Evidence for measurement bias of the short form health survey based on sex and metropolitan influence zone in a secondary care population.

BACKGROUND AND OBJECTIVES: The 12-item Short Form Health Survey (SF-12) is a widely used measure of health related quality of life, but has been criticized for lacking an empirically supported model and producing biased estimates of mental and physical health status for some groups. We explored a model of measurement with the SF-12 and explored evidence for measurement invariance of the SF-12. RESEARCH DESIGN AND METHODS: The SF-12 was completed by 429 caregivers who accompanied patients with cognitive concerns to a memory clinic designed to service rural/remote-dwelling individuals. A multi-group confirmatory factor analysis was used to compare the theoretical measurement model to two empirically identified factor models reported previously in general population studies. RESULTS: A model that allowed mental and physical health to correlate, and some items to cross-load provided the best fit to the data. Using that model, measurement invariance was then assessed across sex and metropolitan influence zone (MIZ; a standardized measure of degree of rurality). DISCUSSION: Partial scalar invariance was demonstrated in both analyses. Differences by sex in latent item intercepts were found for items assessing feelings of energy and depression. Differences by MIZ in latent item intercepts were found for an item concerning how current health limits activities. IMPLICATIONS: The fitting model was one where the mental and physical health subscales were correlated, which is not provided in the scoring program offered by the publishers. Participants' sex and MIZ should be accounted for when comparing their factor scores on the SF-12. Additionally, consideration of geographic residence and associated cultural influences is recommended in future development and use of psychological measures with such populations.

Comparison across age groups of causes, circumstances, and consequences of falls among individuals living in Canada: A cross-sectional analysis of participants aged 45 to 85 years from the Canadian Longitudinal Study on Aging.

Falls are a leading cause of injury-related deaths and hospitalizations among Canadians. Falls risk has been reported to be increased in individuals who are older and with certain health conditions. It is unclear whether rurality is a risk factor for falls. This study aimed to investigate: 1) fall profiles by age group e.g., 45 to 54 years, 55 to 64 years, 65 to 74 years, 75 to 85 years; and 2) falls profiles of individuals, by age group, living in rural versus urban areas of Canada. Data (N = 51,338) from the Canadian Longitudinal Study on Aging was used to examine the relationship between falls and age, rurality, chronic conditions, need for medical attention, and fall characteristics (manner, location, injury). Self-reported falls within a twelve-month period occurred in only 4.8% (single fall) and 0.8% (multiple falls) of adults. Falls were not related to rural residence or age, but those with memory impairment, multiple sclerosis, as well as other chronic conditions such as mood disorder, anxiety disorder, and hyperthyroidism not often thought to be associated with falls, were also more likely to fall. Older individuals were more likely to fall indoors or fall while standing or walking. In contrast, middle-aged individuals were more likely to fall outdoors or while exercising. Type of injury was not associated with age, but older individuals were more likely to report hospitalization after a fall. This study shows that falls occur with a similar frequency in individuals regardless of age or urban/rural residence. Age was associated with fall location and activity. A more universally applicable multi-facted approach, rather than one solely based on older age considerations, to screening, primary prevention and management may reduce the personal, social, and economic burden of falls and fall-related injuries.

Hippocampal atrophy and cognitive function in transient ischemic attack and minor stroke patients over three years.

Introduction: Transient ischemic attack (TIA) and minor ischemic stroke (IS) is associated with a increased risk of late life dementia. In this study we aim to study the extent to which the rates of hippocampal atrophy in TIA/IS differ from healthy controls, and how they are correlated to neuropsychological measurements. Methods: TIA or minor stroke patients were tested with a neuropsychological battery including tests of executive function, and verbal and non-verbal memory at three time points out to 3 years. Annualized rates of hippocampal atrophy in TIA/IS patients were compared to controls. A linear-mixed regression model was used to assess the difference in rates of hippocampal atrophy after adjusting for time and demographic characteristics. Results: TIA/IS patients demonstrated a higher hippocampal atrophy rate than healthy controls over a 3-year interval: the annual percentage change of the left hippocampal volume was 2.5% (78 mm3 per year (SD 60)) for TIA/IS patients compared to 0.9% (29 mm3 per year (SD 32)) for controls (p < 0.01); and the annual percentage change of the right hippocampal volume was 2.5% (80 mm3 per year (SD 46)) for TIA/IS patients compared to 0.5% (17 mm3 per year (SD 33)) for controls (P < 0.01). Patients with higher annual hippocampal atrophy were more likely to report higher TMT B times, but lower ROC total score, lower California Verbal Learning Test-II total recall, and lower ROC Figure recall scores longitudinally. Conclusion: TIA/IS patients experience a higher rate of hippocampal atrophy independent of TIA/IS recurrence that are associated with changes in episodic memory and executive function over 3 years.

Reliable change and minimum clinically important difference (MCID) of the Repeatable Battery for the Assessment of Neuropsychology Status (RBANS) in a heterogeneous dementia sample: Support for reliable change methods but not the MCID.

We compare reliable change scores and recently published anchor-based cutoffs for minimum clinically important difference (MCID) for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in a sample of patients diagnosed with various forms of dementia. For memory clinic patients with dementia evaluated twice over a one-year interval (N = 53), observed retest RBANS index scores were compared with predicted retest index scores based on regression formulae developed from cognitively healthy older adults. Patient RBANS change scores were also compared to suggested MCID anchors. Patients with dementia demonstrated a reliable decline on most RBANS indices, with evidence that the Visuospatial/Constructional and Language Indices might be less sensitive to decline over time. Although there was consistency between MCID and reliable changes in this sample, there was a substantial proportion where the MCID was exceeded, with no reliable change. We attempted to create MCIDs from the Clinical Dementia Rating Sum of Box scores for RBANS reliable change scores, but failed to find significant associations. Overall, the findings support use of the regression based reliable change approach, but we caution use of the MCID approach for the RBANS.

Scoring algorithms for a computer-based cognitive screening tool: An illustrative example of overfitting machine learning approaches and the impact on estimates of classification accuracy.

Computerized cognitive screening tools, such as the self-administered Computerized Assessment of Memory Cognitive Impairment (CAMCI), require little training and ensure standardized administration and could be an ideal test for primary care settings. We conducted a secondary analysis of a data set including 887 older adults (M age = 72.7 years, SD = 7.1 years; 32.1% male; M years education = 13.4, SD = 2.7 years) with CAMCI scores and independent diagnoses of mild cognitive impairment (MCI). A study by the CAMCI developers used a portion of this data set with a machine learning decision tree model and suggested that the CAMCI had high classification accuracy for MCI (sensitivity = 0.86, specificity = 0.94). We found similar support for accuracy (sensitivity = 0.94, specificity = 0.94) by overfitting a decision tree model, but we found evidence of lower accuracy in a cross-validation sample (sensitivity = 0.62, specificity = 0.66). A logistic regression model, however, discriminated modestly in both training (sensitivity = 0.72, specificity = 0.80) and cross-validation data sets (sensitivity = 0.69, specificity = 0.74). Evidence for strong accuracy when overfitting a decision tree model and substantially reduced accuracy in cross-validation samples was replicated across 500 bootstrapped samples. In contrast, the evidence for accuracy of the logistic regression model was similar in the training and cross-validation samples. The logistic regression model produced accuracy estimates consistent with other published CAMCI studies, suggesting evidence for classification accuracy of the CAMCI for MCI is likely modest. This case study illustrates the general need for cross-validation and careful evaluation of the generalizability of machine learning models. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Longitudinal Brain Atrophy Rates in Transient Ischemic Attack and Minor Ischemic Stroke Patients and Cognitive Profiles.

Introduction: Patients with transient ischemic attack (TIA) and minor stroke demonstrate cognitive impairment, and a four-fold risk of late-life dementia. Aim: To study the extent to which the rates of brain volume loss in TIA patients differ from healthy controls and how they are correlated with cognitive impairment. Methods: TIA or minor stroke patients were tested with a neuropsychological battery and underwent T1 weighted volumetric magnetic resonance imaging scans at fixed intervals over a 3 years period. Linear mixed effects regression models were used to compare brain atrophy rates between groups, and to determine the relationship between atrophy rates and cognitive function in TIA and minor stroke patients. Results: Whole brain atrophy rates were calculated for the TIA and minor stroke patients; n = 38 between 24 h and 18 months, and n = 68 participants between 18 and 36 months, and were compared to healthy controls. TIA and minor stroke patients demonstrated a significantly higher whole brain atrophy rate than healthy controls over a 3 years interval (p = 0.043). Diabetes (p = 0.012) independently predicted higher atrophy rate across groups. There was a relationship between higher rates of brain atrophy and processing speed (composite P = 0.047 and digit symbol coding P = 0.02), but there was no relationship with brain atrophy rates and memory or executive composite scores or individual cognitive tests for language (Boston naming, memory recall, verbal fluency or Trails A or B score). Conclusion: TIA and minor stroke patients experience a significantly higher rate of whole brain atrophy. In this cohort of TIA and minor stroke patients changes in brain volume over time precede cognitive decline.