Conceptualizing a Quantitative Measurement Suite to Evaluate Healthcare Teams

Background Current team assessment instruments in healthcare tend to involve rater-based evaluations that are susceptible to well-known biases. Recent advances in technology include portable devices to measure team-based activities. Consequently, the possibility exists to move away from rater-based assessments of team function by identifying quantitative measures to replace them. Aim This article aims to provide potential approaches to developing quantitative measurement suites involving large amounts of data to address the challenges of assessment presented by the complex nature of teamwork. Conclusion By addressing construct, measurement, and context components, we provide a practical approach to developing a suite to capture quantitative measurements that, through incorporation of social network analysis and aggregated other values, aligns with the Team Strategies & Tools to Enhance Performance and Patient SafetyTM (TeamSTEPPSTM) dimensions for fostering teamwork.

Measuring Infusion of Service-Learning on Student Program Development and Implementation Competencies

This study piloted a service-learning assessment suite to measure students’ perceived self-efficacy on program development and implementation competencies (Service-Learning Self-Efficacy on Program Development and Implementation [SL-SEPDI]), Service-Learning Belief Inventory (SLBI), and an Overall Service-Learning Self-Efficacy on Program Development and Implementation (OVSL-SEPDI) scales. MPH students in a required course participated in the study during 2011-2015 ( N = 87). Baseline survey was used to assess the reliabilities of the 12-item SL-SEPDI and the nine-item SLBI scales, and posttest survey assessed the 10-item OVSL-SEPDI scale. Confirmatory factor analysis showed good model fit index and all items loaded significantly on both the SL-SEPDI (χ2/ df = 1.34; root mean square error of approximation [RMSEA] = .067; Tucker–Lewis index [TLI] = .92; comparative fit index [CFI] = .94; incremental fit index [IFI] = .94; goodness-of-fit index [GFI] = .86) and SLBI (χ2/ df = 1.28; RMSEA = .061; TLI = .97; CFI = .98; IFI = .98; GFI = .91) scales. Data also showed satisfactory reliability scores, with Cronbach’s alphas of .87, .88, and .91 for the SL-SEPDI, SLBI, and OVSL-SEPDI scales. This study provides data supporting the validities and reliabilities of this service-learning measurement suite, and has implications to assess student self-efficacy outcomes.

Speciation of OH reactivity above the canopy of an isoprene-dominated forest

Measurements of OH reactivity, the inverse lifetime of the OH radical, can provide a top–down estimate of the total amount of reactive carbon in an air mass. Using a comprehensive measurement suite, we examine the measured and modeled OH reactivity above an isoprene-dominated forest in the southeast United States during the 2013 Southern Oxidant and Aerosol Study (SOAS) field campaign. Measured and modeled species account for the vast majority of average daytime reactivity (80–95 %) and a smaller portion of nighttime and early morning reactivity (68–80 %). The largest contribution to total reactivity consistently comes from primary biogenic emissions, with isoprene contributing ∼ 60 % in the afternoon, and ∼ 30–40 % at night and monoterpenes contributing ∼ 15–25 % at night. By comparing total reactivity to the reactivity stemming from isoprene alone, we find that ∼ 20 % of the discrepancy is temporally related to isoprene reactivity, and an additional constant ∼ 1 s−1 offset accounts for the remaining portion. The model typically overestimates measured OVOC concentrations, indicating that unmeasured oxidation products are unlikely to influence measured OH reactivity. Instead, we suggest that unmeasured primary emissions may influence the OH reactivity at this site.

Speciation of OH reactivity above the canopy of an isoprene-dominated forest

Measurements of OH reactivity, the inverse lifetime of the OH-radical, can provide a top-down estimate of the total amount of reactive carbon in an airmass. Because OH reactivity is tied to the RO2 production rate, the absolute value of OH reactivity has direct implications for ozone production. Additionally, as molecular structure determines volatility, the speciation of reactivity affects the production of secondary organic aerosol (SOA). Several studies have focused on the agreement of measured and calculated or modeled OH reactivity above and within the canopy of isoprene-dominated forests, as well as the relative contributions of volatile organic compounds (VOCs) and oxidized VOCs (OVOCs). Drawing definitive conclusions about the identity of the missing OH reactivity has been limited by the availability of VOC and OVOC measurements. In this work, using a comprehensive measurement suite, we examine the measured and modeled OH reactivity above an isoprene-dominated forest in the South East United States during the 2013 Southern Oxidant and Aerosol Study (SOAS) field campaign. We find good agreement between measured and modeled OH reactivity, with the largest contribution consistently coming from primary biogenic emissions. In contrast, there are small but significant discrepancies in the increase in OH reactivity per isoprene. As the model typically overestimates OVOCs, we do not attribute this discrepancy to unmeasured oxidation products. Instead, we suggest that unmeasured primary emissions may influence the OH reactivity at this site.

Ozone production chemistry in the presence of urban plumes

Ozone pollution affects human health, especially in urban areas on hot sunny days. Its basic photochemistry has been known for decades and yet it is still not possible to correctly predict the high ozone levels that are the greatest threat. The CalNex_SJV study in Bakersfield CA in May/June 2010 provided an opportunity to examine ozone photochemistry in an urban area surrounded by agriculture. The measurement suite included hydroxyl (OH), hydroperoxyl (HO2), and OH reactivity, which are compared with the output of a photochemical box model. While the agreement is generally within combined uncertainties, measured HO2 far exceeds modeled HO2 in NOx-rich plumes. OH production and loss do not balance as they should in the morning, and the ozone production calculated with measured HO2 is a decade greater than that calculated with modeled HO2 when NO levels are high. Calculated ozone production using measured HO2 is twice that using modeled HO2, but this difference in calculated ozone production has minimal impact on the assessment of NOx-sensitivity or VOC-sensitivity for midday ozone production. Evidence from this study indicates that this important discrepancy is not due to the HO2 measurement or to the sampling of transported plumes but instead to either emissions of unknown organic species that accompany the NO emissions or unknown photochemistry involving nitrogen oxides and hydrogen oxides, possibly the hypothesized reaction OH + NO + O2 → HO2 + NO2.

Missing peroxy radical sources within a rural forest canopy

Organic peroxy (RO2) and hydroperoxy (HO2) radicals are key intermediates in the photochemical processes that generate ozone, secondary organic aerosol and reactive nitrogen reservoirs throughout the troposphere. In regions with ample biogenic hydrocarbons, the richness and complexity of peroxy radical chemistry presents a significant challenge to current-generation models, especially given the scarcity of measurements in such environments. We present peroxy radical observations acquired within a Ponderosa pine forest during the summer 2010 Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen – Rocky Mountain Organic Carbon Study (BEACHON-ROCS). Total peroxy radical mixing ratios reach as high as 180 pptv and are among the highest yet recorded. Using the comprehensive measurement suite to constrain a near-explicit 0-D box model, we investigate the sources, sinks and distribution of peroxy radicals below the forest canopy. The base chemical mechanism underestimates total peroxy radicals by as much as a factor of 3. Since primary reaction partners for peroxy radicals are either measured (NO) or under-predicted (HO2 and RO2, i.e. self-reaction), missing sources are the most likely explanation for this result. A close comparison of model output with observations reveals at least two distinct source signatures. The first missing source, characterized by a sharp midday maximum and a strong dependence on solar radiation, is consistent with photolytic production of HO2. The diel profile of the second missing source peaks in the afternoon and suggests a process that generates RO2 independently of sun-driven photochemistry, such as ozonolysis of reactive hydrocarbons. The maximum magnitudes of these missing sources (~ 120 and 50 pptv min−1, respectively) are consistent with previous observations alluding to unexpectedly intense oxidation within forests. We conclude that a similar mechanism may underlie many such observations.