Greater Predictive Utility Research Articles

The Perceived Economic Scarcity Scale: A valid tool with greater predictive utility than income.

This article introduces the Perceived Economic Scarcity Scale (PESS), a novel instrument measuring the subjective evaluation and experience of economic scarcity (the feeling of having insufficient financial resources to meet one's needs). We conducted three high-powered preregistered studies (total N = 1900) to rigorously evaluate the PESS's psychometric properties. In Study 1, we generated a pool of items and used both Principal Component Analysis and Exploratory Factor Analysis to select the most appropriate items. In Study 2, we examined the PESS's construct validity, demonstrating that it measures a distinct construct from related constructs such as subjective social class. In Study 3, we examined the PESS's predictive validity, demonstrating that it is a robust predictor of both affective outcomes (e.g. anxiety-depressive symptoms) and cognitive outcomes (e.g. economic risk-taking). Critically, we found that the PESS not only has incremental validity over and above income but also has greater predictive utility than income. We also found that the PESS score varies depending on the distance-to-pay and has excellent test-retest reliability. Overall, the PESS appears to be a valid and reliable instrument for assessing perceived economic scarcity, and we encourage researchers to use it to better understand the psychological consequences of 'not having enough'.

Investigating biological age as a predictor of symptom progression in Alzheimer’s disease

AbstractBackgroundAge is the strongest risk factor for dementia, including Alzheimer’s disease (AD). However, across individuals of the same chronological age there is considerable heterogeneity in rates of cognitive decline. These differences have been attributed to individual differences in age‐related biological processes, including brain protein expression. To capture these differences, we developed a measure of protein brain age from cerebrospinal fluid (CSF)‐proteins, and validated its predictive utility.MethodsIn older adults across the dementia continuum enrolled in DELCODE (training cohort; N = 488, 5‐year follow‐up) and patients with subjective cognitive decline and mild cognitive impairment (MCI) from the memory‐clinic based Fundació ACE (FACE) cohort (test cohort; N = 509, 3‐year follow‐up), 1063 CSF‐proteins were measured using OLINK‐technology. Proteins optimally predicting chronological age in A/T/N‐negative individuals without dementia from DELCODE (N = 196) were selected based on a LASSO‐regression and summarized into a BrainProteinAge‐score for all participants. A harmonized, age‐sensitive cognitive composite was created and the association between BrainProteinAge and cognitive decline assessed using structural equation modeling. Further, the predictive utility of ProteinBrainAge for incident all‐cause‐dementia was examined using time‐dependent ROC analysis in MCI patients from the test cohort.Results118 CSF‐proteins were selected and used to calculate BrainProteinAge. In the training (Est[SE] = 0.06[0.02],p<0.001) and test (Est[SE] = 0.04[0.02],p = 0.013) cohorts, BrainProteinAge predicted cognitive decline beyond demographic characteristics (chronological age, sex, education) and A/T/N profiles. ProteinBrainAge captured 40% of the processes linking chronological age and cognitive decline, and improved prediction to all‐cause dementia beyond demographic characteristics and A/T/N profiles in MCI‐patients (1‐year AUC: 0.78 versus 0.82, p(difference) = 0.006). Specifically, within the AD‐continuum, BrainProteinAge (HR[CI] = 1.056[1.004‐1.110]), compared to chronological age (HR[CI] = 1.022[0.990‐1.054]), has greater predictive utility. Whilst an 8.6‐year ProteinBrainAge difference corresponded to the same risk increase observed between A+/T+ and A+/T‐ MCI patients, a difference of 24.6‐years was required for chronological age. All results remained substantively unchanged when using an optimized BrainProteinAge based on 10 proteins most strongly linked to cognitive decline.ConclusionsA new measure of biological age improves individualized prediction of cognitive decline and conversion to dementia in memory clinic patients. This provides an opportunity for precision medicine and a better understanding of age‐related biological processes contributing to dementia.

Abstract P150: Blood Pressure Trajectories For 16 Years And The Development Of Left Ventricular Hypertrophy And Increased Left Atrial Size: The Korean Genome And Epidemiology Study

Background: Single blood pressure (BP) measurement is associated with the development of target organ damage including left ventricular hypertrophy (LVH) and left atrial (LA) enlargement (LAE). However, long-term patterns of BP and their effects on LVH and LAE are poorly understood. We evaluated the association between BP trajectories and the presence of LVH and LAE. Methods: This analysis enrolled participants who attended a health examination from 2001 to 2016 (visit 1 to 8) in Ansan cohort study. Among the initial total of 10030 participants, we excluded 1787 participants because their BP measurements were less than three times. An additional 5678 participants were excluded because they had no echocardiographic examinations to evaluate LVH at visit 8. Thus, we enrolled 2,565 participants (1267 males, 47.8 ± 6.7 years old) in this study. The previous studies selected mid-BP for identifying trajectories because Mid-BP showed the greatest predictive utility for cardiovascular diseases. Based on the previous study, we also used mid-BP to identify trajectories. The current sample has more than three times times of BP measurements over 16 years. Latent mixture modeling was used to identify trajectories in mid-BP over time. Linear logistic regression was used for assessing BP trajectories with the outcomes. Results: We identified 4 distinct mid-BP trajectories: group 1 (lowest, 20.9%, n = 536), group 2 (36.2%, n = 928), group 3 (32.3%, n = 828), and group 4 (highest, 10.6%, n = 273). Compared with the lowest group, trajectories with elevated mid BP had greater odds ratios having LVH and LAE by multivariable-adjusted regression models. Adjusted odd ratios for LVH were 1.432 (95% CI = 1.138 -1.802, P = 0.002) for group 2, 2.718 (95% CI = 2.103 - 3.513, P < 0.001) for group 3, and 2.480 (95% CI = 1.742 - 3.530, P < 0.001) for group 4. Adjusted odd ratios for LAE were 1.200 (95% CI = 0.814 - 1.769, P = 0.358) for group 2, 1.599 (95% CI = 1.084 - 2.360, P = 0.018) for group 3, and 1.944 (95% CI = 1.212 - 3.118, P = 0.006) for group 4. Conclusions: Our study suggests that long-term higher mid-BP were an independent risk factor for having LVH among middle-aged males and females. Also, higher mid-BP was an independent risk factor for having future LAE in middle-aged females. Higher long-term mid-BP was an independent risk factor of cardiac structural changes such as LVH and LAE among middle-aged population.

Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling study

The emergence of fentanyl around 2013 represented a new, deadly stage of the opioid epidemic in the USA. We aimed to develop a statistical regression approach to identify counties at the highest risk of high overdose mortality in the subsequent years by predicting annual county-level overdose death rates across the contiguous USA and to validate our approach against observed overdose mortality data collected between 2013 and 2018. We fit mixed-effects negative binomial regression models to predict overdose death rates in the subsequent year for 2013-18 for all contiguous state counties in the USA (ie, excluding Alaska and Hawaii). We used publicly available county-level data related to health-care access, drug markets, socio-demographics, and the geographical spread of opioid overdose as model predictors. The crude number of county-level overdose deaths was extracted from restricted US Centers for Disease Control and Prevention mortality records. To predict county-level overdose rates for the year 201X: (1) a model was trained on county-level predictor data for the years 2010-201(X-2) paired with county-level overdose deaths for the year 2011-201(X-1); (2) county-level predictor data for the year 201(X-1) was fed into the model to predict the 201X county-level crude number of overdose deaths; and (3) the latter were converted to a population-adjusted rate. For comparison, we generated a benchmark set of predictions by applying the observed slope of change in overdose death rates in the previous year to 201(X-1) rates. To assess the predictive performance of the model, we compared predicted values (of both the model and benchmark) to observed values by (1) calculating the mean average error, root mean squared error, and Spearman's correlation coefficient and (2) assessing the proportion of counties in the top decile (10%) of overdose death rates that were correctly predicted as such. Finally, in a post-hoc analysis, we sought to identify variables with greatest predictive utility. Between 2013 and 2018, among the 3106 US counties included, our modelling approach outperformed the benchmark strategy across all metrics. The observed average county-level overdose death rate rose from 11·8 per 100 000 people in 2013 to 15·4 in 2017 before falling to 14·6 in 2018. Our negative binomal modelling approach similarly identified an increasing trend, predicting an average 11·8 deaths per 100 000 in 2013, up to 15·1 in 2017, and increasing further to 16·4 in 2018. The benchmark model over-predicted average death rates each year, ranging from 13·0 per 100 000 in 2013 to 18·3 in 2018. Our modelling approach successfully ranked counties by overdose death rate identifying between 42% and 57% of counties in the top decile of overdose mortality (compared with 29% and 43% using the benchmark) each year and identified 194 of the 808 counties with emergent overdose outbreaks (ie, newly entered the top decile) across the study period, versus 31 using the benchmark. In the post-hoc analysis, we identified geospatial proximity of overdose in nearby counties, opioid prescription rate, presence of an urgent care facility, and several economic indicators as the variables with the greatest predictive utility. Our model shows that a regression approach can effectively predict county-level overdose death rates and serve as a risk assessment tool to identify future high mortality counties throughout an emerging drug use epidemic. National Institute on Drug Abuse.

Age-adjusted shock index: From injury to arrival

BackgroundStudies have demonstrated the superiority of the shock index, pediatric age-adjusted (SIPA) in predicting outcomes in pediatric blunt trauma patients. However, all have utilized SIPA calculated on emergency department (ED) arrival. We sought to evaluate the utility of SIPA at the trauma scene and describe changes in SIPA from the trauma scene to the ED. MethodsWe used 2014–2016 Trauma Quality Improvement Program Data to identify blunt trauma patients 1–15 years old with an injury severity score (ISS) > 15. We calculated SIPA using vitals obtained at the trauma scene and on ED arrival. Outcome measures included ISS, transfusion within 24 h, intensive care unit (ICU), hospital length of stay (LOS), ventilator days, and mortality. ResultsWe identified 2917 patients, and 34.2% had a persistently elevated SI from the injury scene to ED arrival, whereas 17.9% had a persistently elevated SIPA. An elevated SIPA at the trauma scene was more predictive of greater ISS, LOS, and ventilator requirements. Furthermore, a SIPA that remained abnormal was associated with greater ISS, LOS, ICU admission, mechanical ventilation, and mortality. ConclusionsPrehospital SIPA values predict worse outcomes in pediatric trauma patients, and their change over time may have greater predictive utility than a single value alone. Level of EvidenceII Type of StudyPrognosis Study.

Glomerular Filtration Rate Derived from Cystatin C is More Predictive of Death Following Cardiac Surgery Than Creatinine Based Estimates

510 Gender Differences in Outcomes Amongst Patients Undergoing Coronary Angiography M.Arstall 1,2,∗, R.Dreyer 1,3, R.Tavella 1,3, M.Worthley1,4, S. Worthley1,4, D. Chew5,6, C. Zeitz 1,3, J. Beltrame1,3 1 The University of Adelaide, Australia 2 Lyell McEwin Hospital, Australia 3 The Queen Elizabeth Hospital, Australia 4 Royal Adelaide Hospital, Australia 5 Flinders University, Australia 6 Flinders Medical Centre, Australia Background: Despite extensive research within gender differences in acute coronary syndrome’s (ACS) (i.e. myocardial infarction), there is comparatively little data on gender-based differences in registries pertaining to diagnostic catheterisation. Methods: The Coronary Angiogram Database of South Australia (CADOSA) Registry is a comprehensive database of all public cardiac catheterisation procedures performed within South Australia. Registry data for 2012 was utilised to assess gender differences in (a) procedure information for diagnostic coronary angiography, (b) in-hospital outcomes and (c) discharge referral status/medications. Results: Men N= 2825 Women N= 1388 p Age (mean±SD) 64± 12 66± 13 <0.001 Elective Angiography (n %) 1519 (57%) 790 (59%) 0.058 Angiography for ST-elevation myocardial infarction (STEMI) (n, %) 398 (155) 134 (10%) <0.001 Percutaneous coronary intervention (PCI) performed (n, %) 859 (32%) 275 (21%) <0.001 No Coronary Disease Finding (n, %) 318 (12%) 344 (26%) <0.001 In-hospital death (n, %) 30 (1%) 22 (2%) 0.195 Referral for coronary artery bypass grafting (n, %) 340 (13%) 104 (8%) <0.001 Cardiac rehabilitation referral (n, %) 925 (33%) 323 (23%) 0.001 Discharge Aspirin (n, %) 2340 (83%) 1024 (74%) <0.001 Discharge Statin (n, %) 2058 (73%) 914 (66%) <0.001 Discharge ACE Inhibitor (n, %) 1346 (48%) 525 (38%) <0.001 Discharge Beta blocker (n, %) 1420 (50%) 574 (41%) <0.001 Discharge Calcium channel blocker (n, %) 996 (35%) 428 (31%) 0.003 Conclusion:Consistent with ACS data, women are both less likely to undergo angiography for STEMI and receive less life saving PCI. On discharge, women are also managedpoorlyanddonot receiveappropriate cardiac referral or maintenance medications in comparison to men. http://dx.doi.org/10.1016/j.hlc.2013.05.512 511 Glomerular Filtration Rate Derived from Cystatin C is MorePredictiveofDeathFollowingCardiacSurgeryThan Creatinine Based Estimates J. Mooney1,2,∗, C. Chow1,2, B. Cuthbertson3,4, B. Croal 5, G. Hillis 1,6 1 The George Institute for Global Health, Sydney, Australia 2 Department of Cardiology, Westmead Hospital, Sydney, Australia 3 Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Canada 4 Department of Anesthesia, University of Toronto, Toronto, Ontario, Canada 5 Department of Clinical Biochemistry, Aberdeen Royal Infirmary, Aberdeen, United Kingdom 6 Department of Cardiology, Concord Repatriation General Hospital, Sydney, Australia Background: Renal dysfunction predicts mortality after cardiac surgery. Estimated glomerular filtration rate (eGFR) and cystatin C are better predictors of postoperative death than creatinine alone. The relative prognostic value of newer methods of calculating eGFR with the CKD-EPI equation, including cystatin C, has not been analysed in this setting. Methods: A prospective cohort study was conducted of 1010 patients undergoing cardiac surgery. Creatinine and cystatin C was collected prior to surgery, and eGFR calculated from these. Clinical variables were collected, and post-operative vital status established. Results:Mean age was 66 years with 77%male. Average followupwas4.8 yearswith 141deaths.Renal functionwas a powerful and independent predictor of death however measured.After adjustmentwith theEUROSCORE, eGFR derived from cystatin C showed the strongest association with death, though other measures remained significant (see table). Receiver operating characteristic curves showed eGFRderived fromcystatinC showed the greatest predictive utility (see table). Conclusions: EstimatedGFR using cystatin C levels and the CKD-EPI equation are more powerful predictors of death following cardiac surgery than creatinine based measures. Marker Hazard Ratio 95% Confidence Interval P-valueArea under the Curve 95% Confidence Interval Cystatin C 2.05 1.57–2.69 0.000 0.67 0.62–0.72 eGFR (Modified Diet in Renal Disease) 0.98 0.97–0.99 0.001 0.61 0.58–0.66 eGFR (CKD-EPI) 0.98 0.96–0.99 0.000 0.63 0.58–0.68 eGFR (cystatin c CKD-EPI) 0.97 0.96–0.98 0.000 0.68 0.63–0.73 eGFR (creatinine and cystatin c CKD-EPI) 0.98 0.97–0.99 0.000 0.66 0.61–0.71 CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration. http://dx.doi.org/10.1016/j.hlc.2013.05.513

Serum matrix metalloproteinase 9 and colorectal neoplasia: a community-based evaluation of a potential diagnostic test

Background:A blood test may be a more acceptable routine colorectal cancer (CRC) screening test than faecal occult blood test, flexible sigmoidoscopy or colonoscopy, and could be safer and cheaper. We evaluated the accuracy of a serum matrix metalloproteinase (MMP9) test for CRC in a non-presenting symptomatic population.Methods:A cohort, aged 50–69 with lower gastrointestinal symptoms, was identified by community-based survey. Accuracy of serum MMP9 was assessed by comparison with colonoscopy. Logistic regression identified predictors of neoplasia and receiver operating characteristic curve analyses determined the cutoff to maximise the sensitivity.Results:Data were available for 748 patients. Overall, 46 cases of neoplasia were identified. Univariate analysis demonstrated that demographic characteristics, behavioural factors, clinical symptoms and raised serum MMP9 concentration were all significantly associated with the presence of neoplasia. Our final logistic regression model had a sensitivity of 79% and specificity of 70%.Conclusion:We demonstrated a significant association between serum MMP9 concentration and the presence of neoplasia. Serum MMP9 levels are raised in those with cancer and high-risk adenomas, although MMP9 estimation is likely to have the greatest predictive utility when used as part of a panel of biomarkers. Further work is required to identify biomarkers that are sufficiently accurate for implementing into routine practice.

Determinants of Seat Belt Use Among Drivers in Sabzevar, Iran: A Comparison of Theory of Planned Behavior and Health Belief Model

Objective: Although seat belt use can significantly decrease the risk of injury, few car drivers make use of seat belts in Iran. The aim of this study was to test the utility and efficiencyof the theory of planned behavior (TPB) and the health beliefmodel (HBM) in predicting intention to use a seat belt among car drivers in Sabzevar, Iran. Methods: A cross-sectional, correlational design was employed. Cluster sampling was used to recruit 340 drivers to participate in the study. A self-administered questionnaire was applied to investigate variables of interest. Reliability and validity of the instruments were examined. The statistical analyses of the data included t test, one-way analysis of variance (ANOVA), bivariate correlation, and stepwise regression. Results: All TPB and HBM variables were related to intention to use a seat belt in car drivers. All TPB (perceived behavioral control, subjective norms, and attitude) and HBM (perceived susceptibility and severity, benefits and barriers, and cues to action) variables were statistically significant predictors of seat belt use intention and accounted for 37.9 and 15.4 percent of the variation, respectively. Conclusions: Our results showed that the rate of seat belt use in Iran as a developing country is very low. Thus, developing and implementing effective interventional programs in order to promote seat belt use among car drivers is recommended. The findings of this study provide preliminary support for the TPB model as a more effective framework than HBM for examining seat belt use in car drivers. Our results demonstrated that TPB has greater predictive utility than HBM in seat belt use intention.

81. Biomarkers of Lung Contusion With/Without Superimposed Gastric Aspiration in Rats

Introduction: Lung contusion (LC) is an independent risk factor for ALI/ARDS. Previous work in our laboratory suggests that lung injury in LC is self-limiting and it is the additional insult such as gastric aspiration that may be responsible for progression of LC into ALI/ARDS. Considering that gastric aspiration, a common injury seen in victims of blunt trauma, is usually unwitnessed, it is important to analyze the biomarker profiles of these two insults individually and in combination. Materials and Methods: Rats received LC, CASP (combined acid and small particles), LC+CASP, uninjured controls (n=9-12) and were analyzed at 5 and 24hr following the insults. A qualitative, quantitative cellular analysis of the BAL (broncho-alveolar Lavage) along with levels of albumin, IL-1β, TNFα, IL-6, IL-10, CINC-1, MIP-2, MCP-1 in the BAL were determined by ELISA. Additionally, total lung MPO levels were also determined. Statistical Methods: JMP statistical software was used to perform hierarchial clusters of the biomarker profiles of the individual insults. The prediction of injury type was carried out using an approach recently defined by Hutson to extend standard ROC methodology. In brief, lung injury type was modeled as a two-by-two outcome with injury group. Analyses tested the predictive accuracy of models incorporating a maximum of two inflammatory mediators at a fixed time of injury and for a fixed type of aspiration. Results: A hierachial cluster analyses at 5hr (figure 1) and 24hr suggested that LC, CASP, LC+CASP, control groups had very different biomarker profiles. Additionally using the prediction model methodology, the cytokines with the greatest predictive utility in rats at 5 hr (Table 1) varied with the type of insult, with IL-10 and BAL macrophages found to be best predictor for LC, and total lung MPO best for CASP. Only 1/30 rats were misclassified for the type of injury based on modeling with cytokine levels at 5 hr. At 24 hr based on just 2 mediators IL-10 and BAL PMNs, all but 1/37 rats were correctly classified (Table 1). Only one rat in the LC group was misclassified as LC+CASP. The predictive modeling worked perfectly well with CASP and LC+CASP suggesting distinct inflammatory signature profiles for differing lung insults. Conclusions: Biomarker profiles in inflammatory lung injuries may play a key role in early diagnosis of these clinically relevant problems. Tabled 1

Predicting the 2 1/2-year outcome of dysthymic disorder: the roles of childhood adversity and family history of psychopathology.

Follow-up studies of dysthymic disorder (DD) indicate that demographic and clinical variables are not strong predictors of its outcome. The present study extended this literature by examining the relationship between the early home environment and family history of psychopathology and outcome in DD. Eighty-six outpatients with DD were followed up over a 30-month period using structured clinical interviews. A number of measures of childhood adversity and familial psychopathology assessed at baseline predicted outcome, even after controlling for baseline severity and clinical variables. The best predictors included a history of sexual abuse, quality of the patient's relationship with both parents, and higher familial loadings for drug abuse and Cluster A personality disorders. These findings indicated that childhood adversity and familial psychopathology have greater predictive utility for DD than for demographic and clinical variables.

Hispanic adults' beliefs, attitudes, and intentions regarding the female condom.

The present study used the theory of planned behavior (TPB) (Ajzen, 1985) augmented by AIDS knowledge to investigate factors influencing intentions of Hispanic adults to use the female condom. A total of 146 persons (75 women and 71 men; mean age, 27 years) recruited from community-based organizations completed an anonymous survey regarding intentions to use the female condom with their main sex partner. The TPB model had greater predictive utility for women's, than for men's, female condom use intentions. For men, attitudes and norms did not predict female condom use intentions, but greater AIDS knowledge was related to lower intentions to use the female condom, above and beyond the TPB constructs. Perceived behavioral control, operationalized as self-efficacy, significantly increased the predictive utility of the TPB model for women's female condom use intentions but not for men's. Behavior change strategies to increase female condom use are discussed in light of these findings.

An MCMI-III Discriminant Function Analysis of Incarcerated Felons

Discriminant function analyses were employed to predict institutional misconduct in a sample of 128 incarcerated offenders. Misconduct was divided into two categories: reprimands and behavioral consequences (i.e., early lockups, segregation, monetary penalties, and suspensions). Results indicated that the MCMI-III provides greater predictive utility than does demographic information alone. In the prediction of reprimands, an overall correct classification rate of 79% was obtained using both demographic and MCMI-III data. A correct classification rate of 75% was found in the prediction of misconduct related to more behavioral ramifications. The clinical implications of these results and directions for future research are discussed.

Predicting and understanding safety helmet use among schoolboy cyclists: A comparison of the theory of planned behaviour and the health belief model

The paper reports a prospective longitudinal comparison of the Health Belief Model (Rosenstock, 1966) and the Theory of Planned Behaviour (Ajzen, 1985) in which the ability of the models to predict and understand the factors determining use of protective helmets among 162 schoolboy cyclists was examined by path analysis. The TPB emerged with greater economy and less redundancy than the HBM. A second path analysis examined whether intention, which is not included among the original components of the HBM, might mediate the links between the predictor variables and behaviour, and this proved to be correct. Lastly, the effects of prior behaviour were examined and found to have a significant effect on helmet use in both models. It was concluded that the TPB had greater predictive utility than the HBM. The implications of the findings are discussed and suggestions for future research are offered.

Lead Poisoning Risk Determination in a Rural Setting

To determine the prevalence of elevated blood lead levels among children living in a rural area and to determine the effectiveness of the Centers for Disease Control and Prevention (CDC) Lead Risk Assessment Questionnaire and additional questionnaire items in correctly identifying rural children having elevated blood lead levels. Comparison of results of a questionnaire that is intended to identify children as being at low or high risk for lead poisoning with children's blood lead levels. The three practice sites of the only pediatric group in a rural county of upstate New York. A consecutive sample of 705 children ages 6 to 72 months who were seen for health supervision visits between June and September 1993. Sixty-nine percent of the children were considered to be at high risk for lead poisoning by the CDC questionnaire. Overall, 8.4% of the children in the study had blood lead levels of 10 micrograms/dL (0.48 mumol/L) or higher, and 2.1% had blood lead levels of 15 micrograms/dL (0.72 mumol/L) or higher. No significant difference was noted between the percentages of high- and low-risk children who had elevated blood lead levels. To devise a more effective lead risk assessment tool for children in this setting, the two items from the CDC questionnaire and the two additional items that had the greatest predictive utility were combined to form a short alternative questionnaire. The alternative questionnaire thus consisted of items concerning whether the child has a sibling or playmate with lead poisoning, whether the child lives near an industry that potentially may release lead, whether the child lives in rented or owner-occupied housing, and whether the child has a parent who is a migrant farm worker. Children categorized as high risk with the alternative questionnaire were much more likely to have elevated blood lead levels than those who were categorized as low risk. The alternative questionnaire was very effective in correctly identifying children with elevated blood lead levels. Eighty-eight percent of children having blood lead levels of 10 micrograms/dL or higher and 100% of children having blood lead levels of 15 micrograms/dL or higher were classified as high risk by the questionnaire. Children classified as low risk were very unlikely to have elevated blood lead levels; 98% of low-risk children had blood lead levels of less than 10 micrograms/dL, and 100% had blood lead levels of less than 15 micrograms/dL. These results suggest that the CDC lead risk assessment questionnaire is of limited benefit in identifying rural children with blood lead levels 10 micrograms/dL or higher or 15 micrograms/dL or higher. An alternative questionnaire, however, seems to have marked clinical utility for identifying rural children with elevated blood lead levels.

Prediction of Participation in Continuing Professional Education: A Test of Two Behavioral Intention Models

Data from a survey of veterinarians was used to test the applicability of two competing models of behavioral intention to participate in a continuing professional education (CPE) program. The Triandismodel accounted for nearly 50% of the variance in intention to participate and proved to have greater predictive utility than the Fish be in and Ajzen model. Disciminant analysis revealed that 85% of the respondents were classified appropriately as participants and non-participants by the variables in the behavioral intention model. The results strongly support the hypothesis that variables external to thebehavioralintentionmodelindirectlyinfluencebehavioralintentionandparticipationbehavior. The study extends existing research by identifying essential social psychological variables for inclusion in the development of a future theoretical model of CPE participation. Implications for future research are proposed.

Psychological Versus Sociological Explanations for Delinquent Conduct and Gang Formation

Sociological and psychological factors are frequently used to explain juvenile delinquency and the emergence and persistence of juvenile gangs. Sociological theories, such as social control, containment, differential association, anomie, and labeling each reflect different levels of predictive utility relative to delinquent conduct. Psychological theories, such as developmental theory, stages of moral development, social learning, and psychodynamic theories are frequently invoked to account for juvenile offending behavior. A survey of literature discloses that both psychological and sociological factors are often employed simultaneously to explain juvenile gangs, since the interface between these two general classes of theory is invariably intertwined. It is suggested that using theoretical strategies from several disciplines simultaneously in the creation of synthesized theoretical schemes to account for delinquent conduct and gang formation, including biological variables, has greater predictive utility as opposed to using single-discipline explanations.