The 2022 Russian invasion of Ukraine raised for many parties the question of how to position themselves in view of urgently requested arms deliveries. Since, the topic of arms trade, which has hitherto rarely been addressed, has become a heavily politicized and divisive issue and partly even polarized public opinion. A major prerequisite for parties’ position-taking is to anticipate how voters react to such arms transfers and, more specifically, whether their respective attitudes are structured along the predominant left-right axis. Based on a large-scale survey experiment with French and German voters ($N = 6617$) in the year before the Russian invasion, we are able to focus on the relationship between ideological predispositions, vote intentions, and issue attitudes in a non-politicized period. Using both vignette and conjoint experiments, we demonstrate that voters’ attitudes on military transfers can be subsumed remarkably well under the left-right scale. Differentiating the impact of normative and economic considerations, the former is stronger among the left, while the latter also affects the attitudes of rightist citizens. However, normative considerations are the most important concern along the whole political spectrum. The turn of the German Green Party in 2022 to assist countries that are being aggressively attacked (because of the Responsibility to Protect), was not reflected in our data.

The number of relatives and geographical proximity between them affects informal support provided to older persons. In this study, we investigate whether (a) childless persons and parents living remotely from their adult children experience similar shortages in informal support, and (b) whether neighbours, friends and other non-family helpers compensate for these shortages. On the basis of Survey on Health, Ageing and Retirement in Europe (SHARE) data for 12 European countries, we estimate the probability and amount of informal non-financial support received by persons aged 65 and over who remain childless or live at different distances to their children. The contribution of non-family individuals is rather complementary to the help from family. Parents residing in the proximity of their children rely almost exclusively on family; as the geographical distance between adult children and older parents increases, the probability and amount of non-family support increase as well. But childless individuals differ from parents of remotely living children: the former rely on smaller support networks and resort more often to other relatives than the latter. Non-family individuals compensate for the scarcity of informal support only in the case of parents of distant children, but not in the case of childless individuals.

Quantitative comparative social scientists have long worried about the performance of multilevel models when the number of upper-level units is small. Adding to these concerns, an influential Monte Carlo study by Stegmueller (2013) suggests that standard maximum-likelihood (ML) methods yield biased point estimates and severely anti-conservative inference with few upper-level units. In this article, the authors seek to rectify this negative assessment. First, they show that ML estimators of coefficients are unbiased in linear multilevel models. The apparent bias in coefficient estimates found by Stegmueller can be attributed to Monte Carlo Error and a flaw in the design of his simulation study. Secondly, they demonstrate how inferential problems can be overcome by using restricted ML estimators for variance parameters and a t-distribution with appropriate degrees of freedom for statistical inference. Thus, accurate multilevel analysis is possible within the framework that most practitioners are familiar with, even if there are only a few upper-level units.

This paper has re-analysed and compared data between three studies conducted in the United Kingdom and in Sweden (the OPUS ‘Older People's Use of Unfamiliar Space’ study in the United Kingdom and the Swedish studies ‘Let's Go for a Walk’ and ‘Walking in Old Age’) to provide a comprehensive account of the issues facing older people in the outdoor environment. All three studies draw on the ‘fit’ between the person and their environment as a guiding conceptual base – capturing the dynamics of the relationship between older people's personal needs and their wider environmental context. This common conceptual base allowed us to test theory against practice, and to explore the utility of this concept across different geographical contexts. Participatory research was also applied, highlighting the importance of the voice of older people and involving older people in research. The studies also used a mixed-method approach involving both quantitative and qualitative methods. The paper highlights that although not generalisable, you can compare cross-locales and cross-nationally using different methodology; it investigates the challenges of cross-national comparative analysis and draws on findings from the three studies to illustrate the different challenges and solutions and finally looks at lessons that are transferable.

The main objective of the present study was to compare the athletic retirement of elite Greek and Spanish athletes in terms of (a) pre-conditions of retirement, (b) transitional period, and (c) consequences of the transition. For this purpose, elite athletes from Greece (n = 76) and Spain (n = 57) described in retrospect their experience leaving competitive sports through the Retirement from Sports Survey (Alfermann, Stambulova, & Zemaityte, 2004). Separate one-way ANOVAs and chi-square tests revealed differences and similarities between the transitional processes of athletes from the two countries. More similarities than differences were detected in the retirement of Greek and Spanish athletes. Based on these commonalities, we proposed a Southern European perspective on the topic. According to the present results the main characteristics of this pattern could be the lack of retirement planning, high athletic identity after the sports career, and predominance of relocation in the sports world after retirement.

Cross-national comparisons employed welfare state classifications to explain differences in care use in the European older population. Yet these classifications do not cover all care-related societal characteristics and limit our understanding of which specific societal characteristics are most important. Using the Survey of Health, Ageing and Retirement (second wave, 2006–07), the effect of societal determinants relating to culture, welfare state context and socio-economic and demographic composition on informal and formal care use of older adults in 11 European countries was studied. Multinomial multi-level regression analyses showed that, in addition to individual determinants, societal determinants are salient for understanding care use. In countries with fewer home-based services, less residential care, more informal care support and women working full time, older adults are more likely to receive informal care only. Older adults are more likely to receive only formal home care or a combination of formal and informal care in countries with more extensive welfare state arrangements (i.e. more home-based services, higher pension generosity), whereas the odds of receiving a combination of informal and formal care are also larger in countries that specify a legal obligation to care for parents. We tentatively conclude that the incorporation of societal determinants rather than commonly used welfare state classifications results in more understanding of the societal conditions that determine older adults’ care use.

The relationship between age and loneliness is intriguing. While loneliness has been widely perceived as a problem of old age, there is evidence suggesting that adolescence is the peak age for experiencing loneliness and there are demonstrable variations between nations in reported rates of loneliness. However, comparative data for examining both the prevalence of loneliness across age groups and across nations are sparse. As the first phase of a larger project, we explore the prevalence of loneliness across different age groups in 25 European nations, with a focus on people of an advanced age. After discussing issues of comparability, we present our empirical findings employing data collected in the third round (2006–07) of the European Social Survey (total sample size 47,099, age range 15–101) which included a ‘self-rating’ loneliness scale. Our results suggest that the prevalence of loneliness does increase with age for the combined sample. However, the nation in which one lives shows a greater impact than age on reported levels of loneliness, with Russia and Eastern European nations having the highest proportions of lonely people (about 10–34% for different age groups) and Northern European nations the lowest (mostly below 6%). Possible explanatory factors are identified and discussed, which provides the groundwork of a subsequent and formal study.

This paper presents a case study of the challenges and requirements associated with harmonising data from two independently-conceived datasets from The Netherlands and the United Kingdom: the Longitudinal Aging Study Amsterdam (LASA) and the Nottingham Longitudinal Study of Activity and Ageing (NLSAA). The objectives were to create equivalent samples and variables, and to identify the methodological differences that affect the comparability of the samples. Data are available from the two studies' 1992–93 surveys for respondents born during 1908–20, and the common data set had 1,768 records and enabled the creation of 26 harmonised variables in the following domains: demographic composition and personal finances, physical health, mental health and loneliness, contacts with health services, physical activity, religious attendance and pet ownership. The ways in which the methodological differences between the two studies and their different selective attrition might lead to sample differences were carefully considered. It was concluded that the challenges of conducting cross-national comparative research using independent datasets include differences in sampling, study design, measurement instruments, response rates and selective attrition. To reach conclusions from any comparative study about substantive socio-cultural differences, these challenges must first be identified and addressed.