Doe one need to go a long way to dig deep? An empirical comparison of online and traditional focus groups.

We evaluate the potential of online focus groups to trigger deep level customer information, which is the major aim of focus groups. We do so by comparing its yield to that of its traditional counterpart. The traditional focus group substantially outperforms online focus groups in level of disclosure, in number of words generated, and in number of ideas generated. However, participants do not reveal these differences in their self-reports. Further, in line with the view that disclosure requires gradual warming up, we find increases in disclosure during the interview in traditional focus groups but not in online focus groups. We conclude that in its present form, the online focus group is not particularly suitable to yield deep level customer information. Starting from our finding that the difference in communication speed explains the differences in disclosure, we suggest some methodological improvements to online focus groups that might increase their yield.Characteristics; Communication; Disclosure; Focus groups; Group dynamics; Implications;

Enhancing value of information analyses

ABSTRACTObjectiveThe aim of this study was to demonstrate that it is feasible and recommendable to present value of information (VOI) outcomes in terms of underlying costs and effects in addition to costs alone.MethodsThe benefits of collecting additional information on health economic outcomes before deciding on a preferred policy when evaluating alternative strategies with uncertain outcomes are quantified in a VOI analysis. In general, costs and effects are combined into one single dimension to determine the expected monetary VOI. Separate information on costs and effects is lost. This information, however, remains relevant to the decision-maker. The concept of the attributable VOI (AVOI) is introduced which enables separate presentation of expected changes in health outcomes and costs.ResultsThe use of the attributable expected value of perfect information is illustrated with a few examples. These examples demonstrate the benefits of the new approach, as well as its calculation. The benefits are: 1) insight into the expected costs and expected effects gained as a result of carrying out further research to reduce or eliminate decision uncertainty; and 2) the likelihood that the outcome of additional research will result in a change in preferred policy.ConclusionsDecision-making may be enhanced and clarified by adding results from AVOI analyses. Obtaining these results is straightforward and requires only a minimal computational effort. Therefore, use of the AVOI extension is recommended for all future VOI analyses

Identifying suitable substrates for high-quality graphene-based heterostructures

We report on a scanning confocal Raman spectroscopy study investigating the strain-uniformity and the overall strain and doping of high-quality chemical vapour deposited (CVD) graphene-based heterostuctures on a large number of different substrate materials, including hexagonal boron nitride (hBN), transition metal dichalcogenides, silicon, different oxides and nitrides, as well as polymers. By applying a hBN-assisted, contamination free, dry transfer process for CVD graphene, high-quality heterostructures with low doping densities and low strain variations are assembled. The Raman spectra of these pristine heterostructures are sensitive to substrate-induced doping and strain variations and are thus used to probe the suitability of the substrate material for potential high-quality graphene devices. We find that the flatness of the substrate material is a key figure for gaining, or preserving high-quality graphene.Comment: 6 pages, 5 figure

Pseudo-subarachnoid haemorrhage due to chronic hypoxaemia: case report and review of the literature

Background: The specificity of computed tomography (CT) for subarachnoid haemorrhage (SAH) is very high. However, physicians should be aware of rare false positive findings, also referred to as "pseudo-SAH". We present an unusual case in which such a finding was caused by chronic hypoxaemia. Case presentation: A 37-year-old male patient presented with headaches. His CT-scan showed multiple confluent subarachnoid hyperattenuations, which mimicked SAH. However, the headache was chronic and had no features typical for SAH. The patient suffered from severe chronic hypoxaemia due to congenital heart failure. On CT-angiography diffuse intracranial vessel proliferation was found and laboratory results revealed a highly raised level of haematocrit, which had both probably developed as compensatory mechanisms. A combination of these findings explained the subarachnoid hyperdensities. Magnetic resonance imaging (MRI) showed no signs of SAH and visualized hypoxaemia in cerebral veins. A diagnosis of pseudo-SAH was made. The patient's symptoms were likely due to a secondary headache attributed to hypoxia and/or hypercapnia. Therapy was symptomatic. Conclusions: Severe chronic hypoxaemia should be recognised as a rare cause of pseudo-SAH. Clinical evaluation and MRI help differentiate SAH from pseudo-SAH

Ultra-distal access of the M1 segment with the 5 Fr Navien distal access catheter in acute (anterior circulation) stroke: is it safe and efficient?

Background and aim The importance of mechanical thrombectomy in acute stroke treatment has grown over recent years. Mechanical thrombectomy comprises many different techniques. Technical improvements in the catheter material have led to the development of large-bore distal access catheters which can enter tortuous intracranial vessels. This has promising applications for endovascular stroke treatment. This study evaluated the safety and success rate of ultra-distal access of the middle cerebral artery (MCA) M1 segment with the 5 Fr Navien 58 distal access catheter in the treatment of acute stroke in combination with stent retrievers. Methods We retrospectively analyzed 81 patients with an acute stroke of the anterior circulation in whom ultra-distal access to the M1 segment was carried out using the Navien 58 catheter with an anchoring technique with a stent retriever for mechanical thrombectomy. Technical complications, success rates of catheter placement, success rates of thrombectomy using the modified Thrombolysis In Cerebral Infarction (mTICI) score, and the procedure times were evaluated. Results Ultra-distal access with the Navien 58 was successful in 75% (61/81) of cases. Recanalization success with a mTICI score of 2b and better was achieved in 83% overall (67/81), in 90% (55/61) of cases with successful ultra-distal access and in 60% (12/20) of cases without ultra-distal access. No severe adverse effects such as dissections or perforations occurred as a result of the ultra-distal catheter placement in the M1 segment. In 4% (3/81) of the cases a reversible MCA vasospasm occurred. Conclusions Ultra-distal placement of the Navien 58 distal access catheter into the M1 segment in acute anterior circulation stroke can be achieved consistently, is safe in practice, and results in good recanalization success rates

Aiming for a representative sample: Simulating random versus purposive strategies for hospital selection

Background A ubiquitous issue in research is that of selecting a representative sample from the study population. While random sampling strategies are the gold standard, in practice, random sampling of participants is not always feasible nor necessarily the optimal choice. In our case, a selection must be made of 12 hospitals (out of 89 Dutch hospitals in total). With this selection of 12 hospitals, it should be possible to estimate blood use in the remaining hospitals as well. In this paper, we evaluate both random and purposive strategies for the case of estimating blood use in Dutch hospitals. Methods Available population-wide data on hospital blood use and number of hospital beds are used to simulate five sampling strategies: (1) select only the largest hospitals, (2) select the largest and the smallest hospitals (‘maximum variation’), (3) select hospitals randomly, (4) select hospitals from as many different geographic regions as possible, (5) select hospitals from only two regions. Simulations of each strategy result in different selections of hospitals, that are each used to estimate blood use in the remaining hospitals. The estimates are compared to the actual population values; the subsequent prediction errors are used to indicate the quality of the sampling strategy. Results The strategy leading to the lowest prediction error in the case study was maximum variation sampling, followed by random, regional variation and two-region sampling, with sampling the largest hospitals resulting in the worst performance. Maximum variation sampling led to a hospital level prediction error of 15 %, whereas random sampling led to a prediction error of 19 % (95 % CI 17 %-26 %). While lowering the sample size reduced the differences between maximum variation and the random strategies, increasing sample size to n = 18 did not change the ranking of the strategies and led to only slightly better predictions. Conclusions The optimal strategy for estimating blood use was maximum variation sampling. When proxy data are available, it is possible to evaluate random and purposive sampling strategies using simulations before the start of the study. The results enable researchers to make a more educated choice of an appropriate sampling strateg

The Role of Reinforcement Learning in the Emergence of Conventions: Simulation Experiments with the Repeated Volunteer’s Dilemma

We use reinforcement learning models to investigate the role of cognitive mechanisms in the emergence of conventions in the repeated volunteer’s dilemma (VOD). The VOD is a multi-person, binary choice collective goods game in which the contribution of only one individual is necessary and sufficient to produce a benefit for the entire group. Behavioral experiments show that in the symmetric VOD, where all group members have the same costs of volunteering, a turn-taking convention emerges, whereas in the asymmetric VOD, where one “strong” group member has lower costs of volunteering, a solitary-volunteering convention emerges with the strong member volunteering most of the time. We compare three different classes of reinforcement learning models in their ability to replicate these empirical findings. Our results confirm that reinforcement learning models can provide a parsimonious account of how humans tacitly agree on one course of action when encountering each other repeatedly in the same interaction situation. We find that considering contextual clues (i.e., reward structures) for strategy design (i.e., sequences of actions) and strategy selection (i.e., favoring equal distribution of costs) facilitate coordination when optima are less salient. Furthermore, our models produce better fits with the empirical data when agents act myopically (favoring current over expected future rewards) and the rewards for adhering to conventions are not delayed

D7.4 Evaluation and Outlook WP7 Results, aggregates internal deliverables ID7.17-ID7.18

Herder, E., Kärger, P., Berlanga, A., Drachsler, H., Janssen, J., Kalz, M., & Heyenrath, S. (2009). D7.4 Evaluation and Outlook WP7 Results, aggregates internal deliverables ID7.17-ID7.18. TENCompetence.Summary of the results of TENCompetence WP7 between M42 and M48. Update of the Learning Path Specification, new version of the Learning Path Editor and evaluation of the Competence Matching ToolThe work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Combining Social- and Information-based Approaches for Personalised Recommendation on Sequencing Learning Activities

Lifelong learners who assign learning activities (from multiple sources) to attain certain learning goals throughout their lives need to know which learning activities are (most) suitable and in which sequence these should be performed. Learners need support in this way finding process (selection and sequencing), and we argue this could be provided by using personalised recommender systems. To enable personalisation, collaborative filtering could use information about learners and learning activities, since their alignment contributes to learning efficiency. A model for way finding has been developed that presents personalised recommendations in relation to information about learning goals, learning activities and learners. A personalised recommender system has been developed accordingly, and recommends learners on the best next learning activities. Both model and system combine social-based (i.e., completion data from other learners) and information-based (i.e., metadata from learner profiles and learning activities) approaches to recommend the best next learning activity to be completed