Assessment of air quality in the Philadelphia, Pennsylvania subway.

BACKGROUND: Subways are popular and efficient modes of transportation in cities. However, people are exposed to high levels of particulate matter (PM) in subways. Subway air quality in the United States has been investigated in a few cities, but data is lacking on simultaneous measurement of several pollutants, especially ultrafine particles (UFP) and black carbon (BC), in combination with different size fractions of PM. OBJECTIVES: The goals of this study are to assess air quality in a belowground subway and compare it with outdoor ambient levels, to examine temporal variability of PM in the subway, and to analyze the correlation between PM and BC. METHODS: Particulate matter of varying sizes (PM1, PM2.5, PM10), UFP, and BC were measured using DustTrak, nanoparticle detector, and micro aethalometer, respectively. Measurements were made at the belowground subway platform and the aboveground street level at 15th Street subway station in Philadelphia during summer 2022. RESULTS: Belowground mean PM1, PM2.5, and PM10 were 112.2 ± 61.3 µg/m3, 120 ± 65.5 µg/m3, and 182.1 ± 132 µg/m3, respectively, which were 5.4, 5.7, and 7.6 times higher than the respective aboveground street levels. The UFP lung deposited surface area (LDSA) (59.4 ± 36.2 µm2/cm3) and BC (9.5 ± 5.4 µg/m3) belowground were 1.7 times and 10.7 times higher than the aboveground. The pollutant concentration varied from day-to-day on both the locations. A higher positive correlation was found between the belowground BC and PM2.5 (r = 0.51, p < 0.05) compared to the aboveground (r = 0.16, p < 0.05). IMPACT: This study showed high levels of particulate matter exposure at a belowground subway station in Philadelphia. Particulate matter levels were about 5 to 8 times higher at belowground subway station than the corresponding aboveground street level. Higher levels were also observed for UFP lung deposited surface area (LDSA), while black carbon levels showed the highest concentration at the belowground level by a factor of ten compared to the aboveground level. The study shows the need for air quality management at belowground subways to reduce particulate matter exposure for the commuters.

Essential team science skills for biostatisticians on collaborative research teams.

Introduction: Despite the critical role that quantitative scientists play in biomedical research, graduate programs in quantitative fields often focus on technical and methodological skills, not on collaborative and leadership skills. In this study, we evaluate the importance of team science skills among collaborative biostatisticians for the purpose of identifying training opportunities to build a skilled workforce of quantitative team scientists. Methods: Our workgroup described 16 essential skills for collaborative biostatisticians. Collaborative biostatisticians were surveyed to assess the relative importance of these skills in their current work. The importance of each skill is summarized overall and compared across career stages, highest degrees earned, and job sectors. Results: Survey respondents were 343 collaborative biostatisticians spanning career stages (early: 24.2%, mid: 33.8%, late: 42.0%) and job sectors (academia: 69.4%, industry: 22.2%, government: 4.4%, self-employed: 4.1%). All 16 skills were rated as at least somewhat important by > 89.0% of respondents. Significant heterogeneity in importance by career stage and by highest degree earned was identified for several skills. Two skills ("regulatory requirements" and "databases, data sources, and data collection tools") were more likely to be rated as absolutely essential by those working in industry (36.5%, 65.8%, respectively) than by those in academia (19.6%, 51.3%, respectively). Three additional skills were identified as important by survey respondents, for a total of 19 collaborative skills. Conclusions: We identified 19 team science skills that are important to the work of collaborative biostatisticians, laying the groundwork for enhancing graduate programs and establishing effective on-the-job training initiatives to meet workforce needs.

Physical, Mental, and General Health Outcomes Among Childhood Cancer Survivors From the Behavioral Risk Factor Surveillance System Survey.

OBJECTIVES: To examine the physical, mental, and general health among young adult childhood cancer survivors (CCS). SAMPLE & SETTING: This secondary analysis study used data from the Behavioral Risk Factor Surveillance System. The analytic sample included 697 young adult CCS (537 women; 160 men). METHODS & VARIABLES: Chi-square tests of independence were done to compare the rates across cancer survivorship groups on categorical variables. Logistic regression was performed to determine correlates with physical, mental, and general health. RESULTS: Female CCS had a significantly (p < 0.0001) greater number of "no days" in which they reported good physical, mental, and general health compared to male CCS. Female CCS were more likely to experience 30 days of poor physical health compared to male CCS (odds ratio [OR] = 1.8, p < 0.05) when controlling for education, race, and age. Depressed female CCS had higher odds of being in poor physical, mental, and general health (OR = 2.9, 7.6, and 2.6, respectively). IMPLICATIONS FOR NURSING: Findings support the need for continued screening, following published practice guidelines, among young adult female CCS for emotional distress with the use of well-established distress and psychosocial assessment measures.

Using Treatment Fidelity Measures to Understand Walking Recovery: A Secondary Analysis From the Community Ambulation Project.

OBJECTIVES: Physical therapist intervention studies can be deemed ineffective when, in fact, they may not have been delivered as intended. Measurement of treatment fidelity (TF) can address this issue. The purpose of this study was to describe TF of a home-based intervention, identify factors associated with TF, and examine whether components of TF were associated with the outcome of change in 6-minute walk distance (∆6MWD). METHODS: This is a secondary analysis of community-dwelling hip fracture participants who completed standard therapy and were randomly assigned to the active intervention (Push). Push was 16 weeks of lower extremity strengthening, function, and endurance training. TF was defined as delivery (attendance rate, exercise duration) and receipt (progression in training load, heart rate reserve [HRR] during endurance training, and exercise position [exercise on floor]). The outcome was ∆6MWD. Independent variables included baseline (demographic and clinical) measures. Descriptive statistics were calculated; linear and logistic regressions were performed. RESULTS: Eighty-nine participants were included in this analysis; 59 (66%) had attendance of 75% or greater. Participants walked for 20 minutes or more for 78% of sessions. The average training load increased by 22%; the mean HRR was 35%; and 61 (69%) participants exercised on the floor for at least 75% of sessions. Regression analyses showed that a higher body mass index and greater baseline 6MWD were related to components of TF; 4 out of 5 components of TF were significantly related to ∆6MWD. The strongest TF relationship showed that those who exercised on the floor improved by 62 m (95% CI = 31-93 m) more than those who did not get on the floor. CONCLUSIONS: Measures of TF should extend beyond attendance rate. This analysis demonstrates how measures of TF, including program attendance, progression in training load, endurance duration, and exercising on the floor were significantly related to improvement in 6MWD in participants post hip fracture. IMPACT: This careful analysis of treatment fidelity assured that the intervention was delivered and received as intended. Analysis of data from a large trial with participants after hip fracture showed that regular attendance, frequent endurance training for 20 minutes, increases in lower extremity training loads, and exercising on the floor were associated with improvements in the outcome of 6-minute-walk distance. The strongest association with improvement was exercising on the floor.

An Electronic Screening System for Oral Health Examination and Collection of Critical Data in a Nonclinical Setting: Validation Trial.

OBJECTIVE: To evaluate the reliability, ease, and efficiency of data entry for an oral health screening app that allows iPad® entry of data, including permanent versus deciduous teeth present, visual image comparison grading of demineralization/caries, fluorosis, periodontal inflammation, oral hygiene status, identification of sealants/restorations, dental trauma, orthodontic malocclusion, mandibular joint dysfunction, and early childhood caries. METHODS: 89 consented children were examined first by a public health dental hygienist in a dental office reception area and then by a dentist in a treatment operatory. The same research associate was used to prompt and record both examinations. RESULTS: The screenings prompted by the electronic oral health screening system were completed in 2 to 3 minutes each with favorable levels of comparison between examiners as assessed by weighted Kappa scores measuring 0.531 for all teeth examined, with the lower back teeth showing the greatest agreement (K = 0.601) and the upper back and upper front demonstrating less agreement (K = 0.446 and 0.468, respectively). Neither examiner identified any carious lesions among the lower front teeth. CONCLUSIONS: This study provides the first description of an oral health screening entry app with visual image comparisons and touchscreen data entry for efficient collection of oral health information.

Engagement in High-Risk Behaviors Among Young Adult Survivors of Childhood Cancer Compared to Healthy Same-Age Peers Surveyed in the National Longitudinal Study of Adolescent Health.

PURPOSE: This secondary data analysis compared smoking rates, alcohol consumption, and binge drinking, and examined risk factors for engaging in these behaviors among 90 young adult-aged childhood cancer survivors (CSS) with 15,490 young adults in the general population. METHODS: The sample was drawn from the National Longitudinal Study of Adolescent Health. The sampling distribution of these healthy matched young adults was estimated through the use of bootstrapping, which involved randomly repeated for 10,000 samples of healthy controls. RESULTS: The findings of repeated sampling analysis revealed that CCS were more likely to smoke daily (34.5% vs. 20.6 healthy matched controls; p = 0.03). The proportion of respondents who had any signs of alcohol abuse symptoms was 72.2% of CCS compared with 81.1% of matched controls (p = 0.16), while CCS with severe alcohol abuse was 51.1% compared with 59.1% of matched controls (p = 0.28). Whether they engaged in binge drinking in the past 12 months was 43.3% for CCS and 46.4% for healthy respondents. Logistic regression analyses were performed to examine predictors of smoking, alcohol use, and binge drinking among CCS. Smoking was very strongly associated with optimism. An optimism score of one unit higher was associated with a 39% reduction in odds of smoking (odd ratio [OR] = 0.61, p < 0.0001). Black CSS were less likely to smoke (OR = 0.15, p < 0.05). CCS in good health were more likely to binge drink (OR = 3.67, p < 0.05). CONCLUSIONS: Data generated from this secondary data analyses add to the evidence base about the engagement in high risk behaviors among young adult-aged CCS. These findings further emphasize the need for widespread, available effective theory-based screening guidelines and interventions.

Psychological distress between young adult female survivors of childhood cancer and matched female cohorts surveyed in the adolescent health study.

BACKGROUND: The psychological health of childhood cancer survivors is an essential treatment outcome. Female survivors are a subgroup of survivors with an increased risk for poor psychological outcomes. OBJECTIVE: This study compared psychological distress in young adult female survivors of childhood cancer with that in young adult females in the general population with no history of childhood cancer. Psychological distress was measured by assessing respondents' subjective degree of depressive symptoms, anxiety, and somatization. METHODS: The study was a secondary data analysis. The sample was drawn from the National Longitudinal Study of Adolescent Health, which used a representative, probability-based sampling technique. The sample included 66 young adult female survivors of childhood cancer and 8186 young adult females with no history of cancer. Randomized, nonparametric testing was used to construct 10 000 different age-matched female cohort samples from the general population. RESULTS: Young adult female survivors of childhood cancer had more depressive symptoms (P < .05) as compared with matched cohorts with 589 of the 10,000 matched samples. There were no statistically significant differences between the cancer survivors and the matched cohort groups on anxiety and somatization symptoms. CONCLUSION: Young adult female survivors of childhood cancer are at an increased risk of experiencing depression, which can decrease their psychological functioning and emotional well-being. IMPLICATIONS FOR PRACTICE: Healthcare professionals who care for these cancer survivors need to be aware that female survivors are at risk for depression and should screen and refer accordingly.

Cigarette Smoking and Alcohol Use among Adolescents and Young Adults with Asthma.

Asthma is one of the most common, serious chronic diseases in pediatric and young adult populations. Health-risk behaviors, including cigarette smoking and alcohol use, may exacerbate chronic diseases and complicate their management. The aim of this study was to longitudinally analyze rates of cigarette smoking and alcohol use in adolescents and young adults who have asthma and those who do not have asthma. A secondary analysis of data from the National Longitudinal Study of Adolescent Health was undertaken. Individuals with asthma were found to exhibit increasing rates of cigarette smoking and alcohol use as they aged. When an adolescent with a chronic health issue begins health-risk-taking behaviors, behavior change interventions must be planned. Pediatric nurses, practitioners, and clinicians are uniquely positioned to assess for health-risk behaviors in youth with asthma and to intervene with plans of care that are tailored for the needs of this vulnerable population.

Post-hospital medical respite care and hospital readmission of homeless persons.

Medical respite programs offer medical, nursing, and other care as well as accommodation for homeless persons discharged from acute hospital stays. They represent a community-based adaptation of urban health systems to the specific needs of homeless persons. This article examines whether post-hospital discharge to a homeless medical respite program was associated with a reduced chance of 90-day readmission compared to other disposition options. Adjusting for imbalances in patient characteristics using propensity scores, respite patients were the only group that was significantly less likely to be readmitted within 90 days compared to those released to Own Care. Respite programs merit attention as a potentially efficacious service for homeless persons leaving the hospital.

Improving follow-up to abnormal breast cancer screening in an urban population. A patient navigation intervention.

Delays in follow-up after cancer screening contribute to racial/ethnic disparities in cancer outcomes. We evaluated a patient navigator intervention among inner-city women with breast abnormalities. A full-time patient navigator supported patients using the care management model. Female patients 18 years and above, referred to an urban, hospital-based, diagnostic breast health practice from January to June 2000 (preintervention) and November 2001 to February 2003 (intervention), were studied. Timely follow-up was defined as arrival to diagnostic evaluation within 120 days from the date the original appointment was scheduled. Data were collected via computerized registration, medical records, and patient interview. Bivariate and multivariate logistic regression analyses were conducted, comparing preintervention and intervention groups, with propensity score analysis and time trend analysis to address the limitations of the pre-post design. 314 patients were scheduled preintervention; 1018, during the intervention. Overall, mean age was 44 years; 40% black, 36% non-Hispanic white, 14% Hispanic, 4% Asian, 5% other; 15% required an interpreter; 68% had no or only public insurance. Forty-four percent of referrals originated from a community health center, 34% from a hospital-based practice. During the intervention, 78% had timely follow-up versus 64% preintervention (P < .0001). In adjusted analyses, women in the intervention group had 39% greater odds of having timely follow-up (95% CI, 1.01-1.9). Timely follow-up in the adjusted model was associated with older age (P = .0003), having private insurance (P = .006), having an abnormal mammogram (P = .0001), and being referred from a hospital-based practice, as compared to a community health center (P = .003). Our data suggest a benefit of patient navigators in reducing delay in breast cancer care for poor and minority populations. Cancer 2007. (c) 2006 American Cancer Society.

Evaluation of the Centers for Disease Control and Prevention's recommendations regarding routine testing for human immunodeficiency virus by an inpatient service: who are we missing?

OBJECTIVE: To assess the proportion of hospitalized patients who tested positive for human immunodeficiency virus (HIV) by a routine inpatient testing service, as recommended by the Centers for Disease Control and Prevention, who might not have been identified had routine testing not been offered. PATIENTS AND METHODS: In this retrospective cohort study, the medical records of patients who tested HIV positive by the inpatient testing service between 1999 and 2003 were compared with the medical records of inpatients who tested HIV negative by the inpatient testing service and the medical records of patients who tested HIV positive in ambulatory settings. We compared HIV risk factors, discharge diagnoses, CD4 cell counts, and HIV RNA concentrations. RESULTS: A total of 243 patients participated in this study: 81 patients who tested HIV positive and 81 who tested HIV negative by the inpatient testing service, and 81 patients who tested HIV positive in ambulatory settings. Both HIV-positive inpatients and HIV-positive outpatients had similar frequencies of HIV risk factors (46% vs 43%; P=.75). Both groups differed significantly from HIV-negative inpatients (4%; P<.001). Comparing HIV-positive inpatients with HIV-positive outpatients, CD4 cell counts were lower (196 vs 371 cells/mm3; P<.001), and HIV RNA levels were higher (4.61 vs 4.09 Iog, HIV RNA; P=.001). At diagnosis, 64 HIV-positive inpatients (79%) met criteria for acquired immunodeficiency syndrome compared with 21 HIV-positive outpatients (26%) (P<.001). CONCLUSION: Patients who tested HIV positive through inpatient testing have more advanced disease than those identified as outpatients. Half of these patients would not have been identified had testing not been routinely offered. Routine inpatient HIV testing offers an important opportunity to identify patients with HIV infection.

Pap smear rates among Haitian immigrant women in eastern Massachusetts.

OBJECTIVE: Given limited prior evidence of high rates of cervical cancer in Haitian immigrant women in the U.S., this study was designed to examine self-reported Pap smear screening rates for Haitian immigrant women and compare them to rates for women of other ethnicities. METHODS: Multi-ethnic women at least 40 years of age living in neighborhoods with large Haitian immigrant populations in eastern Massachusetts were surveyed in 2000-2002. Multivariate logistic regression analyses were used to examine the effect of demographic and health care characteristics on Pap smear rates. RESULTS: Overall, 81% (95% confidence interval 79%, 84%) of women in the study sample reported having had a Pap smear within three years. In unadjusted analyses, Pap smear rates differed by ethnicity (p=0.003), with women identified as Haitian having a lower crude Pap smear rate (78%) than women identified as African American (87%), English-speaking Caribbean (88%), or Latina (92%). Women identified as Haitian had a higher rate than women identified as non-Hispanic white (74%). Adjustment for differences in demographic factors known to predict Pap smear acquisition (age, marital status, education level, and household income) only partially accounted for the observed difference in Pap smear rates. However, adjustment for these variables as well as those related to health care access (single site for primary care, health insurance status, and physician gender) eliminated the ethnic difference in Pap smear rates. CONCLUSIONS: The lower crude Pap smear rate for Haitian immigrants relative to other women of color was in part due to differences in (1) utilization of a single source for primary care, (2) health insurance, and (3) care provided by female physicians. Public health programs, such as the cancer prevention programs currently utilized in eastern Massachusetts, may influence these factors. Thus, the relatively high Pap rate among women in this study may reflect the success of these programs. Public health and elected officials will need to consider closely how implementing or withdrawing these programs may impact immigrant and minority communities.

Mammography use.

OBJECTIVES: The goal of this study was to compare mammography use in Haitian women versus that of other racial/ethnic groups in the same neighborhoods and to identify factors associated with mammography use in subpopulations that are seldom studied. METHODS: A community-based, cross-sectional survey sampled a multiethnic group of inner-city women from eastern Massachusetts. Bivariate analyses and logistic regression models were used to predict lifetime and recent (within two years) mammography screening. RESULTS: Self-reported lifetime mammography use was similar for Haitian (82%), African-American (78%), Caribbean (81%) and Latina women (86%) but higher for white women (94%, p = 0.008). Mammography use in the past two years was also similar in all groups (66-82%, p = 0.41). In multivariate models, African-American (adjusted odds ratio [AOR]; 0.3; 95% CI 0.1-0.9) and Haitian women (AOR 0.3; 95% CI 0.1-0.9) had lower odds of lifetime mammography compared to white women. Factors independently related to lifetime and recent mammography included having a regular healthcare provider, greater knowledge of breast cancer screening; higher education, and private health insurance. CONCLUSIONS: Haitian women with a regular provider and knowledge of breast cancer screening reported recent mammography use similar to women from other racial/ethnic groups. The racial/ethnic patterns of mammography use in our study do not explain racial/ethnic differences in breast cancer stage or mortality.

Do variations in disease prevalence limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions?

BACKGROUND: Studies of geographic variation in hospitalizations commonly examine age- and gender-adjusted population-based hospitalization rates (ie, the numbers of persons hospitalized relative to what is expected given the age/gender distributions in the area population). OBJECTIVE: To determine whether areas identified as extreme using population-based hospitalization rates remain extreme when ranked by disease-based hospitalization rates (the numbers of persons hospitalized relative to what is expected given the amount of disease in the area). DESIGN: The authors examined 1997 Medicare data on both inpatient admissions and outpatient visits of patients 65 years and older in each of 71 small areas in Massachusetts for 15 medical conditions. For each area, the number of people having each condition was calculated as the sum of those hospitalized plus those treated as outpatients only. The authors used hierarchical Bayesian modeling to estimate area-specific population-based hospitalization rates, disease-based hospitalization rates (DHRs), and disease prevalence. MAIN OUTCOME MEASURE: The extent to which the same areas were identified as extreme based on population-based hospitalization rates versus DHRs. RESULTS: Area-specific population-based hospitalization rates, DHRs, and disease prevalence varied substantially. Areas identified as extreme using population-based hospitalization rates often were not extreme when ranked by DHRs. For 11 of the 15 conditions, 5 or more of the 14 areas ranked in top and bottom deciles by population-based hospitalization rates were more likely than not (ie, with probability > or = 0.50) to be at least 2 deciles less extreme when ranked by DHRs. CONCLUSION: Differences in disease prevalence can limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions.

Using claims data to examine mortality trends following hospitalization for heart attack in Medicare.

OBJECTIVE: To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. DATA SOURCES: Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995-1999 we retain diagnoses from one year prior, and during, the case-defining admission. STUDY DESIGN: We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996-1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is--without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses--those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996-1999. PRINCIPAL FINDINGS: The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. CONCLUSIONS: Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends.

Comparing the importance of disease rate versus practice style variations in explaining differences in small area hospitalization rates for two respiratory conditions.

Many studies have reported large variations in age- and sex-adjusted rates of hospitalizations across small geographic areas. These variations have often been attributed to differences in medical practice style which are not reflected in differences in health care outcomes. There is, however, another potentially important source of variation that has not been examined much in the literature: geographic differences in the age-sex adjusted size of the pool of patients who present with the disease and are candidates for hospitalization. Previous studies of small area variations in hospitalization rates have only used data on hospitalizations. Thus, it has not been possible to distinguish the extent to which differences in hospitalization rates are due to (i). differences in the chance that patients diagnosed with a disease are admitted to a hospital, which we refer to as the 'practice style effect,' versus (ii). geographic differences in the total amount of diagnosed disease, which we refer to as the 'disease effect.' Elementary methods for estimating the relative strength of the two effects directly from the data can be misleading, since equal amounts of variability in each effect result in unequal impacts on hospitalization rates. In this paper we describe a model-based approach for estimating the relative importance of the practice style effect and the disease effect in explaining variations in hospitalization rates. The key to our approach is the use of data on both inpatient and outpatient visits. We use 1997 Medicare data for two respiratory medical conditions across 71 small areas in Massachusetts: chronic bronchitis and emphysema, and bacterial pneumonia. Based on a Poisson model for the process generating hospitalizations and outpatient visits, we use a Bayesian framework and Gibbs sampling to compute and compare the correlation between the number of people hospitalized and each of these two sources of variation. Our results show that for the two conditions, disease rate variation explains at least as much of the variation in hospitalization rates as does practice style variation.

Do "we just know"? Masked assessors' ability to accurately identify children with prenatal cocaine exposure.

This study evaluated perceptions of masked assessors to determine whether there are subtle differences in cocaine-exposed and unexposed children who might be identified by those interacting with children. As part of a longitudinal study, developmental assessors were masked to 163 4-year-old children's actual in utero cocaine exposure status and developmental history. After each battery, assessors documented their guesses of the child's cocaine exposure. Thirty-seven percent of the children who were exposed were misclassified as unexposed, whereas 74% of those unexposed were incorrectly classified as exposed. Although the sample did not differ on assessment scores when results were analyzed by actual cocaine exposure status ( >.3), children who did less well on assessments were more likely to be labeled by assessors as cocaine-exposed ( <.001). Results highlight the potential of stereotyping and negative attributions that might distort observations, both in unmasked studies of prenatal cocaine exposure and in clinical settings.