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Efrem Kulagin
Efrem Kulagin

Wheel Of Time Epub 16

Chemical induction of intestinal inflammation via graded doses of DSS resulted in a dose-dependent reduction in VWR behaviour in 1% and 1.5% DSS-treated mice (Fig 1B). In contrast, increased clinical scores and reduced body weights appeared delayed and occurred only in the 1.5% treatment group, suggesting that VWR is an earlier and more sensitive indicator of compromised welfare (Fig 1A and S2A Fig). Similarly, serial blood sampling by facial vein phlebotomy led to reduced VWR behaviour in both control and DSS-treated mice but was not discernible by clinical scoring (S2B Fig). In addition, and rather unexpectedly to this extent, aggravation of the course of colitis as reflected by increased histological scores and a greater reduction of body weight were also observed due to serial blood sampling (S4 Fig and Fig 1C and 1D). In a recent study, facial vein phlebotomy had the mildest effect on animal welfare when the impact of single sublingual vein puncture, tail vein puncture, retrobulbar plexus/sinus puncture, and facial vein puncture were compared [26]. In another study, tail tip amputation was identified as the least compromising procedure when compared to facial vein puncture and lateral tail vein incision [27]. Blood sampling is a common procedure in laboratory animal-based research and may not only have a potential impact on the animal with regard to compromised welfare but may also interfere with the research model of choice and the respective readouts. In the present study, the utilized blood-sampling routine was a complex procedure comprising routine handling, restraining, and the actual transfer of the animals in itself. Therefore, at this time, we cannot identify the most compromising act, and this needs to be addressed in future investigations.

wheel of time epub 16

All mice of this study had access to running wheels. Prior to study initiation, a 2-week adaption phase to the running wheel was chosen as outlined below. In the cohorts, the experimental set up was as follows: animals were treated with DSS (0% [control], 1%, or 1.5%) from d 1 to d 5. In these mice, faecal sampling was performed on d 0, d 5, and d 14. Additional DSS-treated mice (0% [control], 1%, or 1.5%) underwent faecal sampling as well as phlebotomy on d 0, d 5, and d 14. Additional mice were used in the restraint stress model. In these groups, restraint stress was applied from d 1 to d 10. In these and respective control mice, faecal sampling was performed on d 0, d 7, and d 10.

After a 2-week habituation to the animal room, animals were divided into treatment and control groups by applying a random selection procedure (drawing lots). A 2-week adaption phase to wheel running was chosen.

(a) Determination of the cluster number by scree plot analysis. Within the scree plot method, three clusters were identified as the optimal size for k-means clustering (dashed line). (b) Utilization of the BIC to validate the number of clusters. All multivariate models except EII and VII had a maximum BIC at three clusters (dashed line). (c) Monitoring of cluster stability by seeding permutations. The median upper threshold at random seeding over 100 iterations was WR20 = 87.37% (95% CB [83.75; 90.39]), the lower median threshold WR20 = 50.16% (95% CB [46.43; 53.57]). BIC, Bayesian information criterion; CB, confidence border; WR20, wheel rotations during 20 hours/day

Design: This study will be a multi-centre, randomised, controlled trial with concealed allocation, assessor blinding, and intention-to-treat analysis, comparing a 6-week behaviour change intervention aimed at reducing sedentary time with a sham intervention in people with chronic obstructive pulmonary disease.

Intervention: The behaviour change intervention aims to reduce sedentary time through a process of guided goal setting with participants to achieve two target behaviours: (1) replace sitting and lying down with light-intensity physical activity where possible, and (2) stand up and move for 2minutes after 30minutes of continuous sedentary time. Three face-to-face sessions and three phone sessions will be held with a physiotherapist over the 6-week intervention period. The 'capability', 'opportunity', 'motivation' and 'behaviour' (COM-B) model will be applied to each participant to determine which components of behaviour (capability, opportunity or motivation) need to change in order to reduce sedentary time. Based on this 'behavioural diagnosis', the Behaviour Change Wheel will be used to systematically select appropriate behaviour change techniques to assist participants in achieving their weekly goals. Behaviour change techniques will include providing information about the health consequences of sedentary behaviour, self-monitoring and review of weekly goals, problem-solving of barriers to achieving weekly goals, and providing feedback on sedentary time using the Jawbone UP3 activity monitor.

Measurements: Outcomes will be assessed at baseline, at the end of the 6-week intervention period, and at the 3-month follow-up. Primary outcome measures will be: (1) total sedentary time, including the pattern of accumulation of sedentary time, assessed by the activPAL3 activity monitor, and (2) feasibility of the intervention assessed by uptake and retention of participants, participant compliance, self-reported achievement of weekly goals, and adverse events. Secondary outcome measures will include functional exercise capacity, health-related quality of life, domain-specific and behaviour-specific sedentary time, patient activation, and anxiety and depression. Semi-structured interviews will be conducted with participants who receive the behaviour change intervention to explore acceptability and satisfaction with the different components of the intervention.

Analysis: Analysis of covariance (ANCOVA) will be used to calculate between-group comparisons of total sedentary time and the number of bouts of sedentary time>30minutes after adjusting baseline values. Uncertainty about the size of the mean between-group differences will be quantified with 95% CI. Within-group comparisons will be examined using paired t-tests and described as mean differences with 95% CIs. Secondary outcome measures will be analysed similarly. The feasibility measures will be analysed descriptively. Semi-structured interviews will be conducted until data saturation is achieved and there are no new emerging themes. De-identified interview transcripts will be coded independently by two researchers and analysed alongside data collection using the COM-B model as a thematic framework.

Discussion/significance: If behaviour change interventions are found to be an effective and feasible method for reducing sedentary time, such interventions may be used to reduce cardiometabolic risk in people with chronic obstructive pulmonary disease. An approach that emphasises participation in light-intensity physical activity may increase the confidence and willingness of people with chronic obstructive pulmonary disease to engage in more intense physical activity, and may serve as an intermediate goal to increase uptake of pulmonary rehabilitation.

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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. 350c69d7ab


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