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Patient non-compliance with paper diaries

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Comparative study of electronic vs. paper VAS ratings: a randomized, crossover trial using healthy volunteers

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Using the iPod Touch for Patient Health Behavior Assessment and Health Promotion in Primary Care

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Mobilapplikationen und Management der Hypertonie

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A Randomized Trial of the Disabilities of the Arm, Shoulder, and Hand Administration: Tablet Computer Versus Paper and Pencil

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Recording Practices and Satisfaction of Hemophiliac Patients Using Two Different Data Entry Systems

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Personalised Ambient Monitoring (PAM) of the mentally ill

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M-Psychiatry: Sensor Networks for Psychiatric Health Monitoring

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Measuring population health: costs of alternative survey approaches in the Nouna Health and Demographic Surveillance System in rural Burkina Faso

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A randomized trial of standardized nursing patient assessment using wireless devices.

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5. Personalised Ambient Monitoring: Supporting Mental Health at Home

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AusPlots Rangelands Field Data Collection and Publication: Infrastructure for Ecological Monitoring

Tokmakoff, A. A., Sparrow, B. D., Turner, D., & Lowe, A. J. (2014) · IEEE International Conference on eScience · doi:10.1109/escience.2014.55 · Cited by 11

Online electronic data capture and research data repository system for clinical and translational research.

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Evaluating the Feasibility of Using Mobile Devices for Nurse Documentation.

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DNVF-Memorandum – Gesundheits- und Medizin-Apps (GuMAs)

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Accelerating and improving survey implementation with mobile technology: Lessons from PMA2020 implementation in Lagos, Nigeria

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Security Approaches in Using Tablet Computers for Primary Data Collection in Clinical Research

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Fundamentals of Data Collection in Clinical Studies: Simple Steps to Avoid “Garbage In, Garbage Out”

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Context guided and personalized activity classification system

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Computer-Assisted versus Oral-and-Written History Taking for the Prevention and Management of Cardiovascular Disease: a Systematic Review of the Literature

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Use of online and paper-and-pencil questionnaires to assess the distribution of orthorexia nervosa, muscle dysmorphia and eating disorders among university students: can different approaches lead to different results?

Gorrasi, I. S. R., Ferraris, C., Degan, R., Daga, G. A., Bo, S., Tagliabue, A., Guglielmetti, M., Roppolo, M., Gilli, G., Maran, D. A., et al. (2021) · Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity · doi:10.1007/s40519-021-01231-3 · Cited by 10

Correction: Meeting Community Health Worker Needs for Maternal Health Care Service Delivery Using Appropriate Mobile Technologies in Ethiopia

Little, A., Medhanyie, A. A., Yebyo, H. G., Spigt, M., Dinant, G., & Blanco, R. (2014) · PLoS ONE · doi:10.1371/annotation/fedf94d2-cf4e-494c-8828-85861ce282a5 · Cited by 10

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders

Perez, T. M., Glue, P., Adhia, D. B., Navid, M. S., Zeng, J., Dillingham, P., Smith, M., Niazi, I. K., Young, C. K., & De Ridder, D. (2022) · Trials · doi:10.1186/s13063-022-06863-z · Cited by 8

Customized-Language Voice Survey on Mobile Devices for Text and Image Data Collection Among Ethnic Groups in Thailand: A Proof-of-Concept Study

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Using portable computers in home visits: Effects on programs, data quality, home visitors and caregivers

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Mobile Crowdsensing for the Juxtaposition of Realtime Assessments and Retrospective Reporting for Neuropsychiatric Symptoms

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Methods for Collecting Paired Observations From Emergency Medical Services and Emergency Department Providers for Pediatric Cervical Spine Injury Risk Factors

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Enabling Sophisticated Lifecycle Support for Mobile Healthcare Data Collection Applications

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Supporting Medical Staff from Psycho-Oncology with Smart Mobile Devices: Insights into the Development Process and First Results

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mHealth and Applications

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Towards adoption of mobile data collection for effective adaptation and climate risk management in Africa

Adekola, O. A., Lamond, J. E., Adelekan, I., Bhattacharya‐Mis, N., Ekinya, M., Eze, E. B., & Ujoh, F. (2022) · Geoscience Data Journal · doi:10.1002/gdj3.156 · Cited by 9

Identifying patterns of obesity risk behavior to improve pediatric primary care

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Computer-assisted versus oral-and-written family history taking for identifying people with elevated risk of type 2 diabetes mellitus

Pappas, Y., Wei, I., Car, J., Majeed, A., & Sheikh, A. (2011) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008489.pub2 · Cited by 9

Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus.

Wei, I., Pappas, Y., Car, J., Sheikh, A., & Majeed, A. (2011) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008488.pub2 · Cited by 15

Community mapping by non-literate citizen scientists in the rainforest

Vitos, M., Stevens, M., Lewis, J., & Haklay, M. (2013) · UCL Discovery (University College London) · Cited by 9

Acceptability and adoption of handheld computer data collection for public health research in China: a case study

Wan, X., Raymond, H. F., Wen, T., Ding, D., Wang, Q., Shin, S. S., Yang, G., Chai, W., Zhāng, P., & Novotny, T. E. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-68 · Cited by 8

A survey of patients with haemophilia to understand how they track product used at home

Sholapur, N. S., Barty, R., Wang, G., Almonte, T., & Heddle, N. M. (2013) · Haemophilia · doi:10.1111/hae.12170 · Cited by 8

A quality analysis of clinical anaesthesia study protocols from the Chinese clinical trials registry according to the SPIRIT statement

Yang, L., Chen, S., Yang, D., Li, J., Wu, T., & Zuo, Y. (2018) · Oncotarget · doi:10.18632/oncotarget.24982 · Cited by 8

Patient Versus Professional Based Psychosocial Risk Factor Screening for Adverse Pregnancy Outcomes

Quispel, C., van Veen, M. J., Zuijderhoudt, C., Steegers, E. A. P., Hoogendijk, W. J. G., Birnie, E., Bonsel, G. J., & den Berg, M. P. L. (2014) · Maternal and Child Health Journal · doi:10.1007/s10995-014-1456-5 · Cited by 8

Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment

Schwab, J. D., Schobel, J., Werle, S. D., Fürstberger, A., Ikonomi, N., Szekely, R., Thiam, P., Hühne, R., Jahn, N., Schuler, R., et al. (2021) · IEEE Access · doi:10.1109/access.2021.3087315 · Cited by 8

Algorithmic approaches to detecting interviewer fabrication in surveys

Borriello, G., Karlin, A. R., & Birnbaum, B. (2012) · ResearchWorks at the University of Washington (University of Washington) · Cited by 8

Standardising pharmacist patient-profiling activities in a rehabilitation hospital in Malta

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Telemedicine and Tele-echocardiography in India

Raju, K. P., & Prasad, S. G. (2017) · Journal of The Indian Academy of Echocardiography & Cardiovascular Imaging · doi:10.4103/jiae.jiae_57_17 · Cited by 7

Natural-Setting PHR Usability Evaluation using the NASA TLX to Measure Cognitive Load of Patients

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Smart Assist: Smartphone-Based Drug Compliance for Elderly People and People with Special Needs

Khan, A., & Khusro, S. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-319-96139-2_10 · Cited by 7

Patient adherence and response time in electronic patient-reported outcomes: insights from three longitudinal clinical trials

Nowojewski, A., Bark, E., Shih, V. H., & Dearden, R. (2024) · Quality of Life Research · doi:10.1007/s11136-024-03644-w · Cited by 6

The Development and Piloting of a Mobile Data Collection Protocol to Assess Compliance With a National Tobacco Advertising, Promotion, and Product Display Ban at Retail Venues in the Russian Federation

Grant, A., Kennedy, R. D., Spires, M., & Cohen, J. E. (2016) · JMIR Research Protocols · doi:10.2196/resprot.5302 · Cited by 6

PDAs in socio-economic surveys: instrument bias, surveyor bias or both?

Escobal, J., & Benites, S. (2012) · International Journal of Social Research Methodology · doi:10.1080/13645579.2011.648420 · Cited by 6

Call Me Maybe: Experimental Evidence on Using Mobile Phones to Survey MicroenterprisesPreprint

Garlick, R., Orkin, K., & Quinn, S. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2816064 · Cited by 6

Factors Affecting the Readiness of Medical Doctors and Patients with Chronic Conditions toward the Usage of Smartphones in the Saudi Arabian Healthcare Sector

Al-Mahadeen, B. M. (2015) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v9i1.4279 · Cited by 5

Tablet computers for recording tuberculosis data at a community health centre in King Sabata Dalindyebo Local Municipality, Eastern Cape: a proof of concept report

O’Mahony, D., & Wright, G. (2014) · South African Family Practice · doi:10.1080/20786204.2014.936666 · Cited by 5

Attitudes and Knowledge About Learning Disabilities: A Comparison Between Arabic- and Hebrew-Speaking University Students

Shecter-Lerner, M., Lipka, O., & Khouri, M. (2019) · Journal of Learning Disabilities · doi:10.1177/0022219419836397 · Cited by 5

Integrating paper-based habitat mapping with mobile electronic field recording procedures

Rogers, D. A., McCann, T., & Cooper, A. B. (2010) · Ecological Informatics · doi:10.1016/j.ecoinf.2010.06.004 · Cited by 5

Diabetes & Metabolism Journal

Won, K. C. (2018) · Cited by 5

USING HEURISTIC EVALUATION TO IMPROVE THE USABILITY OF ELECTRONIC MEDICAL RECORD (EMR) MOBILE INTERFACE OF THE CARDIOTHORACIC SURGERY AND ANESTHESIA SYSTEM (CSAS)

Salman, H. M., Kamaruddin, A., Affendey, L. S., Mansor, E. I., Rahmat, R. W. O. K., & Jantan, A. H. (2015) · Jurnal Teknologi · doi:10.11113/jt.v77.6254 · Cited by 4

The Effect of 'Device' in Task-Technology Fit: A Study of German Hospitals

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

Nagarajappa, S., & Vyas, S. (2021) · Medicine and Pharmacy Reports · doi:10.15386/mpr-1467 · Cited by 4

Evaluation of an Adjustable Epidemiologic Information System

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Context Aware Mobile Knowledge Management System in Healthcare

Lakkaraju, S. (2013) · Cited by 3

The Methods for Foot Function Index and Foot and Ankle Outcome Score Measurement: A Comparison between Paper-and-Pencil Method and Electronic Method

Kim, J.-B., Kwon, M.-S., Kim, J.-G., Yi, Y., Lee, W.-C., Ha, J. K., & Jang, S.-H. (2017) · Journal of Korean Foot and Ankle Society · doi:10.14193/jkfas.2017.21.1.33 · Cited by 3

Apps for Health-Related Education in Pharmacy Practice: Needs Assessment Survey Among Patients Within a Large Metropolitan Area

Mirk, S. M., & Wegrzyn, N. (2017) · JMIR Research Protocols · doi:10.2196/resprot.5886 · Cited by 3

Coletas de dados por meio de tablets – prático, barato e de fácil programação

Teixeira, I. P., Nakamura, P. M., Smirmaul, B. P. C., de Campos, L., & Kokubun, E. (2018) · Revista Brasileira de Atividade Física & Saúde · doi:10.12820/rbafs.23e0014 · Cited by 3

Measuring Mental Effort for Creating Mobile Data Collection Applications

Schobel, J., Probst, T., Reichert, M., Schlee, W., Schickler, M., Kestler, H. A., & Pryss, R. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17051649 · Cited by 3

Electronic data capture for health surveys in developing countries: use of a mobile phone based application in southern India

Garg, S., & Mony, P. K. (2013) · Indian Journal of Medical Informatics/Indian journal of medical informatics · Cited by 3

Computer tablet or telephone? A randomised controlled trial exploring two methods of collecting data from drug and alcohol outpatients

Hobden, B., Bryant, J., Carey, M. L., Sanson‐Fisher, R., & Oldmeadow, C. J. (2017) · Addictive Behaviors · doi:10.1016/j.addbeh.2017.03.009 · Cited by 3

Evaluation of Informative Content of Health Data Submitted Through a Mobile Serious Game

Peters, K., Bührer, S., Silbernagl, M., Kayali, F., Hlavacs, H., & Lawitschka, Á. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-34644-7_30 · Cited by 3

The ISAD (Infraslow Neurofeedback for Anxiety and Depression) Study: A Protocol for a Trans-Diagnostic, Randomized, Double-Blind, Sham-Controlled, Dose-Response, Parallel-Group TrialPreprint

Perez, T. M., Glue, P., Adhia, D. B., Smith, M. J., Ridder, D. D., Zeng, J., Dillingham, P. W., & Niazi, I. K. (2021) · Research Square · doi:10.21203/rs.3.rs-173667/v1 · Cited by 3

Computer-assisted versus oral-and-written dietary history taking for diabetes mellitus

Wei, I., Pappas, Y., Car, J., Majeed, A., & Sheikh, A. (2010) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008488 · Cited by 3

How you ask the question really matters: A randomized comparison of four questionnaire delivery modes to assess validity and reliability of self-reported socially censured data in rural Zimbabwean youth

Langhaug, L. F. (2009) · UCL Discovery (University College London) · Cited by 3

Implementation and Adherence of a Custom Mobile Application for Anonymous Bidirectional Communication Among Nearly 4000 Participants: Insights from the Longitudinal RisCoin Study

Zhelyazkova, A., Koletzko, S., Adorjan, K., Schrimf, A., Völk, S., Koletzko, L., Fabry-Said, A., Osterman, A., Badell, I., Eden, M., et al. (2025) · Infectious Disease Reports · doi:10.3390/idr17040088 · Cited by 1

Screen2Care – digitale Erfassung von psychoonkologischem Unterstützungsbedarf

Pichler, T., Härdtner, M., Pipia, I., Kiechle, M. B., Lackmann, K. G., Meier, V., Tröster, F., Kokaras, G., Nest, A., & Herschbach, P. (2019) · Der Onkologe · doi:10.1007/s00761-019-0632-z · Cited by 2

Tablet-based adaptation and administration of the Castles and Coltheart Reading Test 2 for a large longitudinal study

Bennett, C., Cullinane, M., Bennetts, S. K., Love, J., Hackworth, N. J., Mensah, F. K., Reilly, S., Nicholson, J. M., & Westrupp, E. M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0239420 · Cited by 2

The use of the computerized version of quality of life and health status questionnaires in a community sample in southern Brazil

Zúbaran, C., & Tres, I. (2011) · Sao Paulo Medical Journal · doi:10.1590/s1516-31802011000100007 · Cited by 2

Mobile Health, Self-Management, Diabetes & the Impact of Self-Efficacy: A Systematic Review of Literature

Patterson, J. (2013) · uO Research (University of Ottawa) · Cited by 2

Erfahrungen bei der Messung der Ergebnisqualität in der interventionellen Schmerztherapie

Kirrstetter, A. R., Brenig, C., Gengenbacher, M., Meier, B., Ott, A., & Theiler, R. (2016) · Der Schmerz · doi:10.1007/s00482-016-0173-y · Cited by 2

SMS text messaging to measure working time: the design of a time use study among general practitioners

van Hassel, D., van der Velden, L., de Bakker, D. H., & Batenburg, R. S. (2018) · BMC Health Services Research · doi:10.1186/s12913-018-2926-z · Cited by 2

Developing a Cohort Web Application: Real-time Monitoring of Breastfeeding Indicators

Silva, M. D. B., de Almeida, J. A. G., Melo, E. C. P., & Leite, V. R. (2020) · Journal of the International Society for Telemedicine and eHealth · doi:10.29086/jisfteh.8.e20 · Cited by 2

Developing, implementing, and evaluating tuberculosis laboratory information systems for resource-poor settings

Blaya, J. A. (2008) · Cited by 2

Computer-assisted versus oral-and-written family history taking for identifying people with elevated risk of type 2 diabetes mellitus

Pappas, Y., Wei, I., Car, J., Majeed, A., & Sheikh, A. (2010) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008489 · Cited by 2

How do people feel about sleep diaries? Factors influencing sleep diaries completion with and without daily exposure to light

Gass, B., Pierné, G., Ruppert, É., Kilic-Huck, Ü., Hugueny, L., Bourgin, P., & Chambe, J. (2025) · PLoS ONE · doi:10.1371/journal.pone.0317788 · Cited by 1

Beyond the clipboard: data collection with GridScore NEXT

Raubach, S., Schreiber, M., Hamilton, R., McKenzie, G., McCallum, S., Kilian, B., Humphries, A. W., Nguyen, L. H., Tin, H. Q., Singh, A., et al. (2026) · BMC Bioinformatics · doi:10.1186/s12859-025-06352-5 · Cited by 1

Experiences with a PDA-based Documentation System in Clinical Research

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Beantwortung von Selbstbeurteilungsfragebögen mit mobilen Apps im Vergleich zu anderen Methoden

Schneidewind, L., Borgmann, H., & Schmidt, S. (2016) · Der Urologe · doi:10.1007/s00120-016-0239-6 · Cited by 1

Rett Syndrome Behaviour Questionnaire: Variability of Scores and Related Factors

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Infraslow Closed-Loop Brain Training for Anxiety and Depression (ISAD): A pilot randomised, sham-controlled trial in adult females with internalizing disorders

Perez, T. M., Adhia, D. B., Glue, P., Zeng, J., Dillingham, P. W., Navid, M. S., Niazi, I. K., Young, C. K., Smith, M. L., & Ridder, D. J. M. K. D. (2025) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-025-01279-z · Cited by 2

Handheld Devices

Prasad, R. (2008) · Computers in health care · doi:10.1007/978-0-387-76418-4_21 · Cited by 1

Smart Wearable Sensor Design Techniques For Mobile Health Care Solutions

Vijaya, K., & Laxmi, B. P. (2023) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9789815050592123010015 · Cited by 1

Letter to the Editor

McEntegart, D. J. (2009) · Contemporary Clinical Trials · doi:10.1016/j.cct.2009.06.001 · Cited by 1

Use of Smartphone and GIS Technology for Sustainable Forestry in Eastern Ontario

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