Precision Across Scientific Methods: Integrating Rigor and Care Into Assessment of Nutrition Education and Behavior Outcomes

Precision Across Scientific Methods: Integrating Rigor and Care Into Assessment of Nutrition Education and Behavior Outcomes

From JNEB Precision Across Scientific Methods: Integrating Rigor and Care Into Assessment of Nutrition Education and Behavior Outcomes An ongoing chal...

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From JNEB Precision Across Scientific Methods: Integrating Rigor and Care Into Assessment of Nutrition Education and Behavior Outcomes An ongoing challenge in the field of nutrition education and behavior is the ability to gather nutrition-related data (whether food and nutrient intakes or the knowledge, attitudes, and behaviors leading to intake) in a manner that is representative, accurate, and valid. A thread that is woven throughout this issue of JNEB is that of establishing trustworthiness and precision to improve the methodological rigor and the quality of data in our research. During a time when the nutrition field is experiencing intense and increasing scrutiny regarding the reliability and validity of the reported data, a focus on improving our methods—qualitative, quantitative, and mixed method designs—is timely, necessary, and critical for maintaining the contribution of nutrition education and behavior science to the intervention and health care fields. Goodell et al1 examine the concept of trustworthiness in the context of qualitative research and the impact that training and experience have upon the building of trustworthiness in qualitative studies. As these authors point out, attention to the details of training for both interviewers and coders often is left undescribed in our publications but can have a profound impact upon the gathering of data as well as the findings of our research. This point is both intuitive and underappreciated. However, most

interesting to me was the discussion of how investigator experience can translate into bad habits and, therefore, bias in results. These authors point out that there can be a fine line between the insight born of previous experience and the unwanted influence that can creep into interview guides and spontaneous probes during qualitative data gathering. The challenge for researchers is to insert sufficient rigor in training and to stay aware of the bias that can unwittingly alter data collection and analysis. A similar stance of improving the validity and reliability of nutrition data is considered by Hand et al2 in their discussion of ecological momentary assessment (EMA). These authors make a compelling case for the inclusion of EMA to help address some of the limitations of more traditional survey methods (ie, dietary assessments and subjective assessments of hunger and satiety) as EMA can address concerns related to social desirability, poor memory, and systematic underreporting. Because these methods utilize repeated, real-time assessments and occur in naturalistic settings (like the use of pedometers or mobile applications that measure food intake or physical activity), they may have the capacity to offer less biased information and a broader perspective of individual health-related habits. As technological innovations become increasingly accessible for data collection, the prospect of utilizing EMA to form databases that provide a larger overall picture of nutrition-related outcomes

is becoming more feasible. The challenge, however, will be to also learn how to manage and analyze the ‘‘big data’’ that comes with these approaches. While each methodology has its advantages and pitfalls, the focus on improvements in rigor and the care with which protocols are implemented could not be deliberated at a more opportune moment. Nutrition education and behavior research must continue to strive to be its best self: insightful, meticulous, and innovative. It appears that the old adage may be true: the devil may very well be in the details. But in this case, the devilish aspects will prove to increase the confidence and ability of the researchers to hypothesize, interpret, and create programs and resources that improve the likelihood of facilitating knowledge acquisition and positive behavior change. Susan L. Johnson, PhD Associate Editor

REFERENCES 1. Goodell LS, Stage VC, Cooke NK. Practical qualitative research strategies: training interviewers and coders. J Nutr Educ Behav. 2016;48:578-585. 2. Hand RK, Perzynski AT. Ecologic momentary assessment: perspectives on applications and opportunities in research and practice regarding nutrition behaviors. J Nutr Educ Behav. 2016;48: 568-577.