Physician Practice Patterns and Variation in the Delivery of Preventive Services

BACKGROUND: Strategies to improve preventive services delivery (PSD) have yielded modest effects. A multidimensional approach that examines distinctive configurations of physician attributes, practice processes, and contextual factors may be informative in understanding delivery of this important form of care. OBJECTIVE: We identified naturally occurring configurations of physician practice characteristics (PPCs) and assessed their association with PSD, including variation within configurations. DESIGN: Cross-sectional study. PARTICIPANTS: One hundred thirty-eight family physicians in 84 community practices and 4,046 outpatient visits. MEASUREMENTS: Physician knowledge, attitudes, use of tools and staff, and practice patterns were assessed by ethnographic and survey methods. PSD was assessed using direct observation of the visit and medical record review. Cluster analysis identified unique configurations of PPCs. A priori hypotheses of the configurations likely to perform the best on PSD were tested using a multilevel random effects model. RESULTS: Six distinct PPC configurations were identified. Although PSD significantly differed across configurations, mean differences between configurations with the lowest and highest PSD were small (i.e., 3.4, 7.7, and 10.8 points for health behavior counseling, screening, and immunizations, respectively, on a 100-point scale). Hypotheses were not confirmed. Considerable variation of PSD rates within configurations was observed. CONCLUSIONS: Similar rates of PSD can be attained through diverse physician practice configurations. Significant within-configuration variation may reflect dynamic interactions between PPCs as well as between these characteristics and the contexts in which physicians function. Striving for a single ideal configuration may be less valuable for improving PSD than understanding and leveraging existing characteristics within primary care practices

Age of the Mt. Ortles ice cores, the Tyrolean Iceman and glaciation of the highest summit of South Tyrol since the Northern Hemisphere Climatic Optimum

In 2011 four ice cores were extracted from the summit of Alto dell'Ortles (3859 m), the highest glacier of South Tyrol in the Italian Alps. This drilling site is located only 37 km southwest from where the Tyrolean Iceman, similar to 5.3 kyrs old, was discovered emerging from the ablating ice field of Tisenjoch (3210 m, near the Italian-Austrian border) in 1991. The excellent preservation of this mummy suggested that the Tyrolean Iceman was continuously embedded in prehistoric ice and that additional ancient ice was likely preserved elsewhere in South Tyrol. Dating of the ice cores from Alto dell'Ortles based on Pb-210, tritium, beta activity and C-14 determinations, combined with an empirical model (COPRA), provides evidence for a chronologically ordered ice stratigraphy from the modern glacier surface down to the bottom ice layers with an age of similar to 7 kyrs, which confirms the hypothesis. Our results indicate that the drilling site has continuously been glaciated on frozen bedrock since similar to 7 kyrs BP. Absence of older ice on the highest glacier of South Tyrol is consistent with the removal of basal ice from bedrock during the Northern Hemisphere Climatic Optimum (6-9 kyrs BP), the warmest interval in the European Alps during the Holocene. Borehole inclinometric measurements of the current glacier flow combined with surface ground penetration radar (GPR) measurements indicate that, due to the sustained atmospheric warming since the 1980s, an acceleration of the glacier Alto dell'Ortles flow has just recently begun. Given the stratigraphic-chronological continuity of the Mt. Ortles cores over millennia, it can be argued that this behaviour has been unprecedented at this location since the Northern Hemisphere Climatic Optimum

Dementia in Latin America : paving the way towards a regional action plan

Regional challenges faced by Latin American and Caribbean countries (LACs) to fight dementia, such as heterogeneity, diversity, political instabilities, and socioeconomic disparities, can be addressed more effectively grounded in a collaborative setting based on the open exchange of knowledge. In this work, the Latin American and Caribbean Consortium on Dementia (LAC-CD) proposes an agenda for integration to deliver a Knowledge to Action Framework (KtAF). First, we summarize evidence-based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking and translational research) and align them to current global strategies to translate regional knowledge into actions with transformative power. Then, by characterizing genetic isolates, admixture in populations, environmental factors, and barriers to effective interventions and mapping these to the above challenges, we provide the basic mosaics of knowledge that will pave the way towards a KtAF. We describe strategies supporting the knowledge creation stage that underpins the translational impact of KtAF

Helping Misfits to Commit: How Justice Climate Attenuates the Effects of Personality Dissimilarity on Organizational Commitment

In the present study, we examined whether greater personality dissimilarity would indirectly lead to lower organizational commitment as a result of heightened emotional exhaustion. We also proposed and tested the notion that the experience of being dissimilar to one’s workgroup members in the traits of (a) agreeableness, (b) conscientiousness, or (c) emotional stability would have the strongest positive effect on emotional exhaustion in workgroups with low justice climates. The data from 8196 members of the U.S. Armed Services confirmed the predicted negative indirect effect for agreeableness dissimilarity, but showed that conscientiousness dissimilarity resulted in a positive indirect effect on commitment. Contrary to expectations, emotional stability dissimilarity did not demonstrate a significant relationship. Multilevel moderated mediation analyses revealed that the presence of a strong workgroup justice climate attenuated the significant mediated relationships. Finally, we report supplementary polynomial regression analyses and discuss their implications for workgroup composition and individual career development. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)

Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)

Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems

Data from air, englacial and permafrost temperature measurements on Mt. Ortles (Eastern European Alps)

The *.xlsx files report the temperature data recorded between 2010 and 2016 and presented in the paper “Modern air, englacial and permafrost temperatures at high altitude on Mt. Ortles, (3905 m a.s.l.) in the Eastern European Alps” (Carturan et al., 2023, submitted). The data were used to display the time series reported in the paper, which details variable names, data quality flags, maintenance logs of field operations, and characteristics of measurement sites. The data files are the following: Ortles_Air_temperature.xlsx: includes the air temperature data measured by five sensors installed on an automatic weather station. Ortles_englacial_temperature.xlsx: includes the englacial temperature measured at different depths by four thermistor strings. Ortles_soilsurface_temperature.xlsx: includes the soil surface temperature measured at six different locations over deglaciated terrain. Ortles_rockwall_temperature.xlsx: includes the rockwal temperature measured at three different depths and six different locations. Each *.xlsx file contains the following fields: “Date and hour (UTC)”: format day/month/year hour:minute; “Variable name (depth m)”: name of the measured variable and the sensor depth (if applicable); “Quality flag code”: a code reporting data quality; Different spreadsheet report temperature data from different measurement sites.This dataset was collected in the framework of the Ortles Project (a program supported by two NSF awards no. 1060115 & no. 1461422 to The Ohio State University and by the Ripartizione Protezione Antincendi e Civile of the Autonomous province of Bolzano in collaboration with the Ripartizione Opere idrauliche e Ripartizione Foreste of the Autonomous province of Bolzano and the Stelvio National Park) and of the Italian MIUR Project (PRIN 2010-11), "Response of morphoclimatic system dynamics to global changes and related geomorphological hazards" (local and national coordinators G. Dalla Fontana and C. Baroni)