Elementary disruptions? Exploring residential move type, timing, and duration of implications during middle childhood.

Moving is common during middle childhood, but links between move type and children's development are less well understood. Using nationally-representative, longitudinal data (2010-2016) of ~9900 U.S. kindergarteners (52% boys, 51.48% White, 26.11% Hispanic/Latino, 10.63% Black, 11.78% Asian/Pacific Islander), we conducted multiple-group fixed-effects models estimating associations of within- and between-neighborhood moves, family income, and children's achievement and executive function, testing whether associations persisted or varied by developmental timing. Analyses suggest important spatial and temporal dimensions of moving during middle childhood: between-neighborhood moves had stronger associations than within-neighborhood moves, earlier moves benefited development whereas later moves did not, and associations persisted with significant effect sizes (cumulative Hedges' g = -0.09-1.35). Research and policy implications are discussed.

Can we improve clinical prediction of at-risk older drivers?

OBJECTIVES: To conduct a pilot study to evaluate the predictive value of the Montreal Cognitive Assessment test (MoCA) and a brief test of multiple object tracking (MOT) relative to other tests of cognition and attention in identifying at-risk older drivers, and to determine which combination of tests provided the best overall prediction. METHODS: Forty-seven currently licensed drivers (58-95 years), primarily from a clinical driving evaluation program, participated. Their performance was measured on: (1) a screening test battery, comprising MoCA, MOT, Mini-Mental State Examination (MMSE), Trail-Making Test, visual acuity, contrast sensitivity, and Useful Field of View (UFOV) and (2) a standardized road test. RESULTS: Eighteen participants were rated at-risk on the road test. UFOV subtest 2 was the best single predictor with an area under the curve (AUC) of .84. Neither MoCA nor MOT was a better predictor of the at-risk outcome than either MMSE or UFOV, respectively. The best four-test combination (MMSE, UFOV subtest 2, visual acuity and contrast sensitivity) was able to identify at-risk drivers with 95% specificity and 80% sensitivity (.91 AUC). CONCLUSIONS: Although the best four-test combination was much better than a single test in identifying at-risk drivers, there is still much work to do in this field to establish test batteries that have both high sensitivity and specificity.