Papers by Sunday Oluwafemi Oyeyemi
Journal of Medical Internet Research, Mar 5, 2020
Background: Electronic health (eHealth) has been described as a silver bullet for addressing how ... more Background: Electronic health (eHealth) has been described as a silver bullet for addressing how challenges of the current health care system may be solved by technological solutions in future strategies and visions for modern health care. However, the evidence of its effects on service quality and cost effectiveness remains unclear. In addition, patients' psychological and emotional reactions to using eHealth tools are rarely addressed by the scientific literature. Objective: This study aimed to assess how the psychological and emotional well-being of eHealth service users is affected by the use of eHealth tools. Methods: We analyzed data from a population-based survey in Norway, conducted in the years 2015-2016 and representing 10,604 eHealth users aged over 40 years, to identify how the use of eHealth tools was associated with feeling anxious, confused, knowledgeable, or reassured. Associations between these four emotional outcomes and the use of four types of eHealth services (Web search engines, video search engines, health apps, and social media) were analyzed using logistic regression models. Results: The use of eHealth tools made 72.41% (6740/9308) of the participants feel more knowledgeable and 47.49% (4421/9308) of the participants feel more reassured about their health status. However, 25.69% (2392/9308) reported feeling more anxious and 27.88% (2595/9308) reported feeling more confused using eHealth tools. A high level of education and not having a full-time job were associated with positive reactions and emotions (feeling more knowledgeable and reassured), whereas low self-reported health status and not having enough friends who could provide help and support predicted negative reactions and emotions (ie, feeling anxious and confused). Overall, the positive emotional effects of eHealth use (feeling knowledgeable and reassured) were relatively more prevalent among users aged over 40 years than the negative emotional effects (ie, feeling anxious and confused). About one-fourth of eHealth users reported being more confused and anxious after using eHealth services. Conclusions: The search for health information on the internet can be motivated by a range of factors and needs (not studied in this study), and people may experience a range of reactions and feelings following health information searching on the Web. Drawing on prior studies, we categorized reactions as positive and negative reactions. Some participants had negative reactions, which is challenging to resolve and should be taken into consideration by eHealth service providers when designing services (ie,
JMIR formative research, Feb 25, 2022
Background: Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the ... more Background: Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the 4 main noncommunicable diseases. These noncommunicable diseases share 4 modifiable risk factors (tobacco use, harmful use of alcohol, physical inactivity, and unhealthy diet). Short smartphone surveys have the potential to identify modifiable risk factors for individuals to monitor trends. Objective: We aimed to pilot a smartphone-based information communication technology solution to collect nationally representative data, annually, on 4 modifiable risk factors. Methods: We developed an information communication technology solution with functionalities for capturing sensitive data from smartphones, receiving, and handling data in accordance with general data protection regulations. The main survey comprised 26 questions: 8 on socioeconomic factors, 17 on the 4 risk factors, and 1 about current or previous noncommunicable diseases. For answers to the continuous questions, a keyboard was displayed for entering numbers; there were preset upper and lower limits for acceptable response values. For categorical questions, pull-down menus with response options were displayed. The second survey comprised 9 yes-or-no questions. For both surveys, we used SMS text messaging. For the main survey, we invited 11,000 individuals, aged 16 to 69 years, selected randomly from the Norwegian National Population Registry (1000 from each of the 11 counties). For the second survey, we invited a random sample of 100 individuals from each county who had not responded to the main survey. All data, except county of residence, were self-reported. We calculated the distribution for socioeconomic background, tobacco use, diet, physical activity, and health condition factors overall and by sex.
JMIR medical informatics, Mar 5, 2020
Background: Electronic health (eHealth) services may help people obtain information and manage th... more Background: Electronic health (eHealth) services may help people obtain information and manage their health, and they are gaining attention as technology improves, and as traditional health services are placed under increasing strain. We present findings from the first representative, large-scale, population-based study of eHealth use in Norway. Objective: The objectives of this study were to examine the use of eHealth in a population above 40 years of age, the predictors of eHealth use, and the predictors of taking action following the use of these eHealth services. Methods: Data were collected through a questionnaire given to participants in the seventh survey of the Tromsø Study (Tromsø 7). The study involved a representative sample of the Norwegian population aged above 40 years old. A subset of the more extensive questionnaire was explicitly related to eHealth use. Data were analyzed using logistic regression analyses. Results: Approximately half (52.7%; 9752/18,497) of the respondents had used some form of eHealth services during the last year. About 58% (5624/9698) of the participants who had responded to a question about taking some type of action based on information gained from using eHealth services had done so. The variables of being a woman (
Background: Electronic health (eHealth) has been described as a silver bullet for addressing how ... more Background: Electronic health (eHealth) has been described as a silver bullet for addressing how challenges of the current health care system may be solved by technological solutions in future strategies and visions for modern health care. However, the evidence of its effects on service quality and cost effectiveness remains unclear. In addition, patients' psychological and emotional reactions to using eHealth tools are rarely addressed by the scientific literature. Objective: This study aimed to assess how the psychological and emotional well-being of eHealth service users is affected by the use of eHealth tools. Methods: We analyzed data from a population-based survey in Norway, conducted in the years 2015-2016 and representing 10,604 eHealth users aged over 40 years, to identify how the use of eHealth tools was associated with feeling anxious, confused, knowledgeable, or reassured. Associations between these four emotional outcomes and the use of four types of eHealth services (Web search engines, video search engines, health apps, and social media) were analyzed using logistic regression models. Results: The use of eHealth tools made 72.41% (6740/9308) of the participants feel more knowledgeable and 47.49% (4421/9308) of the participants feel more reassured about their health status. However, 25.69% (2392/9308) reported feeling more anxious and 27.88% (2595/9308) reported feeling more confused using eHealth tools. A high level of education and not having a full-time job were associated with positive reactions and emotions (feeling more knowledgeable and reassured), whereas low self-reported health status and not having enough friends who could provide help and support predicted negative reactions and emotions (ie, feeling anxious and confused). Overall, the positive emotional effects of eHealth use (feeling knowledgeable and reassured) were relatively more prevalent among users aged over 40 years than the negative emotional effects (ie, feeling anxious and confused). About one-fourth of eHealth users reported being more confused and anxious after using eHealth services. Conclusions: The search for health information on the internet can be motivated by a range of factors and needs (not studied in this study), and people may experience a range of reactions and feelings following health information searching on the Web. Drawing on prior studies, we categorized reactions as positive and negative reactions. Some participants had negative reactions, which is challenging to resolve and should be taken into consideration by eHealth service providers when designing services (ie,
Journal of Medical Internet Research, Mar 5, 2020
Background: Patients who suffer from different diseases may use different electronic health (eHea... more Background: Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases. Objective: The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources. Methods: Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 7854 (7854/21,083; 37.25%) participants reported to have used some kind of eHealth resource in the last year and suffered (or had suffered) from some kind of specified disease. Logistic regression was used to determine which diseases significantly predicted the use of each eHealth resource. Results: The use of apps was increased among those individuals that (had) suffered from psychological problems (odds ratio [OR] 1.39, 95% CI 1.23-1.56) and cardiovascular diseases (OR 1.12, 95% CI 1.01-1.24) and those part-time workers that (had) suffered from any of the diseases classified as others (OR 2.08, 95% CI 1.35-3.32). The use of search engines for accessing health information increased among individuals who suffered from psychological problems (OR 1.39, 95% CI 1.25-1.55), cancer (OR 1.26, 95% CI 1.11-1.44), or any of the diseases classified as other diseases (OR 1.27, 95% CI 1.13-1.42). Regarding video services, their use for accessing health information was more likely when the participant was a man (OR 1.31, 95% CI 1.13-1.53), (had) suffered from psychological problems (OR 1.70, 95% CI 1.43-2.01), or (had) suffered from other diseases (OR 1.43, 95% CI 1.20-1.71). The factors associated with an increase in the use of social media for accessing health information were as follows: (had) suffered from psychological problems (OR 1.65, 95% CI 1.42-1.91), working part time (OR 1.35, 95% CI 0.62-2.63), receiving disability benefits (OR 1.42, 95% CI 1.14-1.76), having received an upper secondary school education (OR 1.20, 95% CI 1.03-1.38), being a man with a high household income (OR 1.67, 95% CI 1.07-2.60), suffering from cardiovascular diseases and having a high household income (OR 3.39, 95% CI 1.62-8.16), and suffering from respiratory diseases while being retired (OR 1.95, 95% CI 1.28-2.97).
BACKGROUND The World Health Organization recently declared vaccine hesitancy or refusal as a thre... more BACKGROUND The World Health Organization recently declared vaccine hesitancy or refusal as a threat to global health. The novel coronavirus disease 2019 (COVID-19) vaccines have been proven efficacious and central to combatting the pandemic. However, many - including skilled healthcare workers (HCWs) - have been hesitant in taking the vaccines. Conspiracy theories spread on social media may play a central role in fueling vaccine hesitancy. OBJECTIVE This study investigates HCWs' belief in COVID-19 vaccines conspiracy theories (the vaccines could alter one's DNA or genetic information; and that vaccines contain microchips), and trust in government information on COVID-19 vaccines. METHODS Healthcare workers in Ondo-State, Nigeria, representing different healthcare professions, were asked to participate anonymously in an online survey. The participants were asked about their beliefs in two viral conspiracy theories, and their trust in government information on COVID-19 vaccine...
Studies in Health Technology and Informatics, 2021
The role of e-health is increasing worldwide. We surveyed the use of e-health in a large-scale po... more The role of e-health is increasing worldwide. We surveyed the use of e-health in a large-scale population-based study, involving a representative sample of the Norwegian population aged above 40 years. Two-thirds of the health professionals had used search engines, apps, social media or video services for health purposes – while this was the case for approximately half of the non-health professionals.
BACKGROUND Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the 4... more BACKGROUND Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the 4 main noncommunicable diseases. These noncommunicable diseases share 4 modifiable risk factors (tobacco use, harmful use of alcohol, physical inactivity, and unhealthy diet). Short smartphone surveys have the potential to identify modifiable risk factors for individuals to monitor trends. OBJECTIVE We aimed to pilot a smartphone-based information communication technology solution to collect nationally representative data, annually, on 4 modifiable risk factors. METHODS We developed an information communication technology solution with functionalities for capturing sensitive data from smartphones, receiving, and handling data in accordance with general data protection regulations. The main survey comprised 26 questions: 8 on socioeconomic factors, 17 on the 4 risk factors, and 1 about current or previous noncommunicable diseases. For answers to the continuous questions, a keyboard was dis...
<strong>List of articles that were excluded in the full-text review</strong> <stro... more <strong>List of articles that were excluded in the full-text review</strong> <strong>Included studies: Submission &amp; publication dates, funding and declared conflict of interests</strong>
International Journal of Integrated Care
Introduction: The Internet and the social media offer great potential for empowering patients, wh... more Introduction: The Internet and the social media offer great potential for empowering patients, who can obtain updated information, peer support, and Internet-based treatment [1-3]. However, initial research and feedback from some patients have suggested that it is unclear to what degree the social media, including Twitter, overall are beneficial to patients [4, 5]. We therefore examined to what degree tweet content could be perceived of as negative or non-supportive of various disorders. Methods: We used the Twitter search engine to sample 150 random tweets containing either #schizophrenia, #bipolar, or #breastcancer. We classified the tweets as supportive, non-supportive or as a misuse of the disease term. As we examined the tweets, we became particularly interested in their affective content, thinking that this was of importance to how patients would react to the tweets. We therefore sampled 1000 random tweets relating to the same three disorders, and in addition, 1000 random tweets including #depression, #HIV, #AIDS, #COPD, #diabetes, and #Alzheimer, respectively (in total 9000 tweets). We subsequently used the computer program LIWC [6] to analyze the tweets. We focused specifically on the affective categories of ‘negative emotion’, ‘positive emotion’, ‘anxiety,’ and ‘sadness’. Results: Nearly all of the breast cancer tweets were supportive, while a majority of the tweets on schizophrenia and bipolar disorder were non-supportive or in the misuse of term category. Interestingly, the tweets including the terms #depression and #bipolar ranked highest in the categories of ‘negative emotion’, ‘anxiety’, and ‘sadness’, with #schizophrenia in third (‘anxiety’) and fourth place (‘sadness’ and ‘negative emotion’). #AIDS came in third for ‘negative emotion’ and diabetes third for ‘sadness’. For the ‘positive emotion’ category, #breast cancer ranked highest, followed by #depression, #HIV, and #bipolar, suggesting that there are also many tweets with positive affective content related to depression and bipolar disorder. Discussion, limitations, and lessons learned: While this is an initial, relatively small study, it suggests that social media such as Twitter may not consistently be a source of support or comfort to all patient groups, and patients and clinicians should be aware of this. References: 1. Santana S, Lausen B, Bujnowska-Fedak M, et al. Informed citizen and empowered citizen in health: results from an European survey. BMC Fam Pract 2011 Apr 16;12:20. 2. Kummervold PE, Wynn R. Health information accessed on the Internet: the development in 5 European countries. Int J Telemed Appl 2012;2012:297416. 3. Vambheim SM, Wangberg SC, Johnsen JAK, Wynn R. Language use in an internet support group for smoking cessation: development of sense of community. Inform Health Soc Care 2013;38:67-78. 4. DeAndrea DC, Anthony JC. Online peer support for mental health problems in the United States: 2004-2010. Psychol Med 2013;43:2277-88. 5. Oyeyemi SO, Gabarron E, Wynn R. Ebola, Twitter, and misinformation: a dangerous combination? BMJ 2014;349:g6178. 6. Pennebaker JW, Chung CK, Ireland M, Gonzales A, Booth RJ. The development and psychometric properties of LIWC2007. Austin, TX, LIWC. Net, 2007. Available at http://www.liwc.net/LIWC2007LanguageManual.pdf.
BACKGROUND The Internet is being widely used for seeking health information. However, there is no... more BACKGROUND The Internet is being widely used for seeking health information. However, there is no consensus on what impact this behavior has on the use of health care services. Therefore, a better understanding of the impact of health information seeking on the use of health care services is needed. OBJECTIVE The study aims to examine the effect of health information seeking via the Internet on doctor visits. METHODS A cross-sectional health survey data were collected in the Tromsø 7 study. The study participants are individuals aged 40 years and above and live in Tromsø, Norway. Controlling for demographic, socioeconomic status, and health status, logistic regression models were developed to examine the effect of online health information seeking on doctor visits, decisions to visit a doctor, and decisions not to visit a doctor. RESULTS The survey had 65% response rate, and 18,197 participants were included in the study. Use of web search engines (OR = 1.63, 95%CI = 1.49, 1.78) and...
Bulletin of the World Health Organization
BMJ Open Gastroenterology
BackgroundIt remains unclear whether or which prediagnostic lifestyle and dietary factors influen... more BackgroundIt remains unclear whether or which prediagnostic lifestyle and dietary factors influence colorectal cancer (CRC) survival following diagnosis. This study used competing mortality risks analysis to evaluate the association between these factors and CRC survival.MethodsA total of 96 889 cancer-free participants of the Norwegian Women and Cancer Study completed the study’s baseline questionnaire on lifestyle and dietary factors between 1996 and 2004. Of the 1861 women who subsequently developed CRC, 550 had CRC as the cause of death, while 110 had a non-CRC cause of death. We used multiple imputation to handle missing data. We performed multivariable competing mortality risks analyses to determine the associations between prediagnostic lifestyle and dietary factors and CRC survival. Cause-specific HRs were estimated by Cox regression and subdistribution HRs were estimated by the Fine-Gray regression with corresponding 95% CIs.ResultsFollowing multivariable adjustment, a pred...
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Papers by Sunday Oluwafemi Oyeyemi