{"title":"在患有多种慢性疾病(合并症)的患者中获取和使用移动医疗(mHealth)进行通信、健康监测和决策","authors":"Safa Elkefi","doi":"10.1080/24725579.2023.2267085","DOIUrl":null,"url":null,"abstract":"AbstractMultiple co-existing chronic diseases impact patients' ability to manage their medical conditions. MHealth provides opportunities for continuous access to and better quality of care. This study explored access to mHealth and its Usage among people with comorbidities. Based on Social Cognitive Theory (SCT), this study also explores how environmental factors (quality of care and having a regular provider) and personal factors (self-efficacy and perception of health status) can impact behavioral factors (mHealth use for communication, health monitoring, and decision-making) of people with comorbidities. Multivariate logistic regression models use Health Information National Trends Survey data (2020-2021). The study included 9303 participants, and 3260 of them had comorbidities. The hypotheses are tested on people with comorbidities who used mHealth for health purposes.The use of mHealth to monitor health-related issues was significantly correlated with comorbidity. Having a regular provider impacts the decision to use mHealth for health monitoring, communication, and decision-making. Self-efficacy perception of patients with comorbidities impacts their use of mHealth for health monitoring and decision-making. Finally, a good perception of health status impacts the use of mHealth for health monitoring. Even though different factors impact different behaviors, the findings support the hypotheses of the social cognitive theory linking the person's behavior to their perceptions and environmental factors. These findings extend the literature supporting the validity of the social cognitive theory in healthcare applications and give insights into the importance of mHealth in supporting care for patients with comorbidities.Key Words: Chronic diseasesComorbiditymhealthCommunicationDecision makingAccess to careConsumer health informaticsQuality of CareDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. FundingThe author(s) reported there is no funding associated with the work featured in this article.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":1.5000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Access and Usage of mobile health (mHealth) for communication, health monitoring, and decision-making among patients with multiple chronic diseases (comorbidities)\",\"authors\":\"Safa Elkefi\",\"doi\":\"10.1080/24725579.2023.2267085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractMultiple co-existing chronic diseases impact patients' ability to manage their medical conditions. MHealth provides opportunities for continuous access to and better quality of care. This study explored access to mHealth and its Usage among people with comorbidities. Based on Social Cognitive Theory (SCT), this study also explores how environmental factors (quality of care and having a regular provider) and personal factors (self-efficacy and perception of health status) can impact behavioral factors (mHealth use for communication, health monitoring, and decision-making) of people with comorbidities. Multivariate logistic regression models use Health Information National Trends Survey data (2020-2021). The study included 9303 participants, and 3260 of them had comorbidities. The hypotheses are tested on people with comorbidities who used mHealth for health purposes.The use of mHealth to monitor health-related issues was significantly correlated with comorbidity. Having a regular provider impacts the decision to use mHealth for health monitoring, communication, and decision-making. Self-efficacy perception of patients with comorbidities impacts their use of mHealth for health monitoring and decision-making. Finally, a good perception of health status impacts the use of mHealth for health monitoring. Even though different factors impact different behaviors, the findings support the hypotheses of the social cognitive theory linking the person's behavior to their perceptions and environmental factors. These findings extend the literature supporting the validity of the social cognitive theory in healthcare applications and give insights into the importance of mHealth in supporting care for patients with comorbidities.Key Words: Chronic diseasesComorbiditymhealthCommunicationDecision makingAccess to careConsumer health informaticsQuality of CareDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. 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Access and Usage of mobile health (mHealth) for communication, health monitoring, and decision-making among patients with multiple chronic diseases (comorbidities)
AbstractMultiple co-existing chronic diseases impact patients' ability to manage their medical conditions. MHealth provides opportunities for continuous access to and better quality of care. This study explored access to mHealth and its Usage among people with comorbidities. Based on Social Cognitive Theory (SCT), this study also explores how environmental factors (quality of care and having a regular provider) and personal factors (self-efficacy and perception of health status) can impact behavioral factors (mHealth use for communication, health monitoring, and decision-making) of people with comorbidities. Multivariate logistic regression models use Health Information National Trends Survey data (2020-2021). The study included 9303 participants, and 3260 of them had comorbidities. The hypotheses are tested on people with comorbidities who used mHealth for health purposes.The use of mHealth to monitor health-related issues was significantly correlated with comorbidity. Having a regular provider impacts the decision to use mHealth for health monitoring, communication, and decision-making. Self-efficacy perception of patients with comorbidities impacts their use of mHealth for health monitoring and decision-making. Finally, a good perception of health status impacts the use of mHealth for health monitoring. Even though different factors impact different behaviors, the findings support the hypotheses of the social cognitive theory linking the person's behavior to their perceptions and environmental factors. These findings extend the literature supporting the validity of the social cognitive theory in healthcare applications and give insights into the importance of mHealth in supporting care for patients with comorbidities.Key Words: Chronic diseasesComorbiditymhealthCommunicationDecision makingAccess to careConsumer health informaticsQuality of CareDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. FundingThe author(s) reported there is no funding associated with the work featured in this article.
期刊介绍:
IISE Transactions on Healthcare Systems Engineering aims to foster the healthcare systems community by publishing high quality papers that have a strong methodological focus and direct applicability to healthcare systems. Published quarterly, the journal supports research that explores: · Healthcare Operations Management · Medical Decision Making · Socio-Technical Systems Analysis related to healthcare · Quality Engineering · Healthcare Informatics · Healthcare Policy We are looking forward to accepting submissions that document the development and use of industrial and systems engineering tools and techniques including: · Healthcare operations research · Healthcare statistics · Healthcare information systems · Healthcare work measurement · Human factors/ergonomics applied to healthcare systems Research that explores the integration of these tools and techniques with those from other engineering and medical disciplines are also featured. We encourage the submission of clinical notes, or practice notes, to show the impact of contributions that will be published. We also encourage authors to collect an impact statement from their clinical partners to show the impact of research in the clinical practices.