A pilot randomized controlled trial of group-based indoor gardening and art activities demonstrates therapeutic benefits to healthy women.

BackgroundThere is mounting anecdotal and empirical evidence that gardening and art-making afford therapeutic benefits.ObjectivesThis randomly controlled pilot study tested the hypothesis that participation in group-based indoor gardening or art-making activities for one hour twice a week for four weeks would provide quantifiably different therapeutic benefits to a population of healthy women ages 26-49.MethodsA population of 42 volunteers was randomly assigned to parallel gardening or art-making treatment groups. A total of 36 participants initiated the treatment protocol and 32 (Gardening n = 15 and Art n = 17) received the interventions and completed all assessments. Treatments included eight one-hour group-based gardening or art intervention sessions. Self-report psychometric assessments were conducted for anxiety, depression symptomatology, mood disturbance, stress, satisfaction with discretionary social activities, and quality of life measures. Cardiac physiological data were also collected. Outcomes were measured at baseline, during, and post-intervention.ResultsEngaging in both gardening and art-making activities resulted in apparent therapeutic improvements for self-reported total mood disturbance, depression symptomatology, and perceived stress with different effect sizes following eight one-hour treatment sessions. Gardening also resulted in improvements for indications of trait anxiety. Based on time-course evidence, dosage responses were observed for total mood disturbance, perceived stress, and depression symptomatology for both gardening and art-making. However, gardening or art-making did not have an apparent influence on heart rate or blood pressure or result in marked improvement for satisfaction with discretionary leisure activities.ConclusionThe data did not support the hypothesis of differential therapeutic benefits of gardening and art-making for healthy women. When taken together, group-based gardening or art-making can provide quantitatively measurable improvements in healthy women's psychosocial health status that imply potentially important public health benefits.Trial registrationClinicalTrials.gov NCT03266120

Multiple models for outbreak decision support in the face of uncertainty

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020

Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020