7 research outputs found
Implementation findings from a hybrid III implementation-effectiveness trial of the Diabetes Prevention Program (DPP) in the Veterans Health Administration (VHA).
BackgroundThe Diabetes Prevention Program (DPP) is an effective lifestyle intervention to reduce incidence of type 2 diabetes. However, there are gaps in knowledge about how to implement DPP. The aim of this study was to evaluate implementation of DPP via assessment of a clinical demonstration in the Veterans Health Administration (VHA).MethodsA 12-month pragmatic clinical trial compared weight outcomes between the Veterans Affairs Diabetes Prevention Program (VA-DPP) and the usual care MOVE!® weight management program (MOVE!). Eligible participants had a body mass index (BMI) ≥30 kg/m2 (or BMI ≥ 25 kg/m2 with one obesity-related condition), prediabetes (glycosylated hemoglobin (HbA1c) 5.7-6.5% or fasting plasma glucose (FPG) 100-125 mg/dL), lived within 60 min of their VA site, and had not participated in a weight management program within the last year. Established evaluation and implementation frameworks were used to guide the implementation evaluation. Implementation barriers and facilitators, delivery fidelity, participant satisfaction, and implementation costs were assessed. Using micro-costing methods, costs for assessment of eligibility and scheduling and maintaining adherence per participant, as well as cost of delivery per session, were also assessed.ResultsSeveral barriers and facilitators to Reach, Adoption, Implementation, Effectiveness and Maintenance were identified; barriers related to Reach were the largest challenge encountered by site teams. Fidelity was higher for VA-DPP delivery compared to MOVE! for five of seven domains assessed. Participant satisfaction was high in both programs, but higher in VA-DPP for most items. Based on micro-costing methods, cost of assessment for eligibility was 328/participant, and cost of delivery was $101/session.ConclusionsMulti-faceted strategies are needed to reach targeted participants and successfully implement DPP. Costs for assessing patients for eligibility need to be carefully considered while still maximizing reach to the targeted population
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Implementation findings from a hybrid III implementation-effectiveness trial of the Diabetes Prevention Program (DPP) in the Veterans Health Administration (VHA).
BackgroundThe Diabetes Prevention Program (DPP) is an effective lifestyle intervention to reduce incidence of type 2 diabetes. However, there are gaps in knowledge about how to implement DPP. The aim of this study was to evaluate implementation of DPP via assessment of a clinical demonstration in the Veterans Health Administration (VHA).MethodsA 12-month pragmatic clinical trial compared weight outcomes between the Veterans Affairs Diabetes Prevention Program (VA-DPP) and the usual care MOVE!® weight management program (MOVE!). Eligible participants had a body mass index (BMI) ≥30 kg/m2 (or BMI ≥ 25 kg/m2 with one obesity-related condition), prediabetes (glycosylated hemoglobin (HbA1c) 5.7-6.5% or fasting plasma glucose (FPG) 100-125 mg/dL), lived within 60 min of their VA site, and had not participated in a weight management program within the last year. Established evaluation and implementation frameworks were used to guide the implementation evaluation. Implementation barriers and facilitators, delivery fidelity, participant satisfaction, and implementation costs were assessed. Using micro-costing methods, costs for assessment of eligibility and scheduling and maintaining adherence per participant, as well as cost of delivery per session, were also assessed.ResultsSeveral barriers and facilitators to Reach, Adoption, Implementation, Effectiveness and Maintenance were identified; barriers related to Reach were the largest challenge encountered by site teams. Fidelity was higher for VA-DPP delivery compared to MOVE! for five of seven domains assessed. Participant satisfaction was high in both programs, but higher in VA-DPP for most items. Based on micro-costing methods, cost of assessment for eligibility was 328/participant, and cost of delivery was $101/session.ConclusionsMulti-faceted strategies are needed to reach targeted participants and successfully implement DPP. Costs for assessing patients for eligibility need to be carefully considered while still maximizing reach to the targeted population
Implementation findings from a hybrid III implementation-effectiveness trial of the Diabetes Prevention Program (DPP) in the Veterans Health Administration (VHA)
Abstract Background The Diabetes Prevention Program (DPP) is an effective lifestyle intervention to reduce incidence of type 2 diabetes. However, there are gaps in knowledge about how to implement DPP. The aim of this study was to evaluate implementation of DPP via assessment of a clinical demonstration in the Veterans Health Administration (VHA). Methods A 12-month pragmatic clinical trial compared weight outcomes between the Veterans Affairs Diabetes Prevention Program (VA-DPP) and the usual care MOVE!® weight management program (MOVE!). Eligible participants had a body mass index (BMI) ≥30 kg/m2 (or BMI ≥ 25 kg/m2 with one obesity-related condition), prediabetes (glycosylated hemoglobin (HbA1c) 5.7–6.5% or fasting plasma glucose (FPG) 100–125 mg/dL), lived within 60 min of their VA site, and had not participated in a weight management program within the last year. Established evaluation and implementation frameworks were used to guide the implementation evaluation. Implementation barriers and facilitators, delivery fidelity, participant satisfaction, and implementation costs were assessed. Using micro-costing methods, costs for assessment of eligibility and scheduling and maintaining adherence per participant, as well as cost of delivery per session, were also assessed. Results Several barriers and facilitators to Reach, Adoption, Implementation, Effectiveness and Maintenance were identified; barriers related to Reach were the largest challenge encountered by site teams. Fidelity was higher for VA-DPP delivery compared to MOVE! for five of seven domains assessed. Participant satisfaction was high in both programs, but higher in VA-DPP for most items. Based on micro-costing methods, cost of assessment for eligibility was 328/participant, and cost of delivery was $101/session. Conclusions Multi-faceted strategies are needed to reach targeted participants and successfully implement DPP. Costs for assessing patients for eligibility need to be carefully considered while still maximizing reach to the targeted population
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative
impact, these new capabilities are as yet poorly characterized. In order to
inform future research, prepare for disruptive new model capabilities, and
ameliorate socially harmful effects, it is vital that we understand the present
and near-future capabilities and limitations of language models. To address
this challenge, we introduce the Beyond the Imitation Game benchmark
(BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442
authors across 132 institutions. Task topics are diverse, drawing problems from
linguistics, childhood development, math, common-sense reasoning, biology,
physics, social bias, software development, and beyond. BIG-bench focuses on
tasks that are believed to be beyond the capabilities of current language
models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense
transformer architectures, and Switch-style sparse transformers on BIG-bench,
across model sizes spanning millions to hundreds of billions of parameters. In
addition, a team of human expert raters performed all tasks in order to provide
a strong baseline. Findings include: model performance and calibration both
improve with scale, but are poor in absolute terms (and when compared with
rater performance); performance is remarkably similar across model classes,
though with benefits from sparsity; tasks that improve gradually and
predictably commonly involve a large knowledge or memorization component,
whereas tasks that exhibit "breakthrough" behavior at a critical scale often
involve multiple steps or components, or brittle metrics; social bias typically
increases with scale in settings with ambiguous context, but this can be
improved with prompting.Comment: 27 pages, 17 figures + references and appendices, repo:
https://github.com/google/BIG-benc