Variation in the timing and duration of autumn leaf phenology among temperate deciduous trees, native shrubs and non-native shrubs.

The timing and duration of autumn leaf phenology marks important transitions in temperate deciduous forests, such as, start of senescence, declining productivity and changing nutrient cycling. Phenological research on temperate deciduous forests typically focuses on upper canopy trees, overlooking the contribution of other plant functional groups like shrubs. Yet shrubs tend to remain green longer than trees, while non-native shrubs, in particular, tend to exhibit an extended growing season that confers a competitive advantage over native shrubs. We monitored leaf senescence and leaf fall (2017-2020) of trees and shrubs (native and non-native) in an urban woodland fragment in Wisconsin, USA. Our findings revealed that, the start of leaf senescence did not differ significantly between vegetation groups, but leaf fall started (DOY 273) two weeks later in shrubs. Non-native shrubs exhibited a considerably delayed start (DOY 262) and end of leaf senescence (DOY 300), with leaf-fall ending (DOY 315) nearly four weeks later than native shrubs and trees. Overall, the duration of the autumn phenological season was longer for non-native shrubs than either native shrubs or trees. Comparison of the timing of spring phenophases with the start and end of leaf senescence revealed that when spring phenology in trees starts later in the season senescence also starts later and ends earlier. The opposite pattern was observed in native shrubs. In conclusion, understanding the contributions of plant functional groups to overall forest phenology requires future investigation to ensure accurate predictions of future ecosystem productivity and help address discrepancies with remote sensing phenometrics.

Characterizing spring phenology in a temperate deciduous urban woodland fragment: trees and shrubs.

Phenological research in temperate-deciduous forests typically focuses on upper canopy trees, due to their overwhelming influence on ecosystem productivity and function. However, considering that shrubs leaf out earlier and remain green longer than trees, they play a pivotal role in ecosystem productivity, particularly at growing season extremes. Furthermore, an extended growing season of non-native shrubs provides a competitive advantage over natives. Here, we report spring phenology, budburst, leaf-out, and full-leaf unfolded (2017-2021) of a range of co-occurring species of tree (ash, American basswood, red oak, white oak, and boxelder) and shrub (native species: chokecherry, pagoda dogwood, nannyberry, American wild currant and Eastern wahoo, and non-native species: buckthorn, honeysuckle, European privet, and European highbush cranberry) in an urban woodland fragment in Wisconsin, USA, to determine how phenology differed between plant groups. Our findings show that all three spring phenophases of shrubs were 3 weeks earlier (p < 0.05) than trees. However, differences between shrubs groups were only significant for the later phenophase; full-leaf unfolded, which was 6 days earlier (p < 0.05) for native shrubs. The duration of the spring phenological season was 2 weeks longer (p < 0.05) for shrubs than trees. These preliminary findings demonstrate that native shrubs, at this site, start full-leaf development earlier than non-native species suggesting that species composition must be considered when generalizing whether phenologies differ between vegetation groups. A longer time series would be necessary to determine future implications on ecosystem phenology and productivity and how this might impact forests in the future, in terms of species composition, carbon sequestration, and overall ecosystem dynamics.

Fostering effective and sustainable scientific collaboration and knowledge exchange: a workshop-based approach to establish a national ecological observatory network (NEON) domain-specific user group.

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA's National Ecological Observatory Network's (NEON's) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON's first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG's kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

Integrating Community Health Workers' Dual Clinic-Community Role in Safety-Net Primary Care: Implementation Lessons from a Pragmatic Diabetes-Prevention Trial.

BACKGROUND: Over a third of US adults carry a diagnosis of prediabetes, 70% of whom may progress to type 2 diabetes mellitus ("diabetes"). Community health workers (CHWs) can help patients undertake healthy behavior to prevent diabetes. However, there is limited guidance to integrate CHWs in primary care, specifically to address CHWs' dual clinic-based and community-oriented role. OBJECTIVE: Using evidence from CHWs' adaptations of a diabetes-prevention intervention in safety-net hospitals in New York City, we examine the nature, intent, and possible consequences of CHWs' actions on program fidelity. We propose strategies for integrating CHWs in primary care. DESIGN: Case study drawing on the Model for Adaptation Design and Impact (MADI) to analyze CHWs' actions during implementation of CHORD (Community Health Outreach to Reduce Diabetes), a cluster-randomized pragmatic trial (2017-2022) at Manhattan VA and Bellevue Hospital. PARTICIPANTS: CHWs and clinicians in the CHORD study, with a focus in this analysis on CHWs. APPROACH: Semi-structured interviews and focus group discussion with CHWs (n=4); semi-structured interviews with clinicians (n=17). Interpretivist approach to explain CHWs' adaptations using a mix of inductive and deductive analysis. KEY RESULTS: CHWs' adaptations extended the intervention in three ways: by extending social assistance, healthcare access, and operational tasks. The adaptations were intended to improve fit, reach, and retention, but likely had ripple effects on implementation outcomes. CHWs' focus on patients' complex social needs could divert them from judiciously managing their caseload. CONCLUSIONS: CHWs' community knowledge can support patient engagement, but overextension of social assistance may detract from protocolized health-coaching goals. CHW programs in primary care should explicitly delineate CHWs' non-health support to patients, include multiprofessional teams or partnerships with community-based organizations, establish formal communication between CHWs and clinicians, and institute mechanisms to review and iterate CHWs' work to resolve challenges in their community-oriented role.

Implementation fidelity to a behavioral diabetes prevention intervention in two New York City safety net primary care practices.

BACKGROUND: It is critical to assess implementation fidelity of evidence-based interventions and factors moderating fidelity, to understand the reasons for their success or failure. However, fidelity and fidelity moderators are seldom systematically reported. The study objective was to conduct a concurrent implementation fidelity evaluation and examine fidelity moderators of CHORD (Community Health Outreach to Reduce Diabetes), a pragmatic, cluster-randomized, controlled trial to test the impact of a Community Health Workers (CHW)-led health coaching intervention to prevent incident type 2 Diabetes Mellitus in New York (NY). METHODS: We applied the Conceptual Framework for Implementation Fidelity to assess implementation fidelity and factors moderating it across the four core intervention components: patient goal setting, education topic coaching, primary care (PC) visits, and referrals to address social determinants of health (SDH), using descriptive statistics and regression models. PC patients with prediabetes receiving care from safety-net patient-centered medical homes (PCMHs) at either, VA NY Harbor or at Bellevue Hospital (BH) were eligible to be randomized into the CHW-led CHORD intervention or usual care. Among 559 patients randomized and enrolled in the intervention group, 79.4% completed the intake survey and were included in the analytic sample for fidelity assessment. Fidelity was measured as coverage, content adherence and frequency of each core component, and the moderators assessed were implementation site and patient activation measure. RESULTS: Content adherence was high for three components with nearly 80.0% of patients setting ≥ 1 goal, having ≥ 1 PC visit and receiving ≥ 1 education session. Only 45.0% patients received ≥ 1 SDH referral. After adjusting for patient gender, language, race, ethnicity, and age, the implementation site moderated adherence to goal setting (77.4% BH vs. 87.7% VA), educational coaching (78.9% BH vs. 88.3% VA), number of successful CHW-patient encounters (6 BH vs 4 VA) and percent of patients receiving all four components (41.1% BH vs. 25.7% VA). CONCLUSIONS: The fidelity to the four CHORD intervention components differed between the two implementation sites, demonstrating the challenges in implementing complex evidence-based interventions in different settings. Our findings underscore the importance of measuring implementation fidelity in contextualizing the outcomes of randomized trials of complex multi-site behavioral interventions. TRIAL REGISTRATION: The trial was registered with ClinicalTrials.gov on 30/12/2016 and the registration number is NCT03006666 .

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Ten best practices for effective phenological research.

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project's needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

Self-Assessed Severity as a Determinant of Coronavirus Disease 2019 Symptom Specificity: A Longitudinal Cohort Study.

Coronavirus disease 2019 symptom definitions rarely include symptom severity. We collected daily nasal swab samples and symptom diaries from contacts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case patients. Requiring ≥1 moderate or severe symptom reduced sensitivity to predict SARS-CoV-2 shedding from 60.0% (95% confidence interval [CI], 52.9%-66.7%) to 31.5% (95% CI, 25.7%- 38.0%) but increased specificity from 77.5% (95% CI, 75.3%-79.5%) to 93.8% (95% CI, 92.7%-94.8%).

National Health Policy Leadership Program for General Internists.

INTRODUCTION: Early or mid-career physicians have few opportunities to participate in career development programs in health policy and advocacy with experiential and mentored training that can be incorporated into their busy lives. AIM: The Society of General Internal Medicine (SGIM) created the Leadership in Health Policy (LEAHP) program, a year-long career development program, to prepare participants with a sufficient depth of knowledge, skills, attitudes, and behaviors to continue to build mastery and effectiveness as leaders, advocates, and educators in health policy. We sought to evaluate the program's impact on participants' self-efficacy in the core skills targeted in the curriculum. SETTING/PARTICIPANTS: Fifty-five junior faculty and trainees across three scholar cohorts from 2017 to 2021. PROGRAM DESCRIPTION: Activities included workshops and exercises at an annual meeting, one-on-one mentorship, monthly webinars and journal clubs, interaction with policy makers, and completion of capstone projects. PROGRAM EVALUATION: Self-administered, electronic surveys conducted before and following the year-long program showed a significant improvement in mean self-efficacy scores for the total score and for each of the six domains in general knowledge, teaching, research, and advocacy in health policy. Compared to the baseline scores, after the program the total mean score increased from 3.1 to 4.1, an increase of 1.1 points on a 5-point Likert scale (95% CI: 0.9-1.3; Cohen's D: 1.7), with 61.4% of respondents increasing their mean score by at least 1 point. Responses to open-ended questions indicated that the program met scholars' stated needs to improve their knowledge base in health policy and advocacy skills. DISCUSSION: The LEAHP program provides an opportunity for mentored, experiential training in health policy and advocacy, can build the knowledge and amplify the scale of physicians engaged in health policy, and help move physicians from individual patient advocacy in the clinic to that of populations.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018.

BACKGROUND: Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent. OBJECTIVE: To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment. METHODS: The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum. RESULTS: In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001). CONCLUSION: Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Who is Responsible for Discharge Education of Patients? A Multi-Institutional Survey of Internal Medicine Residents.

BACKGROUND: Safely and effectively discharging a patient from the hospital requires working within a multidisciplinary team. However, little is known about how perceptions of responsibility among the team impact discharge communication practices. OBJECTIVE: Our study attempts to understand residents' perceptions of who is primarily responsible for discharge education, how these perceptions affect their own reported communication with patients, and how residents envision improving multidisciplinary communication around discharges. DESIGN: A multi-institutional cross-sectional survey. PARTICIPANTS: Internal medicine (IM) residents from seven US residency programs at academic medical centers were invited to participate between March and May 2019, via email of an electronic link to the survey. MAIN MEASURES: Data collected included resident perception of who on the multidisciplinary team is primarily responsible for discharge communication, their own reported discharge communication practices, and open-ended comments on ways discharge multidisciplinary team communication could be improved. KEY RESULTS: Of the 613 resident responses (63% response rate), 35% reported they were unsure which member of the multidisciplinary team is primarily responsible for discharge education. Residents who believed it was either the intern's or the resident's primary responsibility had 4.28 (95% CI, 2.51-7.30) and 3.01 (95% CI, 1.66-5.71) times the odds, respectively, of reporting doing discharge communication practices frequently compared to those who were not sure who was primarily responsible. To improve multidisciplinary discharge communication, residents called for the following among team members: (1) clarifying roles and responsibilities for communication with patients, (2) setting expectations for communication among multidisciplinary team members, and (3) redefining culture around discharges. CONCLUSIONS: Residents report a lack of understanding of who is responsible for discharge education. This diffusion of ownership impacts how much residents invest in patient education, with more perceived responsibility associated with more frequent discharge communication.

Evaluating autumn phenology derived from field observations, satellite data, and carbon flux measurements in a northern mixed forest, USA.

Common approaches currently used to monitor forest phenology include direct field observation and indirect approaches such as satellite remote sensing and carbon flux measurements. However, differences in both temporal and spatial scales of these methods make direct comparison challenging. In order to evaluate the reliability of indirect measures of autumn phenology in estimating direct observations, we compared the timing of three transition dates and the rate of autumn progression derived from (i) satellite data (MOD13Q1 006 enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) products, 2000-2017), (ii) carbon flux measurements (net ecosystem exchange (NEE) and gross primary production (GPP), 1997-2016), and (iii) field observation (2010, 2012 for the north site and 2010, 2012, and 2013 for the south site) from a mixed forest in northern Wisconsin, USA. Overall, the transition dates and progression rates derived from NDVI were closest to that of field observations. Furthermore, the start of autumn derived from satellite data was earlier than directly observed leaf coloration (LC), which resulted from species-specific canopy senescence patterns and the sensitivity of the vegetation indices. Even after full leaf fall was reached, EVI continued to detect coloring which was likely due to the presence of understory plant species. Finally, NEE and GPP changes tended to start before LC as a result of tree physiological and environmental changes and continued after full leaf fall possibly due to understory and coniferous activity. These results highlight the need for long-term field observations of both trees and understory species, information on species-specific canopy senescence patterns, and species composition in understanding the efficiency of indirect approaches in estimating autumn forest phenology.

Why don't phenophase dates in the current year affect the same phenophase dates in the following year?

Examining whether a phenophase occurrence date in the current year affects the same phenophase occurrence date in the following year is crucial for developing cross-year phenological prediction models. Here, we carried out correlation analyses between leaf unfolding start (LUS)/leaf fall end (LFE) dates in the current and following years for four dominant tree species in temperate northern China from 1981 to 2012. Then, we calculated the recurrence intervals of LUS and LFE between two adjacent years for each species. Moreover, we investigated temperature effects on LUS/LFE dates, growing season and non-growing season lengths. Results show that correlation coefficients between LUS/LFE dates in the current and following years are nonsignificant at most stations. The recurrence interval of a phenophase has slight interannual variation and correlates significantly (and negatively) with the phenophase occurrence date of the current year. Further analyses indicate that LUS dates correlate significantly (and negatively) with spring mean temperatures, while LFE dates correlate significantly (and positively) with autumn mean temperatures, but negatively with growing season mean temperatures. In addition, spring mean temperatures can influence growing season length by controlling LUS date but cannot influence the following non-growing season length. Similarly, autumn mean temperatures and growing season mean temperatures can influence the subsequent non-growing season length but cannot influence the growing season length of the following year. Our study highlights that recurrence interval and time restrictions in the effects of seasonal temperatures on phenophase dates are the main environmental causes of nonsignificant correlations between phenophase occurrence dates in the current and following years.

How well do the spring indices predict phenological activity across plant species?

The spring indices, models that represent the onset of spring season biological activity, were developed using a long-term observational record from the mid-to-late twentieth century of three species of lilacs and honeysuckles contributed by volunteer observers across the nation. The USA National Phenology Network (USA-NPN) produces and freely delivers maps of spring index onset dates at fine spatial scale for the USA. These maps are used widely in natural resource planning and management applications. The extent to which the models represent activity in a broad suite of plant species is not well documented. In this study, we used a rich record of observational plant phenology data (37,819 onset records) collected in recent years (1981-2017) to evaluate how well gridded maps of the spring index models predict leaf and flowering onset dates in (a) 19 species of ecologically important, broadly distributed deciduous trees and shrubs, and (b) the lilac and honeysuckle species used to construct the models. The extent to which the spring indices predicted vegetative and reproductive phenology varied by species and with latitude, with stronger relationships revealed for shrubs than trees and with the Bloom Index compared to the Leaf Index, and reduced concordance between the indices at higher latitudes. These results allow us to use the indices as indicators of when to expect activity across widely distributed species and can serve as a yardstick to assess how future changes in the timing of spring will impact a broad array of trees and shrubs across the USA.

Association of Geographic Differences in Prevalence of Uncontrolled Chronic Conditions With Changes in Individuals' Likelihood of Uncontrolled Chronic Conditions.

Importance: The prevalence of leading risk factors for morbidity and mortality in the US significantly varies across regions, states, and neighborhoods, but the extent these differences are associated with a person's place of residence vs the characteristics of the people who live in different places remains unclear. Objective: To estimate the degree to which geographic differences in leading risk factors are associated with a person's place of residence by comparing trends in health outcomes among individuals who moved to different areas or did not move. Design, Setting, and Participants: This retrospective cohort study estimated the association between the differences in the prevalence of uncontrolled chronic conditions across movers' destination and origin zip codes and changes in individuals' likelihood of uncontrolled chronic conditions after moving, adjusting for person-specific fixed effects, the duration of time since the move, and secular trends among movers and those who did not move. Electronic health records from the Veterans Health Administration were analyzed. The primary analysis included 5 342 207 individuals with at least 1 Veterans Health Administration outpatient encounter between 2008 and 2018 who moved zip codes exactly once or never moved. Exposures: The difference in the prevalence of uncontrolled chronic conditions between a person's origin zip code and destination zip code (excluding the individual mover's outcomes). Main Outcomes and Measures: Prevalence of uncontrolled blood pressure (systolic blood pressure level >140 mm Hg or diastolic blood pressure level >90 mm Hg), uncontrolled diabetes (hemoglobin A1c level >8%), obesity (body mass index >30), and depressive symptoms (2-item Patient Health Questionnaire score ≥2) per quarter-year during the 3 years before and the 3 years after individuals moved. Results: The study population included 5 342 207 individuals (mean age, 57.6 [SD, 17.4] years, 93.9% men, 72.5% White individuals, and 12.7% Black individuals), of whom 1 095 608 moved exactly once and 4 246 599 never moved during the study period. Among the movers, the change after moving in the prevalence of uncontrolled blood pressure was 27.5% (95% CI, 23.8%-31.3%) of the between-area difference in the prevalence of uncontrolled blood pressure. Similarly, the change after moving in the prevalence of uncontrolled diabetes was 5.0% (95% CI, 2.7%-7.2%) of the between-area difference in the prevalence of uncontrolled diabetes; the change after moving in the prevalence of obesity was 3.1% (95% CI, 2.0%-4.2%) of the between-area difference in the prevalence of obesity; and the change after moving in the prevalence of depressive symptoms was 15.2% (95% CI, 13.1%-17.2%) of the between-area difference in the prevalence of depressive symptoms. Conclusions and Relevance: In this retrospective cohort study of individuals receiving care at Veterans Health Administration facilities, geographic differences in prevalence were associated with a substantial percentage of the change in individuals' likelihood of poor blood pressure control or depressive symptoms, and a smaller percentage of the change in individuals' likelihood of poor diabetes control and obesity. Further research is needed to understand the source of these associations with a person's place of residence.

Protocol for the CHORD project (community health outreach to reduce diabetes): a cluster-randomized community health worker trial to prevent diabetes.

BACKGROUND: Type 2 diabetes mellitus (DM) affects 9.4% of US adults and children, while another 33.9% of Americans are at risk of DM. Health care institutions face many barriers to systematically delivering the preventive care needed to decrease DM incidence. Community health workers (CHWs) may, as frontline public health workers bridging clinic and community, help overcome these challenges. This paper presents the protocol for a pragmatic, cluster-randomized trial integrating CHWs into two primary care clinics to support DM prevention for at-risk patients. METHODS: The trial will randomize 15 care teams, stratified by practice site (Bellevue Hospital and Manhattan VA), totaling 56 primary care physicians. The study cohort will consist of ~ 2000 patients who are 18-75 years of age, actively enrolled in a primary care team, able to speak English or Spanish, and have at least one glycosylated hemoglobin (HbA1c) result in the prediabetic range (5.7-6.4%) since 2012. Those with a current DM diagnosis or DM medication prescription (other than metformin) are ineligible. The intervention consists of four core activities - setting health goals, health education, activation for doctor's appointments, and referrals to DM prevention programs - adjustable according to the patient's needs and readiness. The primary outcome is DM incidence. Secondary outcomes include weight loss, HbA1C, and self-reported health behaviors. Clinical variables and health behaviors will be obtained through electronic medical records and surveys, respectively. Implementation outcomes, namely implementation fidelity and physicians' perspectives about CHW integration into the clinic, will be assessed using interviews and CHW activity logs and analyzed for the influence of moderating organizational factors. DISCUSSION: This is the first rigorous, pragmatic trial to test the effectiveness of integrating CHWs into primary care for DM prevention reaching a population-based sample. Our study's limitations include language-based eligibility and the use of HbA1c as a measure of DM risk. It will measure both clinical and implementation outcomes and potentially broaden the evidence base for CHWs and patient-centered medical home implementation. Further, the intervention's unique features, notably patient-level personalization and referral to existing programs, may offer a scalable model to benefit patients at-risk of DM. TRIAL REGISTRATION: Clinicaltrials.gov NCT03006666 (Received 12/27/2016).

Qualitative study on decision-making by prostate cancer physicians during active surveillance.

OBJECTIVE: To explore and identify factors that influence physicians' decisions while monitoring patients with prostate cancer on active surveillance (AS). SUBJECTS AND METHODS: A purposive sampling strategy was used to identify physicians treating prostate cancer from diverse clinical backgrounds and geographic areas across the USA. We conducted 24 in-depth interviews from July to December 2015, until thematic saturation was reached. The Applied Thematic Analysis framework was used to guide data collection and analysis. Interview transcripts were reviewed and coded independently by two researchers. Matrix analysis and NVivo software were used for organization and further analysis. RESULTS: Eight key themes emerged to explain variation in AS monitoring: (i) physician comfort with AS; (ii) protocol selection; (iii) beliefs about the utility and quality of testing; (iv) years of experience and exposure to AS during training; (v) concerns about inflicting 'harm'; (vi) patient characteristics; (vii) patient preferences; and (viii) financial incentives. CONCLUSION: These qualitative data reveal which factors influence physicians who manage patients on AS. There is tension between providing standardized care while also considering individual patients' needs and health status. Additional education on AS is needed during urology training and continuing medical education. Future research is needed to empirically understand whether any specific protocol is superior to tailored, individualized care.

An observation-based progression modeling approach to spring and autumn deciduous tree phenology.

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade (p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade (p < 0.02) during the 1970-2012 period; two simulated autumn phenophases were significantly delayed at a rate of 0.37 (mid-leaf coloration) and 0.50 (full-leaf coloration) days/decade (p < 0.01) during the 1970-2012 period. Consequently, the simulated growing season lengthened at a rate of 0.45 and 2.50 days/decade (p < =0.001), respectively, during the two periods. Our results further showed the variability of responses to climate between early and late spring phenophases, as well as between leaf coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.