The Anticipation Builds: Preparing Data for Analysis

Hey y’all!

I’m so excited to send out my first research update! During my time in the lab thus far, I have been conducting an in-depth literature review of mentoring studies. The bulk of the literature focuses on youth characteristics that influence the mentoring relationship. These characteristics include youth environmental stress and behavioral challenges. I have only found one study that touches on mentor emotional background so I hope that I will be able to meaningfully contribute to the mentoring literature at the conclusion of my research! I will analyze mentor stress using two scales: The Risky Families Questionnaire, which measures early life and familial stress, and the Student Stress Scale, which measures previous or ongoing stress in multiple aspects of life. Combined, these two scales will allow me to not only measure mentor stress, but also will allow me to better understand the effects of different types of stressors on mentoring relationships. I will measure mentor depression using the CESDR-10 scale, and I will run analyses analyzing the relationship between mentor’s reported depression and stress levels.

In preparation for these analyses, I have been working on my data sets, making sure they are fully cleaned and ready to go. I am working with the data from Dr. Raposa’s longitudinal study which partners with two school-based mentoring programs, one in the United States and one in Mexico. These partnerships give us access to data on hundreds of mentor/mentee pairs from colleges across the US and Mexico, but before we can analyze the data, we need to enter, code, clean, and de-identify it. The data for my study is almost ready for analyses, and since I manage the data work for all Dr. Raposa’s mentoring study, I’ve also been training research assistants and working on some other data tasks. Additionally, we also do separate data work for our mentoring program partner organizations to help them improve their programs. So right now I am also working on a task for our partner in the United States related to mentor retention.

Check back next week for some cool findings about the relationship between mentor stress and depression and youth/mentor relationship satisfaction!

Comments

  1. This is so interesting! I can’t wait to hear about your future findings

  2. Hi Emma, your research topic, predicting the effectiveness of youth mentoring interventions, really aroused my interest. I am Psychology major myself, so I read a lot about the youth depression and the program you mentioned, mentoring program. I always wondering about whether the mentoring program is useful or, it might just be “placebo”? So I really expect to see your final result. In addition, you mentioned that you have 271 participants selected randomly, I wonder how you ensure the randomness of the sample? Moreover, I really like the point that you used the longitudinal data, since the focus of research is to examine the before and after. I have friend used the cross-sectional study instead.
    By the way, I will take Dr. Raposa’s Psyc318 Abnormal psychology next semester!

  3. egpreston says:

    Hi! That is a great question, but not quite the focus of my research so unfortunately I do not have a great answer for you. The literature extensively supports the theory of attachment and has shown that mentoring programs can have the potential to impact youth (see my post “Mentors are Necessary”). Therefore my work focuses more on specific elements of mentoring programs with the intent of increasing program efficacy and evidence based mentoring practices. However it would be quite interesting to look at the potential of a placebo effect in a mentoring program!

    This study is unique because the mentor pairs are randomly assigned. Since we work with a national mentoring organization, we offered admission to the study to all youth/mentors who signed up for the program. Most mentoring programs use questions asked at the time of enrollment to guide their matching process. For example, they might match a child who loved baseball to a mentor who played baseball. This has the potential to confound data, particularly data regarding relational satisfaction. In order more accurately assess characteristics of the mentoring relationship such as stress and depression, it was important to us that the match pairs were random. This is the randomization element I referred to.

    I took abnormal with Dr. Raposa last fall and it was awesome–enjoy 🙂

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