The validity and acceptability of a text-based monitoring system for pediatric asthma studies

Abstract

A meaningful analysis in research requires robust, valid data. Paper diaries allow the collection of data from individuals over time but are notorious for poor compliance and validity. SMS-technology is a novel method for data collection in medical research. Time-tagged SMS are transferred directly to an electronic file. We used SMS to collect symptoms and peak flow rate (PEFR) meter readings from 32 children with asthma. Parents responded first to five SMS daily for 7 days during an asymptomatic period and then for 14 days during a cold. Compliance with use of PEFR meter and SMS system were assessed. Digital PEFR meters enabled data download at the end of the study to confirm validity of transmitted data. Parents of 24 participants provided feedback about this data collection tool. Mean (±SD) "SMS-diary and PEFR-meter compliance" were 96% (±8) and 84% (±21) during baseline and 91% (±12) and 82% (±20) during cold respectively. Correctly reported PEFR values were found in 65.5% of all cases, in 8.3% PEFR values sent were "self-invented" and 2.4% of values were missing. All of the 22 parents completing the baseline questionnaire were happy to use SMS for this study. Of the 20 parents completing the follow up questionnaire, 95% (19/20) found the system user-friendly, 55% (11/20) would be more likely to participate in studies if they were using SMS data collection and 25% (5/20) were "sometimes unhappy" about receiving messages. This real-time capture of data is well accepted and could avoid some of the pitfalls of backfilled paper diaries.

An Automated Text-Messaging Platform for Enhanced Retention and Data Collection in a Longitudinal Birth Cohort: Cohort Management Platform Analysis

“…This can be particularly useful since measurement can be timed to be contemporaneous with key behaviors as they occur during the participant’s daily life (eg, asking participants in the morning when they went to sleep the night before and when they woke up). In general, shortening the recall period for certain behaviors, such as sleep, improves accuracy [18,19]. In addition, it can be a lot easier for participants to respond quickly to a text message than to fill out a paper-based log and the data is captured automatically, thereby avoiding the need for staff to manually enter such data.…”

“…The advantages to this method include convenience for both participants and staff, cost efficiency, and real-time responses. Real-time responding increases data quality by reducing recall burden [18,19]. Immediacy of data collection can also provide a more complete picture of exposures, thoughts, emotions, and other variables of interest as they are experienced throughout the day.…”

Best practices for collecting repeated measures data using text messages

“…As a result, for Chernick et al only 71% of the 1650 messages sent were successfully delivered [29]. In Gahleitner et al's study collecting asthma and biometric data via text messages, even though a number of participants had pay-as-you-go phone plans, response rates were 82% or higher over 21 days of survey data collection [25].…”

“…Secure data platforms are advised for data collection [1,10,11,19,24]. Investigators in several studies were careful to remove as much identifying participant information as possible, using telephone numbers or participant IDs in the datasets [11,25], recommending that participants immediately delete messages after answering them, and encouraging participants to password protect their phones [16,17,24].…”

A scoping review of mHealth monitoring of pediatric bronchial asthma before and during COVID-19 pandemic

“…The app further features the modules for medication reminders, facilitation of therapy adherence, various alerts, and educational component Randomized controlled intervention study (RCT) NA First author, last name reference number Publica-tion year Targeted patient group; targeted Childhood Asthma Control Test (C-ACT), if available Brief description of mHealth app or device or software or platform, or Internet-of-Things device Study design Additional comments Real [40] 2019 Children (4 - 11 years), C-ACT score < 20 CHANGE Asthma (“Clinic, Home, And on the Go Education for Asthma”) mHealth app, whose primary purposes were asthma knowledge and self-management, with educational components tailored to pediatric audience Randomized controlled intervention study (RCT) NA Kosse [49] 2019 Adolescents (mean [SD] age: 15.0 [2.0] years) ADolescent Adherence Patient Tool (ADAPT), based on a validated questionnaires, (Control of Allergic Rhinitis and Asthma Test, CARAT). This mHealth app permits asthma self-monitoring and synchronous monitoring by a healthcare professional, as well as direct communication with the latter (via chat) Qualitative and/or mixed methods study NA Huffaker [32] 2018 Children and adolescents (5 - 18 years) BCG accelerometer–based passive bed sensor (SCA11H; Murata Technologies, Kyoto, Japan) for nighttime collection of important functional health parameters (e.g., heart rate, heart rate variability, stroke volume, respiration rate, respiration rate variability, and derivatives of these parameters; activity indication) Uncontrolled intervention study NA Grossman [50] 2017 Children (11 - 16 years) The mHealth system comprises a Bluetooth-enabled inhaler and a Social Pervasive Visualization (SPV) Asthma app, in conjunction with the cloud server Development of an mHealth platform, combined with an uncontrolled intervention study NA Gahleitner [55] 2016 Children (5 - 11 years) SMS text messages Uncontrolled intervention study NA First author, last name reference number Publica-tion year Targeted patient group; targeted Childhood Asthma Control Test (C-ACT), if available Brief description of mHealth app or device or software or platform, or Internet-of-Things device Study design …”