PHP: Learning from 2 Perspectives
During the interview phase of the PHP, Emmelyn expressed that she wanted to get on a more consistent eating schedule, since last semester she sometimes missed both breakfast and lunch because of her busy class schedule, and then had to have a large dinner to fill her up. Emmelyn wanted to stop running into this issue and eat meals throughout the day to keep her full and alert in class. To collect daily data, Emmelyn wrote down everything she ate as well as what time she ate it. I then took this information and logged the number of meals she had eaten that day, and also calculated the percentage of each food group that she consumed that day. Though Emmelyn’s primary goal was to eat 3 meals a day, she also expressed some interest in eating healthier, so this additional data allowed us to compare her daily food group intake percentages with the recommended values.
From the preliminary data, before intervention, I noticed that this semester her schedule allows her to eat lunch, but she still rarely eats breakfast. Because we wanted to plan an intervention that would be easy to follow and that would not add a lot of time to her busy schedule, I had her try taking a piece of fruit from the dining hall at dinner so that she could save it and eat it in the morning, possibly even on her way to class to save time. Emmelyn felt that the fruit intervention helped, but only when she remembered to grab it from the dining hall and eat it in the morning. She thinks that an intervention like this could work long-term if she got into the habit of grabbing food the night before and putting it in her backpack so she wouldn’t forget to eat it. Also, Emmelyn expressed that it would be more helpful to grab cereal or yogurt instead, since a piece of fruit isn’t the most filling breakfast.
Emmelyn also noticed that writing down everything she was eating made her more conscious of her diet and in the beginning it encouraged her to make healthier decisions. However, as time went on, other situational and environmental factors (ex. candy at IDEAS report meetings) were more influential and she was less concerned with eating healthy. Emmelyn also commented on how the calculated food group percentages seemed skewed and that she felt they didn’t accurately represent the relative proportions she was eating. We think that some of this is attributed to the small portions at Newcomb and also the fact that she doesn’t always eat all of the food she puts on her plate. Turning her food log into food group percentages was something I also struggled with, as I found it difficult to determine what counted as, for example, 1 serving of fruit or meat, and make these percentages relevant to portion size. I learned that although it seemed that it would be insightful to break down the original data into additional data, doing so can sometimes result in inaccuracies when there isn’t a hard line for classification.
About halfway through this process, we also started tracking Emmelyn’s alertness in class to see if eating breakfast and lunch helped keep her more focused in class. From the data, it seemed to me that eating three meals on a given day didn’t necessarily help her focus in class; it seemed that her alertness was moreso related to other factors such as teaching styles. Interestingly, Emmelyn noticed that eating food during class helped her stay focused because she had something to do in addition to listening to the lecture. Although she noticed this, Emmelyn thinks that the class alertness data was impacted largely by the fact that she was sick during the week we collected the data.
When Emmelyn and I talked about the data and reflected on this first round of the PHP, we found it interesting to listen to each other’s explanations and interpretations of the data. Discussing some of the flaws and confounding variables affecting the data helped fill in the gaps and better understand the data collected throughout the process.
BME Design 