Mobile applications for data collection in longitudinal epidemiological studies: Possibilities, problems and perspectives identified by a scoping review (Preprint)

BACKGROUND The broad availability of smartphones and the number of health applications (health apps) in app stores have risen in recent years. Health apps have benefits for individuals to monitor their health as well as for the researcher to collect data in population-based, clinical, and observational studies. Although the number of health apps on the global app market is huge and its potential seems to be high, smartphone app-based questionnaires for collecting patient-related data have not played an important role so far. OBJECTIVE This study aims to provide an overview of studies that have collected patient data using an app-based approach, with a particular focus on longitudinal studies. This literature review describes the current state of affairs in terms of the extent to which smartphones have been used for collecting (patient) data for research purposes, and the potentials and challenges associated with this approach. METHODS A scoping review of studies using data collection via apps was conducted. PubMed was used to identify studies describing the utilization of smartphone app questionnaires for collecting data over time. Overall, 17 articles were included in the summary. RESULTS There are only a few studies integrating smartphone apps into data-collection approaches. Studies dealing with the collection of health-related data via smartphone apps have mainly been developed in the field of psychosomatic, neurodegenerative, respiratory, and cardiovascular diseases, as well as malign neoplasm. The study duration for data collection varied from four weeks to twelve months, and the participants’ mean ages ranged from 7 to 69 years. Potential can be seen for real-time information transfer, fast data synchronization from entry to provision (which saves time and increases effectivity), and the possibility of tracking responses longitudinally. Furthermore, smartphone-based data-collection techniques might prevent biases such as reminder bias or mistakes occurring during manual data transfers. In chronic diseases, real-time communication with the physician and early detection of symptoms enable rapid modifications in the management of the disease. CONCLUSIONS The results indicate that using mobile technologies can help to overcome challenges linked with data collection in epidemiological research. However, further feasibility studies need to be conducted in the near future to test the applicability and acceptance of these mobile applications for epidemiological research in various subpopulations. CLINICALTRIAL

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Remote evaluations of violence against women and girls interventions: a rapid scoping review of tools, ethics and safety

BMJ Global Health ◽

10.1136/bmjgh-2021-006780 ◽

2021 ◽

Vol 6 (9) ◽

pp. e006780

Author(s):

Ilana Seff ◽

Luissa Vahedi ◽

Samantha McNelly ◽

Elfriede Kormawa ◽

Lindsay Stark

Keyword(s):

Data Collection ◽

Best Practices ◽

Violence Against Women ◽

Scoping Review ◽

Mobile Applications ◽

Best Practice ◽

Online Surveys ◽

Humanitarian Settings ◽

Telephone Interviews ◽

Women And Girls

Although programmes and policies targeting violence against women and girls (VAWG) have increased in the past decade, there is a paucity of evidence on the effectiveness of these interventions. To expand this evidence base, researchers increasingly employ remote data collection (RDC)—including online surveys, mobile applications and telephone interviews—in their evaluations. Although RDC allows for evaluations without in-person interactions—which are restricted during crises such as the COVID-19 pandemic— information about these methods is necessary to understand their potential usefulness and limitations. This scoping review examines remote evaluations of VAWG interventions to describe the landscape of RDC methods, reflect on safety and ethical considerations, and offer best practices for RDC in VAWG research. Fourteen studies met eligibility criteria, with seven, five, and two studies employing telephone interviews, online surveys, and mobile applications, respectively. Studies commonly stated that participants were asked to use a safe email or device, but the method for verifying such safety was rarely specified. Best practices around safety included creating a ‘quick escape’ button for online data collection to use when another individual was present, explaining to participants how to erase browsing history and application purchases, and asking participants to specify a safe time for researchers to call. Only eight studies established referral pathways for respondents as per best practice. None of the eligible studies took place in low/middle-income countries (LMICs) or humanitarian settings, likely reflecting the additional challenges to using RDC methods in lower resource settings. Findings were used to create a best practice checklist for programme evaluators and Institutional Review Boards using RDC for VAWG interventions. The authors found that opportunities exist for researchers to safely and effectively use RDC methodologies to gather VAWG data, but that further study is needed to gauge the feasibility of these methods in LMICs and humanitarian settings.

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SMS as a promising data collection tool for repeated measurements of consumption and incidence – Results from epidemiological studies on drinking water and acute gastroenteritis in 2012

10.26226/morressier.57fe118cd462b8028d8907bb ◽

2016 ◽

Author(s):

Melle Säve-Söderbergh

Keyword(s):

Drinking Water ◽

Data Collection ◽

Acute Gastroenteritis ◽

Epidemiological Studies ◽

Repeated Measurements ◽

Data Collection Tool

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Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041673 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1673

Author(s):

Ying Pin Chua ◽

Ying Xie ◽

Poay Sian Sabrina Lee ◽

Eng Sing Lee

Keyword(s):

Scoping Review ◽

Chronic Conditions ◽

Meta Analysis ◽

Epidemiological Studies ◽

Cross Sectional ◽

Coding Systems ◽

Wide Range ◽

Scoping Reviews ◽

Retrospective Cohort Studies ◽

Definition Of

Background: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design. Methods: We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results. Results: Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used. Conclusions: We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity.

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Evaluating data quality collected by volunteers for first-level inspection of hydraulic structures in mountain catchments

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-2681-2014 ◽

2014 ◽

Vol 14 (10) ◽

pp. 2681-2698 ◽

Cited By ~ 5

Author(s):

V. J. Cortes Arevalo ◽

M. Charrière ◽

G. Bossi ◽

S. Frigerio ◽

L. Schenato ◽

...

Keyword(s):

Data Collection ◽

Data Quality ◽

Mobile Applications ◽

Rating Scales ◽

Hydraulic Structures ◽

Future Research ◽

Civil Protection ◽

Learning Session ◽

Learning Group ◽

Collection Methods

Abstract. Volunteers have been trained to perform first-level inspections of hydraulic structures within campaigns promoted by civil protection of Friuli Venezia Giulia (Italy). Two inspection forms and a learning session were prepared to standardize data collection on the functional status of bridges and check dams. In all, 11 technicians and 25 volunteers inspected a maximum of six structures in Pontebba, a mountain community within the Fella Basin. Volunteers included civil-protection volunteers, geosciences and social sciences students. Some participants carried out the inspection without attending the learning session. Thus, we used the mode of technicians in the learning group to distinguish accuracy levels between volunteers and technicians. Data quality was assessed by their accuracy, precision and completeness. We assigned ordinal scores to the rating scales in order to get an indication of the structure status. We also considered performance and feedback of participants to identify corrective actions in survey procedures. Results showed that volunteers could perform comparably to technicians, but only with a given range in precision. However, a completeness ratio (question/parameter) was still needed any time volunteers used unspecified options. Then, volunteers' ratings could be considered as preliminary assessments without replacing other procedures. Future research should consider advantages of mobile applications for data-collection methods.

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Meaningful Information in the Age of Big Data: A Scoping Review on Social Determinants of Health Data Collection for Electronic Health Records

10.21203/rs.2.16433/v1 ◽

2019 ◽

Author(s):

Kelsey Berg ◽

Chelsea Doktorchik ◽

Hude Quan ◽

Vineet Saini

Keyword(s):

Big Data ◽

Data Collection ◽

Electronic Health Records ◽

Social Determinants Of Health ◽

Health Systems ◽

Social Determinants ◽

Scoping Review ◽

Determinants Of Health ◽

Health Records ◽

Automated Technology

Abstract Background: Electronic Health Records (EHRs) are key tools for integrating patient data into health information systems (IS). Advances in automated data collection methodology, particularly the collection of social determinants of health (SDOH), provide opportunities to advance health promotion and illness prevention through advanced analytics (i.e. “Big Data” techniques). We ask how current data collection processes in EHRs permit SDOH data to flow throughout health systems. Methods: Using a scoping review framework, we searched through medical literature to identify current practices in SDOH data collection within EHR systems. We extracted relevant information on data collection methodology, specifically focusing on uses of automated technology. We discuss our findings in the context of research methodology and potential for health equity. Results: Practitioners collect a variety of SDOH data at point of care through EHR, predominantly via embedded screening tools and clinical notes, and primarily capturing data on financial security, housing status, and social support. Health systems are increasingly using digital technology in data collection, including natural language processing algorithms. However overall use of automated technology is limited to date. End uses of data pertain to improving system efficiency, patient care-coordination, and addressing health disparities. Discussion & Conclusion: EHRs can realistically promote collection and meaningful use of SDOH data, although EHRs have not extensively been used to collect and manage this type of information. Future applied research on systems-level application of SDOH data is necessary, and should incorporate a range of stakeholders and interdisciplinary teams of researchers and practitioners in fields of health, computing, and social sciences.

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Injury and illness definitions and data collection procedures for use in epidemiological studies in Athletics (track and field): Consensus statement

British Journal of Sports Medicine ◽

10.1136/bjsports-2013-093241 ◽

2014 ◽

Vol 48 (7) ◽

pp. 483-490 ◽

Cited By ~ 142

Author(s):

Toomas Timpka ◽

Juan-Manuel Alonso ◽

Jenny Jacobsson ◽

Astrid Junge ◽

Pedro Branco ◽

...

Keyword(s):

Data Collection ◽

Consensus Statement ◽

Epidemiological Studies ◽

Track And Field

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Augmented and Virtual Reality Evolution and Future Tendency

Applied Sciences ◽

10.3390/app10010322 ◽

2020 ◽

Vol 10 (1) ◽

pp. 322 ◽

Cited By ~ 7

Author(s):

Luis Muñoz-Saavedra ◽

Lourdes Miró-Amarante ◽

Manuel Domínguez-Morales

Keyword(s):

Virtual Reality ◽

Augmented Reality ◽

Scoping Review ◽

Mobile Applications ◽

New Technologies ◽

Future Trend ◽

The Other ◽

Videogame Industry ◽

Depth Study ◽

Technological Improvements

Augmented reality and virtual reality technologies are increasing in popularity. Augmented reality has thrived to date mainly on mobile applications, with games like Pokémon Go or the new Google Maps utility as some of its ambassadors. On the other hand, virtual reality has been popularized mainly thanks to the videogame industry and cheaper devices. However, what was initially a failure in the industrial field is resurfacing in recent years thanks to the technological improvements in devices and processing hardware. In this work, an in-depth study of the different fields in which augmented and virtual reality have been used has been carried out. This study focuses on conducting a thorough scoping review focused on these new technologies, where the evolution of each of them during the last years in the most important categories and in the countries most involved in these technologies will be analyzed. Finally, we will analyze the future trend of these technologies and the areas in which it is necessary to investigate to further integrate these technologies into society.

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