MiniCog: A method for administering psychological tests and experiments on a handheld personal digital assistant

Abstract

Because of their minimal cost, size, and weight, handheld personal digital assistants (PDAs) are appealing as a means for administering response time tasks "in the field" or to participants in longitudinal studies who need repeated access to the testing equipment. We have developed a software package that allows investigators to author simple scripts on their desktop computers and administer the compiled tasks on PDAs. MiniCog presents instructions, practice trials with auditory feedback, and visual stimuli in random or fixed sequential orders with fixed or variable durations and intertrial intervals and records single-button responses and response times. Data from each trial are stored with a user ID, user-entered demographics and notes, and a time-and-date stamp, for later upload to a desktop computer. MiniCog performs automatic calculations of mean response time and error rate, available to users with a password and stored with the other data for upload.

Momentary assessment of impulsive choice and impulsive action: Reliability, stability, and correlates

“…A 360-trial modified Continuous Performance Test-II (CPT-II; Conners, 2004) was administered at the baseline laboratory visit (using DMDX software, Forster & Forster, 2003) and a 60–66-trial (mean 60.47, SD =.78 trials) version of the task was presented at every EMA report (using MiniCog software, Cambridge, MA; Shephard, Kho, Chen, & Kosslyn, 2006). Respondents were instructed to press a key whenever a letter appeared, except when the letter was an X; 90% of trials were non-X trials in which the correct response was a key press, 10% of trials were X “no-go” trials in which the correct response was to inhibit responding.…”

The identification and prediction of frailty based on Bayesian network analysis in a community-dwelling older population

“…The following factors were considered to be covariates, which were obtained from comprehensive questionnaires: (a) demographic characteristics including age, gender, education, marital status, living condition, and monthly income; (b) lifestyle factors such as tobacco and alcohol use, and exercise habits; (c) clinical indicators including physician-diagnosed medical conditions, number of regular medications, hospital admissions and history of falls in the past one year; (d) physical function assessment on basic/instrumental activities of daily living (ADL/IADL) evaluated by the Katz scale [ 12 ] and Lawton instrumental activities of daily living scale [ 13 ]; balance capacity evaluated with the timed up and go test [ 14 ]; (e) sensory assessments including vision, hearing, and continence, answering “normal, mild impaired, impaired” on a three-point scale; (f) a psychophysiological assessment in which depression, anxiety, and insomnia were assessed by the geriatric depression scale-4 (GDS-4) [ 15 ], generalized anxiety disorder scale-7 (GAD-7) [ 16 ], and Athens insomnia scale (AIS) [ 17 ], respectively; chronic pain assessed with the numerical rating scale (NRS) [ 18 ]; (g) cognitive function evaluated using the minicog scale [ 19 ]; (h) dietary diversity score focusing on nine types of food including grains, vegetables, fruits, meat, seafood, eggs, dairy products, beans, and tea. The dietary diversity score was calculated based on the sum of the frequency of each type of food.…”

Using Adobe Flash Lite on mobile phones for psychological research: Reaction time measurement reliability and interdevice variability

“…As we saw in the examples of Shephard et al (2006) and Hogarth et al (2007), they allow testing to be done "in the field," where it would be harder to test using a traditional computer-based setup. Shephard et al used the extreme example of testing in space, but also suggested that there may be down-to-earth scenarios that could be explored using mobile devices.…”