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Physical activity (PA) estimates from the Fitbit Flex 2 were compared to those from the ActiGraph GT9X Link in 123 elementary school children. Steps and intensity-specific estimates of PA and 3-month PA change were calculated using two different ActiGraph cut-points (Evenson and Romanzini). Fitbit estimates were 35% higher for steps compared to the ActiGraph. Fitbit and ActiGraph intensity-specific estimates were closest for sedentary and light PA, while estimates of moderate and vigorous PA varied substantially depending upon the ActiGraph cut-points used. Spearman correlations between device estimates were higher for steps (r[subscript s] = 0.70) than for moderate (r[subscript s] = 0.54 to 0.55) or vigorous (r[subscript s] = 0.29 to 0.48) PA. There was low concordance between devices in assessing PA changes over time. Agreement between Fitbit Flex 2 and ActiGraph estimates may depend upon the cut-points used to classify PA intensity. However, there is fair to good agreement between devices in ranking children's steps and MVPA.

Physical activity (PA) estimates from the Fitbit Flex 2 were compared to those from the ActiGraph GT9X Link in 123 elementary school children. Steps and intensity-specific estimates of PA and 3-month PA change were calculated using two different ActiGraph cut-points (Evenson and Romanzini). Fitbit estimates were 35% higher for steps compared to the ActiGraph. Fitbit and ActiGraph intensity-specific estimates were closest for sedentary and light PA, while estimates of moderate and vigorous PA varied substantially depending upon the ActiGraph cut-points used. Spearman correlations between device estimates were higher for steps (rs =.70) than for moderate (rs =.54 to.55) or vigorous (rs =.29 to.48) PA. There was low concordance between devices in assessing PA changes over time. Agreement between Fitbit Flex 2 and ActiGraph estimates may depend upon the cut-points used to classify PA intensity. However, there is fair to good agreement between devices in ranking children's steps and MVPA. [ABSTRACT FROM AUTHOR]

This article discusses a service quality study conducted in the Pennsylvania State University Libraries. The Wisconsin-Ohio Reference Evaluation Program survey was selected as a valid, standardized instrument. We present our results, highlighting the impact on reference training. A second survey a year later demonstrated that focusing on behavioral aspects of reference can improve service quality ratings.

A usability study was undertaken at Penn State University to explore how students search the library's online catalog after they have received library instruction. In 2004, eight first-year students received library instruction and were subsequently recruited for the study. Participants were recorded using the online catalog, and a think-aloud protocol was employed to capture students' thoughts. Results were compared with nine first-year students observed in 2002, using the same methodology. Analysis of both groups revealed subtle differences in how they utilized the online catalog. Although these differences cannot be definitively attributed to library instruction, the evidence suggests that instruction can have a positive effect on user search behaviors. The article recommends strategies for increasing the impact of library instruction. (Contains 35 notes.)

Discussion of electronic library reference services focuses on an overview of the chief methodologies available for conducting assessments of electronic services. Highlights include quantitative measures and benchmarks, including equity and access; quality measures; behavioral aspects of quality, including librarian-patron interaction; and future developments. (Author/LRW)