- Klíčová slova
- Mediately,
- MeSH
- digitální zdraví * MeSH
- lidé MeSH
- mobilní aplikace MeSH
- nádory prsu diagnóza MeSH
- nádory terapie MeSH
- protinádorové látky imunologicky aktivní aplikace a dávkování škodlivé účinky MeSH
- telemedicína MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- rozhovory MeSH
BACKGROUND: Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences. OBJECTIVE: This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS). METHODS: A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17). RESULTS: Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features. CONCLUSIONS: When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.
- MeSH
- deprese * psychologie MeSH
- dospělí MeSH
- epilepsie * psychologie MeSH
- kvalitativní výzkum * MeSH
- lidé středního věku MeSH
- lidé MeSH
- mobilní aplikace MeSH
- nositelná elektronika MeSH
- pacientova volba psychologie statistika a číselné údaje MeSH
- roztroušená skleróza * psychologie MeSH
- senioři MeSH
- telemedicína MeSH
- vizualizace dat MeSH
- zjišťování skupinových postojů * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Background: Diabetes mellitus (DM) is one of the most prevalent metabolic disorders, with type 2 DM being the most common form. It ranks as the sixth-leading cause of death worldwide, yet medication adherence and self-care remain low. Given that knowledge significantly influences these outcomes, this paper aims to evaluate the effect of mobile phone-assisted health education programs on patients with type 2 DM. Methods: A comprehensive literature search was conducted using databases such as Scopus, Web of Science, PubMed, and EBSCOhost, employing keywords relevant to the research topic. The research question was structured using the PICOS framework: (1) Population: patients with type 2 diabetes mellitus; (2) Intervention: health education via mobile phone; (3) Comparison: conventional health education; (4) Outcome: diabetes self-management, glycemic control, and medication adherence; (5) Study design: randomized controlled trials. Results: The search identified approximately 678 articles discussing health education interventions using mobile phones. After a thorough screening process, 10 articles met the inclusion criteria. The findings suggest that mobile phone-based education interventions can enhance adherence to diabetes self-management, improve glycemic control, and positively impact clinical parameters such as lipid levels, body mass index, blood pressure, and medication adherence. Conclusion: Health education interventions delivered by healthcare professionals through mobile phones can significantly improve self-care management and prevent complications in patients with type 2 diabetes who maintain controlled blood glucose levels.
Background: Telehealth is electronic information and telecommunications technology for medical personnel and doctors to handle patient health. This electronic information can include digital images, videos, or text files stored on a computer. Telehealth is beneficial for improving the general psychology of chronic patients. However, no assessment of the impact of telehealth on individuals suffering from chronic obstructive pulmonary disease has been done. As a result, in order to assess the impact of telehealth treatments on the quality of life of patients with chronic obstructive pulmonary disease, researchers reviewed the literature. Methods: The inclusion criteria were articles published in open access in English between 2014 and 2023, with the full text of the original article. COPD patients were the participants in this study, the intervention was telehealth, the outcome was quality of life, and the research design was a randomized controlled trial. This review has been registered on Prospero, registration number CRD42024496062. Results: The review was carried out in five databases: PubMed, Scopus, Proquest, Emerald Insight, and ScienceDirect. Articles that met inclusion criteria were assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Data was synthesized using Review Manager version 5.4. Ten RCT studies (1,297 patients) met the inclusion criteria. This review showed that there was a significant effect on the quality of life after intervention using telehealth, with moderate heterogeneity of 70% [SMD = 0.27 CI 95%, (0.03, 0.50), (P 0.02)]. Conclusion: Telehealth interventions can improve patients' quality of life. Telehealth can be integrated into the medical service system to treat chronic obstructive pulmonary disease patients.
BACKGROUND: Mobile Ecological Momentary Assessment (EMA) is increasingly used to gather intensive, longitudinal data on behavioral nutrition, physical activity and sedentary behavior and their underlying determinants. However, a relevant concern is the risk of non-random non-compliance with mobile EMA protocols, especially in older adults. This study aimed to examine older adults' compliance with mobile EMA in health behavior studies according to participant characteristics, and prompt timing, and to provide recommendations for future EMA research. METHODS: Data of four intensive longitudinal observational studies employing mobile EMA to understand health behavior, involving 271 community-dwelling older adults (M = 71.8 years, SD = 6.8; 52% female) in Flanders, were pooled. EMA questionnaires were prompted by a smartphone application during specific time slots or events. Data on compliance (i.e. information whether a participant answered at least one item following the prompt), time slot (morning, afternoon or evening) and day (week or weekend day) of each prompt were extracted from the EMA applications. Participant characteristics, including demographics, body mass index, and smartphone ownership, were collected via self-report. Descriptive statistics of compliance were computed, and logistic mixed models were run to examine inter- and intrapersonal variability in compliance. RESULTS: EMA compliance averaged 77.5%, varying from 70.0 to 86.1% across studies. Compliance differed among subgroups and throughout the day. Age was associated with lower compliance (OR = 0.96, 95%CI = 0.93-0.99), while marital/cohabiting status and smartphone ownership were associated with higher compliance (OR = 1.83, 95%CI = 1.21-2.77, and OR = 4.43, 95%CI = 2.22-8.83, respectively). Compliance was lower in the evening than in the morning (OR = 0.82, 95%CI = 0.69-0.97), indicating non-random patterns that could impact study validity. CONCLUSIONS: The findings of this study shed light on the complexities surrounding compliance with mobile EMA protocols among older adults in health behavior studies. Our analysis revealed that non-compliance within our pooled dataset was not completely random. This non-randomness could introduce bias into study findings, potentially compromising the validity of research findings. To address these challenges, we recommend adopting tailored approaches that take into account individual characteristics and temporal dynamics. Additionally, the utilization of Directed Acyclic Graphs, and advanced statistical techniques can help mitigate the impact of non-compliance on study validity.
- MeSH
- adherence pacienta * MeSH
- chytrý telefon MeSH
- cvičení * MeSH
- index tělesné hmotnosti MeSH
- lidé MeSH
- longitudinální studie MeSH
- mobilní aplikace MeSH
- okamžité posouzení v přirozeném prostředí * MeSH
- průzkumy a dotazníky MeSH
- sedavý životní styl MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- zdravé chování * MeSH
- zpráva o sobě MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- MeSH
- Aspirin aplikace a dávkování terapeutické užití MeSH
- chronická renální insuficience farmakoterapie MeSH
- diabetes mellitus 2. typu * prevence a kontrola terapie MeSH
- klinická studie jako téma MeSH
- klopidogrel aplikace a dávkování terapeutické užití MeSH
- kontinuální monitorování glukózy MeSH
- koronární angioplastika MeSH
- lidé MeSH
- mobilní aplikace MeSH
- spironolakton aplikace a dávkování terapeutické užití MeSH
- životní styl MeSH
- Check Tag
- lidé MeSH
- Klíčová slova
- aplikace EULAR, aplikace ACR, aplikace RheumaHelper,
- MeSH
- dospělí MeSH
- lidé MeSH
- mobilní aplikace * trendy MeSH
- psoriatická artritida * diagnóza farmakoterapie klasifikace MeSH
- revmatologie * MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- kazuistiky MeSH
- zprávy MeSH
