Differential Associations of Distinct Forms of Childhood Adversity With Neurobehavioral Measures of Reward Processing: A Developmental Pathway to Depression

Childhood adversity is associated with altered reward processing, but little is known about whether this varies across distinct types of adversity. In a sample of 94 children (6–19 years), we investigated whether experiences of material deprivation, emotional deprivation, and trauma have differential associations with reward-related behavior and white matter microstructure in tracts involved in reward processing. Material deprivation (food insecurity), but not emotional deprivation or trauma, was associated with poor reward performance. Adversity-related influences on the integrity of white matter microstructure in frontostriatal tracts varied across childhood adversity types, and reductions in frontostriatal white matter integrity mediated the association of food insecurity with depressive symptoms. These findings document distinct behavioral and neurodevelopmental consequences of specific forms of adversity that have implications for psychopathology risk.     

A Maximal Graded Exercise Test to Accurately Predict VO2max in 18–65-Year-Old Adults

The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO_2max) based on a maximal treadmill graded exercise test (GXT; George, 1996) George, J. D. 1996. Alternative approach to maximal exercise testing and VO_2max prediction in college students. Research Quarterly for Exercise and Sport, 67: 452–457. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]. Participants (N?=?100), ages 18–65 years, reached a maximal level of exertion (mean?±?standard deviation [SD]; maximal heart rate [HR_max]?=?185.2?±?12.4 beats per minute (bpm); maximal respiratory exchange ratio [RER_max]?=?1.18?±?0.05; maximal rating of perceived exertion (RPE_max)?=?19.1?±?0.7) during the GXT to assess VO_2max (mean?±?SD; 40.24?±?9.11 mL·kg^?1·min^?1). Multiple linear regression generated the following prediction equation (R?=?.94, standard error of estimate [SEE]?=?3.18 mL·kg^?1·min^?1, %SEE?=?7.9): VO_2max (mL·kg^?1·min^?1)?=?13.160?+?(3.314 × gender; females?=?0, males?=?1) ? (.131 × age) ? (.334 × body mass index (BMI))?+?(5.177 × treadmill speed; mph)?+?(1.315 × treadmill grade; %). Cross validation using predicted residual sum of squares (PRESS) statistics revealed minimal shrinkage (R_p ?=?.93 and SEE _p ?=?3.40 mL·kg^?1·min^?1); consequently, this model should provide acceptable accuracy when it is applied to independent samples of comparable adults. Standardized β-weights indicate that treadmill speed (.583) was the most effective at predicting VO_2max followed by treadmill grade (.356), age (?.197), gender (.183), and BMI (?.148). This study provides a relatively accurate regression model to predict VO_2max in relatively fit men and women, ages 18–65 years, based on maximal exercise (treadmill speed and grade), biometric (BMI), and demographic (age and gender) data.     

Continuing Research by PhD Graduates

A survey of Australian PhD graduates has revealed that they do not necessarily fit traditional stereotypes in terms of age, previous or concurrent work experience nor, perhaps most importantly, a prospective career in research. Two years after graduating with PhD, just 36 per cent of those who found employment in the non-academic workforce continued to be 'xtensively' involved in research, while only 56 per cent of those in academic employment (other than those with postdoctoral fellowships) were so involved. Many of those trained in research are frustrated in not being able to implement and extend that training through appropriate employment, others who have the opportunity do not have the desire. Factors predictive of and related to continuing involvement in research are examined, with some surprising results and policy implications regarding postgraduate research degrees.