scholarly journals Smartphone assisted oral health data recording – an android based software application development

2021 ◽  
Vol 94 (3) ◽  
pp. 333-340
Author(s):  
Sandesh Nagarajappa ◽  
Shaleen Vyas
Keyword(s):  
Oral Health ◽  
General Population ◽  
Data Collection ◽  
User Satisfaction ◽  
Data Entry ◽  
Health Data ◽  
Data Recording ◽  
Data Loss ◽  
Software Application ◽  
Paper Method

Background. Smartphone compared to the traditional pen-paper method could enhance oral health data recording procedure by reducing the cost of data collection, risk of data loss, early detection of errors and reducing data entry time. The present research developed a mobile/tablet-based software application to capture oral health data and test its adaptability and operations in oral health surveys. Methods. A comparative cross-sectional study was conducted among the general population of Sanwer town, Indore district. The initial testing of the application was done on 120 individuals. A random sampling (lottery method) followed by a systematic sampling strategy was employed to select 120 households. A “one per household” design was implemented for the survey. The initial oral health data collection was done using mobile-assisted software application followed by a second examination scheduled after 15 days on the same participants using the conventional Pen-paper method to collect oral health data.  Results. Six Investigator Recorder (IR) teams conducted the oral health data collection. Data collection through Smartphone-based application displayed less meantime (3.57 minutes) in comparison to pen-paper method (4.87 minutes) (p≤0.001). Survey team response showed the majority of investigators having strong agreement on user satisfaction and speed of data entry using software application. Conclusion. The initial testing of mobile-assisted recording system (MARS) efficiently captured oral health data among the general population with wide variations in oral disease level. The application facilitated minimal or no wastage of paper and had a high level of user-satisfaction, accuracy, speed of entry and low potential for any data loss.

Equity in Environmental Health: Data Collection and Interpretation Issues

1993 ◽  
Vol 9 (5) ◽  
pp. 775-795 ◽  
Author(s):  
Diane K. Wagener ◽  
David R. Williams ◽  
Patrick M. Wilson
Keyword(s):  
General Population ◽  
Data Collection ◽  
Health Effects ◽  
Complex Mixture ◽  
Health Data ◽  
Environmental Hazards ◽  
Environmental Equity ◽  
Policy Makers ◽  
Wide Range ◽  
Underlying Mechanisms

In order to assess the issue of inequity in exposure to environmental hazards, researchers must identify subgroups whose exposure is disproportionately greater than the average exposure experienced by the remainder of the population. The general population is a complex mixture of subgroups, each consisting of individuals who experience a wide range of exposures and whose ability to cope with the consequences of those exposures is equally varied. Therefore, large efforts are needed to collect data that will enable researchers to determine compreliensively which subgroups are highly exposed and which subgroups have disproportionately greater health effects as a result of exposures to environmental hazards. The interpretation of findings is more of an art than a science, especially when two population subgroups are being contrasted. Addressing environmental equity requires explicit comparisons between groups, and racial and ethnic contrasts will be prominent. It is often difficult to identify the underlying mechanisms that produce particular patterns of results. However, researchers and policy makers must understand the dynamics that may have produced a particular pattern of results so they can separate those factors that are amenable to change from those that are not.

A framework for federal health data collection

1976 ◽  
Author(s):  
N. Phillip Ross ◽  
Meyer Katzper
Keyword(s):  
Data Collection ◽  
Health Data

scholarly journals Improving Specimen Labelling and Data Collection in Bio-science Research using Mobile and Web Applications

2020 ◽  
Vol 10 (1) ◽  
pp. 1-16
Author(s):  
Isaac Nyabisa Oteyo ◽  
Mary Esther Muyoka Toili
Keyword(s):  
Data Collection ◽  
Web Applications ◽  
Data Entry ◽  
Science Research ◽  
Quality Data ◽  
Quality Of Data ◽  
Data Entry Form ◽  
Research Activities ◽  
Daunting Task

AbstractResearchers in bio-sciences are increasingly harnessing technology to improve processes that were traditionally pegged on pen-and-paper and highly manual. The pen-and-paper approach is used mainly to record and capture data from experiment sites. This method is typically slow and prone to errors. Also, bio-science research activities are often undertaken in remote and distributed locations. Timeliness and quality of data collected are essential. The manual method is slow to collect quality data and relay it in a timely manner. Capturing data manually and relaying it in real time is a daunting task. The data collected has to be associated to respective specimens (objects or plants). In this paper, we seek to improve specimen labelling and data collection guided by the following questions; (1) How can data collection in bio-science research be improved? (2) How can specimen labelling be improved in bio-science research activities? We present WebLog, an application that we prototyped to aid researchers generate specimen labels and collect data from experiment sites. We use the application to convert the object (specimen) identifiers into quick response (QR) codes and use them to label the specimens. Once a specimen label is successfully scanned, the application automatically invokes the data entry form. The collected data is immediately sent to the server in electronic form for analysis.

scholarly journals Opportunities and Challenges in Public Health Data Collection in Southern Asia: Examples from Western India and Kathmandu Valley, Nepal

2017 ◽  
Vol 9 (7) ◽  
pp. 1106 ◽  
Author(s):  
Amruta Nori-Sarma ◽  
Anobha Gurung ◽  
Gulrez Azhar ◽  
Ajit Rajiva ◽  
Dileep Mavalankar ◽  
...  
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Health Data ◽  
Kathmandu Valley ◽  
Western India ◽  
Southern Asia ◽  
Public Health Data

scholarly journals Willingness of Greek general population to get a COVID-19 vaccine

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Georgia Kourlaba ◽  
Eleni Kourkouni ◽  
Stefania Maistreli ◽  
Christina-Grammatiki Tsopela ◽  
Nafsika-Maria Molocha ◽  
...  
Keyword(s):  
Public Health ◽  
General Population ◽  
Data Collection ◽  
Sample Size ◽  
Significant Proportion ◽  
Control Measures ◽  
Systematic Sampling ◽  
Computer Assisted ◽  
Public Health Officials ◽  
To Receive

Abstract Background Epidemiological data indicate that a large part of population needs to be vaccinated to achieve herd immunity. Hence, it is of high importance for public health officials to know whether people are going to get vaccinated for COVID-19. The objective of the present study was to examine the willingness of adult residents in Greece to receive a COVID-19 vaccine. Methods A cross-sectional was survey conducted among the adult general population of Greece between April 28, 2020 to May 03, 2020 (last week of lockdown), using a mixed methodology for data collection: Computer Assisted Telephone Interviewing (CATI) and Computer Assisted web Interviewing (CAWI). Using a sample size calculator, the target sample size was found to be around 1000 respondents. To ensure a nationally representative sample of the urban/rural population according to the Greek census 2011, a proportionate stratified by region systematic sampling procedure was used to recruit particpants. Data collection was guided through a structured questionnaire. Regarding willingness to COVID-19 vaccination, participants were asked to answer the following question: “If there was a vaccine available for the novel coronavirus, would you do it?” Results Of 1004 respondents only 57.7% stated that they are going to get vaccinated for COVID-19. Respondents aged > 65 years old, those who either themselves or a member of their household belonged to a vulnerable group, those believing that the COVID-19 virus was not developed in laboratories by humans, those believing that coronavirus is far more contagious and lethal compared to the H1N1 virus, and those believing that next waves are coming were statistically significantly more likely to be willing to get a COVID-19 vaccine. Higher knowledge score regarding symptoms, transmission routes and prevention and control measures against COVID-19 was significantly associated with higher willingness of respondents to get vaccinated. Conclusion A significant proportion of individuals in the general population are unwilling to receive a COVID-19 vaccine, stressing the need for public health officials to take immediate awareness-raising measures.

Understanding Data Collection Mechanisms Used by Health and Wellness Applications (Preprint)

2021 ◽  
Author(s):  
Ben Philip ◽  
Mohamed Abdelrazek ◽  
Alessio Bonti ◽  
Scott Barnett ◽  
John Grundy
Keyword(s):  
Data Collection ◽  
User Experience ◽  
Health Data ◽  
Domain Model ◽  
Health And Wellness ◽  
Related Services ◽  
Related Data ◽  
Medical Apps ◽  
App Development ◽  
Health Related

UNSTRUCTURED Our objective is to better understand health-related data collection across different mHealth app categories. This would help in developing a health domain model for mHealth apps to facilitate app development and data sharing between these apps to improve user experience and reduce redundancy in data collection. We identified app categories listed in a curated library which was then used to explore the Google Play Store for health/medical apps that were then filtered using our inclusion criteria. We downloaded and analysed these apps using a script we developed around the popular AndroGuard tool. We analysed the use of Bluetooth peripherals and built-in sensors to understand how a given app collects/generates health data. We retrieved 3,251 applications meeting our criteria, and our analysis showed that only 10.7% of these apps requested permission for Bluetooth access. We found 50.9% of the Bluetooth Service UUIDs to be known in these apps, with the remainder being vendor specific. The most common health-related services using the known UUIDs were Heart Rate, Glucose and Body Composition. App permissions show the most used device module/sensor to be the camera (20.57%), closely followed by GPS (18.39%). Our findings are consistent with previous studies in that not many health apps were found to use built-in sensors or peripherals for collecting health data. The use of more peripherals and automated data collection along with integration with other apps could increase usability and convenience which would eventually also improve user experience and data reliability.

Validation of a Musculoskeletal Digital Assessment Routing Tool (DART): Protocol for a Pilot Randomised Crossover Non-Inferiority Trial (Preprint)

2021 ◽  
Author(s):  
Cabella Lowe ◽  
Harry Hanuman Sing ◽  
William Marsh ◽  
Dylan Morrissey
Keyword(s):  
Clinical Trials ◽  
Data Collection ◽  
Real World ◽  
User Satisfaction ◽  
Allocation Concealment ◽  
Trial Methodology ◽  
Primary Analysis ◽  
Digital Assessment ◽  
System Usability Scale ◽  
The Impact

BACKGROUND Musculoskeletal conditions account for 16% of global disability, resulting in a negative effect on millions of patients and an increasing burden on healthcare utilization. Digital technologies to improve health care outcomes and efficiency are considered a priority; however, innovations are rarely tested with sufficient rigor in clinical trials, the gold standard for clinical proof of safety and efficacy. We have developed a new musculoskeletal Digital Assessment Routing Tool (DART) that allows users to self-assess and be directed to the right care. DART requires validation in a real-world setting prior to implementation. OBJECTIVE This pilot study will assess the feasibility of a future trial by exploring key aspects of trial methodology, assess the procedures and collect exploratory data to inform the design of a definitive, randomized, crossover, non-inferiority trial to assess DART safety and effectiveness. METHODS We will collect data from 76 adult participants presenting to an NHS England GP practice with a musculoskeletal condition. Participants will complete both a DART assessment and a physiotherapist-led triage with the order determined by randomization. The primary analysis will involve an absolute agreement ICC (A,1) estimate with 95% confidence intervals between DART and the clinician for assessment outcomes sign-posting to condition management pathways. Data will be collected to allow analysis of participant recruitment and retention, randomization, allocation concealment, blinding, data collection process and bias. In addition, the impact of trial burden and potential barriers to intervention delivery will be considered. DART user satisfaction will be measured using the System Usability Scale. RESULTS A UK NHS ethics submission will be submitted during June 2021 and pending approval, recruitment will commence during August 2021 with data collection anticipated to last for 3 months. Results will be reported in a follow-up paper later in 2021. CONCLUSIONS This study will inform the design of a randomized controlled crossover non-inferiority study that will provide evidence concerning mHealth DART system clinical sign posting in an NHS setting prior to real-world implementation. Success should produce evidence of a safe, effective system with excellent usability, facilitating quicker and easier patient access to appropriate care while reducing the burden on primary and secondary care musculoskeletal services. This rigorous approach to mHealth system testing could be used as a guide for other developers of similar applications. CLINICALTRIAL This trial is registered with Clinical Trials number NCT04904029

scholarly journals Collecting standardised oral health data via mobile application: A proof of concept study in the Netherlands

PLoS ONE ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. e0191385 ◽  
Author(s):  
Joost C. L. den Boer ◽  
Ward van Dijk ◽  
Virginie Horn ◽  
Patrick Hescot ◽  
Josef J. M. Bruers
Keyword(s):  
Oral Health ◽  
The Netherlands ◽  
Mobile Application ◽  
Health Data ◽  
Proof Of Concept ◽  
Concept Study

scholarly journals Oral health inequality in people with severe mental illness: a cross-sectional study using National Health and Nutrition Examination Survey 1999-2016

2021 ◽  
Author(s):  
Jing Kang ◽  
Jianhua Wu ◽  
Vishal Aggarwal ◽  
David Shiers ◽  
Tim Doran ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mental Illness ◽  
Oral Health ◽  
General Population ◽  
Health Outcomes ◽  
Severe Mental Illness ◽  
Tooth Loss ◽  
List Type ◽  
Cross Sectional ◽  
Oral Health Outcomes

AbstractOBJECTIVETo explore whether people with severe mental illness (SMI) experience worse oral health compared to the general population, and the risk factors for poor oral health in people with SMI.METHODThis study used cross-sectional data from the National Health and Nutrition Examination Survey (1999-2016) including on self-rated oral health, ache in mouth, tooth loss, periodontitis stage, and number of decayed, missing, and filled teeth. Candidate risk factors for poor oral health included demographic characteristics, lifestyle factors, physical health comorbidities, and dental hygiene behaviours. The authors used ordinal logistic regression and zero-inflated negative binomial models to explore predictors of oral health outcomes.RESULTS53,348 cases were included in the analysis, including 718 people with SMI. In the fully adjusted model, people with SMI were more likely to suffer from tooth loss (OR 1.40, 95% CI: 1.12-1.75). In people with SMI, the risk factors identified for poor oral health outcomes were older age, white ethnicity, lower income, smoking history, and diabetes. Engaging in physical activity and daily use of dental floss were associated with better oral health outcomes.CONCLUSIONSPeople with SMI experience higher rates of tooth loss than the general population, and certain subgroups are particularly at risk. Having a healthy lifestyle such as performing regular physical exercise and flossing may lower the risk of poor oral health. These findings suggest opportunities for targeted prevention and early intervention strategies to mitigate adverse oral health outcomes.Significant outcomes (x3)People with severe mental illness were at 40% higher risk of tooth loss when compared to the general population.Older adults, smokers and people with diabetes were at particularly high risk of poor oral health.Physical exercise and daily use of dental floss were associated with better oral health outcomes.Limitations (x3)The number of cases with data on periodontal disease was limited.The study was cross-sectional so causation could not be inferred.The analysis used prescriptions of antipsychotic and mood stabilising medication as a proxy measure of severe mental illness, as clinical diagnoses were not available in the dataset.Data availability statementThe NHANES 1999-2016 data is available at CDC website: https://www.cdc.gov/nchs/nhanes/index.htm, and is accessible and free to download for everyone.

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