The all-hazards willingness to respond (WTR) of local public health personnel is critical to emergency preparedness. This study applied a threat-and efficacy-centered framework to characterize these ...workers' scenario and jurisdictional response willingness patterns toward a range of naturally-occurring and terrorism-related emergency scenarios.
Eight geographically diverse local health department (LHD) clusters (four urban and four rural) across the U.S. were recruited and administered an online survey about response willingness and related attitudes/beliefs toward four different public health emergency scenarios between April 2009 and June 2010 (66% response rate). Responses were dichotomized and analyzed using generalized linear multilevel mixed model analyses that also account for within-cluster and within-LHD correlations.
Comparisons of rural to urban LHD workers showed statistically significant odds ratios (ORs) for WTR context across scenarios ranging from 1.5 to 2.4. When employees over 40 years old were compared to their younger counterparts, the ORs of WTR ranged from 1.27 to 1.58, and when females were compared to males, the ORs of WTR ranged from 0.57 to 0.61. Across the eight clusters, the percentage of workers indicating they would be unwilling to respond regardless of severity ranged from 14-28% for a weather event; 9-27% for pandemic influenza; 30-56% for a radiological 'dirty' bomb event; and 22-48% for an inhalational anthrax bioterrorism event. Efficacy was consistently identified as an important independent predictor of WTR.
Response willingness deficits in the local public health workforce pose a threat to all-hazards response capacity and health security. Local public health agencies and their stakeholders may incorporate key findings, including identified scenario-based willingness gaps and the importance of efficacy, as targets of preparedness curriculum development efforts and policies for enhancing response willingness. Reasons for an increased willingness in rural cohorts compared to urban cohorts should be further investigated in order to understand and develop methods for improving their overall response.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Local public health agencies play a central role in response to an influenza pandemic, and understanding the willingness of their employees to report to work is therefore a critically relevant ...concern for pandemic influenza planning efforts. Witte's Extended Parallel Process Model (EPPM) has been found useful for understanding adaptive behavior in the face of unknown risk, and thus offers a framework for examining scenario-specific willingness to respond among local public health workers. We thus aim to use the EPPM as a lens for examining the influences of perceived threat and efficacy on local public health workers' response willingness to pandemic influenza.
We administered an online, EPPM-based survey about attitudes/beliefs toward emergency response (Johns Hopkins approximately Public Health Infrastructure Response Survey Tool), to local public health employees in three states between November 2006-December 2007. A total of 1835 responses were collected for an overall response rate of 83%. With some regional variation, overall 16% of the workers in 2006-7 were not willing to "respond to a pandemic flu emergency regardless of its severity". Local health department employees with a perception of high threat and high efficacy--i.e., those fitting a 'concerned and confident' profile in the EPPM analysis--had the highest declared rates of willingness to respond to an influenza pandemic if required by their agency, which was 31.7 times higher than those fitting a 'low threat/low efficacy' EPPM profile.
In the context of pandemic influenza planning, the EPPM provides a useful framework to inform nuanced understanding of baseline levels of--and gaps in--local public health workers' response willingness. Within local health departments, 'concerned and confident' employees are most likely to be willing to respond. This finding may allow public health agencies to design, implement, and evaluate training programs focused on emergency response attitudes in health departments.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The decision to proceed with tonsillectomy to treat pediatric obstructive sleep-disordered breathing (OSDB) often falls on individual families. Despite emphasis on shared decision-making between ...parents and surgeons about tonsillectomy for OSDB, the extent to which parents have already decided about surgery prior to the child's consultation is not known.
To identify predictors of parent choice predisposition for surgical treatment of OSDB with tonsillectomy and describe its association with parent-clinician communication.
Observational cohort study conducted at 3 outpatient clinical sites (urban-based outpatient center, suburban off-site outpatient center, and community-based medical center) associated with a large academic center. A total of 149 parents of children undergoing their initial otolaryngology consultation for OSDB were identified through clinic scheduling records and deemed eligible for participation in this study. Of the 149 parents, a volunteer sample of 64 parents (42.9%) agreed to participate and have their consultation audiorecorded. Of these 64 participants, 12 parents were excluded because their child had previously been evaluated for OSDB by a specialist.
The primary outcomes and measures were treatment choice predisposition scale (a measure of the strength of a patient's treatment decision prior to entering a medical consultation), parent communication behaviors coded in consultation audiorecordings (substantive questions asked, introduced medical jargon, expression of treatment preference, and scores on the OSDB and Adenotonsillectomy Knowledge Scale for parents).
A total of 52 parent participants were included in the final analysis. Most parent participants were female (n = 48; 92%); 50% (n = 26) of parents were non-Hispanic White, 37% (n = 19) were Black, 10% (n = 5) were Hispanic/Latino, and 4% (n = 2) self-reported race/ethnicity as "Other." Mean (range) choice predisposition was 6.84 (2-10), with 22 parents (42%) more predisposed to choose tonsillectomy. Parents more predisposed to choose tonsillectomy used more medical jargon during the consultation (odds ratio OR, 3.95; 95% CI, 1.16-15.15) and were less likely to ask questions (OR, 0.22; 95% CI, 0.05-0.87). Parental predictors of greater predisposition toward choosing surgery were White race (OR, 7.31; 95% CI, 1.77-39.33) and prior evaluation by a pediatrician for OSDB (OR, 6.10; 95% CI, 1.44-33.34).
In this cohort study of parents of children with OSDB, many parents were predisposed to choose treatment with tonsillectomy prior to initial surgical consultation, which may lessen engagement and influence 2-way communication. In this cohort, greater predisposition for tonsillectomy was observed in non-Hispanic White parents and parents of patients who had been previously evaluated by a pediatrician for OSDB. Understanding parent choice predisposition for surgery may promote improved communication and parental engagement during surgical consultations. It may also help direct education about sleep and tonsillectomy to nonsurgical forums.
In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff ...between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect's fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were computed for both tasks and analyzed using ROC and LROC analysis methodologies. The results of this study suggest that collimators with somewhat poorer resolution and higher sensitivity than those of a typical low-energy high-resolution (LEHR) collimator were optimal for both defect detection and joint detection and localization tasks in myocardial perfusion SPECT for the range of defect sizes investigated. This study also indicates that optimizing instrumentation for a detection task may provide near-optimal performance on the more challenging detection-localization task.
Objective:
Effective delivery of discharge instructions and access to postoperative care play a critical role in outcomes after pediatric surgery. Previous studies in the pediatric emergency ...department suggest that caregivers with language barriers have less comprehension of discharge instructions despite use of interpretation services. However, the impact of language barriers during discharge on surgical outcomes in a pediatric surgical setting has not been studied. This study examined the effect of parental language during discharge on number and mode of healthcare contact following pediatric adenotonsillectomy.
Methods:
A retrospective cohort study was conducted on children who underwent adenotonsillectomy at a tertiary care pediatric academic medical center from July 1, 2016 to June 1, 2018. Data were collected on consecutive patients with non-English-speaking caregivers and a systematic sampling of patients with English-speaking caregiver. Surgery-related complications and healthcare contacts within 90 days after discharge were collected. Two-tailed t tests, χ2 tests, and logistic regression were performed to assess the association between parental primary language and incidence of healthcare contact after surgery.
Results:
A total of 136 patients were included: 85 English-speaking and 51 non-English-speaking. The groups were comparable in age, sex, and comorbidities. The non-English group had more patients with public insurance (86% vs. 56%; P < .001). Number of encounters and types of complications following discharge were similar, but the non-English group was more likely to utilize the emergency department compared to phone calls (OR, 9.3; 95% CI, 2.3-38.2), even after adjustment for insurance type (OR, 7.9; 95% CI, 1.6-39.4).
Conclusion:
Language barriers at discharge following pediatric otolaryngology surgery is associated with a meaningful difference in how patients utilized medical care. Interventions to improve comprehension and access may help reduce preventable emergency department visits and healthcare costs.
Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the ...components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.
We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.
The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.
The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).
Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). ...In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.
The Hotelling Observer (HO) is widely used to evaluate image quality in medical imaging. However, applying it to data that are not multivariate-normally (MVN) distributed is not optimal. In this ...paper, we apply two multi-template linear observer strategies to handle such data. First, the entire data ensemble is divided into sub-ensembles that are exactly or approximately MVN and homoscedastic. Next, a different linear observer template is estimated for and applied to each sub-ensemble. The first multi-template strategy, adapted from previous work, applies the HO to each sub-ensemble, calculates the area under the receiver operating characteristics curve (AUC) for each sub-ensemble, and averages the AUCs from all the sub-ensembles. The second strategy applies the Linear Discriminant (LD) to estimate test statistics for each sub-ensemble and calculates a single global AUC using the pooled test statistics from all the sub-ensembles. We show that this second strategy produces the maximum AUC when only shifting of the HO test statistics is allowed. We compared these strategies to the use of a single HO template for the entire data ensemble by applying them to the non-MVN data obtained from reconstructed images of a realistic simulated population of myocardial perfusion SPECT studies with the goal of optimizing the reconstruction parameters. Of the strategies investigated, the multi-template LD strategy yielded the highest AUC for any given set of reconstruction parameters. The optimal reconstruction parameters obtained by the two multi-template strategies were comparable and produced higher AUCs for each sub-ensemble than the single-template HO strategy.
Quantum noise as well as anatomic and uptake variability in patient populations limits observer performance on a defect detection task in myocardial perfusion SPECT (MPS). The goal of this study was ...to investigate the relative importance of these two effects by varying acquisition time, which determines the count level, and assessing the change in performance on a myocardial perfusion (MP) defect detection task using both mathematical and human observers. We generated ten sets of projections of a simulated patient population with count levels ranging from 1/128 to around 15 times a typical clinical count level to simulate different levels of quantum noise. For the simulated population we modeled variations in patient, heart and defect size, heart orientation and shape, defect location, organ uptake ratio, etc. The projection data were reconstructed using the OS-EM algorithm with no compensation or with attenuation, detector response and scatter compensation (ADS). The images were then post-filtered and reoriented to generate short-axis slices. A channelized Hotelling observer (CHO) was applied to the short-axis images, and the area under the receiver operating characteristics (ROC) curve (AUC) was computed. For each noise level and reconstruction method, we optimized the number of iterations and cutoff frequencies of the Butterworth filter to maximize the AUC. Using the images obtained with the optimal iteration and cutoff frequency and ADS compensation, we performed human observer studies for four count levels to validate the CHO results. Both CHO and human observer studies demonstrated that observer performance was dependent on the relative magnitude of the quantum noise and the patient variation. When the count level was high, the patient variation dominated, and the AUC increased very slowly with changes in the count level for the same level of anatomic variability. When the count level was low, however, quantum noise dominated, and changes in the count level resulted in large changes in the AUC. This behavior agreed with a theoretical expression for the AUC as a function of quantum and anatomical noise levels. The results of this study demonstrate the importance of the tradeoff between anatomical and quantum noise in determining observer performance. For myocardial perfusion imaging, it indicates that, at current clinical count levels, there is some room to reduce acquisition time or injected activity without substantially degrading performance on myocardial perfusion defect detection.
Surges in demand for professional mental health services occasioned by disasters represent a major public health challenge. To build response capacity, numerous psychological first aid (PFA) training ...models for professional and lay audiences have been developed that, although often concurring on broad intervention aims, have not systematically addressed pedagogical elements necessary for optimal learning or teaching. We describe a competency-based model of PFA training developed under the auspices of the Centers for Disease Control and Prevention and the Association of Schools of Public Health. We explain the approach used for developing and refining the competency set and summarize the observable knowledge, skills, and attitudes underlying the 6 core competency domains. We discuss the strategies for model dissemination, validation, and adoption in professional and lay communities.
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