Should We Be Confident in Published Research? A Case Study of Confidence Interval Reporting in Health Education and Behavior Research

Confidence intervals (CIs) have been highlighted as “the best” reporting device when reporting statistical findings. However, researchers often fail to maximize the utility of CIs in research. We seek to (a) present a primer on CIs; (b) outline reporting practices of health researchers; and (c) discuss implications for statistical best practice reporting in social science research. Approximately 1,950 peer-reviewed articles were examined from six health education, promotion, and behavior journals. We recorded: (a) whether the author(s) reported a CI; (b) whether the author(s) reported a CI estimate width, either numerical or visual; and (c) whether an associated effect size was reported alongside the CI. Of the 1,245 quantitative articles in the final sample, 46.5% (n = 580) reported confidence interval use; , and 518 provided numerical/visual interval estimates. Of the articles reporting CIs, 383 (64.2%) articles reported a CI with an associated effect size, meeting the American Psychological Association’s (APA) recommendation for statistical reporting best-practice. Health education literature demonstrates inconsistent statistical reporting practices, and falls short in employing best practices and consistently outlining the minimum expectations recommended by APA. In an effort to maximize utility and implications of health education, promotion, and behavior research, future investigations should provide comprehensive information regarding research findings

Understanding Contraceptive Behaviors Among Latinas

In the United States, Latinas account for one-fourth of unintended pregnancies with more than half become pregnant before they even turn 20 years old. Exploring influential factors that impact contraception behaviors could aid in understanding unintended pregnancy among this population. The aim of this dissertation was to assess reproductive autonomy beliefs, marianismo beliefs, and contraception behaviors among an exclusively Latina sample and explore the relationships between these constructs. In the United States, Latinas account for one-fourth of unintended pregnancies with more than half becoming pregnant before they even turn 20 years old. Exploring influential factors that impact contraception behaviors could aid in understanding unintended pregnancy among this population. The aim of this dissertation was to assess reproductive autonomy beliefs, marianismo beliefs, and contraception behaviors among an exclusively Latina sample and explore the relationships between these constructs. Participant survey data from 567 Latinas was used to run Structural Equation Models. Results indicated that aspects of reproductive autonomy influence contraception negotiation skills, in a monogamous relationship (est. = 0.582; p = 0.000) and while single (est. = 0.198; p = 0.000). Marianismo beliefs were seen to influence contraception negotiation skills in a monogamous relationship (est. = -0.349; p = 0.003) and current contraception use (est. = -0.516; p = 0.008). Mediation models also confirmed that marianismo beliefs partially mediated the relationship between certain reproductive autonomy beliefs and contraception negotiation skills in a monogamous relationship. Culturally tailored interventions are needed to reduce unintended pregnancy rates among Latinas

Microcontroller-based fitness monitoring system

Knowledge of one\u27s personal health condition is widely talked about these days. Monitoring our own health condition could lead us to different kinds of action. However, health and fitness monitoring systems that are available these days aren\u27t capable of measuring and detecting different king of health and fitness status of a person. This research project aims to monitor and check a person\u27s health and fitness conditions, specifically a person\u27s weight, height, blood pressure, and heart. With these parameters measured and detected, other different parameters can also be computed by means of different scientifically tested formulas and equations. These other said parameters such as the Body Mass Index, Body Fat Content, Maximum Heart Rate, and Target Heart Rate could help a person tell whether he or she is physically fit or not. The system could also tell a person\u27s physical condition such as Obese, Physically Fit, Normal Weight, Underweight, and Overweight. A Microcontroller is used as the main control of the system. The system will be using different kind of sensors for measuring and detecting the different said parameters. Sensors such as a load sensor, ultrasonic sensor, and a digital blood pressure sphygmomanometer detect the weight, height, and the blood pressure respectively. By automating the system, the person can right away identify the said parameters in just a small amount of time. With these parameters measured, a person can right away tell his or her physical condition. Physical activities and having a good nutrition are known key factors in leading to a person\u27s healthy lifestyle and reducing risk for some certain known diseases. However, checking ones fitness condition by means of such health and fitness monitoring systems can also help a person prevent and reduce such diseases