A workbook of exercises for following directions to be used with high achieving children in grades one, three and five

Thesis (Ed.M.)--Boston Universit

Should EOAD patients be included in clinical trials?

Alzheimer disease (AD) is a devastating neurodegenerative disease affecting 1 in 68 in the population. An arbitrary cutoff 65 years as the age of onset to distinguish between early- and late-onset AD has been proposed and has been used in the literature for decades. As the majority of patients develop AD after 65 years of age, most clinical trials address this population. While the early-onset cases represent only 1% to 6% of AD cases, this population is the active working subset and thus contributes to a higher public health burden per individual, and early-onset cases are the most devastating at the level of the individual and their families. In this review, we compare and contrast the clinical, neuropsychological, imaging, genetic, biomarker, and pathological features of these two arbitrary groups. Finally, we discuss the ethical dilemma of non-abandonment and justice as it pertains to exclusion of the early-onset AD patients from clinical trials

Progress in understanding variability in cognitive responses to cholinesterase inhibitor treatment

Limitations on the duration of clinical trials, and the constraints of participant selection for such studies, have left many unanswered questions regarding the optimal duration of drug treatment for Alzheimer's disease patients, as well as the subgroups of patients that benefit most. Carefully designed observational studies in naturalistic settings can provide important supplementary information to aid clinical decision-making and patient counseling. A paper by Wattmo and colleagues published recently in Alzheimer's Research & Therapy has provided important new information on differential responses to cholinesterase inhibitor (ChEI) treatment in specific subgroups of patients over a 3-year follow-up period. All of the participants in their study were started on one of three ChEIs after their initial assessment, and periodic assessments of cognitive change and the dosage of ChEIs as well as concomitant medications were subsequently recorded. In addition to providing strong evidence of nondifferential effects on cognition of the three ChEIs as used in this practice, the study identified clinically significant differences in the responses of specific subgroups of patients to the initiation of ChEI treatment. Of particular interest to clinicians is the finding that older patients and those with worse cognitive functioning at baseline had a better treatment response. The notion that treatment may be futile in the oldest or the most impaired patients was thus not supported by Wattmo and colleagues' cohort. Additional well-designed naturalistic studies of this type are needed to advance our knowledge of the long-term outcomes obtained with different therapeutic agents, and of the covariates that significantly modify responses to Alzheimer's disease treatments

Longitudinal Sensitivity of alzheimer\u27s Disease Severity Staging

Understanding Alzheimer\u27s disease (AD) dynamics is essential in diagnosis and measuring progression for clinical decision-making; however, clinical instruments are imperfect at classifying true disease stages. This research evaluates sensitivity and determinants of AD stage changes longitudinally using current classifications of mild, moderate, and severe AD, using Mini-Mental State Examination (MMSE), Alzheimer\u27s Disease Assessment Scale-Cognitive subscale (ADAS-Cog), and the Clinical Dementia Rating-Sum of Boxes (CDR-SB) thresholds. Age and pre-progression rate were significant determinants of AD progression using MMSE alone to stage AD, and pre-progression was found to impact disease progression with CDR-SB. Sensitivity of these instruments for identifying clinical stages of AD to correctly staging a moderate level of disease severity for outcomes MMSE, CDR-SB, and ADAS-Cog was 92%, 78%, and 92%, respectively. This research derives longitudinal sensitivity of clinical instruments used to stage AD useful for clinical decision-making. The MMSE and ADAS-Cog provided adequate sensitivity to classify AD stages

Validity, Significance, Strengths, Limitations, and Evidentiary Value of Real-World Clinical Data for Combination Therapy in Alzheimer's Disease: Comparison of Efficacy and Effectiveness Studies

Background: Randomized controlled efficacy trials (RCTs), the scientific gold standard, are required for regulatory approval of Alzheimer's disease (AD) interventions, yet provide limited information regarding real-world therapeutic effectiveness. Objective: To compare the nature of evidence regarding the combination of approved AD treatments from RCTs versus long-term observational controlled studies (LTOCs). Methods: Comparisons of strengths, limitations, and evidence level for monotherapy [cholinesterase inhibitor (ChEI) or memantine] and combination therapy (ChEI + memantine) in RCTs versus LTOCs. Results: RCTs examined highly selected populations over months. LTOCs collected data across multiple AD stages in large populations over many years. RCTs and LTOCs show similar patterns favoring combination over monotherapy over placebo/no treatment. Long-term combination therapy compared to monotherapy reduced cognitive and functional decline and delayed time to nursing home admission. Persistent treatment was associated with slower decline. While LTOCs used control groups, adjusted for multiple covariates, had higher external validity, and favorable ethical, practical and cost considerations, their limitations included potential selection bias due to lack of placebo comparisons and randomization. Conclusions: Naturalistic LTOCs provide complementary long-term level II evidence to complement level I evidence from short-term RCTs regarding therapeutic effectiveness in AD that may otherwise be unobtainable. A coordinated strategy/consortium to pool LTOC data from multiple centers to estimate long-term comparative effectiveness, risks/benefits, and costs of AD treatments is needed

Using mental-modelling to explore how irrigators in the Murray-Darling Basin make water-use decisions

Study region: Water stress and over-allocation are at the forefront of water management and policy challenges in Australia, especially in the Murray–Darling Basin (MDB). Because irrigated agriculture is a major social and economic component of the MDB, farmer decision-making plays a major role in water sustainability in the region. Study focus: This study used a fuzzy cognitive mapping methodology, ‘mental modeling’, to understand the perceived constraints of irrigator water-use decisions in the MDB, for two different types of irrigation: permanent and annual crops. The approach elicits and documents irrigator insights into the complex and networked nature of irrigation water use decisions in relation to farm-based dynamics. New hydrological insights for the region: Results suggest support for greater local and irrigator involvement in water management decisions. Many, if not most, of the irrigators understood the need for, or at least the inevitability of, governmental policies and regulations. However, a lack of accountability, predictability, and transparency has added to the uncertainty in farm-based water decision-making. Irrigators supported the concept of environmental sustainability, although they might not always agree with how the concept is implemented. The mental modelling approach facilitated knowledge sharing among stakeholders and can be used to identify common goals. Future research utilizing the mental modelling approach may encourage co-management and knowledge partnerships between irrigators, water managers and government officials.Ellen M. Douglas, Sarah Ann Wheeler, David J. Smith, Ian C. Overton, Steven A. Gray, Tanya M. Doody, Neville D. Crossma

Reducing MCPA herbicide pollution at catchment scale using an agri-environmental scheme

Publication history: Accepted - 16 May 2022; Published online - 20 May 2022.In river catchments used as drinking water sources, high pesticide concentrations in abstracted waters require an expensive treatment step prior to supply. The acid herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA) is particularly problematic as it is highly mobile in the soil-water environment following application. Here, an agri-environmental scheme (AES) was introduced to a large-scale catchment (384 km2) to potentially reduce the burden of pesticides in the water treatment process. The main measure offered was contractor application of glyphosate by weed wiping as a substitute for boom spraying of MCPA, supported by educational and advisory activities. A combined innovation applied in the assessment was, i) a full before-after-control-impact (BACI) framework over four peak application seasons (April to October 2018 to 2021) where a neighbouring catchment (386 km2) did not have an AES and, ii) an enhanced monitoring approach where river discharge and MCPA concentrations were measured synchronously in each catchment. During peak application periods the sample resolution was every 7 h, and daily during quiescent winter periods. This sampling approach enabled flow- and time-weighted concentrations to be established, and a detailed record of export loads. These loads were up to 0.242 kg km−2 yr−1, and over an order of magnitude higher than previously reported in the literature. Despite this, and accounting for inter-annual and seasonal variations in river discharges, the AES catchment indicated a reduction in both flow- and time-weighted MCPA concentration of up to 21% and 24%, respectively, compared to the control catchment. No pollution swapping was detected. Nevertheless, the percentage of MCPA occurrences above a 0.1 μg L−1 threshold did not reduce and so the need for treatment was not fully resolved. Although the work highlights the advantages of catchment management approaches for pollution reduction in source water catchments, it also indicates that maximising participation will be essential for future AES.This work was carried out as part of Source to Tap (IVA5018), a project supported by the European Union's INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB)

Socio-technical factors influencing current trends in material throughput in the UK automotive industry

This paper investigates why material throughput remains high in the UK automotive industry when there are opportunities for material efficiency improvements. Informed by socio-technical studies of automobility, the paper emphasises the importance of recognising how decisions regarding material use are always shaped by more than simply cost considerations. Drawing on industry interviews, six interconnected socio-technical factors are identified that guide the vehicle design and manufacturing process. These are: (1) customer preferences; (2) market positioning; (3) techno-economic feasibility; (4) supply chain feasibility; (5) regulation and (6) organisational attributes. These factors can provide insights into the current operating context of the UK automotive industry and help explain why the average material intensity of vehicles and vehicle throughput are increasing. Overall, the paper shows that the efficiency of material use in the UK automotive industry is the outcome of complex and advanced design and manufacturing processes. Understanding these processes and the factors that guide them can potentially increase the likelihood of the automotive industry adopting material efficiency initiatives.S. Cooper is supported by a UK Engineering and Physical Sciences Research Council (EPSRC) PhD studentship (reference EP/L504920/1). Professor J.M. Allwood and Dr B.J. Doody by grant number EP/N02351X/1. None of the funding sources were involved with conducting the research