ArticleBehavior research methods2023
To BYOD or not: Are device latencies important for bring-your-own-device (BYOD) smartphone cognitive testing?
Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Developing a psychological test battery to measure cognition in daily life.Behavior research methods · 2026Article
- Remote, self-administered, smartphone cognitive testing in a registry-based cohort: Feasibility, reliability, and validity findings.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Using Android Smartphones to Collect Precise Measures of Reaction Times to Multisensory Stimuli.Sensors (Basel, Switzerland) · 2025Article
- Investigating Measurement Equivalence of Smartphone Sensor-Based Assessments: Remote, Digital, Bring-Your-Own-Device Study.Journal of medical Internet research · 2025Article
- Criterion validity of five open-source app-based cognitive and sensory tasks in an Australian adult life course sample aged 18 to 82: Labs without walls.Behavior research methods · 2025Article
- Feasibility, adherence and usability of an observational digital health study built using Apple's ResearchKit among adults aged 18-84 years.Frontiers in digital health · 2025Article
- Exploring the relationship between mean performance and within-person variability on smartphone-based cognitive testing in adults across the lifespan.NPP - digital psychiatry and neuroscience · 2025Article
- Feasibility of Deploying Home-Based Digital Technology, Environmental Sensors, and Web-Based Surveys for Assessing Behavioral Symptoms and Identifying Their Precipitants in Older Adults: Longitudinal, Observational Study.JMIR formative research · 2024Article
- Digital Neuropsychology beyond Computerized Cognitive Assessment: Applications of Novel Digital Technologies.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2024Review
- Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes.NPJ digital medicine · 2024Article
- Relationships between hourly cognitive variability and risk of Alzheimer's disease revealed with mixed-effects location scale models.Neuropsychology · 2024Article
- Augmented reality versus standard tests to assess cognition and function in early Alzheimer's disease.NPJ digital medicine · 2023Article
- Usability of the Mayo Test Drive remote self-administered web-based cognitive screening battery in adults aged 35-100 with and without cognitive impairment.Journal of clinical and experimental neuropsychologyArticle
- Reliability of remote self-administered Web-based digital cognitive measures and comparison to in-person neuropsychological tests: Stricker Learning Span, Symbols Test, and the Mayo Test Drive Screening Battery Composite.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Review
- Moving toward the digitalization of neuropsychological tests: An exploratory study on usability and operator perception.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Studies using remote cognitive testing must make a critical decision: whether to allow participants to use their own devices or to provide participants with a study-specific device. Bring-your-own-device (BYOD) studies have several advantages including increased accessibility, potential for larger sample sizes, and reduced participant burden. However, BYOD studies offer little control over device performance characteristics that could potentially influence results. In particular, response times measured by each device not only include the participant's true response time, but also latencies of the device itself. The present study investigated two prominent sources of device latencies that pose significant risks to data quality: device display output latency and touchscreen input latency. We comprehensively tested 26 popular smartphones ranging in price from < $100 to $1000+ running either Android or iOS to determine if hardware and operating system differences led to appreciable device latency variability. To accomplish this, a custom-built device called the Latency and Timing Assessment Robot (LaTARbot) measured device display output and capacitive touchscreen input latencies. We found considerable variability across smartphones in display and touch latencies which, if unaccounted for, could be misattributed as individual or group differences in response times. Specifically, total device (sum of display and touch) latencies ranged from 35 to 140 ms. We offer recommendations to researchers to increase the precision of data collection and analysis in the context of remote BYOD studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.