Data Collection Using Mobile Devices and Cloud/Web-based GIS

2016 ◽  
Vol 2016 (10) ◽  
pp. 5901-5912
Author(s):  
Matt Winkelman ◽  
Andy Lovell ◽  
Adam Fisher
2021 ◽  
Vol 8 ◽  
Author(s):  
Jutta G. Richter ◽  
Anja Weiß ◽  
Christina Bungartz ◽  
Rebecca Fischer-Betz ◽  
Angela Zink ◽  
...  

Background: The German pregnancy register Rhekiss is designed as a nationwide, web-based longitudinal observational cohort established in 2015. The register follows women with inflammatory rheumatic disease prospectively from child wish or early pregnancy until 2 years post-partum. Information on clinical and laboratory parameters, drug treatment, and (adverse) pregnancy outcomes are documented in pre-specified intervals. Physicians and patients report data for the same time periods via separated accounts and forms into a web-based application (app). As data entry on mobile devices might improve response rates of patients, a responsive app as a further convenient documentation option was developed.Methods: The Rhekiss-app is available for self-reported data retrieval since August 2017 from the App stores. For the current analysis, Rhekiss register data were used from the start of the register until 30 September 2020. The analyses were performed for forms containing information on devices. Outcome parameters were compared for mobile and desktop users for the quantity and quality of filled forms.Results: In total, 5,048 forms were received and submitted by 966 patients. About 57% of forms were sent from mobile devices with the highest numbers in patients with child wishes (63%). Users of mobile devices were slightly younger and often had less high-education level (62 vs. 79%) compared with desktop users. The proportion of forms submitted via mobile devices increased steadily from 48% in the fourth quarter of 2018 to 64% in the third quarter of 2020. The proportion of forms received before and after the Rhekiss-app implementation increased with the highest increase of 12% for forms filled at time point 12 months post-partum. Mobile users submitted significantly more forms than desktop users (2.9 vs. 2.1), data sent via desktops were more often complete (88 vs. 86%).Conclusion: The responsive app is a valuable additional tool for data collection and is well-accepted by patients as indicated by its increasing use in Rhekiss. Apart from desktop/browser developments, the technological adoptions within observational cohorts and registries should take smartphone requirements and developments into account, especially when patient-reported data in young, mobile patients are collected, bearing in mind that data quality could be compromised and concepts for improving data quality should be implemented.


2020 ◽  
Author(s):  
Minhaaj Rehman ◽  
John Anthony Johnson

The NEO-IPIP-300 is a 300-item version scale of freely available personality tests based on the OCEAN Model of 30 distinctive personality traits. The scale measures human personality preferences and groups them into five distinct factors, namely Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The scale has been translated into many languages before, but there was no translation and norms available for the Urdu language.Paper reports the translation, creation of web version, data collection (N=869), and reliability of Urdu version of NEO-IPIP-300. We also did a CFA Analysis and Measurement Invariance test as part of the paper. Full measurement invariance was met for the full model, and partial measurement invariance was met for neuroticism (metric and scalar) and extraversion (metric). In general, all models fit well and suggest that the Urdu IPIP-300-NEO aligns well with the English IPIP-300-NEO. In some cases, the Urdu inventory performed better (e.g., higher internal consistency) than the English inventory.


Field Methods ◽  
2021 ◽  
pp. 1525822X2198984
Author(s):  
April Y. Oh ◽  
Andrew Caporaso ◽  
Terisa Davis ◽  
Laura A. Dwyer ◽  
Linda C. Nebeling ◽  
...  

Behavioral research increasingly uses accelerometers to provide objective estimates of physical activity. This study extends research on methods for collecting accelerometer data among youth by examining whether the amount of a monetary incentive affects enrollment and compliance in a mail-based accelerometer study of adolescents. We invited a subset of adolescents in a national web-based study to wear an accelerometer for seven days and return it by mail; participants received either $20 or $40 for participating. Enrollment did not significantly differ by incentive amount. However, adolescents receiving the $40 incentive had significantly higher compliance (accelerometer wear and return). This difference was largely consistent across demographic subgroups. Those in the $40 group also wore the accelerometer for more time than the $20 group on the first two days of the study. Compared to $20, a $40 incentive may promote youth completion of mail-based accelerometer studies.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734


2016 ◽  
Vol 56 (4) ◽  
pp. 482-495
Author(s):  
Ilona Pezenka

Destination image is among the most studied constructs in tourism research. Many researchers are still convinced that the rating scale method is the most accurate for assessing destination image. This study presents alternative methods of data collection, namely, free-sorting and reduced paired comparisons, and investigates their applicability in a Web-based environment. The study then subjects these data collection methods to empirical analysis and compares the judgment task’s effects on perceived difficulty, fatigue, and boredom, on data quality, and on perceptual maps derived with MDS. The findings demonstrate that these methods are more accurate whenever a large number of objects have to be judged, which is particularly the case for positioning and competitiveness studies.


KREA-TIF ◽  
2017 ◽  
Vol 5 (2) ◽  
pp. 58
Author(s):  
Dahlia Widhyaestoeti ◽  
Guntara Guntara

<h1 align="center">Abstrak</h1><p>Sistem informasi pendataan siswa Di RA Sami’na Waathanaa, proses pendataan siswa/siswi baik ketika siswa/siswi yang baru masuk, atau yang sudah lulus di data oleh operator sekolah tersebut masih menggunakan Microsoft Office. Hal tersebut menghambat pekerjaan operator serta data-data siswa mudah hilang atau rusak. Pengembangan sistem berupa sistem informasi pendataan siswa berbasis web, sehingga membantu kecepatan dan kualitas dalam penyampaian informasi. Tujuan dari penelitian ini adalah untuk menyediakan Sistem Pendataan Siswa terkomputerisasi dalam database. Metode pengembangan sistem informasi yang digunakan model waterfall, dari mulai analisis masalah, perancangan, hingga implementasi. Menu pada sistem pendataan siswa ini dapat diakses oleh user tertentu yaitu siswa, guru dan admin. Sistem informasi pendataan siswa ini berbasis web dengan pemanfaatan bahasa pemprogram Personal Hypertext Prepocessor (PHP) dan Structured Query Language (SQL). Pengunaan sistem informasi pendataan siswa ini dapat menghemat waktu dan menghasilkan informasi yang dibutuhkan.</p><h1 align="center"><em>Abstract</em></h1><p><em>Student data collection system At RA Sami’na Waathanaa, the student data collection process is good when students who have just entered, or who have graduated in data by the school operator are still using Microsoft Office. This hinders the work of operators and student data is easily lost or damaged. The development of the system in the form of a web-based student data collection system, so that it helps speed and quality in delivering information. The purpose of this study is to provide a computerized Student Data Collection System in a database. The information system development method used is the waterfall model, from problem analysis, design, to implementation. Menus in the student data collection system can be accessed by certain users, namely students, teachers and admins. This student data collection system is web based with the use of Personal Hypertext Prepocessor (PHP) and Structured Query Language (SQL) programming languages. Using this student data collection system can save time and produce the information needed.</em></p><p align="left"> </p>


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