Dataset Information

Impact of Illness on Electronic Health Use (The Seventh Tromso Study - Part 2): Population-Based Questionnaire Study.

ABSTRACT: 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). CONCLUSIONS:Our findings show that different diseases are currently associated with the use of different eHealth resources. This knowledge is useful for those who plan eHealth interventions as they can take into account which type of eHealth resource may be used for gaining the attention of the different user groups.

SUBMITTER: Marco-Ruiz L

PROVIDER: S-EPMC7082738 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Impact of Illness on Electronic Health Use (The Seventh Tromsø Study - Part 2): Population-Based Questionnaire Study.

Marco-Ruiz Luis L Wynn Rolf R Oyeyemi Sunday Oluwafemi SO Budrionis Andrius A Yigzaw Kassaye Yitbarek KY Bellika Johan Gustav JG

Journal of medical Internet research 20200305 3

<h4>Background</h4>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.<h4>Objective</h4>The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources.<h4>Methods</h4>Data from the seventh survey of the ...[more]

PMID: 32134390

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Project description: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 (OR 1.58; 95% CI 1.47-1.68), of younger age (40-49 year age group: OR 4.28, 95% CI 3.63-5.04), with a higher education (tertiary/long: OR 3.77, 95% CI 3.40-4.19), and a higher income (>1 million kr [US $100,000]: OR 2.19, 95% CI 1.77-2.70) all positively predicted the use of eHealth services. Not living with a spouse (OR 1.14, 95% CI 1.04-1.25), having seen a general practitioner (GP) in the last year (OR 1.66, 95% CI 1.53-1.80), and having had some disease (such as heart disease, cancer, asthma, etc; OR 1.29, 95% CI 1.18-1.41) also positively predicted eHealth use. Self-rated health status did not significantly influence eHealth use. Taking some action following eHealth use was predicted with the variables of being a woman (OR 1.16, 95% CI 1.07-1.27), being younger (40-49 year age group: OR 1.72, 95% CI 1.34-2.22), having a higher education (tertiary/long: OR 1.65, 95% CI 1.42-1.92), having seen a GP in the last year (OR 1.58, 95% CI 1.41-1.77), and having ever had a disease (such as heart disease, cancer or asthma; OR 1.26, 95% CI 1.14-1.39). CONCLUSIONS:eHealth appears to be an essential supplement to traditional health services for those aged above 40 years old, and especially so for the more resourceful. Being a woman, being younger, having higher education, having had a disease, and having seen a GP in the last year all positively predicted using the internet to get health information and taking some action based on this information.

Project description:BACKGROUND:Non-prescription purchase of antibiotics is undesirable and has not recently been investigated in a representative population in a high-income low-use country during travel abroad. This study examined self-reported prevalence of antibiotic purchase abroad with and without prescription among participants reporting international travel in a general adult population in Norway, and the associations with socio-demographic, lifestyle and health factors. METHODS:We analysed questionnaire-data from 19995 participants (10470 women) ?40 years in the population-based Tromsø Study 7, 2015-2016. Data from the Norwegian Prescription Database were used to examine antibiotic use in Norway. We calculated adjusted odds ratios (AOR) for "travel abroad", "any antibiotic purchase abroad", and "antibiotic purchase abroad with" and "without prescription" using multivariable logistic regression. RESULTS:Over half (55.0%, 95%CI 54.3-55.7%) participants reported travel abroad of >1 week duration in the past year. Travelers were more likely than non-travelers to be women (AOR = 2.02, 95%CI 1.42-2.88%) and report high education/income, childhood mostly lived abroad, healthy lifestyle, and good/excellent self-rated health. In total, 17904 travel episodes to 148 countries were reported. Altogether, 3.7% (95% CI 3.4%-4.1%) of travelers had purchased antibiotic abroad in the past year. Non-prescription purchase (1.5%, 95% CI 1.3-1.7) was associated with younger age, being female (AOR 1.41, 1.0-1.97), number of travels (reference: one episode, two: AOR = 1.82, 1.25-2.67, three: 2.60, 1.58-4.28, four: 3.10, 1.40-6.36 and ?five: 4.70, 2.30-9.62), occurrences of diarrhoea (one: 2.42, 1.50-3.93 and ?two: 3.08, 1.29-7.35), and antibiotic use in Norway in the past year (1.84, 1.29-2.62), whereas purchase with prescription (2.4%, 2.1-2.7) was associated with low income, growing-up abroad, recent hospital admission, additionally including number of travels/diarrhoea, and antibiotic use in Norway. Thailand (10.7%, 95% CI 7.8-14.3), Turkey (5.5%, 3.8-7.8) and Spain (3.6%, 3.0-4.3) were the countries most commonly associated with any antibiotic purchase. About two in five travelers who bought antibiotics in Thailand had done so without prescription, three in five in Turkey, and less than one in three in Spain. CONCLUSION:Overall, a small proportion of travelers had bought antibiotics abroad in the past year. Low prevalence of non-prescription purchase may be explained by awareness of the risks associated with self-medication, cultural views, unawareness of the non-prescription availability, and/or few infections. Divergent predictors for purchase abroad with versus without prescription may suggest different reasons for these practices.

Project description:BACKGROUND:The eHealth Impact Questionnaire (eHIQ) provides a standardized method to measure attitudes of electronic health (eHealth) users toward eHealth. It has previously been validated in a population of eHealth users in the United Kingdom and consists of 2 parts and 5 subscales. Part 1 measures attitudes toward eHealth in general and consists of the subscales attitudes towards online health information (5 items) and attitudes towards sharing health experiences online (6 items). Part 2 measures the attitude toward a particular eHealth application and consists of the subscales confidence and identification (9 items), information and presentation (8 items), and understand and motivation (9 items). OBJECTIVE:This study aimed to translate and validate the eHIQ in a Dutch population of eHealth users. METHODS:The eHIQ was translated and validated in accordance with the COnsensus-based Standards for the selection of health status Measurement INstruments criteria. The validation comprised 3 study samples, with a total of 1287 participants. Structural validity was assessed using confirmatory factor analyses and exploratory factor analyses (EFAs; all 3 samples). Internal consistency was assessed using hierarchical omega (all 3 samples). Test-retest reliability was assessed after 2 weeks, using 2-way intraclass correlation coefficients (sample 1). Measurement error was assessed by calculating the smallest detectable change (sample 1). Convergent and divergent validity were assessed using correlations with the remaining measures (all 3 samples). A graded response model was fit, and item information curves were plotted to describe the information provided by items across item trait levels (all 3 samples). RESULTS:The original factor structure showed a bad fit in all 3 study samples. EFAs showed a good fit for a modified factor structure in the first study sample. This factor structure was subsequently tested in samples 2 and 3 and showed acceptable to good fits. Internal consistency, test-retest reliability, convergent validity, and divergent validity were acceptable to good for both the original as the modified factor structure, except for test-retest reliability of one of the original subscales and the 2 derivative subscales in the modified factor structure. The graded response model showed that some items underperformed in both the original and modified factor structure. CONCLUSIONS:The Dutch version of the eHIQ (eHIQ-NL) shows a different factor structure compared with the original English version. Part 1 of the eHIQ-NL consists of 3 subscales: attitudes towards online health information (5 items), comfort with sharing health experiences online (3 items), and usefulness of sharing health experiences online (3 items). Part 2 of the eHIQ-NL consists of 3 subscales: motivation and confidence to act (10 items), information and presentation (13 items), and identification (3 items).

Project description:BackgroundAlthough, studies from Norway indicate a reduction in dental caries experience, in Northern-Norway this non-communicable oral condition is still prevalent. There is conflicting evidence of presence of social inequalities in dental caries in an adult population. Therefore, the aim of this study was to assess an association between educational level and dental caries experience in adults in urban Tromsø municipality, Northern-Norway, using The World Health Organization (WHO) Commission on Social Determinants of Health (CSDH) framework of health determinants.MethodsData from 3752 participants having recorded dental caries status and educational level in the seventh survey of the Tromsø Study: Tromsø7 were included. Dental status was examined clinically as decayed-, missing-, filled-teeth (DMFT score). For statistical analyses DMFT score was grouped into lower (DMFT < 19) and higher (DMFT ≥ 20). Educational level was obtained from a questionnaire and categorized as primary/partly secondary education, upper secondary education, tertiary education, short and tertiary education, long. Data on social and intermediary determinants was also self-reported. Univariable and multivariable binary logistic regression analyses were applied.ResultThis study included 1939 (52%) women and the mean age of the participants was 57.11. The mean DMFT score was 18.03. The odds of having higher DMFT score followed a gradient based on educational level. Participants who reported lower than secondary education had 2.06 -fold increased odds of having higher DMFT score than those with tertiary education, long (OR: 2.06, 95% CI: 1.50-2.83). Those with upper secondary education had 60% higher odds of having higher DMFT score (OR: 1.60, 95% CI: 1.21-2.11), and those with tertiary education, short had 66% higher odds of having higher DMFT score (OR: 1.66, 95% CI: 1.24-2.22).ConclusionThe current cross-sectional study suggested an educational gradient in dental caries experience in an adult population of Northern- Norway. Further studies validating our results and investigating mechanisms of educational inequalities in oral health are warranted.

Project description:BACKGROUND: Emerging evidence indicates an association between mental illness and poor quality of physical health care. To test this, we compared mental health clients (MHCs) with non-MHCs on potentially preventable hospitalisations (PPHs) as an indicator of the quality of primary care received. METHODS: Population-based retrospective cohort study of 139,208 MHCs and 294,180 matched non-MHCs in Western Australia from 1990 to 2006, using linked data from electoral roll registrations, mental health registry (MHR) records, hospital inpatient discharges and deaths. We used the electoral roll data as the sampling frame for both cohorts to enhance internal validity of the study, and the MHR to separate MHCs from non-MHCs. Rates of PPHs (overall and by PPH category and medical condition) were compared between MHCs, category of mental disorders and non-MHCs. Multivariate negative binomial regression analyses adjusted for socio-demographic factors, case mix and the year at the start of follow up due to dynamic nature of study cohorts. RESULTS: PPHs accounted for more than 10% of all hospital admissions in MHCs, with diabetes and its complications, adverse drug events (ADEs), chronic obstructive pulmonary disease (COPD), convulsions and epilepsy, and congestive heart failure being the most common causes. Compared with non-MHCs, MHCs with any mental disorders were more likely to experience a PPH than non-MHCs (overall adjusted rate ratio (ARR) 2.06, 95% confidence interval (CI) 2.03-2.09). ARRs of PPHs were highest for convulsions and epilepsy, nutritional deficiencies, COPD and ADEs. The ARR of a PPH was highest in MHCs with alcohol/drug disorders, affective psychoses, other psychoses and schizophrenia. CONCLUSIONS: MHCs have a significantly higher rate of PPHs than non-MHCs. Improving primary and secondary prevention is warranted in MHCs, especially at the primary care level, despite there may be different thresholds for admission in people with established physical disease that is influenced by whether or not they have comorbid mental illness.

Dataset Information

Impact of Illness on Electronic Health Use (The Seventh Tromso Study - Part 2): Population-Based Questionnaire Study.

Publications

Impact of Illness on Electronic Health Use (The Seventh Tromsø Study - Part 2): Population-Based Questionnaire Study.

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