Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire

Biduski, Daiana; Bellei, Ericles Andrei; Rodriguez, João Pedro Mazuco; Zaina, Luciana A. M.; Marchi, Ana Carolina Bertoletti De

doi:10.1016/j.chb.2019.106169

Cited by 96 publications

(72 citation statements)

References 69 publications

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“…vNE pr = vE pr vE pr (6) vNE px = vE px vE pr (7) Fig. 2 shows the execution flow of the RecSysPA module.…”

Section: ) Physical Activity Results Index (Pari)mentioning

confidence: 99%

“…However, all features and functionalities of the eHealth platform do not guarantee improvement for the patients involved, since they generally do not know or do not comply with the system's information [6]. In addition to a data collection and storage mechanism, an eHealth system must have a tool that allows the search for healthy habits to contribute to the user's health [7].…”

Section: Introductionmentioning

confidence: 99%

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A Physical Activity Recommender System for Patients With Arterial Hypertension

et al. 2020

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Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this context, this study aims to develop a system for recommending physical activities for hypertensive patients to create opportunities for the patients so they can search for and create a healthy lifestyle. To achieve this goal, we elaborated on a hypertensive user profile model, called HyperModel2PAR, and a physical activity recommender system for hypertensive patients, called HyperRecSysPA. The model resulting from this study is composed of 32 elements divided into three groups, which were used in the modeling of user profiles within the system for generating HyperRecSysPA recommendations. The developed system was validated by physicians who answered a specific questionnaire. As a result, ∼ 75% of the recommendations generated were approved. Therefore, this study has prospective contributions to the literature, since both models obtained conclusive results in the assessments performed.

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“…vNE pr = vE pr vE pr (6) vNE px = vE px vE pr (7) Fig. 2 shows the execution flow of the RecSysPA module.…”

Section: ) Physical Activity Results Index (Pari)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Physical Activity Recommender System for Patients With Arterial Hypertension

et al. 2020

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“…Because the interactive support tool encourages patient's self-registration of variables related to health and provides feedback on changes, patient engagement is augmented 34,35 . Registering daily health data on an app can motivate the patient to create a routine, paying more attention to their health by improving adherence to treatment 13,36 . In this sense, we can assume that using the app has positively influenced the patient's commitment to medication intake and, consequently, has influenced with better outcomes in the IG.…”

Section: Discussionmentioning

confidence: 99%

Effects of using a mobile health application on the health conditions of patients with arterial hypertension: A pilot trial in the context of Brazil’s Family Health Strategy

Debon

Bellei

Biduski

et al. 2020

Sci Rep

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Brazil's Family Health Strategy (FHS) leads public health policies and actions regarding community health, addressing arterial hypertension (AH) in primary care settings. In this scenario, the use of communication technologies becomes appropriate for the monitoring of patients with AH. To preliminary verify the intervention approach and the effects of using an m-Health application on the health conditions of patients with AH for a future study, we conducted a non-randomized, controlled, non-blind trial (N = 39), comparing the use of a mobile health app (m-Health) with conventional AH monitoring over 3 months. During the study, we promoted health information workshops to engage patients from both intervention and control groups. Pre and post-intervention, we compared measurements of systolic and diastolic blood pressure; food frequency questionnaire; Appraisal of Self-Care Agency Scale; blood tests of hemogram, creatinine, uric acid, sodium, potassium, lipid profile, and glycemia. Improvements were identified in both groups due to the workshops, including the reduction in total and non-HDL cholesterol, healthier consumption of salads and sugary drinks, and increased selfcare scores. Exclusively in the intervention group, which used the m-Health app, there was a change in systolic and diastolic pressure towards more adequate levels. In addition, the intervention group had improved levels of glucose and HDL cholesterol and reduced consumption of ultra-processed foods. In conclusion, the use of an m-Health app had positive effects on the health conditions of patients with AH under treatment within FHS, especially when combined with health information. On the context of FHS, the use of technology is encouraging supporting better health conditions. Arterial hypertension (AH) is one of the main modifiable risk factors for diseases of the circulatory system. With a high prevalence, AH is considered one of the most important public health problems. The World Health Organization estimates that about 600 million people have AH and, annually, 7.1 million individuals die from this disease, substantially burdening health systems 1. Among the AH modifiable factors, either by medication or by altering habits and behavior, there is obesity, sedentary lifestyle, eating habits, and stress. Controlling blood pressure can still be a challenge since, with everyday activities and lack of time, many people do not bother to maintain their normal blood pressure levels 2. Among the main non-medicinal recommendations that should be followed, there are healthy eating, physical activity, reduction of sodium and alcohol consumption, and non-consumption of tobacco 3 .

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“…The reliability of messages and information along with the trustworthiness of websites are important with regards to health [24]. However, users' views about their health conditions were the same after using an app as before using the app [25]. Compared to men, women post more statements on social media about health problems online and argue more…”

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confidence: 99%

Modeling Impact of Word of Mouth and E-Government on Online Social Presence during COVID-19 Outbreak: A Multi-Mediation Approach

Yasir

Ahmad

et al. 2020

IJERPH

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Although social presence plays an essential role under general conditions, its role becomes significant for societal protection during the quarantine period in epidemic outbreak. In this study, we attempted to identify the role of E-government and COVID-19 word of mouth in terms of their direct impact on online social presence during the outbreak as well as their impacts mediated by epidemic protection and attitudes toward epidemic outbreaks. For this purpose, a unique multi-mediation model is proposed to provide a new direction for research in the field of epidemic outbreaks and their control. Through random sampling, an online survey was conducted and data from 683participants were analyzed. Partial least squares structural equation modeling was used to test the relationships between the variables of interest. The study results revealed that the roles of E-government and COVID-19 word of mouth are positively related to online social presence during the outbreak. Epidemic protection and attitude toward epidemic outbreak were found to positively moderate the impact of the role of E-government and COVID-19 word of mouth on online social presence during the outbreak. The key findings of this study have both practical and academic implications. health protection. This phenomenon encouraged us to formulate a theoretical model based on social presence theory and the role of social media to help examine safety and participation in quarantine. The conceptual model is presented in Figure 1.Word of mouth can be defined as "the intention to share a certain story using one's own social media account" [2]. Many researchers proved that communication has more of an impact through social media with regards to different health issues, and message sharing was found to be the best predictor of emotive and passionate response [3]. Online health information is regularly updated [4]. Nowadays, universal and worldwide flow cannot be ignored [5] and search engines are the most effective method to find information [6]. The Internet is also a useful source for people in the medical field for discussions and interactions about medical issues [7]. A nine-year big data study showed that the use of computers projected emotive improvement [8]. From the health protection point of view, many factors were found to affect the dispersal of cancer information, including anxiety, courage, anticipation, and sharing of experience [9].A study proved that the gestation time of infection (corona virus) was assessed at about 2-14 days [7]. So, a research question was raised about protection during an epidemic outbreak. Social media campaigns with complete research frameworks with theoretical and statistical support for these time periods are essentially to protect society during emergencies. To address this need, our research model includes the factors that trigger safety campaigns and the main effects (direct) of direct relations and the association of mediators on online social presence.The literature shows that for different disease management programm...

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Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire

Cited by 96 publications

References 69 publications

A Physical Activity Recommender System for Patients With Arterial Hypertension

A Physical Activity Recommender System for Patients With Arterial Hypertension

Effects of using a mobile health application on the health conditions of patients with arterial hypertension: A pilot trial in the context of Brazil’s Family Health Strategy

Modeling Impact of Word of Mouth and E-Government on Online Social Presence during COVID-19 Outbreak: A Multi-Mediation Approach

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