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- All Subjects: Technology
- Creators: Electrical Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Purpose: This qualitative research aimed to create a developmentally and gender-appropriate game-based intervention to promote Human Papillomavirus (HPV) vaccination in adolescents. <br/>Background: Ranking as the most common sexually transmitted infection, about 80 million Americans are currently infected by HPV, and it continues to increase with an estimated 14 million new cases yearly. Certain types of HPV have been significantly associated with cervical, vaginal, and vulvar cancers in women; penile cancers in men; and oropharyngeal and anal cancers in both men and women. Despite HPV vaccination being one of the most effective methods in preventing HPV-associated cancers, vaccination rates remain suboptimal in adolescents. Game-based intervention, a novel medium that is popular with adolescents, has been shown to be effective in promoting health behaviors. <br/>Methods: Sample/Sampling. We used purposeful sampling to recruit eight adolescent-parent dyads (N = 16) which represented both sexes (4 boys, 4 girls) and different racial/ethnic groups (White, Black, Latino, Asian American) in the United States. The inclusion criteria for the dyads were: (1) a child aged 11-14 years and his/her parent, and (2) ability to speak, read, write, and understand English. Procedure. After eligible families consented to their participation, semi-structured interviews (each 60-90 minutes long) were conducted with each adolescent-parent dyad in a quiet and private room. Each dyad received $50 to acknowledge their time and effort. Measure. The interview questions consisted of two parts: (a) those related to game design, functioning, and feasibility of implementation; (b) those related to theoretical constructs of the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). Data analysis. The interviews were audio-recorded with permission and manually transcribed into textual data. Two researchers confirmed the verbatim transcription. We use pre-developed codes to identify each participant’s responses and organize data and develop themes based on the HBM and TPB constructs. After the analysis was completed, three researchers in the team reviewed the results and discussed the discrepancies until a consensus is reached.<br/>Results: The findings suggested that the most common motivating factors for adolescents’ HPV vaccination were its effectiveness, benefits, convenience, affordable cost, reminders via text, and recommendation by a health care provider. Regarding the content included in the HPV game, participants suggested including information about who and when should receive the vaccine, what is HPV and the vaccination, what are the consequences if infected, the side effects of the vaccine, and where to receive the vaccine. The preferred game design elements were: 15 minutes long, stories about fighting or action, option to choose characters/avatars, motivating factors (i.e., rewards such as allowing users to advance levels and receive coins when correctly answering questions), use of a portable electronic device (e.g., tablet) to deliver the education. Participants were open to multiplayer function which assists in a facilitated conversation about HPV and the HPV vaccine. Overall, the participants concluded enthusiasm for an interactive yet engaging game-based intervention to learn about the HPV vaccine with the goal to increase HPV vaccination in adolescents. <br/>Implications: Tailored educational games have the potential to decrease the stigma of HPV and HPV vaccination, increasing communication between the adolescent, parent, and healthcare provider, as well as increase the overall HPV vaccination rate.
This honors thesis explores the potential use of LoRa technology for detecting moisture in a diaper. Tests of both onboard and external humidity sensors coupled with LoRa transmission are incredibly promising. The potential scale of the final device also shows much promise, measuring smaller than a U.S. dime. However, the estimated cost for producing these proof-of-concept units in bulk is $19.41 per unit. While this is believed to be a pessimistic estimate of the price, the cost of production remains too high regardless for large-scale implementation. The thesis concludes by emphasizing the need for further research and development to optimize the design and reduce the cost of production. Despite the limitations imposed by price, the idea of using LoRa in detecting moisture in a diaper remains intriguing and promising, however, RFID technology has many advantages, such as size, cost, and passive power features.
There are quite a few readily available products that one can buy if one looks past some of their flaws. A lot of these alarms either require a user to carry an extra communication device, or they are too big or expensive. The proposed solution merges all desirable features of a bike alarm into one module. In light of this, surveys were conducted to ascertain what these qualities would need to be. The top considerations for purchasing this alarm were how costly it would be, the false detection rate, and also the battery life. Additionally, the features that were most requested was the inclusion of a GPS and a camera. In order to incorporate these features, a three year plan was formulated which would culminate into a bike network in which each bike could communicate with other bikes. This would allow for an IOT network to be established, thus far exceeding expectations. The price point for this alarm is USD $10.00-15.00 and can come in a variety of colors. Additionally, this concept can be applied to many different scenarios, from protecting boats/jet skis and other aquatic vehicles, to houses as well. Furthermore, one could miniaturize this technology to be used in jewelry or accessories.
This paper serves to report the research performed towards detecting PD and the effects of medication through the use of machine learning and finger tapping data collected through mobile devices. The primary objective for this research is to prototype a PD classification model and a medication classification model that predict the following: the individual’s disease status and the medication intake time relative to performing the finger-tapping activity, respectively.
This paper serves to report the research performed towards detecting PD and the effects of medication through the use of machine learning and finger tapping data collected through mobile devices. The primary objective for this research is to prototype a PD classification model and a medication classification model that predict the following: the individual’s disease status and the medication intake time relative to performing the finger-tapping activity, respectively.