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Clorie Labeling

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America’s struggles with fast food and its subsequent health consequences have given raise to a number of macro interventions (Harnack et al., 2008). Point of purchase calorie labeling at fast food restaurants has been proposed as an option of improving consumer food choices. However, Harnack et al. (2008) evaluated the effectiveness of calorie labeling amongst 594 fast food consumers and determined that calorie labelling resulted in no significant differences in the calorie count of meals ordered. Increasing the price of fast food through tax has also been proposed as an intervention to decrease fast food consumption. Powell et al.’s (2006) research among adolescents revealed that a 10% increase in the price of fast food resulted in a 3% increase …show more content…

Data from college students revealed that preparing meals at home was strongly associated with healthy dietary patterns such as eating breakfast, infrequent fast food consumption, and increased vegetable and fruit consumption (Laska et al., 2015). Wolfson & Bleich (2014) found that cooking dinner at home frequently (≥2 times/week) was associated with better diet quality, specifically lower consumption of total calories, carbohydrates, fat, sugar, and fast food. Taillie & Poti (2017) research among low income adults demonstated that those who reported daily home cooked dinners had lower solid fat intake, calorie dense meals, and fast food meals. This study suggest that those with a limited budget for food may benefit both financially and physically from home meal …show more content…

The A-B design allows for a timely assessment of the indicators of the goal which compares baseline to intervention. Collecting data from the baseline phase as opposed to only the intervention phase bolsters the study’s internal validity by decreasing the likelihood of confounding variables. This design also allows for adequate collection of data points within the time constraints of this study. Although an A-B-A design could strengthen internal validity and further minimize the risk of confounding variables, the time constraint of this intervention would not allow for adequate data collection in three phases. An A-B-A design would also eliminate the opportunity to use the average score from multiple days which could lead to a difficult visual analysis. The client has also stated a desire to continue with this intervention beyond the scope of this study, therefore, any withdrawal or removal of this intervention would raise ethical concerns.
The baseline (A) phase will last 8 days and the intervention (B) phase will last 22 days. Data will be recorded daily and displayed as a two-day average of the course of study so that there will be 4 data points for the baseline phase and 11 for the intervention phase. Averaging the data from two days will help lessen the effects of confounding data and outliers on the results. Using fewer data points will also create a more decipherable graph which can accurately display the overall trends within the

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