3/2014Glance LG, Dick AW, Osler TM. "ICU scoring systems: after 30 years of reinventing the wheel, isn't it time to build the cart?*." Critical care medicine.. 2014 Mar; 42(3):732-4.
2/2010Li Y, Schnelle J, Spector WD, Glance LG, Mukamel DB. "The "Nursing Home Compare" measure of urinary/fecal incontinence: cross-sectional variation, stability over time, and the impact of case mix." Health services research.. 2010 Feb; 45(1):79-97. Epub 2009 Oct 29.
wheel of time epub 29
Conclusions: Compared with placebo, ocrelizumab significantly delayed time to 24-week confirmed wheelchair requirement in ORATORIO. The plausibility of the extrapolated median time to reach this milestone in the placebo group was supported by observed real-world data from MSBase. Extrapolated benefits for ocrelizumab over placebo could represent a truly meaningful delay in loss of ambulation and independence.
Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity.
Given that policies can only influence behaviour through the interventions that they enable or support, it seemed appropriate to place interventions between these and behaviour. The most parsimonious way of doing this seemed to be to represent the whole classification system in terms of a 'behaviour change wheel' (BCW) with three layers as shown in Figure 2. This is not a linear model in that components within the behaviour system interact with each other as do the functions within the intervention layer and the categories within the policy layer.
We believe that this is the first attempt to undertake a systematic analysis of behaviour intervention frameworks and apply usefulness criteria to them. This is also the first time that a new framework has been constructed from existing frameworks explicitly to overcome their limitations. Moreover, we are not aware of other attempts to assess the reliability with which a framework can be applied in practice.
An existing framework that has made an important contribution to making intervention design more systematic is 'intervention mapping' [16]. A key difference between this and the BCW approach is that intervention mapping aims to map behaviour on to its 'theoretical determinants' in order to identify potential levers for change, whereas the BCW approach recognises that the target behaviour can in principle arise from combinations of any of the components of the behaviour system. It may appear that some components are more important than others because of a lack of variance in (including absence or universal presence of) the variables concerned in the population under study. This can be illustrated by a study of GP advice to smokers, which found that a single variable -- degree of concern that it would harm the doctor-patient relationship -- accounted for significant variance in the rate of advice-giving [49]. 'Intervention mapping' would suggest that concern be the target for an intervention (as long as a judgement were made that this could be modified using interventions that were realistically applicable). The BCW would analyse the target behaviour in context and note that, regardless of what covariation might currently exist, the target behaviour consists of an activity in which capability is not at issue, and the reflective motivation is broadly positive. The problem arises because automatic motivational factors are currently working against the behaviour (e.g., lack of emotional reward for giving advice or punishment for not giving it and lack of cues to action). Moreover, the physical opportunity is limited (lack of time) and the social opportunities are also somewhat limited. It would then consider the full range of ways in which the frequency of advice-giving could be increased. Because the target behaviour is part of a 'system,' a single intervention may have consequences for other parts of the system - these might work against sustainable change or in favour of it.
Thus, the BCW approach is based on a comprehensive causal analysis of behaviour and starts with the question: 'What conditions internal to individuals and in their social and physical environment need to be in place for a specified behavioural target to be achieved?' The 'intervention mapping' approach is based on an epidemiological analysis of co-variation within the behavioural domain and starts with the question: 'What factors in the present population at the present time underlie variation in the behavioural parameter?' When it comes to theoretical underpinnings, the BCW approach draws from a single unifying theory of motivation in context that predicts what aspects of the motivational system will need to be influenced in what ways to achieve a behavioural target, whereas the 'intervention mapping' approach draws on a range of theoretical approaches each of which independently addresses different aspects of the behaviour in question.
Merz AA, Gutiérrez-Sacristán A, Bartz D, Williams NE, Ojo A, Schaefer KM, Huang M, Li CY, Sandoval RS, Ye S, Cathcart AM, Starosta A, Avillach P. Population attitudes toward contraceptive methods over time on a social media platform. Am J Obstet Gynecol. 2021 Jun;224(6):597.e1-597.e14. doi: 10.1016/j.ajog.2020.11.042. Epub 2020 Dec 9. PMID: 33309562.
Ten months old homozygous DJ-1 knockout (DJ-1 KO) mice and C57BL/6 wild-type (WT) littermates were trained to perform running wheel exercise in their individual cages. Daily running distances were recorded for two weeks. (A) Wild-type mice ran 5.57 0.21 miles per day, while DJ-1 knockout mice were significantly slower, running 0.89 0.06 miles per day (n = 6, multi-variance ANOVA test, **p
12-month-old Y39C transgenic mice were divided into Exercise and Non-Exercise groups (n = 7 for each group) following pre-testing of all 14 animals in individual cages with running wheels. Animals were assigned to Exercise and Non-Exercise groups by alternating rank order following their week-long pre-test. Exercise mice had free access to individual cage-mounted running wheels and Non-Exercise mice had a locked, non-functioning running wheel in individual cages. Daily running distances of the Exercise animals were recorded and averaged for each week. (A) Data show that all animals continued running for 12 weeks with some reduction in running speed. Average distance in the first week was 3.76 0.87 miles per day. Average distance in the 12th week was 2.71 0.53 miles per day (no statistical difference between 1st and 12th week, n = 7, multi-variance ANOVA, p = 0.33). After 12-weeks of running wheel activity, all mice were tested for high intensity motor activity on the Rotarod (B) and cognitive function using a Morris water maze (C). (B) In the Rotarod test, the Exercise group could remain on the rod significantly longer at 26 rpm than the Non-Exercise group (n = 7, multi-variance ANOVA, **p = 0.001). (C) In the Morris water maze, the Exercise mice took significantly less time to find the hidden platform at Day 5 than Non-Exercise transgenic mice (n = 7, multi-variance ANOVA, *p = 0.02).
(A) Brain tissues (cortex) were processed for Western blot analysis using antibodies to DJ-1, Hsp70, BDNF and β-actin after 3 months of running wheel Exercise (Ex) or no Exercise (nEx) in Y39C transgenic animals. Representative images are shown for all Western blots. (B-D) Quantitative protein levels in brain are shown for each group after being normalized to β-actin. There were significant increases in DJ-1, Hsp70 and BDNF proteins in Exercise mouse brain compared to Non-Exercise mice (n = 7, t-test, *p
Because exercise produces sweeping changes in all aspects of physiology from sensorimotor activity to lipid metabolism in muscle, it is difficult to define a hierarchy of beneficial effects on brain function. Since mice which lack the DJ-1 gene cannot perform on running wheels or on the Rotarod with the same intensity as wild-type animals, DJ-1 appears to be essential for dealing with the physiological stress created in muscle by sustained motor activity. Because DJ-1 knockout animals have the same cognitive performance as wild-type mice in the Morris Water Maze and on open field exploration, the DJ-1 deficit does not appear to influence cognition nor low intensity motor activity. To precisely define the role of muscle verse brain derived DJ-1, organ-specific DJ-1 knockouts would have to be developed.
Our study gives insight into the mechanism by which exercise prevents α-synuclein oligomer accumulation in brain. While oligomer formation was reduced in brains of mice with access to running wheels, the same animals showed increased plasma concentrations of α-synuclein monomers and dimers. α-Synuclein is known to be present in plasma of humans and other mammals, but the exact source of plasma α-synuclein remains uncertain. While it is possible that red blood cells may release α-synuclein into plasma, the protein may come from central and peripheral neurons [67, 68]. Our findings in Y39C transgenic mice show that plasma α-synuclein comes from neurons rather than red blood cells because plasma α-synuclein is approximately 50:50 human/mouse mixture as is brain. By contrast, red blood cell α-synuclein is 100% mouse in our Y39C animals. 2ff7e9595c
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