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Description
Learning how to manage time efficiently is something that many people struggle with, college students in particular. The purpose of this study was to examine if personalization via self-experimentation of strategies to improve time management skills is a useful strategy for achieving this goal. This study used a multiple baseline

Learning how to manage time efficiently is something that many people struggle with, college students in particular. The purpose of this study was to examine if personalization via self-experimentation of strategies to improve time management skills is a useful strategy for achieving this goal. This study used a multiple baseline approach with three phases: phase one, the baseline, phase two, which included individuals receiving examples of plausible strategies to improve time management skills, and phase three, which involved the self-experimentation component. Results of this study suggest no significant changes in time management based on self-reported completion of tasks but do indicate a trend towards improved time management skills overall based on the time management questionnaire taken at the beginning and end of the study. These results suggest that further exploration in the use of self-experimentation strategies for improving time management is likely warranted but that current strategies likely require additional research. Results from the interviews indicate that the self-experimentation strategy, as delivered via PACO does increase awareness and thinking about time management.
ContributorsCope, Breanna (Author) / Hekler, Eric (Thesis director) / Buman, Matthew (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA

The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA shell surrounding the PLGA core. The microparticles were loaded with bovine serum albumin (BSA) and different volumes of ethanol were added to the PLA shell phase to alter the porosity and release characteristics of the BSA. Different amounts of ethanol varied the total loading percentage of the BSA, the release profile, surface morphology, size distribution, and the localization of the protein within the particles. Scanning electron microscopy images detailed the surface morphology of the different particles. Loading the particles with fluorescently tagged insulin and imaging the particles through confocal microscopy supported the localization of the protein inside the particle. The study suggest that ethanol alters the release characteristics of the loaded BSA encapsulated in the microparticles supporting the use of a polar, protic solvent as a tool for tuning the delayed release profile of biological proteins.
ContributorsFauer, Chase Alexander (Author) / Stabenfeldt, Sarah (Thesis director) / Ankeny, Casey (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description

The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and

The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.

ContributorsHan, Priscilla (Author) / Vernon, Brent (Thesis director) / Nickle, Jacob (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
Introduction: There is currently a lack of industry-wide gold standardization in accelerometer study
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate

Introduction: There is currently a lack of industry-wide gold standardization in accelerometer study
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
ContributorsMartin, Logan Rhett (Author) / Buman, Matthew (Thesis director) / Toledo, Meynard John (Committee member) / Kurka, Jonathan (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12