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Developmental conditions in adolescent athletes, such as ADHD and learning difficulties, are associated with a greater prevalence rate of prior concussion.

The aim of this study was to examine brain neurometabolite concentrations in retired rugby league players who had a history of numerous self-reported concussions. Participants were 16 retired professional rugby league players (ages 30-45 years) with an extensive history of concussion and participation in contact sports, and 16 age- and education-matched controls who had no history of neurotrauma or participation in contact sports. All completed a clinical interview, psychological and cognitive testing, and magnetic resonance spectroscopy (MRS) investigation. MRS voxels were placed in posterior cingulate grey matter and parietal white matter. Neurometabolite concentrations were quantified using LCModel. It was hypothesized that retired athletes would differ on N-acetyl aspartate, myo-inositol, choline, glutamate, and glutathione. Retired players had significantly lower concentrations of grey matter glutathione (p=0.02, d=0.91). They did not significantly differ in concentrations of other neurometabolites. There were no significant differences between groups on measures of depression, anxiety, or cognitive functioning. The retired athletes reported significantly greater alcohol use (p<0.01; Cohen's d=1.49), and they had worse manual dexterity using their non-dominant hand (p=0.03; d=1.08). These preliminary findings suggest that MRS might be modestly sensitive to biochemical differences in athletes after their athletic careers have ended in the absence of clinical differences in cognitive performance and self-reported psychological functioning.

The oral Symbol Digit Modalities Test (SDMT) has been recommended to assess cognition for multiple sclerosis (MS) patients. However, the lack of adequate normative data has limited its clinical utility. Recently published regression-based norms may resolve this limitation but, because these norms were derived from a relatively small sample, their stability is unclear. We aimed to evaluate the stability of regression-based SDMT norms by comparing existing norms to a cross-validation dataset. First, regression-based normative data were created from a similarly-sized, independent, control sample (n = 94). Next the original and cross-validation norms were compared for equivalency, management of demographic influences, construct validity, and impairment classification rates in a mildly affected MS sample (n = 70). Lastly, similar comparisons were made for a large, representative MS clinic sample (n = 354). We found construct validity and management of demographic influences were equivalent for the two sets of regression-based norms but lower T-scores were obtained using the original dataset, resulting in discrepancies in impairment classification. In conclusion, regression-based norms for the oral SDMT attenuate demographic influences and possess adequate construct validity. However, norms generated using small samples may yield unreliable classification of cognitive impairment. Larger, representative databases will be necessary to improve the clinical utility of regression-based norms.

BackgroundAttrition is a persistent issue in online self-help programs, but limited research is available on reasons for attrition or successful methods for improving participant retention. One potential approach to understanding attrition and retention in such programs is to examine person-related variables (eg, beliefs and attitudes) that influence behavior. Theoretical models, such as the Theory of Planned Behavior, that describe conditions influencing human behavior may provide a useful framework for predicting participant retention in online-based program.ObjectiveWe examined predictors of participant retention in a guided online anxiety, depression, and stress self-help program for university students using the theory of planned behavior. We also explored whether age, symptom severity, and type of coaching (ie, email vs phone) affected participant retention.Methods65 university students with mild to moderate depression, anxiety, and stress were enrolled in this prospective cohort study. Participants completed a questionnaire based on the theory of planned behavior prior to commencing the online-based program and the Depression Anxiety and Stress Scale (DASS) during the assessment module of the program. Participant retention was operationalized as the number of program modules completed.ResultsPerceived control over completing the online program significantly predicted intention to complete the program (F3,62=6.7; P=.001; adjusted R2=.2; standardized beta=.436, P=.001). Age (standardized beta=.319, P=.03) and perceived behavioral control (standardized beta=.295, P=.05) predicted the number of program modules completed (F3,61=3.20, P=.03, adjusted R2 =.11). Initial level of distress (ie, symptom severity) did not predict participant retention (P=.55). Participants who chose phone-based coaching completed more program modules than participants who chose email-based coaching (Mann-Whitney’s U=137; P=.004).ConclusionsParticipants’ age, level of perceived behavioral control, and choice of interaction (ie, phone-based or email-based coaching) were found to influence retention in this online-based program.

Among MS patients, greater functional connectivity between medial prefrontal and frontal pole regions appears to facilitate performance stability on complex speed-dependent information processing tasks.

Deficits in information processing speed are among the most commonly reported impairments in multiple sclerosis (MS) and are generally assessed by evaluating mean-level performance on time-limited tests. However, this approach to assessing performance ignores potential within-subject differences in MS patients that may be useful for characterizing cognitive difficulties in MS. An alternative method of measuring performance is by examining the degree of within-subject variability, termed intra-individual variability (IIV). Intra-individual variability provides information about the characteristics of a person's performance over time and may provide novel information about cognitive functioning in MS. This study examined IIV in performance on the Computerized Test of Information Processing (CTIP) using two within-subject variability methods: individual standard deviation and coefficient of variation. Eighteen females with relapsing-remitting MS and 18 healthy female controls completed the CTIP. Consistent with previous research, MS patients demonstrated slower overall mean performance on the CTIP compared with controls, with patients becoming increasingly slower than controls as cognitive demands increased across the tasks. Furthermore, MS patients demonstrated greater IIV as measured by individual standard deviations on all subtests of the CTIP, even with mean-level group differences as well as practice and learning effects controlled. These between-group differences were not found when the coefficient of variation, a more coarse measure of within-subject variability, was used. Intra-individual variability was also found to be a better predictor of neurologic status than mean-level performance. These results suggest that IIV may provide unique insight into cognitive functioning in MS. Int J MS Care. 2012;14:77-83.