Figure 2 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Percent of mHealth apps downloaders trust mHealth apps to record data safely and accurately (n = 182).
Source publication
Our purpose in this descriptive cross-sectional study was to examine the prevalence of mobile health (mHealth) apps use, factors associated with downloading mHealth apps, and to describe characteristics of mHealth apps use among Jordanian patients in government-sponsored outpatient clinics. A total of 182 (41.6%) of the 438 outpatients who complete...
Context in source publication
Context 1
... 45.1% of mHealth apps downloaders reported that they neither trusted or distrusted mHealth apps to record their data accurately, while others reported that they trusted (35.5%) or did not trust (21.4%) mHealth apps to record their data accurately ( Figure 2). mHealth apps discontinuance and non-use. ...
Similar publications
![Figure 1. PRISMA Flow Chart [41].](profile/Vanessa-Heaslip/publication/352757081/figure/fig1/AS:1038795449327616@1624679543691/PRISMA-Flow-Chart-41_Q320.jpg)
Background:
People who are homeless experience poorer health outcomes and challenges accessing healthcare contribute to the experienced health inequality. There has been an expansion in using technology to promote health and wellbeing and technology has the potential to enable people who are socially excluded, including those who are homeless, to...
Citations
... Moreover, women are more interested in body appearance and health-related topics than men and use the internet more frequently for medical and health research [108][109][110]. Studies have also reported that women are more likely to use mHealth interventions focusing on nutrition and self-care apps, whereas men are more likely to use fitness apps [111][112][113]. Therefore, the lower engagement of the participating men in this study might be because the app focused on psychological rather than physiological determinants of overweight and obesity. ...
Background: Given the increase in the prevalence of overweight and obesity worldwide, the number of digital weight loss
interventions has also risen. However, these interventions often lack theoretical background and data on long-term effectiveness.
The consideration of individual and gender differences in weight-related psychological parameters might enhance the efficacy
and sustainability of mobile-based weight loss interventions.
Objective: This paper presented an introduction to and the process evaluation of a 12-week gender-sensitive mobile health
(mHealth) weight loss intervention (I-GENDO) combining computer-based and self-tailoring features.
Methods: Between August 2020 and August 2021, individuals with overweight (BMI 25.0-29.9 kg/m²), those with obesity
class I (BMI 30.0-34.9 kg/m²), and those with obesity class II (BMI 35.0-39.9 kg/m²) were recruited to the I-GENDO project, a
multicenter study in Germany. The mHealth intervention aimed at targeting individual psychological factors associated with the
development and persistence of overweight and obesity (eg, emotional eating) using computer-based tailoring. Moreover, the
intervention took a gender-sensitive approach by implementing self-tailoring of gender-targeted module versions. The
computer-based assignment of the main modules, self-selection of gender-targeted module versions, and use patterns were
evaluated while considering gender. Moreover, gender differences in the usability assessment were analyzed.
Results: Data from the intervention arm of the study were processed. A total of 116 individuals with overweight and obesity
(77/116, 66.4% women; age mean 47.28, SD 11.66 years; BMI mean 33.58, SD 3.79 kg/m2) were included in the analyses.
Overall, the compliance (90/109, 82.6%) and satisfaction with the app (mean 86% approval) were high and comparable with
those of other mobile weight loss interventions. The usability of the intervention was rated with 71% (5.0/7.0 points) satisfaction.
More women obtained the main module that focused on emotion regulation skills. Most men and women selected women-targeted
versions of the main modules. Women used the app more frequently and longer than men. However, women and men did not
differ in the progress of use patterns throughout the intervention.
Conclusions: We developed a tailored gender-sensitive mHealth weight loss intervention. The usability of and engagement
with the intervention were satisfactory, and the overall satisfaction with the intervention was also high. Gender differences must
be considered in the evaluation of the effectiveness and sustainability of the intervention.
... Organization of healthcare вой группы опроса, репрезентативной для жителей Архангельской области в возрасте 35-74 года. Ранее показано, что женщины, как правило, охотнее откликаются на предложения участвовать в опросах, чем мужчины, и более обеспокоены своим здоровьем [12,13]. Преобладали более молодые респонденты, которые чаще используют смартфоны и мобильный интернет по сравнению с лицами старших возрастных групп [2,5]. ...
... Also, there are the free Wi-Fi initiatives that allow free Internet roaming for 2 h daily in specific locations, with more than 60,000 free Wi-Fi hotspots in public places across SA, for example, shopping malls, city parks, and hospitals. SA is the region's largest information and communication technologies (ICTs) market, and Riyadh was named the first Arab Digital Capital in 2020 (21). ...
We aimed to determine the prevalence of MHAs' usage and explore the context and determinants of using MHAs among inhabitants in Saudi Arabia (SA). This cross-sectional study randomly selected 679 adult inhabitants from the 20 health regions in SA through an electronic, self-administered, well-structured, and validated Arabic questionnaire. The prevalence of using MHAs was 47.9%, and it was significantly higher among younger, Saudis, highly educated, and working participants, as well as those with chronic diseases (p < 0.05). The main motives for using MHAs were to promote health status (68.6%) and to lose weight (33.2%). The most used apps were related to daily steps-counting (54.2%), and among females was tracking ovulation period apps (43.5%). The most common reported advantage of using MHAs was saving time (64%). Despite the potential benefits of MHAs, they were used by only about half of the study participants in SA. The most effective MHAs in improving health status were exercise, calorie-related, water uptake, and daily steps-counting apps. Policymakers looking to address reform aimed at improving health with mobile apps will find our study interesting.
... Gender was also a prominent demographic factor, with being female mostly cited as a facilitator, and many studies reporting on the positive relationship between being female and the willingness to use such tools [39,51,55,71,[85][86][87][88], with some researchers describing that this may be because of gender-specific behavioral patterns, as women frequently undertook the role of health care liaison for their families [82], that mothers may experience more anxiety than fathers and are therefore more likely to seek alternative solutions [67]; therefore, these gender-related use patterns may very well be because of the care role that society assigns to women rather than gender per se [54,83]. Furthermore, this may be because of trial bias and self-selection bias presented by female participants, as seen in the patient characteristics of many mHealth studies. ...
... Education was another prominent demographic factor, with lower levels of education mostly cited as a barrier, and many studies have reported a positive relationship between the level of education and the willingness to use mHealth tools [35,49,53,55,64,65,72,84,92,[96][97][98]. This was explained in some studies by lower access to, and skills in using technology [89,90], and lower eHealth literacy among the less educated in some contexts [44]. ...
... Patients' attitudes and preferences are among the most prevalent personal characteristics that may affect mHealth acceptance. For instance, preference for face-to-face interactions with their care team [37,77,115,119,127,128], resistance or openness to change [36,45,129,130], negative or positive perceptions of mHealth [41,43,56,60,62,83,87,102,114,[131][132][133][134], lack of interest [55,58,69,101,103], and fear of technology [135] are all elements that play a role in whether a patient is more or less receptive to these technologies. ...
Background:
Mobile Health (mHealth) tools have emerged as a promising healthcare technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption in order to harness this potential. Patient adoption has been recognized as key challenges that require further exploration.
Objective:
The aim of this review was to systematically investigate the literature to understand the factors impacting patients’ adoption of mHealth tools, by considering socio-technical factors (from technical, social and health perspectives).
Methods:
A structured search was completed following the participants, intervention, comparators, and outcomes (PICO framework. MEDLINE PubMed, the Cochrane Library, and SAGE database were searched for the studies published between January 2011 and July 2021 in the English language, yielding 5873 results, of which 147 studies met the inclusion criteria. The Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines (PRISMA) and the Cochrane handbook were followed to ensure a systematic process.
Results:
The technical factors impacting patients’ adoption of mHealth tools were categorized into 6 key themes: usefulness, ease of use, data related, monetary factors, technical issues, and user experience; which were divided into 20 sub-themes. Health related factors were categorized into 6 key themes: the disease or health condition, the care team’s role, health consciousness and literacy, health behavior, relation to other therapies, integration into patient journey, and the patients’ insurance status. Social and personal factors were split into 3 key clusters: moderating factors, personal characteristics, and social and cultural aspects; these were divided into 19 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them.
Conclusions:
This review builds on the growing body of research that investigates patients’ adoption of mHealth services, and highlights the complexity of the factors impacting adoption, including personal, social, technical, organizational and healthcare aspects. We recommend a more patient-centered approach, by ensuring the tools’ fit into the overall patient journey and treatment plan, emphasizing inclusive design, warranting comprehensive patient education and support, empowering and mobilizing clinicians and care teams, addressing ethical data management issues, and focusing on healthcare policies that may facilitate adoption. Clinical Trial: NA
User opinions are crucial in the development of mobile health (mHealth) applications (apps). This study aimed to investigate and qualitatively assess consumer attitudes toward mHealth apps and the main aspects of their design. The methodology was divided into four steps: (1) data collection, (2) preprocessing, (3) sentiment analysis by valence-aware dictionary and sentiment reasoner (VADER), and (4) thematic analysis by the latent Dirichlet allocation (LDA) algorithm. These steps were implemented in 836 reviews of eight mHealth apps on app stores in Jordan. The current study offers healthcare stakeholders insight into the positive and negative aspects of mHealth apps by identifying user-preferred features and recommending improvements. The findings indicate several aspects of design that mHealth app developers may use to improve overall efficacy, including user experience, client services, usability, and adherence.
