| 1. |
- Aida, Azusa, et al.
(författare)
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eHealth Delivery of Educational Content Using Selected Visual Methods to Improve Health Literacy on Lifestyle-Related Diseases : Literature Review
- 2020
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Ingår i: JMIR mHealth and uHealth. - : JMIR Publications Inc.. - 2291-5222. ; 8:12
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: Lifestyle-related diseases, such as stroke, heart disease, and diabetes, are examples of noncommunicable diseases. Noncommunicable diseases are now the leading cause of death in the world, and their major causes are lifestyle related. The number of eHealth interventions is increasing, which is expected to improve individuals' health literacy on lifestyle-related diseases.OBJECTIVE: This literature review aims to identify existing literature published in the past decade on eHealth interventions aimed at improving health literacy on lifestyle-related diseases among the general population using selected visual methods, such as educational videos, films, and movies.METHODS: A systematic literature search of the PubMed database was conducted in April 2019 for papers written in English and published from April 2, 2009, through April 2, 2019. A total of 538 papers were identified and screened in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. Finally, 23 papers were included in this review.RESULTS: The 23 papers were characterized according to study characteristics (author and year of publication, study design and region where the study was conducted, study objective, service platform, target disease and participant age, research period, outcomes, and research method); the playback time of the educational videos, films, and movies; and the evaluation of the study's impacts on health literacy. A total of 7 studies compared results using statistical methods. Of these, 5 studies reported significant positive effects of the intervention on health literacy and health-related measures (eg, physical activity, body weight). Although most of the studies included educational content aimed at improving health literacy, only 7 studies measured health literacy. In addition, only 5 studies assessed literacy using health literacy measurement tools.CONCLUSIONS: This review found that the provision of educational content was satisfactory in most eHealth studies using selected visual methods, such as videos, films, and movies. These findings suggest that eHealth interventions influence people's health behaviors and that the need for this intervention is expected to increase. Despite the need to develop eHealth interventions, standardized measurement tools to evaluate health literacy are lacking. Further research is required to clarify acceptable health literacy measurements.
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| 2. |
- Aida, Azusa, et al.
(författare)
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Using mHealth to Provide Mobile App Users With Visualization of Health Checkup Data and Educational Videos on Lifestyle-Related Diseases : Methodological Framework for Content Development
- 2020
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Ingår i: JMIR mHealth and uHealth. - : JMIR Publications Inc.. - 2291-5222. ; 8:10
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The number of people with lifestyle-related diseases continues to increase worldwide. Improving lifestyle behavior with health literacy may be the key to address lifestyle-related diseases. The delivery of educational videos using mobile health (mHealth) services can replace the conventional way of educating individuals, and visualization can replace the provision of health checkup data. OBJECTIVE: This paper aimed to describe the development of educational content for MIRAMED, a mobile app aimed at improving users' lifestyle behaviors and health literacy for lifestyle-related diseases. METHODS: All videos were based on a single unified framework to provide users with a consistent flow of information. The framework was later turned into a storyboard. The final video contents were created based on this storyboard and further discussions with leading experts and specialist physicians on effective communication with app users about lifestyle-related diseases. RESULTS: The app uses visualization of personal health checkup data and educational videos on lifestyle-related diseases based on the current health guidelines, scientific evidence, and expert opinions of leading specialist physicians in the respective fields. A total of 8 videos were created for specific lifestyle-related diseases affecting 8 organs: (1) brain-cerebrovascular disorder, (2) eyes-diabetic retinopathy, (3) lungs-chronic obstructive pulmonary disease, (4) heart-ischemic heart disease, (5) liver-fatty liver, (6) kidneys-chronic kidney disease (diabetic kidney disease), (7) blood vessels-peripheral arterial disease, and (8) nerves-diabetic neuropathy. CONCLUSIONS: Providing enhanced mHealth education using novel digital technologies to visualize conventional health checkup data and lifestyle-related diseases is an innovative strategy. Future studies to evaluate the efficacy of the developed content are planned.
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| 3. |
- Hara, Konan, et al.
(författare)
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Association measures of claims-based algorithms for common chronic conditions were assessed using regularly collected data in Japan
- 2018
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Ingår i: Journal of Clinical Epidemiology. - : Elsevier BV. - 1878-5921 .- 0895-4356. ; 99, s. 84-95
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Although claims data are widely used in medical research, their ability to identify persons' health-related conditions has not been fully justified. We assessed the validity of claims-based algorithms (CBAs) for identifying people with common chronic conditions in a large population using annual health screening results as the gold standard.STUDY DESIGN AND SETTING: Using a longitudinal claims database (n=523,267) combined with annual health screening results, we defined the people with hypertension, diabetes, and/or dyslipidemia by applying health screening results as their gold standard, and compared them against various CBAs.RESULTS: By using diagnostic and medication code-based CBAs, sensitivity and specificity were 74.5% (95% Confidence Interval [CI], 74.2-74.8%) and 98.2% (98.2-98.3%) for hypertension, 78.6% (77.3-79.8%) and 99.6% (99.5-99.6%) for diabetes, and 34.5% (34.2-34.7%) and 97.2% (97.2-97.3%) for dyslipidemia, respectively. Sensitivity did not decrease substantially for hypertension (65.2% [95% CI, 64.9-65.5%]) and diabetes (73.0% [71.7-74.2%]) when we used the same CBAs without limiting to primary care settings.CONCLUSION: We employed regularly collected data to obtain CBA association measures which are applicable to a wide range of populations. Our framework can be a basis of the validity assessment of CBAs for identifying persons' health-related conditions with regularly collected data.
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| 4. |
- Hara, Konan, et al.
(författare)
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Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods
- 2021
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 16:9, s. 1-19
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Tidskriftsartikel (refereegranskat)abstract
- Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims-based algorithms (CBAs) are highly dependent on the knowledge level and not necessarily optimized for target conditions. We investigated whether machine learning methods can supplement researchers' knowledge of target conditions in building CBAs. Retrospective cohort study using a claims database combined with annual health check-up results of employees' health insurance programs for fiscal year 2016-17 in Japan (study population for hypertension, N = 631,289; diabetes, N = 152,368; dyslipidemia, N = 614,434). We constructed CBAs with logistic regression, k-nearest neighbor, support vector machine, penalized logistic regression, tree-based model, and neural network for identifying patients with three common chronic conditions: hypertension, diabetes, and dyslipidemia. We then compared their association measures using a completely hold-out test set (25% of the study population). Among the test cohorts of 157,822, 38,092, and 153,608 enrollees for hypertension, diabetes, and dyslipidemia, 25.4%, 8.4%, and 38.7% of them had a diagnosis of the corresponding condition. The areas under the receiver operating characteristic curve (AUCs) of the logistic regression with/without subject-matter knowledge about the target condition were .923/.921 for hypertension, .957/.938 for diabetes, and .739/.747 for dyslipidemia. The logistic lasso, logistic elastic-net, and tree-based methods yielded AUCs comparable to those of the logistic regression with subject-matter knowledge: .923-.931 for hypertension; .958-.966 for diabetes; .747-.773 for dyslipidemia. We found that machine learning methods can attain AUCs comparable to the conventional knowledge-based method in building CBAs.
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| 5. |
- Ikesu, Ryo, et al.
(författare)
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Association of managerial position with cardiovascular risk factors : A fixed-effects analysis for japanese employees
- 2021
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Ingår i: Scandinavian Journal of Work, Environment and Health. - : Scandinavian Journal of Work, Environment and Health. - 0355-3140 .- 1795-990X. ; 47:6, s. 425-434
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Although higher occupational classes have been reported to be associated with better health, researchers do not fully understand whether such associations derive from the position or individual characteristics of the person in that position. We examined the association between being a manager and cardiovascular disease (CVD) risk factors using unique panel data in Japan that annually observed employees’ occupational class and health conditions. Methods We analyzed data for 45 888 observations from a Japanese company from 2013 through 2017. The association between being a manager and CVD risk factors (metabolic risks and health-related behaviors) were evaluated using simple pooled cross-sectional analyses with adjustment for age, sex, marital status, and overtime-working hours. We further incorporated employee-level fixed-effects into the models to examine whether the associations were subject to individual time-invariant factors. Results The pooled cross-sectional analyses showed that, compared to non-managers, managers had 2.0 mg/dl lower low density lipoprotein cholesterol (LDL-C) level, 1.4 mmHg-lower systolic blood pressure, and 0.2 kg/m2 lower body mass index (BMI). After adjusting for employee-level fixed-effects, being a manager was associated with a significantly 2.2 mg/dl higher LDL-C level. However, the associations between an individual’s management status and blood pressure or BMI were not significant. Furthermore, managers were 5.5% less likely to exercise regularly and 6.1% less likely to report sufficient sleep in the fixed-effects models, although the pooled cross-sectional analyses did not demonstrate these significant associations. Conclusions Our findings suggest the necessity of considering these unfavorable health risks associated with being promoted to a manager.
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| 6. |
- Miyashita, Hirotaka, et al.
(författare)
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Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns : Observational Pilot Study
- 2020
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Ingår i: JMIR Formative Research. - : JMIR Publications Inc.. - 2561-326X. ; 4:6
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Measuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion.OBJECTIVE: The purpose of this pilot study was to investigate the association between specific sleep measures and the change of emotional status based on voice patterns measured before and after nighttime sleep.METHODS: A total of 20 volunteers were recruited. Their objective sleep measures were obtained using a portable single-channel electroencephalogram system, and their emotional status was assessed using MIMOSYS, a smartphone app analyzing voice patterns. The study analyzed 73 sleep episodes from 18 participants for the association between the change of emotional status following nighttime sleep (Δvitality) and specific sleep measures.RESULTS: A significant association was identified between total sleep time and Δvitality (regression coefficient: 0.036, P=.008). A significant inverse association was also found between sleep onset latency and Δvitality (regression coefficient: -0.026, P=.001). There was no significant association between Δvitality and sleep efficiency or number of awakenings.CONCLUSIONS: Total sleep time and sleep onset latency are significantly associated with Δvitality, which indicates a change of emotional status following nighttime sleep. This is the first study to report the association between the emotional status assessed using voice pattern and specific sleep measures.
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| 7. |
- Miyashita, Hirotaka, et al.
(författare)
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The Association Between Hemoglobin Upswing in the Reference Range and Sleep Apnea Syndrome
- 2020
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Ingår i: Sleep and Vigilance. - : Springer Science and Business Media LLC. - 2510-2265. ; 4:2, s. 205-212
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Tidskriftsartikel (refereegranskat)abstract
- PurposeSleep apnea syndrome (SAS) is a relatively common disorder, but many patients with SAS are still undiagnosed. Using Japanese annual health check and medical claims data, we analyzed the association between hemoglobin upswing, defined as an increase in hemoglobin level within the reference range, and the incidence of SAS.MethodsIn this study, we used the Japan Medical Database Center (JMDC) annual health check and medical claims data of 351,930 male individuals aged 40−59 who had their hemoglobin concentration checked in 2014. We initially identified the reference range of hemoglobin level based on the mean and the standard deviation of hemoglobin concentration in this population. We examined the effect of hemoglobin upswing on the incidence of SAS using Cox proportional hazards models.ResultsThe hemoglobin upswing was defined as a change greater than 1.19 g/dL in the reference range of 13.1 to 17.2 g/dL. During a mean follow-up period of approximately 1285 days, 1.9% of the individuals with hemoglobin upswing were diagnosed with SAS, while 1.6% of those without hemoglobin upswing were diagnosed with SAS. The hazard ratio of hemoglobin upswing to the incidence of SAS was 1.21 (95% CI; 1.01–1.44, p = 0.04).ConclusionWe herein revealed the association between hemoglobin upswing and the incidence of SAS in a middle-aged male population. A statistically significant increase in hemoglobin concentration even in the reference range should be paid attention to as it may indicate the presence of SAS.
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| 8. |
- Pham, Helena, et al.
(författare)
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Sleep Satisfaction May Modify the Association between Metabolic Syndrome and BMI, Respectively, and Occupational Stress in Japanese Office Workers
- 2022
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI AG. - 1661-7827 .- 1660-4601. ; 19:9
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Tidskriftsartikel (refereegranskat)abstract
- The association between obesity and psychological stress is ambiguous. The aim is to investigate the association between metabolic syndrome (MetS) and body mass index (BMI), respectively, with occupational stress among Japanese office workers. The study is a secondary analysis of the intervention group from a randomized controlled trial. There are 167 participants included in the analysis. Occupational stress is self-reported using the Brief Job Stress Questionnaire (BJSQ). BMI and the classification of MetS/pre-MetS was based on the participants’ annual health check-up data. The primary exposure is divided into three groups: no MetS, pre-MetS, and MetS in accordance with Japanese guidelines. The secondary exposure, BMI, remains as a continuous variable. Multiple linear regression is implemented. Sensitivity analyses are stratified by sleep satisfaction. Pre-MetS is significantly associated with occupational stress (7.84 points; 95% CI: 0.17, 15.51). Among participants with low sleep satisfaction, pre-MetS (14.09 points; 95% CI: 1.71, 26.48), MetS (14.72 points; 95% CI: 0.93, 28.51), and BMI (2.54 points; 95% CI: 0.05, 4.99) are all significantly associated with occupational stress. No significant associations are observed in participants with high sleep satisfaction. The findings of this study indicate that sleep satisfaction may modify the association between MetS and BMI, respectively, and occupational stress.
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| 9. |
- Sjöland, Olivia, et al.
(författare)
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Associations of Subjective Sleep Quality with Wearable Device-Derived Resting Heart Rate During REM Sleep and Non-REM Sleep in a Cohort of Japanese Office Workers
- 2024
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Ingår i: Nature and Science of Sleep. - 1179-1608. ; 16, s. 867-877
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Tidskriftsartikel (refereegranskat)abstract
- Background: Associations between subjective sleep quality and stage-specific heart rate (HR) may have important clinical relevance when aiming to optimize sleep and overall health. The majority of previously studies have been performed during short periods under laboratory-based conditions. The aim of this study was to investigate the associations of subjective sleep quality with heart rate during REM sleep (HR REMS) and non-REM sleep (HR NREMS) using a wearable device (Fitbit Versa). Methods: This is a secondary analysis of data from the intervention group of a randomized controlled trial (RCT) performed between December 3, 2018, and March 2, 2019, in Tokyo, Japan. The intervention group consisted of 179 Japanese office workers with metabolic syndrome (MetS), Pre-MetS or a high risk of developing MetS. HR was collected with a wearable device and sleep quality was assessed with a mobile application where participants answered The St. Mary’s Hospital Sleep Questionnaire. Both HR and sleep quality was collected daily for a period of 90 days. Associations of between-individual and within-individual sleep quality with HR REMS and HR NREMS were analyzed with multi-level model regression in 3 multivariate models. Results: The cohort consisted of 92.6% men (n=151) with a mean age (± standard deviation) of 44.1 (±7.5) years. A non-significant inverse between-individual association was observed for sleep quality with HR REMS (HR REMS −0.18; 95% CI −0.61, 0.24) and HR NREMS (HR NREMS −0.23; 95% CI −0.66, 0.21), in the final multivariable adjusted models; a statistically significant inverse within-individual association was observed for sleep quality with HR REMS (HR REMS −0.21 95% CI −0.27, −0.15) and HR NREMS (HR NREMS −0.21 95% CI −0.27, −0.14) after final adjustments for covariates. Conclusion: The present study shows a statistically significant within-individual association of subjective sleep quality with HR REMS and HR NREMS. These findings emphasize the importance of considering sleep quality on the individual level. The results may contribute to early detection and prevention of diseases associated with sleep quality which may have important implications on public health given the high prevalence of sleep disturbances in the population.
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| 10. |
- Staffini, Alessio, et al.
(författare)
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A Disentangled VAE-BiLSTM Model for Heart Rate Anomaly Detection
- 2023
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Ingår i: Bioengineering. - 2306-5354. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- Cardiovascular diseases (CVDs) remain a leading cause of death globally. According to the American Heart Association, approximately 19.1 million deaths were attributed to CVDs in 2020, in particular, ischemic heart disease and stroke. Several known risk factors for CVDs include smoking, alcohol consumption, lack of regular physical activity, and diabetes. The last decade has been characterized by widespread diffusion in the use of wristband-style wearable devices which can monitor and collect heart rate data, among other information. Wearable devices allow the analysis and interpretation of physiological and activity data obtained from the wearer and can therefore be used to monitor and prevent potential CVDs. However, these data are often provided in a manner that does not allow the general user to immediately comprehend possible health risks, and often require further analytics to draw meaningful conclusions. In this paper, we propose a disentangled variational autoencoder (β-VAE) with a bidirectional long short-term memory network (BiLSTM) backend to detect in an unsupervised manner anomalies in heart rate data collected during sleep time with a wearable device from eight heterogeneous participants. Testing was performed on the mean heart rate sampled both at 30 s and 1 min intervals. We compared the performance of our model with other well-known anomaly detection algorithms, and we found that our model outperformed them in almost all considered scenarios and for all considered participants. We also suggest that wearable devices may benefit from the integration of anomaly detection algorithms, in an effort to provide users more processed and straightforward information.
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