Understanding Continuance Usage of Mobile Learning Applications: The Moderating Role of Habit.
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ABSTRACT:
SUBMITTER: Wang YT
PROVIDER: S-EPMC8631194 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Few studies have been conducted about individuals' continuance to use m-payment, especially in an African context. This study investigates the continuance intention to use m-payment, employing two theoretical models: the DeLone and McLean information system (D&M IS) success model and the expectation-confirmation model (ECM) in an African context. We collected 338 questionnaires through an online survey to evaluate and validate the proposed theoretical model, using partial least squares - structural equation modelling (PLS-SEM). Our results indicate that the most important predictors of continuance intention to use m-payment are individual performance, use, and satisfaction. The results present useful insight to understand continuance intentions toward mobile payment in an African context. The integration of D&M IS success model, and the ECM model is to allow us to understand the main factors affecting the continuance intention to use mobile payment in the African context. By combining these two models we show how to compensate for and complement the weaknesses and strengths of the models, solidifying our findings of continuance intention with a stronger model that is otherwise not possible.
| S-EPMC8379467 | biostudies-literature
Project description:BACKGROUND:With the widespread use of mobile technologies, mobile information systems have become crucial tools in health care operations. Although the appropriate use of mobile health (mHealth) may result in major advances in expanding health care coverage (increasing decision-making speeds, managing chronic conditions, and providing suitable health care in emergencies), previous studies have argued that current mHealth research does not adequately evaluate mHealth interventions, and it does not provide sufficient evidence regarding the effects on health. OBJECTIVE:The aim of this study was to facilitate the widespread use of mHealth systems; an accurate evaluation of the systems from the users' perspective is essential after the implementation and use of the system in daily health care practices. This study extends the expectation-confirmation model by using characteristics of individuals, technology, and tasks to identify critical factors affecting mHealth continuance and performance from the perspective of health care professionals (HCPs). METHODS:A questionnaire survey was used to collect data from HCPs who were experienced in using mHealth systems of a Taiwanese teaching hospital. In total, 282 questionnaires were distributed, and 201 complete and valid questionnaires were returned, thus indicating a valid response rate of 71.3% (201/282). The collected data were analyzed using WarpPLS version 5.0 (ScriptWarp Systems). RESULTS:The results revealed that mHealth continuance (R2=0.522) was mainly affected by perceived usefulness, technology maturity, individual habits, task mobility, and user satisfaction, whereas individual performance (R2=0.492) was affected by mHealth continuance. In addition, user satisfaction (R2=0.548) was affected by confirmation and perceived usefulness of mHealth, whereas perceived usefulness (R2=0.521) was affected by confirmation. This implied that confirmation played a key role in affecting perceived usefulness and user satisfaction. Furthermore, the results showed that mHealth continuance positively affected individual performance. CONCLUSIONS:The identified critical factors influencing mHealth continuance and performance can be used as a useful assessment tool by hospitals that have implemented mHealth systems to facilitate the use and infusion of the systems. Furthermore, the results can help health care institutions that intend to introduce or develop mHealth applications to identify critical issues and effectively allocate limited resources to mHealth systems.
| S-EPMC6441862 | biostudies-other
Project description:BackgroundMobile health applications are being increasingly used for people's health management. The different uses of mobile health applications lead to different health outcomes. Although active usage of mobile health applications is shown to be linked to the effectiveness of mobile health services, the factors that influence people's active usage of mobile health applications are not well studied.ObjectiveThis paper aims to examine the antecedents of active usage of mobile health applications.MethodsGrounded on the 3-factor theory, we proposed 10 attributes of mobile health applications that influence the active usage of mobile health applications through consumers' satisfaction and dissatisfaction. We classified these 10 attributes into 3 categories (ie, excitement attributes, performance attributes, and basic attributes). Using the survey method, 494 valid responses were collected and analyzed using structural equation modeling.ResultsOur analysis results revealed that both consumer satisfaction (β=0.351, t=6.299, P<.001) and dissatisfaction (β=-0.251, t=5.119, P<.001) significantly influenced active usage. With regard to the effect of attributes, excitement attributes (β=0.525, t=12.861, P<.001) and performance attributes (β=0.297, t=6.508, P<.001) positively influenced consumer satisfaction, while performance attributes (β=-0.231, t=3.729, P<.001) and basic attributes (β=-0.412, t=7.132, P<.001) negatively influenced consumer dissatisfaction. The results of the analysis confirmed our proposed hypotheses.ConclusionsOur study provides a novel perspective to study the active usage of mobile health applications. By categorizing the attributes of mobile health applications into 3 categories, the differential effects of different attributes can be tested. Meanwhile, consumer satisfaction and dissatisfaction are confirmed to be independent from each other.
| S-EPMC8734924 | biostudies-literature
Project description:BackgroundPain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pain and opioid abuse crises. The purpose of this study is to qualitatively evaluate the content and functionality of mobile pain management apps.MethodsThe Apple App Store and the Google Play Store were searched to identify pain management apps. The inclusion criteria were as follows: (1) that apps include a pain diary function allowing users to record pain episodes, (2) are available in either Apple App Store or Google Play Store, and (3) are available in the English language. We excluded apps if they were limited to only specific forms of pain or specific diseases.ResultsA total of 36 apps met the inclusion criteria. Most of the apps served as pain diary tools to record the key characteristics of pain. The pain diary features of the apps were grouped into nine categories: the recordings of pain intensity, pain location, pain quality, pain's impacts on daily life, other features of pain, other related symptoms, medication, patients' habits and basic information, and other miscellaneous functions. The apps displayed various problems in use. The problem of not involving healthcare professionals in app development has not been resolved. Approximately 31% of apps including a pain diary function engaged clinicians in app development. Only 19% involved end-users in development and then only in an ad-hoc way. Only one third of the apps supported the cross-platforms, none of the apps supported clinician access to graphical pain data visualization, none secured HIPAA compliance, and none endorsed the PEG tool for primary care physicians' chronic pain management.ConclusionsMost of the 36 pain management apps demonstrated various problems including user interface and security. Many apps lacked clinician and end-user involvement in app development impacting the clinical utility of these apps. We could not find any pain apps suitable for clinical usage despite high demand from clinicians due to the US opioid crisis.
| S-EPMC6543581 | biostudies-literature
Project description:Habits are characterized by an insensitivity to their consequences and, as such, can be distinguished from goal-directed actions. The neural basis of the development of demonstrably outcome-insensitive habitual actions in humans has not been previously characterized. In this experiment, we show that extensive training on a free-operant task reduces the sensitivity of participants' behavior to a reduction in outcome value. Analysis of functional magnetic resonance imaging data acquired during training revealed a significant increase in task-related cue sensitivity in a right posterior putamen-globus pallidus region as training progressed. These results provide evidence for a shift from goal-directed to habit-based control of instrumental actions in humans, and suggest that cue-driven activation in a specific region of dorsolateral posterior putamen may contribute to the habitual control of behavior in humans.
| S-EPMC2758609 | biostudies-literature
Project description:IntroductionThe aim of this study was to evaluate usage habits, attitudes and perceptions towards mobile learning (m-learning), as well as to identify variables related to those attitudes amongst undergraduate dental students.Materials and methodsThe study consists of 81 dental undergraduate students who who volunteered to participate. The data collection tool consists of an m-learning attitude scale, a questionnaire, and open-ended questions. To compare the total scores and factors of m-learning attitude scale for demographic information and mobile technology usage habits of the students; the Mann-Whitney U test was used for two independent groups such as gender, presence of electronic devices, and places of Internet usage. The Kruskal-Wallis test was also used to compare the total scores and factors of m-learning attitude scale for more than two independent groups including internet usage purposes and opinions. Spearman's correlation coefficient was performed, and linear regression analysis was used to predict the change in total score according to the purposes of Internet usage.ResultsThe majority of students thought that the use of mobile devices in dentistry courses was useful and their attitudes towards m-learning were high. The students generally use the Internet for online shopping, connecting to social networks, and communication. They tend to use mobile technologies for personal use, followed by educational purposes. There were significant differences found in the m-learning attitudes for gender, having a portable power supply and use of mobile devices in dentistry courses. Communication was found significant in predicting the change in total score for the m-learning attitude scale according to the purpose of Internet usage.ConclusionDental students have generally positive attitudes towards m-learning. Students raise awareness towards the promise of m-learning in order to apply their individual technology use and learning behaviours. Designing learning materials and applications for mobile devices may increase students' performances.
| S-EPMC6673424 | biostudies-literature
Project description:Different from many previous studies explain mobile social media usage from a technical-center perspective, the present study investigates the factors that influence citizens' mobile government social media (GSM) continuance based on the valence framework. The research model was calculated by using data collected from 509 citizens who are the mobile GSM users in China. A structural equation modeling (SEM)-neural network (NN) method was employed to test the research model. The results of SEM indicated that the positive utilities included social value and hedonic value positively affect mobile GSM continuance, while the negative utility reflected by self-censorship negative affect mobile GSM continuance. This is further supported by the results of the neural network model analysis which indicated that hedonic value is more influencing predictor of continuous usage of mobile GSM, following by social value and self-censorship.
| S-EPMC7861361 | biostudies-literature
Project description:STUDY OBJECTIVES:Sleep disturbances increase vulnerability for depression, but the mechanisms underlying this relationship are not well known. We investigated the effects of experimental sleep disruption on response bias (RB), a measure of reward learning previously linked to depression, and the moderating role of positive affect responses. METHODS:Participants (N = 42) were healthy adults enrolled in a within-subject crossover sleep disruption experiment that incorporated one night of uninterrupted sleep (US) and one night of forced awakenings (FA) in random order. On the day following each experimental sleep night, participants completed a probabilistic reward task to assess RB, and the Positive and Negative Affect Schedule-X. Participants were subgrouped according to positive affect responses: Preserved Positive Affect (i.e. positive affect scores maintained or increased; n = 15) or Reduced Positive Affect (i.e. positive affect scores decreased; n = 27) following FA. RESULTS:Contrary to our hypotheses, across participants, RB did not significantly differ between the US and FA sleep conditions (p = .67). However, the effect of sleep condition on RB was moderated by positive affect response (p = .01); those with preserved positive affect showed heightened RB following FA, whereas those with reduced positive affect showed diminished RB following FA. Changes in negative affect between US and FA did not moderate RB. CONCLUSION:The inability to preserve positive affect through periods of sleep disruption may be a marker of diminished reward learning capability. Understanding how sleep disruption impacts positive affect responses and reward learning identifies a pathway by which sleep disturbances may confer risk for depression.
| S-EPMC6519913 | biostudies-literature
Project description:BACKGROUND:Unintentional medication nonadherence is common and has been associated with poor health outcomes and increased health care costs. Earlier research demonstrated a relationship between habit strength and medication adherence. Previous research also examined a habit's direct effect on adherence and how habit interacts with more conscious factors to influence or overrule them. However, the relationship between habit and adherence and the role of habit-based mobile health (mHealth) interventions remain unclear. OBJECTIVE:This review aimed to systematically evaluate the most recent evidence for habit strength, medication adherence, and habit-based mHealth interventions across chronic medical conditions. METHODS:A keyword search with combinations of the terms habit, habit strength, habit index, medication adherence, and medication compliance was conducted on the PubMed database. After duplicates were removed, two authors conducted independent abstract and full-text screening. The guidelines for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were followed when reporting evidence across the included and reviewed studies. RESULTS:Of the 687 records examined, 11 met the predefined inclusion criteria and were finalized for data extraction, grading, and synthesis. Most included studies (6/11, 55%) were cross-sectional and used a theoretical model (8/11, 73%). The majority of studies measured habit strength using the self-report habit index and self-report behavioral automaticity index (9/11, 82%). Habit strength was positively correlated with medication adherence in most studies (10/11, 91%). Habit mediated the effects of self-efficacy on medication adherence (1/11, 9%), and social norms moderated the effects of habit strength on medication adherence (1/11, 9%). Habit strength also moderated the effects of poor mental health symptoms and medication adherence (1/11, 9%). None of the included studies reported on using or proposing a habit-based mHealth behavioral intervention to promote medication adherence. CONCLUSIONS:Habit strength was strongly correlated with medication adherence, and stronger habit was associated with higher medication adherence rates, regardless of the theoretical model and/or guiding framework. Habit-based interventions should be used to increase medication adherence, and these interventions could leverage widely available mobile technology tools such as mobile apps or text messaging, and existing routines.
| S-EPMC7218590 | biostudies-literature
Project description:In an attempt to reduce the negative consequences of adolescent media use, parents often monitor their children's online activities. However, research suggests that parental monitoring often does not reduce children's problematic mobile phone use as expected. Based on the results of a survey of 584 Chinese adolescents, we found that parental monitoring positively predicted children's problematic mobile phone use (PMPU) within a Chinese cultural context. The results also showed that children's escape motivation partially mediated this relationship, while their level of shyness moderated both the mediated path and the direct impact of parental monitoring on children's PMPU. The findings suggested that a higher level of shyness increased the likelihood that parental monitoring would increase the child's escape motivation and PMPU. The study results provide guidelines for parents and educators regarding interventions for adolescents' problematic phone use.
| S-EPMC7084728 | biostudies-literature