The teaching–learning process developed was based on the effective integration of the Hardware in the Loop (HIL) technique to control a brewing process. This required programming the autonomous ...control of the system and uploading it to a physical controller consisting of a PLC S7-1200, which communicates in real time with a virtual brewing environment, in addition to a SCADA system, providing engineering students with a unique practical experience. The system allows the emission of input signals from sensors and the reception of output signals in actuators, which is reflected accurately and in real time in the virtual environment. Students cannot only observe but also control and manipulate the system using specifically developed programs. This methodology enriched the understanding of industrial processes and fostered the acquisition of control skills. This research work reveals that the combination of the physical and the virtual through the HIL technique offers an effective approach for the training of engineers, improving their understanding of industrial control processes and their ability to intervene practically in real industrial situations.
Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by ...substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.
This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.
We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.
Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.
Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.
Background
Differentiating normal from pathological cognitive change in adults is essential for both preventing and treating abnormal cognitive decline. The Mobile Toolbox (MTB) is an app‐based ...research platform and expandable test library enabling remote assessment of cognition using participants’ own smartphones (iOS and Android). MTB facilitates conduct of diverse types of cognitive research with a broad range of participants, including those who may be hard to reach. However, evidence for MTB test validity, including demonstration of expected age‐related changes in adulthood, is needed to support MTB use. We present findings on associations between age and MTB performance.
Method
1,120 English‐speaking participants, ages 18–90, were recruited by a market research company as part of a larger study. Participants completed MTB remote measures of executive function, episodic and working memory, processing speed, and language on their smartphones. Measure order was fixed ((Vocabulary, Memory for Sequences, Spelling, Picture Sequence Memory (PSM), Flanker, Face Name (FNAME) Learning, Dimensional Change Card Sort (DCCS), Number Match, Face Name Memory)); individual tests could be taken anytime within a 14‐day period. Spearman correlation coefficients were calculated to evaluate relationships between age and test scores.
Result
Our participant sample was 57% female, 13% Hispanic, 72% white; mean age = 45 (sd = 21). Education distribution was: < high school (2%); high school (34%); some college (34%), college (20%), graduate degree (11%). Measures of executive function (DCCS and Flanker: r = ‐0.50; ‐0.57) and processing speed (r = ‐0.56) showed decreased performance with age (all p < 0.001). Episodic memory scores also decreased with age, but correlations were weaker (PSM and FNAME: ‐0.2, ‐0.35; p.<.001). Performance on language tests did not significantly decrease with age.
Conclusion
Most MTB measures correlated with age in the expected directions. Fluid cognition (e.g., executive function and processing speed) and memory typically decrease with age, and this decrease was reflected in MTB test performance. In contrast, crystallized abilities (e.g., spelling and vocabulary), which are typically preserved as we age, did not decrease in our sample. Initial results suggest MTB can be used to identify abnormal cognitive decline and support its use in cognitive aging research.
We describe the development of a new computer adaptive vocabulary test, Mobile Toolbox (MTB) Word Meaning, and validity evidence from 3 studies.
Word Meaning was designed to be a multiple-choice ...synonym test optimized for self-administration on a personal smartphone. The items were first calibrated online in a sample of 7,525 participants to create the computer-adaptive test algorithm for the Word Meaning measure within the MTB app. In Study 1, 92 participants self-administered Word Meaning on study-provided smartphones in the lab and were administered external measures by trained examiners. In Study 2, 1,021 participants completed the external measures in the lab and Word Meaning was self-administered remotely on their personal smartphones. In Study 3, 141 participants self-administered Word Meaning remotely twice with a 2-week delay on personal iPhones.
The final bank included 1363 items. Internal consistency was adequate to good across samples (ρxx = 0.78 to 0.81, p < .001). Test-retest reliability was good (ICC = 0.65, p < .001), and the mean theta score was not significantly different upon the second administration. Correlations were moderate to large with measures of similar constructs (ρ = 0.67-0.75, p < .001) and non-significant with measures of dissimilar constructs. Scores demonstrated small to moderate correlations with age (ρ = 0.35 to 0.45, p < .001) and education (ρ = 0.26, p < .001).
The MTB Word Meaning measure demonstrated evidence of reliability and validity in three samples. Further validation studies in clinical samples are necessary.
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