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Climate equity is a crucial but difficult element in negotiations on a post-2012 climate regime. With respect to the trading of greenhouse gas emissions the equity aspect is considered in the Kyoto Protocol which demands that emissions trading should be supplemental to domestic abatement efforts. The question arises whether a linking of the European Union Emissions Trading Scheme (EU ETS) to non-EU emission trading schemes or the Clean Development Mechanism (CDM) could have an impact on principles of climate justice and thus potentially affect ongoing negotiations. In this study, we present the results of a three step analysis: In a first step, it estimates mid-term greenhouse gas emission entitlements for Annex B and Non-Annex B countries for the year 2020 which keep within reach a stabilization of the CO2 concentration at 450 ppmv in the long-term. In the second step, the resulting emission entitlements are used as an input to an economic partial-equilibrium model in order to assess the shift of abatement efforts under different scenarios of linking the EU ETS. In a third step, we analyze the outcome of the economic model with respect to the future trend of European per capita emissions under the current EU ETS relative to different scenarios of linking the EU ETS. The model results indicate that European per capita emissions have to be reduced to a considerably smaller extent if a linking of the EU ETS is accompanied by an optimal design of the National Allocation Plans and if low-cost CO2 permits became available via the CDM to a large extent. [ABSTRACT FROM AUTHOR]

Background: Implementation of an eRehabilitation intervention named Fit After Stroke @Home (Fast@home) - including cognitive/physical exercise applications, activity-tracking, psycho-education - after stroke resulted in health-related improvements. This study investigated what worked and why in the implementation., Methods: Implementation activities (information provision, integration of Fast@home, instruction and motivation) were performed for 14 months and evaluated, using the Medical Research Council framework for process evaluations which consists of three evaluation domains (implementation, mechanisms of impact and contextual factors). Implementation activities were evaluated by field notes/surveys/user data, it's mechanisms of impact by surveys and contextual factors by field notes/interviews among 11 professionals. Surveys were conducted among 51 professionals and 73 patients. User data ( n  = 165 patients) were extracted from the eRehabilitation applications., Results: Implementation activities were executed as planned. Of the professionals trained to deliver the intervention (33 of 51), 25 (75.8%) delivered it. Of the 165 patients, 82 (49.7%) were registered for Fast@home, with 54 patient (65.8%) using it. Mechanisms of impact showed that professionals and patients were equally satisfied with implementation activities (median score 7.0 [IQR 6.0-7.75] versus 7.0 [6.0-7.5]), but patients were more satisfied with the intervention (8.0 [IQR 7.0-8.0] versus 5.5 [4.0-7.0]). Guidance by professionals was seen as most impactful for implementation by patients and support of clinical champions and time given for training by professionals. Professionals rated the integration of Fast@home as insufficient. Contextual factors (financial cutbacks and technical setbacks) hampered the implementation., Conclusion: Main improvements of the implementation of eRehabilitation are related to professionals' perceptions of the intervention, integration of eRehabilitation and contextual factors.Implication for rehabilitationTo increase the use of eRehabilitation by patients, patients should be supported by their healthcare professional in their first time use and during the rehabilitation process.To increase the use of eRehabilitation by healthcare professionals, healthcare professionals should be (1) supported by a clinical champion and (2) provided with sufficient time for learning to work and getting familiar with the eRehabilitation program.Integration of eRehabilitation in conventional stroke rehabilitation (optimal blended care) is an important challenge and a prerequisite for the implementation of eRehabilitation in the clinical setting.

Objective: To compare the effect on disability and quality of life, of conventional rehabilitation (control group) with individualized, tailored eRehabilitation intervention alongside conventional rehabilitation (Fast@home; intervention group), for people with stroke., Methods: Pre-post design. The intervention comprised cognitive (Braingymmer®) and physical (Telerevalidatie®/Physitrack®) exercises, activity-tracking (Activ8®) and psycho-education. Assessments were made at admission (T0) and after 3 (T3) and 6 months (T6). The primary outcome concerned disability (Stroke Impact Scale; SIS). Secondary outcomes were: health-related quality of life, fatigue, self-management, participation and physical activity. Changes in scores between T0-T3, T3-T6, and T0-T6 were compared by analysis of variance and linear mixed models., Results: The study included 153 and 165 people with stroke in the control and intervention groups, respectively. In the intervention group, 82 (50%) people received the intervention, of whom 54 (66%) used it. Between T3 and T6, the change in scores for the SIS subscales Communication (control group/intervention group -1.7/-0.3) and Physical strength (-5.7/3.3) were significantly greater in the total intervention group (all mean differences< minimally clinically important differences). No significant differences were found for other SIS subscales or secondary outcomes, or between T0-T3 and T0-T6., Conclusion: eRehabilitation alongside conventional stroke rehabilitation had a small positive effect on communication and physical strength on the longer term, compared to conventional rehabilitation only.

An amendment to this paper has been published and can be accessed via the original article.

Background: To improve the use of eRehabilitation after stroke, the identification of barriers and facilitators influencing this use in different healthcare contexts around the world is needed. Therefore, this study aims to investigate differences and similarities in factors influencing the use of eRehabilitation after stroke among Brazilian Healthcare Professionals (BHP) and Dutch Healthcare Professionals (DHP)., Method: A cross-sectional survey study including 88 statements about factors related to the use of eRehabilitation (4-point Likert scale; 1-4; unimportant-important/disagree-agree). The survey was conducted among BHP and DHP (physical therapists, rehabilitating physicians and psychologists). Descriptive statistics were used to analyse differences and similarities in factors influencing the use of eRehabilitation., Results: ninety-nine (response rate 30%) BHP and 105 (response rate 37%) DHP participated. Differences were found in the top-10 most influencing statements between BHP and DHP BHP rated the following factors as most important: sufficient support from the organisation (e.g. the rehabilitation centre) concerning resources and time, and potential benefits of the use of eRehabilitation for the patient. DHP rated the feasibility of the use of eRehabilitation for the patient (e.g. a helpdesk and good instructions) as most important for effective uptake. Top-10 least important statements were mostly similar; both BHP and DHP rated problems caused by stroke (e.g. aphasia or cognitive problems) or problems with resources (e.g. hardware and software) as least important for the uptake of eRehabilitation., Conclusion: The results indicate that the use of eRehabilitation after stroke by BHP and DHP is influenced by different factors. A tailored implementation strategy for both countries needs to be developed.

Incorporating user requirements in the design of e-rehabilitation interventions facilitates their implementation. However, insight into requirements for e-rehabilitation after stroke is lacking. This study investigated which user requirements for stroke e-rehabilitation are important to stroke patients, informal caregivers, and health professionals. The methodology consisted of a survey study amongst stroke patients, informal caregivers, and health professionals (physicians, physical therapists and occupational therapists). The survey consisted of statements about requirements regarding accessibility, usability and content of a comprehensive stroke e-health intervention (4-point Likert scale, 1=unimportant/4=important). The mean with standard deviation was the metric used to determine the importance of requirements. Patients (N=125), informal caregivers (N=43), and health professionals (N=105) completed the survey. The mean score of user requirements regarding accessibility, usability and content for stroke e-rehabilitation was 3.1 for patients, 3.4 for informal caregivers and 3.4 for health professionals. Data showed that a large number of user requirements are important and should be incorporated into the design of stroke e-rehabilitation to facilitate their implementation.