Interpersonal influences on self‐management in the eHealth era: Predicting the uses of eHealth tools for self‐care in America

Sun, Mengru; Jiang, Li

doi:10.1111/hsc.13107

Cited by 8 publications

(12 citation statements)

References 92 publications

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“…The population-based group had fewer treatments and, therefore, fewer problems coping with their symptoms compared with the OCC group [ 41 , 42 ]. The OCC group had more reasons to investigate what could possibly help them, in which case eHealth tools for self-care are an accessible option [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

“…They probably expect that they can improve their health through active participation and self-management. Indeed, the characteristics of the survivors in the OCC group are factors that influence the self-management of individuals in an eHealth environment [ 43 ]. Could this OCC group represent the starting point for user uptake and implementation of web-based interventions, many of which remain on the shelf [ 46 , 47 ]?…”

Section: Discussionmentioning

confidence: 99%

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Comparing Survivors of Cancer in Population-Based Samples With Those in Online Cancer Communities: Cross-sectional Questionnaire Study

Eenbergen¹,

Vromans²,

Tick³

et al. 2022

JMIR Cancer

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Background Most Western countries have websites that provide information on cancer and the opportunity to participate in online cancer communities (OCCs). The number of patients with cancer that participate in these OCCs is growing. These patients are relatively easy to approach for research purposes. Objective The objective of this study is to determine the differences and similarities between survivors of cancer in population-based samples and survivors participating in OCCs who use the internet in relation to their illness. Methods In 2017, we drew a sample of 539 population-based patients and 531 OCC patients. The population-based patients were sent a paper-based questionnaire, and the OCC patients were sent the same questionnaire on the web. In the questionnaire, we asked patients about their sociodemographics, internet use, sources of information, media use, and wishes regarding future internet use for health care–related purposes, and the effect of internet use on their health care consumption. Results The response rate of population-based internet users was 47% (233/496), and that of the OCC group was 40.3% (214/531). The OCC group had a significantly higher education level (P<.001), was younger (P<.001), had more survivors that were employed (P<.001), and attached greater importance to the internet (171/214, 79.9% vs 126/233, 54.1%; P<.001) and fellow survivors (107/214, 50% vs 60/233, 25.8%; P<.001). Compared with the population-based group, the OCC group reported more intensive internet use immediately after diagnosis, during treatment, and during follow-up (P<.001 in each case). There were similarities in terms of the relative importance that survivors attach to the various sources of information, the topics on which they seek information, and their wishes for future eHealth possibilities. The OCC group reported a greater need to participate in a web-based class or chat with others (92/214, 43% vs 44/233, 18.9%). Conclusions We conclude that survivors who are members of an OCC are not representative of survivors of cancer in general. There are significant differences in sociodemographic characteristics, internet use during their treatment journey, internet search frequency during their cancer journey, and participation wishes. Using web-based information and communication can support shared decision-making and may facilitate the active participation of patients during their treatment. For research purposes, it is important to take the bias in OCC groups into account.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Comparing Survivors of Cancer in Population-Based Samples With Those in Online Cancer Communities: Cross-sectional Questionnaire Study

Eenbergen¹,

Vromans²,

Tick³

et al. 2022

JMIR Cancer

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“…Thus, "reminders, " "persuasion, " and "encouragement" against tobacco use likely benefit rural patients' self-management of chronic illness. However, it should be noted that the same population is constrained by limited health literacy and poor access to healthcare resources (e.g., primary care providers, specialist doctors, and online healthcare information) (14,50,51). Thus, middle-aged and older rural patients may not fully benefit from their social networks when it comes to medication use behavior (19,52).…”

Section: Discussionmentioning

confidence: 99%

“…As both Bourdieu and Veenstra in their work on social capital theory note that rich healthcare resources only mean an increasing chances and opportunities to access resources (7,8); the maximum utilization of healthcare resources is closely related to the individuals' ability to maintain long-term social connections and participation in social real-life activities (9)(10)(11), which is social engagement. This because that effective self-management demands social interaction and collaboration between patients and their environment so they may successfully manage the difficulties that arise from having a chronic illness (12)(13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

Social Engagement and Urban–Rural Disparity in Self-Management Behaviors: Study of Middle-Aged and Older Chinese Hypertension Patients

Lü

Liu

Wang

et al. 2022

Front. Public Health

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BackgroundThis study examines the effect of social engagement on urban–rural disparities in self-management behaviors (medication use, self-monitoring, physical activity, and tobacco and alcohol avoidance) among middle-aged and older Chinese patients with hypertension.MethodsData from 2011 to 2018 were extracted from the four latest waves of the China Health and Retirement Longitudinal Study. Chi-square tests and t-tests were performed to examine urban–rural gaps in self-management behaviors. Random-effects panel logit regression models were adopted to confirm the effect of social engagement on urban–rural disparity in self-management behaviors and to explore whether this effect has narrowed or widened with “bilateral flow” between urban and rural residents. A Fairlie decomposition technique was also used to calculate the extent to which social engagement reflects urban–rural disparities.ResultsThere was significant urban–rural disparity in medication use and tobacco avoidance behaviors among the sampled patients. Medication use behavior (p < 0.001) among urban middle-aged and older patients was significantly better, whereas tobacco avoidance behavior (p < 0.05) was significantly lower compared with the rural population. Social engagement significantly enlarged the urban–rural gap in tobacco avoidance behavior (p < 0.01), but significantly narrowed the urban–rural gap in medication use behavior (p < 0.001). The Fairlie decomposition revealed that ~75.000% and 29.412% of the explained urban–rural gap in tobacco avoidance and medication use, respectively, could be attributed to social engagement. The negative effect of social engagement on urban–rural disparity in medication use increased when urban residents moved to rural areas (p < 0.05).ConclusionsThe urban–rural disparities in self-management behaviors of middle-aged and older Chinese hypertensive patients were mainly manifested in medication use and tobacco avoidance behaviors. The gaps in these two behaviors partly changed with social engagement, while the migration of urban population to rural areas weakens the positive role of social engagement in narrowing the urban–rural gap in medication use behavior. The insights of this paper on social engagement and urban–rural disparity in self-management behaviors, and the effect of urban–rural migration thereof, deserve the attention of health policymakers and researchers.

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“…Wang et al ’s meta-analysis of 44 studies on OHIS found that trust of information source, as well as quality and usefulness of information rather than perceived risk and self-efficacy were more important factors that affect individual’s OHIS behavior ( Wang et al , 2021 ). With the advancement of information and communication technologies, patients are expected to take an active role and responsibility for their health, increasing the need for information-related self-management ( Introne and Goggins, 2019 ; Sun and Jiang, 2020 ; Yang and Wu, 2020 ). In China, the outbreak of severe acute respiratory syndrome (SARS) in 2003 marked the emergence of OHIS ( Cao et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Online information and support seeking during COVID-19 lockdown in Wuhan: implications for health promotion

Zhao

Basnyat

2022

Health Promotion International

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The lockdown that was deployed in Wuhan, China to combat the COVID-19 pandemic curbed the infection but also created great information challenges for people in social isolation. This resulted in surge in online health information seeking (OHIS) behaviors of the patients and their families. While the Internet has been widely used by Chinese public to access and search health information, there is relatively little research in the context of pandemic outbreaks, especially at the onset of a strong lockdown while many people were panicking. From a total of 10 908 ‘#COVID-19 Patient Seeking Help’ posts on Weibo in a period of 20 days when the lockdown policy was first initiated, we identified 1496 unique patients living in or with family in Wuhan, China. Using textual analysis, we explored OHIS behaviors at the onset of the pandemic. Many faced increased difficulties accessing offline healthcare services and such turned to social media for help and information. In particular, the findings highlight the following themes: ‘OHIS for medical treatment’, ‘OHIS to manage self-quarantine’, ‘OHIS for tangible support’ and ‘OHIS to navigate information discrepancy’. Overall, our findings provide important insights into health information seeking behaviors and the role of social media during a pandemic. Our findings also highlight the importance of considering people’s information need and challenges created due to the lockdown policies in the future pandemic communication and preparedness.

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Interpersonal influences on self‐management in the eHealth era: Predicting the uses of eHealth tools for self‐care in America

Cited by 8 publications

References 92 publications

Comparing Survivors of Cancer in Population-Based Samples With Those in Online Cancer Communities: Cross-sectional Questionnaire Study

Comparing Survivors of Cancer in Population-Based Samples With Those in Online Cancer Communities: Cross-sectional Questionnaire Study

Social Engagement and Urban–Rural Disparity in Self-Management Behaviors: Study of Middle-Aged and Older Chinese Hypertension Patients

Online information and support seeking during COVID-19 lockdown in Wuhan: implications for health promotion

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