Intimate partner violence among adolescents: Prevalence rates after one decade of research.

INTRODUCTION: Intimate partner violence research and intervention strategies have grown substantially over the last two decades. However, little research has examined whether the intimate partner prevalence has changed or remained stable over time in Spain. Moreover, few studies have analyzed whether intimate partner violence prevalence rates among genders and age groups have fluctuated similarly or not. METHOD: The aim of this study was to analyze the trends observed in intimate partner violence perpetration and victimization rates among adolescents in three sample cohorts from Spain interviewed in 2006, 2010, and 2016 (4591 Spanish adolescents; 53.6% girls and 46.2% boys). ANCOVA was used to compare the population means between the cohorts: sex, age, and the type of intimate partner violence, for example, verbal, physical, and sexual. RESULTS: The results showed a significant decrease in intimate partner violence rates from 2006 to 2016, which was more noticeable within the first half of this decade. Throughout the decade, the girls perpetrated more verbal and mild physical assaults, while the boys perpetrated more sexual assaults. However, these results suggest a clear bidirectional intimate partner violence dynamic between the genders. Additionally, late adolescence reported a higher prevalence of aggressions. CONCLUSIONS: The results highlight the need to adapt current prevention strategies considering the differences in the intimate partner violence trajectories based on sex and age, with the aim of regaining the marked rate of decline in aggression observed up to 2010.

Are valence and arousal related to the development of amodal representations of words? A computational study.

In this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at different developmental stages (five and four developmental stages for English and Spanish, respectively) using the Word Maturity methodology to align different vector spaces. Second, we analyzed the amodal development of words through mixed-effects models with crossed random effects for words and variables using a continuous time metric. Third, the emotional norms were included as covariates in the statistical models. We evaluated more than 23,000 words, whose emotional norms were available for more than 10,000 words, in each language separately. Results showed a curve of amodal development with an increasing linear effect and a small quadratic deceleration. A relevant influence on the amodal development of words was found only for emotional valence (not for arousal), suggesting that positive words have an earlier amodal development and a less pronounced semantic change across early lifespan.

The development of selective stopping: Qualitative and quantitative changes from childhood to early adulthood.

Although progress has been made in elucidating the behavioral and neural development of global stopping across the lifespan, little is known about the development of selective stopping. This more complex form of inhibitory control is required in real-world situations where ongoing responses must be inhibited to certain stimuli but not others, and can be assessed in laboratory settings using a stimulus selective stopping task. Here we used this task to investigate the qualitative and quantitative developmental changes in selective stopping in a large-scale cross-sectional study with three different age groups (children, preadolescents, and young adults). We found that the ability to stop a response selectively to some stimuli (i.e., use a selective strategy) rather than non-selectively to all presented stimuli (i.e., use a global, non-selective strategy) is fully mature by early preadolescence, and remains stable afterwards at least until young adulthood. By contrast, the efficiency or speed of stopping (indexed by a shorter stop-signal reaction time or SSRT) continues to mature throughout adolescence until young adulthood, both for global and selective implementations of stopping. We also provide some preliminary findings regarding which other task variables beyond the strategy and SSRT predicted age group status. Premature responding (an index of "waiting impulsivity") and post-ignore slowing (an index of cognitive control) were among the most relevant predictors in discriminating between developmental age groups. Although present results need to be confirmed and extended in longitudinal studies, they provide new insights into the development of a relevant form of inhibitory control.

Model Selection and Model Averaging for Mixed-Effects Models with Crossed Random Effects for Subjects and Items.

A good deal of experimental research is characterized by the presence of random effects on subjects and items. A standard modeling approach that includes such sources of variability is the mixed-effects models (MEMs) with crossed random effects. However, under-parameterizing or over-parameterizing the random structure of MEMs bias the estimations of the Standard Errors (SEs) of fixed effects. In this simulation study, we examined two different but complementary perspectives: model selection with likelihood-ratio tests, AIC, and BIC; and model averaging with Akaike weights. Results showed that true model selection was constant across the different strategies examined (including ML and REML estimators). However, sample size and variance of random slopes were found to explain true model selection and SE bias of fixed effects. No relevant differences in SE bias were found for model selection and model averaging. Sample size and variance of random slopes interacted with the estimator to explain SE bias. Only the within-subjects effect showed significant underestimation of SEs with smaller number of items and larger item random slopes. SE bias was higher for ML than REML, but the variability of SE bias was the opposite. Such variability can be translated into high rates of unacceptable bias in many replications.

Distilling vector space model scores for the assessment of constructed responses with bifactor Inbuilt Rubric method and latent variables.

In this paper, we highlight the importance of distilling the computational assessments of constructed responses to validate the indicators/proxies of constructs/trins using an empirical illustration in automated summary evaluation. We present the validation of the Inbuilt Rubric (IR) method that maps rubrics into vector spaces for concepts' assessment. Specifically, we improved and validated its scores' performance using latent variables, a common approach in psychometrics. We also validated a new hierarchical vector space, namely a bifactor IR. 205 Spanish undergraduate students produced 615 summaries of three different texts that were evaluated by human raters and different versions of the IR method using latent semantic analysis (LSA). The computational scores were validated using multiple linear regressions and different latent variable models like CFAs or SEMs. Convergent and discriminant validity was found for the IR scores using human rater scores as validity criteria. While this study was conducted in the Spanish language, the proposed scheme is language-independent and applicable to any language. We highlight four main conclusions: (1) Accurate performance can be observed in topic-detection tasks without hundreds/thousands of pre-scored samples required in supervised models. (2) Convergent/discriminant validity can be improved using measurement models for computational scores as they adjust for measurement errors. (3) Nouns embedded in fragments of instructional text can be an affordable alternative to use the IR method. (4) Hierarchical models, like the bifactor IR, can increase the validity of computational assessments evaluating general and specific knowledge in vector space models. R code is provided to apply the classic and bifactor IR method.

Redundancy, isomorphism, and propagative mechanisms between emotional and amodal representations of words: A computational study.

Some proposals claim that language acts as a link to propagate emotional and other modal information. Thus, there is an eminently amodal path of emotional propagation in the mental lexicon. Following these proposals, we present a computational model that emulates a linking mechanism (mapping function) between emotional and amodal representations of words using vector space models, emotional feature-based models, and neural networks. We analyzed three central concepts within the embodiment debate (redundancy, isomorphism, and propagative mechanisms) comparing two alternative hypotheses: semantic neighborhood hypothesis versus specific dimensionality hypothesis. Univariate and multivariate neural networks were trained for dimensional (N = 11,357) and discrete emotions (N = 2,266), and later we analyzed its predictions in a test set (N = 4,167 and N = 875, respectively). We showed how this computational model could propagate emotional responses to words without a direct emotional experience via amodal propagation, but no direct relations were found between emotional rates and amodal distances. Thereby, we found that there were clear redundancy and propagative mechanisms, but no isomorphism should be assumed. Results suggested that it was necessary to establish complex links to go beyond amodal distances of vector spaces. In this way, although the emotional rates of semantic neighborhoods could predict the emotional rates of target words, the mapping function of specific amodal features seemed to simulate emotional responses better. Thus, both hypotheses would not be mutually exclusive. We also showed that discrete emotions could have simpler relations between modal and amodal representations than dimensional emotions. All these results and their theoretical implications are discussed.

Validation of the Guilt associated with Self-Perception as a Burden Scale (G-SPBS).

BACKGROUND: One of the main health-related worries for older adults is becoming dependent. Even healthy older adults may worry about becoming dependent, generating guilt feelings due to the anticipation of future needs that others must solve. The guilt associated with self-perception as a burden has not been studied in older adults, and there is no instrument available to measure these feelings. AIMS: To adapt the Self-Perceived Burden Scale (SPBS; Cousineau et al., 2003) for the assessment of feelings of guilt for perceiving oneself as a burden for the family in older adults without explicit functional or cognitive impairment. METHOD: Participants were 298 older adults living independently in the community. Participants completed the assessment protocol, which included measures of guilt associated with self-perception as a burden, depressive and anxious symptomatology, self-perceived burden, and sociodemographic information. RESULTS: Results from exploratory, parallel and confirmatory factor analyses suggest that the scale, named Guilt associated with Self-Perception as a Burden Scale (G-SPBS), has a unidimensional structure, explaining 57.04% of the variance of guilt. Good reliability was found (Cronbach's alpha = .94). The results revealed significant (p < .01) positive associations with depressive and anxious symptomatology. DISCUSSION: These findings suggest that the G-SPBS shows good psychometric properties which endorse its use with healthy community older adults. Also, guilt associated with perceiving oneself as a burden seems to be a relevant variable that can contribute to improving our understanding of psychological distress in older adults.

Measuring familism in dementia family caregivers: the revised familism scale.

Objectives: Familism is a cultural value that has been shown to be important for understanding the dementia caregiving process. The aim of this study is to analyze the psychometric properties of the Revised Familism Scale (RFS).Method: Face-to-face assessments were done with 199 dementia family caregivers. Exploratory factor analysis, discriminant validity, and reliability analyses of the RFS were carried out.Results: The results suggest that the RFS has good psychometric properties and is composed of three factors: "Familial interconnectedness", "Familial obligations", and "Extended family support".Conclusion: The RFS seems to be a reliable measure of familism, a multidimensional construct measuring a relevant cultural value for dementia family caregivers.

Bridging the theoretical gap between semantic representation models without the pressure of a ranking: some lessons learnt from LSA.

In recent years, latent semantic analysis (LSA) has reached a level of maturity at which its presence is ubiquitous in technology as well as in simulation of cognitive processes. In spite of this, in recent years there has been a trend of subjecting LSA to some criticisms, usually because it is compared to other models in very specific tasks and conditions and sometimes without having good knowledge of what the semantic representation of LSA means, and without exploiting all the possibilities of which LSA is capable other than the cosine. This paper provides a critical review to clarify some of the misunderstandings regarding LSA and other space models. The historical stability of the predecessors of LSA, the representational structure of word meaning and the multiple topologies that could arise from a semantic space, the computation of similarity, the myth that LSA dimensions have no meaning, the computational and algorithm plausibility to account for meaning acquisition in LSA (in contrast to others models based on online mechanisms), the possibilities of spatial models to substantiate recent proposals, and, in general, the characteristics of classic vector models and their ease and flexibility to simulate some cognitive phenomena will be reviewed. The review highlights the similarity between LSA and other techniques and proposes using long LSA experiences in other models, especially in predicting models such as word2vec. In sum, it emphasizes the lessons that can be learned from comparing LSA-based models to other models, rather than making statements about "the best."

Development and validation of a paternalism and autonomist care assessment.

AIM: There is a need for a validated instrument to measure the type of care (paternalism or person-centred) provided for older adults. Since paternalism and person-centred care are the most important caregiving styles in the field of care and as they are usually opposed, the study aims to develop and establish psychometrics data of an instrument to identify paternalistic and autonomist behaviours in older adults care contexts, which can help to enhance care practice. DESIGN: Instrument development. METHODS: After observing and standardizing behaviours in formal care contexts in 2016, an instrument was developed and proceeding to a first validation using standard validation techniques among caregivers in two care settings during 2016-2017: senior citizen centres and older adult day care centres. RESULTS: The Paternalist/Autonomist Care Assessment (PACA) is a 30-item, behaviour-based instrument which measures both the appraisal of caregivers on elements of care (Care Appraisal Scale- PACA-Appraisal) and the occurrence of behaviours (Occurrence of Care in Context- PACA-Occurrence). The Paternalist/Autonomist Care Assessment (PACA) was validated in 160 professional caregivers and was able to discriminate two factors: paternalistic or overprotective behaviours and autonomist behaviours. However, these factors were not fully dichotomous and were shown to coexist to some degree. CONCLUSION: The instrument displayed good psychometric properties to measure paternalism and autonomy in older adult care. Moreover, it showed that the two types of care are not antagonistic and can coexist, with overprotective behaviours being more frequent in contexts of care for more dependent persons. IMPACT: There are no validated instruments to measure paternalism and person-centred behaviour in care contexts. The two measures yielded by the PACA show good construct and concurrent empirical validity, internal consistency, and convergent and discriminant validity. Family caregiver, professional caregivers, nurses, older adults.

Stress and Blood Pressure in Dementia Caregivers: The Moderator Role of Mindfulness.

Objective: Dementia caregiving has been described as a chronically stressful situation with adverse cardiovascular effects. Psychological resources such as mindfulness may reduce the impact of stress on caregivers' cardiovascular health. The objective of this study was to analyze the moderating effect of trait mindfulness on the relationship between frequency of disruptive behaviors of the care recipient and blood pressure (BP) in dementia caregivers. Method: Participants were 110 dementia family caregivers. Two hierarchical regressions (for systolic and diastolic BP) were conducted to analyze whether mindfulness moderates the relationship between disruptive behaviors and BP after controlling for known predictors of cardiovascular outcomes. Results: A significant moderator effect of mindfulness was found between the frequency of disruptive behaviors and diastolic BP (ß = -.195, p < .05). Among those caregivers reporting low levels of mindfulness, the relationship between frequency of disruptive behaviors and diastolic BP was relatively stronger than among those reporting high mindfulness levels. Conclusions: The results suggest that a high level of trait mindfulness may have protective effect on BP when caregivers face high levels of stress. Clinical Implications: Mindfulness seems to be an important variable with potential for buffering the effects of caregiving stressors on caregivers' blood pressure.

Factors influencing intention to help and helping behaviour in witnesses of bullying in nursing settings.

The role played by witnesses of bullying in nursing settings remains little studied, despite their potential relevance in explaining the onset and development of bullying. The objective of this study was to develop a model to account for witnesses' intention to help and helping behaviour in response to bullying in a nursing setting. Three hundred and thirty-seven witnesses completed self-report measures of variables predicting intention to help and helping behaviour. A full structural model was constructed using structural equation modelling. The intention to help victims was elicited by tension, group identity, support to peers' initiative to intervene and absence of fear of retaliation. However, engagement in helping behaviour was only predicted by the absence of fear of retaliation. This study shows that witnesses of bullying in nursing settings do not remain impassive, but their experienced discomfort and intention to help victims is not sufficient to predict helping behaviour. Fear of possible retaliation if intervening in favour of victims constitutes a crucial factor explaining witnesses' hesitation to help victims. Several implications for the implementation of policies directed at eradicating bullying in nursing settings are discussed.

Estimation of planned and unplanned missing individual scores in longitudinal designs using continuous-time state-space models.

Latent change score (LCS) models within a continuous-time state-space modeling framework provide a convenient statistical approach for analyzing developmental data. In this study, we evaluate the robustness of such an approach in the context of accelerated longitudinal designs (ALDs). ALDs are especially interesting because they imply a very high rate of planned data missingness. Additionally, most longitudinal studies present unexpected participant attrition leading to unplanned missing data. Therefore, in ALDs, both sources of data missingness are combined. Previous research has shown that ALDs for developmental research allow recovering the population generating process. However, it is unknown how participant attrition impacts the model estimates. We have three goals: (a) to evaluate the robustness of the group-level parameter estimates in scenarios with empirically plausible unplanned data missingness; (b) to evaluate the performance of Kalman scores (KS) imputations for individual data points that were expected but unobserved; and (c) to evaluate the performance of KS imputations for individual data points that were outside the age ranged observed for each case (i.e., to estimate the individual trajectories for the complete age range under study). In general, results showed lack of bias in the simulated conditions. The variability of the estimates increased with lower sample sizes and higher missingness severity. Similarly, we found very accurate estimates of individual scores for both planned and unplanned missing data points. These results are very important for applied practitioners in terms of forecasting and making individual-level decisions. R code is provided to facilitate its implementation by applied researchers. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Quantum projections on conceptual subspaces: A deeper dive into methodological challenges and opportunities.

In alignment with the distributional hypothesis of language, the work "Quantum Projections on Conceptual Subspaces" (Martínez-Mingo A, Jorge-Botana G, Martinez-Huertas JÁ, et al. Quantum projections on conceptual subspaces. Cogn Syst Res 2023; 82: 101154) proposed a methodology for generating conceptual subspaces from textual information based on previous work (Martinez-Mingo A, Jorge-Botana G and Olmos R. Quantum approach for similarity evaluation in LSA vector space models. 2020). These subspaces enable the utilization of the quantum model of similarity put forth by Pothos and Busemeyer (Pothos E, Busemeyer J. A quantum probability explanation for violations of symmetry in similarity judgments. In Proceedings of the annual meeting of the cognitive science society, 2011, Vol. 33, No. 33), allowing for the empirical examination of the violations of assumptions concerning symmetry and triangular inequality (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327-352; Yearsley JM, Barque-Duran A, Scerrati E, et al. The triangle inequality constraint in similarity judgments. Prog Biophys Mol Biol 2017; 130: 26-32), as well as the diagnosticity effect (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327-352; Yearsley JM, Pothos EM, Barque-Duran A, et al. Context effects in similarity judgments. J Exp Psychol Gen 2022; 151: 711-717), within a data-driven environment. These psychological biases, deeply studied by authors such as Tversky and Kahneman, inform us about the limitations of modeling psychological similarity measures using tools from classical geometry. This commentary aims to offer methodological clarifications, discuss theoretical and practical implications, and speculate on future directions in this field of research. Concretely, it aims to propose the use of different contours (conceptual or contextual) to generate the subspaces, which lead to subspaces of terms or contexts. Once these contours are defined, a differentiation is proposed between Aggregated Terms Subspaces (ATSs), Aggregated Contexts Subspaces (ACSs), and Aggregated Features Subspaces (AFSs) depending on whether we define the subspaces by grouping the terms or contexts within the contour, or from the latent dimensions of the semantic space obtained in the contour window. Finally, new data is provided on the violation of the triangular inequality assumption through the application of the quantum similarity model to ATSs.

A mixed methods study using case studies prepared by nursing students as a clinical practice evaluation tool.

AIM: To identify the presence of variability in the evaluation of case studies prepared by nursing students during their primary care rotations based on the existing evaluation rubric. To explore the difficulties experienced by link lecturers and students in preparing and evaluating case studies. DESIGN: A mixed methods study. METHODS: The scores for the rubric items and the final grades for the case studies were collected from a sample of 132 cases. Qualitative information was collected by conducting open-ended interviews with lecturers and a focus group session with students. RESULTS: Statistically significant differences were identified between the lecturers' mean final grades [F(5.136) = 3.984, p = 0.002] and a variety of items in the evaluation rubric (p < 0.05). In addition, effect sizes [η2 (≈0.14)] of considerable magnitude were found. Two themes emerged from the qualitative data: (1). the challenge of preparing the case studies and (2). the variable nature of the evaluations.

Emotional Valence Precedes Semantic Maturation of Words: A Longitudinal Computational Study of Early Verbal Emotional Anchoring.

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. The neural network was trained and validated in the child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed.

Stress, cognitive fusion and comorbid depressive and anxiety symptomatology in dementia caregivers.

Comorbid depression and anxiety is linked to worse outcomes such as increased impairment, distress, and morbidity, as well as worse treatment outcomes. Transdiagnostic variables such as cognitive fusion are considered potential factors for explaining comorbidity. The aim of this study was to analyze the differences between symptom profiles of caregivers (comorbid, depressive, anxiety, and subclinical) in terms of demographic and contextual factors, stress variables, and cognitive fusion. Individual interviews were conducted with 553 caregivers of a relative with dementia. Sociodemographic variables, stressors, cognitive fusion, and depressive and anxiety symptoms were assessed. Caregivers were grouped into four symptom profiles, comorbid (n = 303), depressed (n = 40) anxiety (n = 86), and subclinical (n = 124), based on their depressive and anxiety symptoms. The likelihood of presenting a comorbid profile relative to the subclinical profile was higher in female caregivers. In addition, higher frequency of disruptive behaviors of the care recipient was a risk factor for presenting a comorbid profile relative to the other three profiles, and higher scores in cognitive fusion were a risk factor of comorbidity relative to the other profiles (anxiety, depressive, and subclinical). The findings suggest that the likelihood of presenting comorbid symptomatology is higher for female caregivers and those reporting higher levels of cognitive fusion and higher frequency of disruptive behaviors. These characteristics may describe a vulnerable profile of dementia family caregivers. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Reciprocal relation between health and academic performance in children through autoregressive models.

This study assessed the reciprocal predictive relation between multiple domains of health and academic performance (AP) in elementary schoolchildren through autoregressive models. A school-based longitudinal observational study was carried out, with a baseline measurement in 2014 and a follow-up at 12 and 24 months, in an Argentine sample of 533 children aged 9-13 years. Health was measured by self-administration of the KIDSCREEN-52 child version in the classroom, which evaluates 10 dimensions of health. AP was established with the final grades in language and mathematics obtained from the school records. Other variables collected were sex, mother's educational level, socioeconomic status, and intellectual capability. To examine the interdependencies between different health domains and AP, autoregressive and cross-lag coefficients between adjacent time points were calculated with structural equation modeling. A substantial portion of AP individual differences was explained by AP in the previous wave (ß above .790). Conversely, health measures were not as stable between different waves (ß around .400). Cross-lag path coefficients showed a significant dependence on health of previous-year AP, as can be seen in the physical well-being, psychological well-being, school environment, and social acceptance dimensions of health. AP also was influenced by previous-year health, as occurs with the self-perception, mood and emotions, and school environment health dimensions that significantly predict the next AP. These results are consistent with a positive two-way association between health and AP in childhood. This analysis is important to identify priority areas of intervention that could to improve both children's AP and well-being. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Multiple Imputation in Multilevel Models. A Revision of the Current Software and Usage Examples for Researchers.

Although modern lines for dealing with missing data are well established from the 1970s, today there is a challenge when researchers encounter this problem in multilevel models. First, there is a variety of existing software to handle missing data based on multiple imputation (MI), currently pointed out by experts as the most promising strategy. Second, the two principal paradigms of MI are joint modelling (JM) and fully conditional specification (FCS), one more complication because they are not equally useful depending on the combination of multilevel model and the estimated parameters affected by missing data. Technical literature do not contribute to ease the number of decisions that researcher has to do. Given these inconveniences, the present paper has three objectives. (1) To present a thorough revision of the most recently developed software and functions about multiple imputation in multilevel models. (2) We derive a set of suggestions, recommendations, and guides for helping researchers to handle missing data. We list a number of key questions to consider when analyzing multilevel models. (3) Finally, based on the previous relevant questions, we present two detailed examples using the recommended R packages to be easy for the researcher applying multiple imputation in multilevel models.

Cultural aging stereotypes in European Countries: Are they a risk to Active Aging?

A growing body of literature acknowledges the association between negative stereotypes and individual components of active aging, but very few studies have tested this association, at both individual and population levels. The Stereotypes Content Model (SCM) states that the cultural aging stereotyping of higher warmth than competence (called paternalistic or ambivalent prejudice) is universal. Our aims in this study are to test the extent to which the universality of this stereotype is confirmed in European Countries as well as how far "positive", "negative" or "ambivalent" views towards older people, and other negative attitudes such as prejudice and behaviours such as discrimination, predict active aging assessed both at individual and population levels. We have analyzed data from the European Social Survey-2008 (ESS-2008), containing SCM stereotypical and other appraisal items (such as direct prejudice and perceived discrimination) about adults aged over-70 from 29 European countries. First, SCM cultural stereotypes about older adults ("friendly", "competent", and "ambivalent") were calculated; secondly, after developing a typology of countries based on their "negative", "ambivalent" and "positive" views about older adults, the universality of cultural stereotypes was tested; thirdly, taking into consideration ESS data of those older persons (over 70s) who self-reported indicators of active aging (health, happiness, satisfaction and social participation), multilevel analyses were performed, taking our inter-individual measure of active aging as dependent variable and our stereotypical classification (positive/negative/ambivalent), direct prejudice and perceived discrimination as predictors; finally, relationships between stereotypical and appraisal items on older adults were examined at population level with country data from Active Aging Indexes. Our results show cultural stereotypes about older people (more friendly than competent) are widespread in most European countries, and negative cultural views of older adults are negatively associated with active aging both at individual and population level, supporting that negative cultural views of older adults could be considered as a threat to active aging.