Investigating the accuracy of parentally reported weights and lengths at 12†months of age as compared to measured weights and lengths in a longitudinal childhood genome study.

BACKGROUND: Childhood obesity studies rely on parentally reported anthropometrics. However, the accuracy of such data has not been evaluated for 12-month-old children. Moreover, methods to improve the accuracy of reported data have not been assessed in prior studies. METHODS: A total of 185 children enrolled in a northern Virginia childhood longitudinal cohort genomic study had parentally completed surveys at 12 months. Measured weights and lengths were recorded for the same children from their 12-month paediatrician visit. Weight for length percentiles were calculated using World Health Organization gender-specific growth charts. The agreement between reported and measured values was examined using Pearson's correlation, paired t-test and κ statistics. The interquartile outlier rule was used to detect and remove outliers. RESULTS: Parentally reported weight was strongly associated with measured weight at 12 months (r=0.90). There was only a moderate correlation between parentally reported and measured lengths (r=0.52) and calculated weight for length percentiles (r=0.65). After removing outliers from parentally reported data, there was an increase in correlation between parentally reported and measured data for weight (r=0.93), length (r=0.69) and weight for length percentiles (r=0.76). Outliers removed compared to all children included were more likely to have maternal education less than a bachelor's degree (p=0.007). CONCLUSIONS: After removal of outliers from reported data, there is a strong correlation between calculated reported and measured weight for length percentiles suggesting that this may be an effective method to increase accuracy when conducting large-scale obesity studies in young children where study costs benefit from using parentally reported data.

The advantages and challenges of unannounced standardized patient methodology to assess healthcare communication.

OBJECTIVE: This paper provides an overview of the implementation of using unannounced standardized patients (USPs) to conduct health communication research in clinical settings. METHODS: Certain types of health communication situations are difficult to capture because of their rarity or unpredictable nature. In primary care the real reasons for a visit are frequently unknown until the consultation is well under way. Therefore, it is logistically difficult for communication studies to capture many real-time communications between patients and their physicians. Although the USP methodology is ideal for capturing these communication behaviors, challenges to using this method include developing collaborative relationships with clinical practices, logistical issues such as safeguarding the identity of the USP, training USPs and creating their identities, maintaining fidelity to the role, and analyzing the resultant data. RESULTS: This paper discusses the challenges and solutions to USP implementation. We provide an example of how to implement a USP study using an on-going study being conducted in primary care practices. CONCLUSION: This paper explores the advantages and challenges as well as strategies to overcome obstacles to implementing a USP study. PRACTICE IMPLICATIONS: Despite the challenges, USP methodology can contribute much to our understanding of health communication and practice.