Ikääntyneiden ryhmätoiminnan taloudellinen arviointi ja vaikutukset osallisuuteen

Osallisuuden edistämistä pidetään keskeisenä yhteiskuntapoliittisena tavoitteena ja ikääntyneiden osallisuutta vahvistavaa toimintaa järjestetään laajasti eri sektoreilla. Erityisesti erilaisten ryhmämuotoisten toimintamallien on nähty edistävän ikääntyneiden osallisuuden kokemusta. Tämä systemaattinen kirjallisuuskatsaus käsittelee tutkimusjulkaisuja, joissa on tarkasteltu ikääntyneiden ryhmätoiminnan vaikutuksia osallisuuteen ja toiminnan taloudellista arviointia. Osallisuuden kokemuksia oli tarkasteltu monissa tutkimuksissa, mutta taloudellisen arvioinnin näkökulma oli harvinaisempi. Lopulliseen tarkasteluun valikoitui viisi artikkelia. Näissä osallisuutta oli arvioitu monilla erilaisilla mittareilla, mikä vaikeutti vertailtavuutta. Lähes kaikissa tutkimuksissa havaittiin, että interventio paransi osallisuutta jolla-kin mittarilla. Koska tutkimusartikkeleita oli vähän ja taloudelliset arvioinnit oli toteutettu erilaisilla menetelmillä, ei interventioiden kustannusvaikuttavuudesta voida tehdä päätelmiä. Economic evaluation of group-based intervention for older people and effects on social inclusion Increasing social inclusion is a central goal of social policy. Activities to increase social inclusion of older people are widely organized in different sectors. Especially, various group-based approaches seem to increase social inclusion of older people. In this systematic review, we examine studies which evaluated the effects of group-based interventions to increase social inclusion of older people, and which also applied an economic evaluation. The perspective of economic evaluation was not common. We could include only five articles in the review. In these articles, social inclusion had been assessed with many different indicators, making studies difficult to compare. Four studies reported that the intervention increased social inclusion regardless of the indicator used. Because the methods in the studies varied, no numerical conclusions could be drawn about the cost-effectiveness of the interventions

The EuCARD2 Future Magnets Program for Particle Accelerator High-Field Dipoles: Review of Results and Next Steps

International audienceThe EuCARD2 collaboration aims at the development of a 10 kA-class superconducting, high current density cable suitable for accelerator magnets, to be tested in small coils and magnets capable to deliver 3-5 T when energized in stand-alone mode, and 15-18 T when inserted in a 12-13 T background magnet. REBCO tape, assembled in a Roebel cable, was selected as conductor. The developed REBCO tape has reached a record engineering critical current density, at 4.2 K and 18 T of ${\text{956 A/mm}}^{2}$. Roebel cable carried up to 13 kA at 20 K when tested in a small coil (FeatherM0.4). Then a first dipole magnet, wound with two low-grade Roebel cables of 25 m each, was assembled and tested. The dipole reached the short sample critical current of 6 kA generating more than 3 T central field at about 5.7 K, with indications of good current transfer among cable strands and of relatively soft transition. The construction of a costheta dipole is also discussed. Eucard2 is reaching its objective and is continuing with the H2020-ARIES program aiming at doubling the Je at 20 T to obtain 6 T as standalone and 18 T as insert in a high field facility

Temporal variations of atmospheric aerosol in four European urban areas

Item does not contain fulltextPURPOSE: The concentrations of PM(10) mass, PM(2.5) mass and particle number were continuously measured for 18 months in urban background locations across Europe to determine the spatial and temporal variability of particulate matter. METHODS: Daily PM(10) and PM(2.5) samples were continuously collected from October 2002 to April 2004 in background areas in Helsinki, Athens, Amsterdam and Birmingham. Particle mass was determined using analytical microbalances with precision of 1 mug. Pre- and post-reflectance measurements were taken using smoke-stain reflectometers. One-minute measurements of particle number were obtained using condensation particle counters. RESULTS: The 18-month mean PM(10) and PM(2.5) mass concentrations ranged from 15.4 mug/m(3) in Helsinki to 56.7 mug/m(3) in Athens and from 9.0 mug/m(3) in Helsinki to 25.0 mug/m(3) in Athens, respectively. Particle number concentrations ranged from 10,091 part/cm(3) in Helsinki to 24,180 part/cm(3) in Athens with highest levels being measured in winter. Fine particles accounted for more than 60% of PM(10) with the exception of Athens where PM(2.5) comprised 43% of PM(10). Higher PM mass and number concentrations were measured in winter as compared to summer in all urban areas at a significance level p < 0.05. CONCLUSIONS: Significant quantitative and qualitative differences for particle mass across the four urban areas in Europe were observed. These were due to strong local and regional characteristics of particulate pollution sources which contribute to the heterogeneity of health responses. In addition, these findings also bear on the ability of different countries to comply with existing directives and the effectiveness of mitigation policies.1 augustus 201

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future