Dataset Information

Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases.

ABSTRACT: Alongside the growing number of older persons, the prevalence of chronic diseases is increasing, leading to higher pressure on health care services. eHealth is considered a solution for better and more efficient health care. However, not every patient is able to use eHealth, for several reasons. This study aims to provide an overview of: (1) sociodemographic factors that influence the use of eHealth; and (2) suggest directions for interventions that will improve the use of eHealth in patients with chronic disease. A structured literature review of PubMed, ScienceDirect, Association for Computing Machinery Digital Library (ACMDL), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) was conducted using four sets of keywords: "chronic disease", "eHealth", "factors", and "suggested interventions". Qualitative, quantitative, and mixed-method studies were included. Four researchers each assessed quality and extracted data. Twenty-two out of 1639 articles were included. Higher age and lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use. Ethnicity revealed mixed outcomes. Suggested solutions were personalized support, social support, use of different types of Internet devices to deliver eHealth, and involvement of patients in the development of eHealth interventions. It is concluded that eHealth is least used by persons who need it most. Tailored delivery of eHealth is recommended.

SUBMITTER: Reiners F

PROVIDER: S-EPMC6406337 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases.

Reiners Fabienne F Sturm Janienke J Bouw Lisette J W LJW Wouters Eveline J M EJM

International journal of environmental research and public health 20190221 4

Alongside the growing number of older persons, the prevalence of chronic diseases is increasing, leading to higher pressure on health care services. eHealth is considered a solution for better and more efficient health care. However, not every patient is able to use eHealth, for several reasons. This study aims to provide an overview of: (1) sociodemographic factors that influence the use of eHealth; and (2) suggest directions for interventions that will improve the use of eHealth in patients wi ...[more]

PMID: 30795623

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Project description:Excessive drugs intake among the elderly population, including self-medication, constitutes an important public health problem. Polypharmacy may lead to numerous adverse health effects, which become more prevalent when combined with biological changes in seniors. In this cross-sectional study, 500 Polish adults aged ≥60 years (M = 67.9 ± 4.2) were asked to complete a questionnaire via telephone calls, allowing us to identify sociodemographic and health-related factors influencing the daily medications consumption. Our findings revealed that all of the participants were receiving medications; 60.2% of them receive at least 1 to 3 drugs per day (301/500). The most commonly used medications included antihypertensive drugs and analgesics (51.0% and 46.0%, respectively). Taking into account clinical conditions, independent predictors of receiving over 3 medications per day turned out to be (1) coronary artery disease (OR = 6.77; CI 95%, 2.86-16.1), (2) diabetes (OR = 3.23, CI 95%, 1.75-5.95), (3) asthma (OR = 4.87, CI 95%, 2.13-11.1), (4) heart failure (OR = 3.38, CI 95%, 1.59-7.19) and (5) gastroesophageal reflux disease (OR = 1.93, CI 95%, 1.03-3.62). Participants suffering from depression were more likely to take drugs for hypertension (OR = 1.70, CI 95%, 1.04-2.78), while those with anxiety and social loneliness took more painkillers (OR = 2.59, CI 95%, 1.58-4.26 and OR = 2.08, CI 95%, 1.38-3.13, respectively). The most significant sociodemographic factors increasing the drugs intake among the population included in our study were high body mass and subsequent increased BMI values (OR = 2.68, CI 95%, 1.50-4.77). Furthermore, living in a city with over 400,000 inhabitants increased the likelihood of taking antidepressants (OR = 2.18, CI 95%, 1.20-3.94). Our study revealed factors increasing the risk of excessive medications intake and hence, increased susceptibility to some iatrogenic diseases among the elderly population. These factors should be considered by primary care physicians while prescribing appropriate drugs to elderly patients.

Project description:BackgroundThe worldwide increase in community-dwelling people with dementia underscores the need for innovative eHealth technologies that aim to provide support to both patients and their informal caregivers in the home setting. However, sustainable implementation of eHealth technologies within this target group can be difficult.ObjectiveThe goal of this study was to gain a thorough understanding of why it is often difficult to implement eHealth technologies in practice, even though numerous technologies are designed to support people with dementia and their informal caregivers at home. In particular, our study aimed to (1) provide an overview of technologies that have been used and studied in the context of informal dementia care and (2) explore factors influencing the implementation of these technologies.MethodsFollowing an umbrella review design, five different databases were searched (PubMed, PsycINFO, Medline, Scopus, and Cochrane) for (systematic) reviews. Among 2205 reviews retrieved, 21 were included in our analysis based on our screening and selection procedure. A combination of deductive and inductive thematic analyses was performed, using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework for organizing the findings.ResultsWe identified technologies designed to be used "by informal caregivers," "by people with dementia," and "with people with dementia." Within those groups, most of the represented technologies included, respectively: (i) devices for in-home monitoring of lifestyle, health, and safety; (ii) technologies for supporting memory, orientation, and day structure; and (iii) technologies to facilitate communication between the informal caregiver and person with dementia. Most of the identified factors influencing implementation related to the condition of dementia, characteristics of the technology, expected/perceived value of users, and characteristics of the informal caregiver. Considerably less information has been reported on factors related to the implementing organization and technology supplier, wider institutional and sociocultural context of policy and regulations, and continued adaptation of technology over time.ConclusionsOur study offers a comprehensive overview of eHealth technologies in the context of informal dementia care and contributes to gaining a better understanding of a broad range of factors influencing their implementation. Our results uncovered a knowledge gap regarding success factors for implementation related to the organizational and broader context and continuous adaptation over the long term. Although future research is needed, the current findings can help researchers and stakeholders in improving the development and implementation of eHealth technologies to support informal dementia care.

Project description:BackgroundImplementation of eHealth is progressing slowly. In-depth insight into patients' preferences and needs regarding eHealth might improve its use.ObjectiveThis study aimed to describe when patients want to use eHealth, how patients want to communicate and receive information digitally, and what factors influence the use of eHealth in clinical practice.MethodsA multimethod study was conducted. Two meetings of ~5.5 hours with plenary information sessions and focus groups were held with 22 patients from the rheumatology, orthopedics, and rehabilitation departments of a Dutch hospital specialized in musculoskeletal disorders. Assignments were performed during the focus groups in which qualitative (eg, semistructured interview questions) and quantitative (ie, voting and ranking factors) data were collected.ResultsThe way patients want to use eHealth varies between patients and moments of a patient's care pathway. Patients' digital channel preferences depended on the need for interaction with a health care provider (HCP). The interaction need is in turn influenced by the degree to which information or communication is specific to an individual patient and leads to consequences for the patient. The 5 most important factors influencing the use of eHealth were access to medical information (eg, electronic health records), perceived control over disease management, correctness and completeness of information, data security, and access to information or an HCP at any time. The 5 least important factors influencing eHealth use were help with using digital devices, having internet or equipment, digital skills, attitude or emotions toward eHealth, and societal benefits.ConclusionsPatients identified opportunities for using eHealth during all moments of their care pathway. However, preferences for eHealth varied between patients and phases in the care pathway. As a consequence, eHealth should be tailored to fit individual patients' preferences but also the need for interaction regarding different topics by offering a variety of digital channels with a gradient of interaction possibilities. Furthermore, digital skills and access to the internet might become less important to focus on in the future. Improving eHealth use by patients may be achieved by providing patients access to correct and safe (medical) information and more control over their care.

Project description:BackgroundChronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions.ObjectiveThis study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance.MethodsWe performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed.ResultsThe acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (β=.37; P<.001), performance expectancy (β=.33; P<.001), and social influence (β=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F25,278=1.74; P=.02).ConclusionsGiven the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.

Project description:BACKGROUND:The Australian population has an unmet need for contraception. However, evidence suggests contraceptive patterns of Aboriginal and Torres Strait Islander populations are unique. To tailor contraceptive services and meet the contraceptive needs of Aboriginal and Torres Strait Islander people, it is important to understand the contributing factors to contraceptive use and non-use. METHODS:This study aimed to systematically review and narratively synthesise the evidence exploring the factors influencing contraceptive use among Aboriginal and Torres Strait Islander people. A systematic literature search was initially run in September 2016 and was updated again in April and August of 2018. A qualitative narrative synthesis was conducted from 2018 to 2019. Factors influencing contraceptive use or non-use were explored using a Social Ecological Model. RESULTS:The review identified 17 studies meeting the inclusion criteria published between 1972 and 2018. Most of the included studies were qualitative (n?=?11), with the remaining studies being mixed methods (n?=?3) or quantitative (n?=?3). The majority focused on either a localised geographic area or specific Aboriginal or Torres Strait Islander community (n?=?11). One study specifically focused on factors influencing contraceptive use, albeit among postpartum women. The remaining studies discussed factors influencing contraceptive use within the context of risky behaviour, sexual transmitted infections, or contraceptive practices more generally. Factors unique to individual communities included community attitudes (e.g. importance of not being too young to have a baby), specific cultural norms (e.g. subincising the penis as part of transition to manhood), and access to culturally appropriate health services. Other factors, including contraceptive characteristics (e.g. discomfort of condoms) and reproductive coercion (e.g. partner wants a baby), were similar to those found in the broader population of Australia and internationally. Most studies were lacking in quality, warranting more methodologically sound studies in the future to further assess the factors contributing to contraceptive use or non-use among Aboriginal and Torres Strait Islander people. CONCLUSIONS:Identifying community specific facilitators, as well as understanding the more broadly applicable factors contributing to contraceptive use or non-use, is essential if wanting to offer appropriate contraceptive services within an Aboriginal or Torres Strait Islander community.

Dataset Information

Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases.

Publications

Sociodemographic Factors Influencing the Use of eHealth in People with Chronic Diseases.

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