6 research outputs found
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How do healthcare professionals interview patients to assess suicide risk?
Background: There is little evidence on how professionals communicate to assess suicide risk. This study analysed how professionals interview patients about suicidal ideation in clinical practice.
Methods: Three hundred nineteen video-recorded outpatient visits in U.K. secondary mental health care were screened. 83 exchanges about suicidal ideation were identified in 77 visits. A convenience sample of 6 cases in 46 primary care visits was also analysed. Depressive symptoms were assessed. Questions and responses were qualitatively analysed using conversation analysis. χ 2 tested whether questions were influenced by severity of depression or influenced patients’ responses.
Results: A gateway closed question was always asked inviting a yes/no response. 75% of questions were negatively phrased, communicating an expectation of no suicidal ideation, e.g., “No thoughts of harming yourself?”. 25% were positively phrased, communicating an expectation of suicidal ideation, e.g., “Do you feel life is not worth living?”. Comparing these two question types, patients were significantly more likely to say they were not suicidal when the question was negatively phrased but were not more likely to say they were suicidal when positively phrased (χ 2 = 7.2, df = 1, p = 0.016). 25% patients responded with a narrative rather than a yes/no, conveying ambivalence. Here, psychiatrists tended to pursue a yes/no response. When the patient responded no to the gateway question, the psychiatrist moved on to the next topic. A similar pattern was identified in primary care.
Conclusions: Psychiatrists tend to ask patients to confirm they are not suicidal using negative questions. Negatively phrased questions bias patients’ responses towards reporting no suicidal ideation
Simulation of the air/fuel mixing of an HSDI diesel engine:part 1: a new dense spray vapour coupling submodel
A numerical study has been performed to investigate the soot emission from a high-speed single-cylinder direct injection diesel engine. The computational conditions were set to be the same as the test conditions in the experiments where measurements had been performed at two running speeds with two injector protrusions. It was shown that the KIVA CFD code can predict the experimental trend, where at a low-speed running condition a higher smoke reading is reached when increasing the injector protrusion into the piston chamber and, conversely, a lower smoke reading was recorded for the same change in injector protrusion at a high running speed condition. Although computational predictions yielded the same trend as the experimental results, the magnitudes of the smoke emissions were an order of magnitude over those predicted. Evidence of inappropriate air/fuel mixing of the model was seen via rates of heat release analyses, especially in the high-speed conditions. Therefore, efforts to reduce this discrepancy by way of improvements to the KIVA submodels were made. In particular, modifications to the breakup and evaporation models have been made in order better to represent the mixing of the high-speed liquid jets. A gaseous sphere per liquid droplet model was employed to improve the current KIVA model by improving the mass coupling effects, which effectively delays the addition of spray source terms to the gas phase equations. Results of the modified models showed improvements in the vapour dispersion of the atomizing liquid jet, thus affecting the mixing rates and predicted smoke emissions. Further improvements on the momentum coupling will be presented in Part 2 of this work