquitous nature of mobile devices to make healthcare accessible to all.

Encouraging progress has been made in the implementation of health care financing reforms in Ethiopia. However, there is shortage of evidence on the effect of the health care financing reforms on access to essential medicines in the country. Thus, a clear need exists for well-organized research on the issue.

Background Widespread adoption by patients is imperative for the success of app-based interventions for enhancing adherence to oral anticancer medications. Patients' attitudes and beliefs should be evaluated to understand determinants of their acceptance and adoption of such interventions. Objective To identify factors that influence cancer patients' intention to adopt an app-based system for enhancing oral anticancer medication adherence. Methods This study was conducted as part of the usability evaluation of an app-based system for enhancing adherence. We followed the grounded theory approach employing audio-recorded face-to-face interviews for data collection from patients taking oral anticancer medications (n = 15) and caregivers of such patients (n = 3). Data analysis involved verbatim transcription of all interviews, coding of the transcripts and field notes, detailed memo writing, and constant comparative evaluation of emergent categories. Results A conceptual framework of facilitating and hindering factors for users' adoption intention for an oral anticancer medication adherence app was developed. Findings suggest that facing difficulties in maintaining adherence and patients' perceived superiority of the app over their current methods facilitate adoption intention. In contrast, having to pay, lack of language options and users' perception of low competence in using an app were the hindrance factors. Conclusion This study showed that adoption of adherence apps could be explained by technology acceptance constructs, such as performance expectancy. Adoption intention was also facilitated by patients perceived vulnerabilities in maintaining adherence to their medications, which was a health behaviour construct. Implementation of app-based programs should address patients' perceived vulnerabilities and relative advantage of the app over their current methods. Clinicians and app developers should also consider the financial, technological and language barriers for end users.

No outside funding supported this study. The authors have no conflicts of interests directly related to this study. Study concept and design were contributed by Loy and Yap. Loy collected the data and took the lead in data interpretation, along with Ali and Yap. The manuscript was primarily written by Loy, along with Yap, and revised primarily by Ali, along with Yap.

Background Patients’ health-related quality of life (HRQoL) and health state utility values are critical inputs in the clinical and economic evaluation of treatments for human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS). However, information on health state utility values is lacking in the context of Ethiopia. Here, we aimed to assess HRQoL and determine health state utility values and factors that influence the values among HIV/AIDS patients in Ethiopia. Methods A cross-sectional study was conducted among 511 HIV/AIDS patients at Tikur Anbessa Specialized Hospital in Ethiopia. Patients aged 18 years or older were eligible for the interview and those who were mentally unstable and with hearing impairment were excluded from the study. We performed face-to-face interviews using EuroQol-5 Dimensions-5 Levels (EQ-5D-5L) in combination with EuroQol-Visual Analog Scales (EQ-VAS). Level-specific disutility coefficients obtained from the general population were used for computing utility values. Patients’ health profiles were described using percentages and different statistical analysis were conducted to determine factors associated with the EQ-5D index and EQ-VAS scores. Results A total of 511 patients participated in the study. A higher proportion of patients reported slight or more severe problems on the anxiety/depression (55.2%) and pain/discomfort (51.3%) dimensions. The overall median utility value of HIV/AIDS patients was 0.94 (IQR = 0.87, 1) from the EQ-5D index and 80% (IQR = 70%, 90%) from the EQ-VAS scores. Demographic characteristics including age, occupational status, and household monthly income significantly affected patient’s utility values. Moreover, statistically significant (p < 0.001) differences were seen between the EQ-5D index values of patients with different CD4 count intervals. Furthermore, number of medicines that the patients were taking at the time of the study and comorbidities were significantly associated with the EQ-5D utility index and EQ-VAS score, p < 0.001. Conclusions The anxiety/depression and pain/ discomfort dimensions were identified to have critical influence in reducing the HRQoL of adult HIV/AIDS patients in the context of Ethiopia. The study is also the first to use the EQ-5D-5L tool to identify health state utility values for Ethiopian adult HIV/AIDS patients. Future economic evaluations of HIV/AIDS interventions are encouraged to employ the identified utility values.