BACKGROUND : Previous studies have suggested positive association between residents' workload and medical errors. However, few studies have investigated the possible associations between procedural errors, workload, and the individual characteristics of residents, including personality, mental state and job satisfaction.
OBJECTIVE : To explore possible associations of workload and individual characteristics of residents with their procedural error rates.
DESIGN : Prospective observational study based on a daily questionnaire.
PARTICIPANTS : Residents of postgraduate year 1 and 2.
MEASUREMENTS : Residents' workload (on-calls, work hours, sleep and napping hours), residents' physical and mental health state, personality inventory, and procedural error rate (defined as procedural error counts divided by overall procedural attempts).
RESULTS : On average, the residents (N=49) were responsible for 9.8 inpatients per day (range, 1.9-23.1), worked for 16.0 hours per day (range, 12.6-19.8), slept for 4.4 hours per day (range, 2.8-5.7), napped for 0.2 hours per day (range, 0-0.7), and experienced 1 overnight work shift every 7.2 days. The procedural error rate was 2.2 per 10 procedures (range, 0.4-5.0). Using a multivariable adjusted regression model, significant factors associated with lower error rates included : longer napping ; reflective personality ; better mental state ; higher job satisfaction ; and, less on-call frequency.
CONCLUSIONS : Procedural error of residents is positively associated with higher on-call frequency and inversely associated with napping, reflective personality, better mental state, and higher job satisfaction. For reducing procedural error among residents, improvement of modifiable factors, such as workload and mental health, is needed.

OBJECTIVESThe objective of this metallomics study is to investigate comprehensively some relationships between cancer risk and minerals, including essential and toxic metals.

METHODSTwenty-four minerals including essential and toxic metals in scalp hair samples from 124 solid-cancer patients and 86 control subjects were measured with inductively coupled plasma mass spectrometry (ICP-MS), and the association of cancer with minerals was statistically analyzed with multiple logistic regression analysis.

RESULTSMultiple logistic regression analysis demonstrated that several minerals are significantly correlated to cancer, positively or inversely. The most cancer-correlated mineral was iodine (I) with the highest correlation coefficient of r = 0.301, followed by arsenic (As; r = 0.267), zinc (Zn; r = 0.261), and sodium (Na; r = 0.190), with p < 0.01 for each case. In contrast, selenium (Se) was inversely correlated to cancer (r = -0.161, p < 0.05), followed by vanadium (V) (r = -0.128). Multiple linear regression value was highly significantly correlated with probability of cancer (R (2) = 0.437, p < 0.0001), and the area under the receiver-operating characteristic (ROC) curve was calculated to be 0.918. In addition, using contingency table analysis and the chi-square test, the precision of discrimination for cancer was estimated to be 0.871 (chi-square = 99.1, p < 0.0001).

CONCLUSIONSThese findings suggest that some minerals such as arsenic, selenium, and probably iodine, zinc, sodium, and vanadium contribute to regulation of cancer and also that metallomics study using multiple logistic regression analysis is a useful tool for estimating cancer risk.