Experiences of Online COVID-19 Information Acquisition among Persons with Type 2 Diabetes and Varying eHealth Literacy

Tele-nursing awareness, needs, and related influences in T2DM patients: qualitative descriptive study

BACKGROUND

Tele-nursing, which utilizes digital health tools, has the potential to enhance the management of Type 2 Diabetes (T2DM). However, patients' awareness, needs, and barriers to using these services are not well understood. This study employed qualitative interviews to explore the perceptions of patients with T2DM towards tele-nursing and to identify factors influencing their adoption, with the aim of providing tailored strategies for effective service implementation.

METHODS

A descriptive qualitative research design was used. From June to August 2023, a purposive sampling method was used to select 20 T2DM patients from a hospital, following the principle of maximum variation. Semi-structured interviews were conducted, and the data were analyzed using thematic analysis.

RESULTS

Four main themes were identified: insufficient awareness and willingness to use tele-nursing, the need for tele-nursing services, facilitators of tele-nursing, and barriers to tele-nursing.

CONCLUSION

The awareness of tele-nursing among T2DM patients needs significant improvement. Patients expressed clear demands for tele-nursing services, including health education, dietary guidance, blood sugar monitoring, and medication reminders. However, the adoption of tele-nursing is influenced by factors such as service accessibility, scope, technological challenges, and associated costs. Tele-nursing should address the specialized nursing needs of T2DM patients by leveraging remote technology to provide personalized and flexible care options that align with their evolving requirements.

eHealth Literacy and Its Association With Demographic Factors, Disease-Specific Factors, and Well-Being Among Adults With Type 1 Diabetes: Cross-Sectional Survey Study

Background

The use of digital health technology in diabetes self-care is increasing, making eHealth literacy an important factor to consider among people with type 1 diabetes. There are very few studies investigating eHealth literacy among adults with type 1 diabetes, highlighting the need to explore this area further.

Objective

The aim of this study was to explore associations between eHealth literacy and demographic factors, disease-specific factors, and well-being among adults with type 1 diabetes.

Methods

The study used data from a larger cross-sectional survey conducted among adults with type 1 diabetes in Sweden (N=301). Participants were recruited using a convenience sampling method primarily through advertisements on social media. Data were collected between September and November 2022 primarily through a web-based survey, although participants could opt to answer a paper-based survey. Screening questions at the beginning of the survey determined eligibility to participate. In this study, eHealth literacy was assessed using the Swedish version of the eHealth Literacy Scale (Sw-eHEALS). The predictor variables, well-being was assessed using the World Health Organization-5 Well-Being Index and psychosocial self-efficacy using the Swedish version of the Diabetes Empowerment Scale. The survey also included research group-developed questions on demographic and disease-specific variables as well as digital health technology use. Data were analyzed using multiple linear regression presented as nested models. A sample size of 270 participants was required in order to detect an association between the dependent and predictor variables using a regression model based on an F test. The final sample size included in the nested regression model was 285.

Results

The mean Sw-eHEALS score was 33.42 (SD 5.32; range 8-40). The model involving both demographic and disease-specific variables explained 31.5% of the total variation in eHealth literacy and was deemed the best-fitting model. Younger age (P=.01; B=-0.07, SE=0.03;95% CI -0.12 to -0.02), lower self-reported glycated hemoglobin levels (P=.04; B=-0.06, SE=0.03; 95% CI -0.12 to 0.00), and higher psychosocial self-efficacy (P<.001; B=3.72, SE=0.53; 95% CI 2.68-4.75) were found associated with higher Sw-eHEALS scores when adjusted for demographic and disease-specific variables in this model. Well-being was not associated with eHealth literacy in this study.

Conclusions

The demographic and disease-specific factors explained the variation in eHealth literacy in this sample. Further studies in this area using newer eHealth literacy tools are important to validate our findings. The study highlights the importance of development and testing of interventions to improve eHealth literacy in this population for better glucose control. These eHealth literacy interventions should be tailored to meet the needs of people in varying age groups and with differing levels of psychosocial self-efficacy.

Living with my diabetes - introducing eHealth into daily practices of patients with type 2 diabetes mellitus

Objective

Diabetes patients can draw on an increasing number of eHealth apps to support them in the self-management of their disease. While studies so far have focused on patients with type 1 diabetes, we explored how patients with type 2 diabetes mellitus (T2DM) integrate eHealth apps into their practices aimed at managing and coping with the disease, which aspects were considered particularly valuable and which challenges users encountered.

Methods

Semi-structured interviews and focus group sessions were conducted to explore how patients cope with T2DM in their daily lives and their attitude towards eHealth. In a further step, four eHealth apps were tested by patients and their expectations and experiences studied by way of qualitative interviews and focus groups.

Results

The analysis showed that the study participants valued in particular the possibility to use eHealth apps to sense and gain a better understanding of their own body, to learn about specific responses of their body to nutrition and physical activity, and to support changes in daily routines and lifestyle. Key challenges encountered related to difficulties in interpreting the data, matching the data to other bodily sensations, getting overly occupied with the disease and difficulties in integrating the apps into personal, family, and care practices.

Conclusion

Under certain conditions, eHealth can play an important role for patients in developing a nuanced, personal understanding of their body and coping with T2DM. A prerequisite is that eHealth needs to be fitted into the specific practices of users, and patients desire a strong role by their care professionals in providing support in interpretation of data.

Relationship Between Electronic Health Literacy and Self-Management in People With Type 2 Diabetes Using a Structural Equation Modeling Approach

BACKGROUND

Electronic health (eHealth) literacy is a relatively new concept used to determine health outcomes. However, it is not well known how eHealth literacy relates to health outcomes such as diabetes self-management.

PURPOSE

This study was designed to examine the relationships among eHealth literacy, self-efficacy, social support, and self-management in people with Type 2 diabetes.

METHODS

A cross-sectional design was used to examine secondary data from a field survey of people with Type 2 diabetes recruited from outpatient clinics from August to December 2021 ( N = 453). A structural equation model was used that first analyzed the measurement model using confirmatory factor analysis and then tested the hypothesized structural model to estimate the expected relationships among the study variables. The significance of the statistical estimates for the model was assessed based on the 95% bias-corrected bootstrap confidence interval from 5,000 bootstrap resamples.

RESULTS

Significant, indirect relationships were found between eHealth literacy and self-management via self-efficacy (β = 0.26, B = 0.17, 95% CI [0.10, 0.24]) and via social support and, in turn, self-efficacy (β = 0.08, B = 0.05, 95% CI [0.04, 0.08]). eHealth literacy, social support, and self-efficacy together explained 58.1% of the variance in self-management.

CONCLUSION/IMPLICATIONS FOR PRACTICE

This study provides new evidence regarding how eHealth literacy relates to self-management in people with Type 2 diabetes via two indirect pathways, including self-efficacy alone and social support and self-efficacy in series. An eHealth literacy program for self-management should be developed in clinical practice that includes strategies for inducing synergistic effects from self-efficacy and social support on self-management in people with Type 2 diabetes.

Telenursing needs and influencing factors in patients with type 2 diabetes mellitus: A cross-sectional study

AIMS AND OBJECTIVES

This study aimed to determine the relationship between the demand for telenursing and the chronic illness resources available to patients with type 2 diabetes mellitus (T2DM), as well as the factors that affect this requirement.

DESIGN

Cross-sectional.

METHODS

This study included 586 participants with T2DM. A telenursing needs questionnaire developed by the research team was used to assess the telenursing needs of patients with T2DM, and the Chinese version of the Chronic Illness Resources Survey was used to assess the participants' community chronic disease resources. A one-way ANOVA and multiple regression analysis were used to determine the factors influencing the demand for telenursing and to estimate the relationship between chronic illness resources and the need for telenursing. The STROBE checklist was followed.

RESULTS

The patients' telenursing needs, ranked from high to low, are as follows: individualized skills and safety; basic disease care; psychological and spiritual needs; respect and social support; and high-level health management. The chronic disease resource score was 3.47 ± .02, which suggested that patients with T2DM have relatively rich disease resources. Multiple regression analyses showed that resources for chronic diseases, the course of diabetes and complications, family income and other chronic diseases accounted for 79.6% of the variance in T2DM patients' telenursing needs.

CONCLUSIONS

The telenursing needs of patients with T2DM are prominent, and primarily focus on basic nursing needs for the disease. To some extent, chronic disease resources affect the telenursing needs of patients with T2DM.

RELEVANCE TO CLINICAL PRACTICE

It is crucial to pay attention to research on telenursing for T2DM patients from the patients' perspective. Enhancing resources for chronic diseases may help meet the telenursing needs of T2DM patients.

PATIENT OR PUBLIC CONTRIBUTION

Parents and diabetes management specialists participated in designing the telenursing needs questionnaire.

Topic Modeling Analysis of Diabetes-Related Health Information during the Coronavirus Disease Pandemic

This study aimed to provide diabetes-related health information by analyzing queries posted in the diabetes-related online community required during the COVID-19 pandemic. A total of 9156 queries from the diabetes-related online community, dated between 1 December 2019 and 3 May 2022, were used in the study. The collected data were preprocessed for bidirectional encoder representation from transformer topic modeling analysis. Topics were extracted using the class-based term frequency-inverse document frequency for nouns and verbs. From the extracted verbs, words with common definitions were subject to substitution and unification processes, which enabled the identification of multifrequent verb categories by noun topics. The following nine noun topics were extracted, in this order: dietary management, drug management, gestational and childhood diabetes, management of diabetic complications, use and cost of medical treatment, blood glucose management, exercise treatment, COVID-19 vaccine and complications, and diabetes in older adults. The top three verb categories by noun topics were permission, method, and possibility. This study provided baseline data that can be used by clinical nurses to deliver diabetes-related education and management based on information sought by patients.

Factors influencing the e-health literacy in cancer patients: a systematic review

PURPOSE

As Internet technology evolves, electronic health (e-health) literacy gradually becomes a key factor in healthy behaviors and health-related decision-making. However, little is known about the influencing factors of e-health literacy among cancer survivors. Thus, the objective of this study was to systematically review the status quo, assessment tools, and influencing factors of e-health literacy in cancer patients.

METHODS

We conducted a comprehensive search in several databases, including PubMed, MEDLINE, Embase, CINAHL, PsycInfo, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese BioMedical Literature Database, and Chinese Science and Technology Journal Database between January 2000 and December 2021.

RESULTS

A total of nine articles were included in this review, all of which were cross-sectional studies. Following the JBI critical appraisal tool, seven of them were rated as high quality. The e-Health Literacy Scale (eHEALS) was the most commonly used measurement for e-health literacy in cancer patients. The level of e-health literacy in cancer survivors was not high, which was associated with a variable of factors. The behavioral model of health services use was adopted to summarize related influencing factors. From an individual's perspective, predisposing characteristics and enabling resources were the most significant factors, without factors related to needs characteristics.

CONCLUSION

The study has identified the influencing factors of e-health literacy among cancer survivors, including age, gender, domicile place, education level, information-seeking behavior, and social support. In the future, e-health literacy lectures need to be carried out for elderly cancer patients, especially those who live in rural areas and have no access to the Internet. Families and friends of cancer survivors should also be encouraged to offer them more support.

IMPLICATIONS FOR CANCER SURVIVORS

These findings of this review provide novel insights for both family members and medical workers to improve e-health literacy in cancer patients. Further research is required to develop easy-to-use electronic health information acquisition devices and establish propagable e-health literacy intervention programs for cancer survivors.

Consuming Health Information and Vulnerable Populations: Factors of Engagement and Ongoing Usage

OBJECTIVES

To summarise the state of the art during the year 2021 in consumer health informatics and education, with a special emphasis on "Inclusive Digital Health: Addressing Equity, Literacy, and Bias for Resilient Health Systems".

METHODS

We conducted a systematic search of articles published in PubMed using a predefined set of queries. In order to build queries, we have used a common understanding of digital inclusion. Leaving no one behind in the digital age requires not only reaching the most vulnerable populations, but also those people and population groups that are not digitally literate. It implies appropriate access, digital skills, and usability and navigability aspects in the development of technological solutions. Thus, we identified 126 potential articles for review. These articles were screened according to topic relevance and 13 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Four papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for exploring inclusive digital health in the year 2021.

RESULTS

Bibliometrics analysis conducted on words found in abstracts of the candidate papers revealed five clusters of articles, where the clustering outcomes explained 93.58% of the dispersion. The first cluster analysed the use of mobile apps to improve quality of communications between racial subgroups (e.g., Black patients and their family members) and healthcare professionals, and reduce racial disparities in core palliative care outcomes. The second cluster revealed studies reporting health literacy and experience of patients with specific diseases or impairments (e.g., type 2 diabetes, asthma and deaf people). The third focused assessing the effectiveness of interactive social media interventions on changing health behaviors, health outcomes and health equity in the adult population. The fourth targeted people with limited health literacy, as well as potentially disadvantaged or marginalized groups (people with cerebrovascular or cancer problems, students with mental problems, African American Young adults), and explored how social media may help reduce health disparities and improve health outcomes. The last explored health literacy levels among groups who experience difficulties with health service engagement and retention (patients with cancer or lay consumers of online disease information).

CONCLUSIONS

Although the query was built to address consumer inclusiveness and digital health, without specifying any health status or disease, COVID-19 was the topic in a lot of retrieved papers. Beyond the classic health issues targeted by social media (e.g., influencing health behaviors, from smoking and diet adherence to preventative screening and exercise habits), the pandemic has exposed many situations of vulnerability and health inequality. There is universal agreement on the necessity of a healthcare policy that addresses issues of gender, age, sexual orientation, and different cultures to ensure health equity for all, regardless of age or resources available. The place of digital health is studied both as a solution and a possible factor of accentuating healthcare disparities, inequalities, and exclusions. Healthcare providers should implement a digital health literacy plan to make sure health information technology is an option for everyone. Public health policies and health promotion strategies must focus on strengthening and adapting the digital health literacy in known vulnerable subgroups (ethnic and racial minorities, sexual and gender minorities, children and adolescents, elderly people, students population, impaired people, patients with cancer and chronic diseases) increasing citizen technology engagement and guaranteeing equity in access to information and in the skills to manage, discriminate, and apply information to health.

Impact of COVID-19 Pandemic on Daily Life, Physical Exercise, and General Health among Older People with Type 2 Diabetes: A Qualitative Interview Study

The COVID-19 pandemic has resulted in significant alterations to and implications for the lives of millions of people, and especially for those with pre-existing medical conditions. The aim of this study was to explore the lived experience of older people with type 2 diabetes mellitus (T2DM) throughout the first 9 months of the pandemic, with emphasis on the habits of physical exercise. We conducted a qualitative study using semi-structured interviews. The data consist of telephone interviews of seventeen older people with T2DM (10 women and 7 men, aged 62-76 years). Using thematic analysis, five themes were generated: (1) an altered social and relational life; (2) changes in routine and attitude regarding physical activity behaviour; (3) home-related activities gained relevance; (4) health and well-being impact and management; and (5) thoughts about the post-pandemic period. The increase in the number of cases and the fear of becoming infected with COVID-19 limited the social (i.e., contact with family and/or friends) and functional (i.e., daily routine, the habit of exercising) lives of these people, reverberating negatively on their health and well-being. Feelings of isolation, loneliness, anxiety were common. The findings of this study help to better understand the impact of the pandemic and determine areas of need for future interventions. A multidisciplinary approach is necessary to provide support for older people with T2DM and tackle the negative effect of the pandemic, including the reduction in physical activity.