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The assessment of views on ageing: a review of self-report measures and innovative extensions

Abstract

This is a review of existing self-report measures for assessing views on ageing. It provides an overview of instruments, for which basic psychometric properties are available and describes them according to the purposes for which they are suitable. Literature search resulted in the inclusion of 89 instruments which were categorised along eight dimensions. The majority of measures focus on explicit cognitions about people’s own age and ageing or other (older) people. A substantial amount of tools account for the multidimensionality and multidirectionality of views on ageing, i.e. the idea that ageing is accompanied by both gains and losses in several different domains. To some extent, measures reflect that ageing is a long-term process and that views on ageing are malleable, rather than just stable traits. Cluster analysis revealed heterogeneity in instruments regarding the dimensions of Ecosystem, Balance, Stability, Dynamics, and Complexity. It becomes apparent, however, that approaches to measure views on ageing should be extended to more specifically target the implicit level as well as affective, physiological, and behavioural manifestations. Additionally, means for capturing views on ageing on the societal level and tools with a distinct time reference are needed. This is particularly important when one wants to account for the lifelong dynamics of views on ageing.

Introduction

This review provides an overview of self-report instruments to assess views on ageing (VoA). It categorises them along eight dimensions, thus enabling researchers to choose suitable instruments according to the specific aims and needs of their research questions. It also highlights the gaps in the existing literature and identifies areas in which new or extended measures may be needed.

VoA are defined as a person’s conceptions about older people, old age, and ageing in general as well as conceptions of one’s own age and ageing, that is, subjective ageing (including self-perceptions of ageing and subjective age; Wurm et al. 2017). Hence, prototypical societal conceptions of the competencies, characteristics, and physical conditions of old age and (other) older people in general (age stereotypes) must be differentiated from expectations and perceptions of one’s own old age or ageing (Miche et al. 2015). These personal experiences are assumed to have a cognitive-evaluative (e.g. Steverink et al. 2001), but also an affective and behavioural component (Diehl et al. 2014). Metastereotypes refer to how we think other people might view older age (Bowen et al. 2011; Staudinger 2015). Against this background, we can distinguish representations of the status of being old from those of the process of getting old (e.g. Wurm et al. 2017).

It is commonly assumed that the development of VoA starts in early childhood (e.g. Gilbert and Ricketts 2008) and continues throughout life based on embodied stereotypes and personal experiences with older people (Levy 2003, 2009). Resource conflicts, in-group appreciation, and defences against death anxiety (Martens et al. 2005) are assumed to cause the distancing from older people, which is expressed in deviating views on one’s own ageing from those on the ageing of other people. Recently, we reasoned that VoA play a powerful role in shaping development across the entire life span and proposed a lifespan bio-psycho-social approach of views on ageing (Kornadt et al. 2019). Starting in younger ages (e.g. Klusmann et al. 2019) VoA exert their influence on the psychological (i.e. the cognitive and affective level), but also the physiological (e.g. as a reaction to age cues) and the behavioural level (Hess 2006; Levy 2009). In addition, as has recently been summarised by Wurm et al. (2017; Westerhof and Wurm 2018), VoA manifest in well-documented effects on health and well-being. VoA are both products as well as drivers of development running through all bioecological levels (Bronfenbrenner and Crouter 1983), meaning a continuous lifelong interaction with social context on the micro-, meso-, and macro-levels.

Tied to the above, VoA are conceptualised as having an outlasting component (trait proportion), but also a variable and malleable component (state proportion), as has also been substantiated by recent research (Beyer et al. 2019; Wolff et al. 2014). For instance, a person can have relatively stable age stereotypes, but these could be challenged by stereotype incongruent experiences. It has recently been shown that attitudes toward one’s own ageing undergo substantial changes following critical life events such as impaired health (cf. Kotter-Gruehn 2015; see also Wurm et al. 2019).

Based on the seminal work of Paul Baltes (1987), which describes human ageing as characterised by both developmental gains and losses, VoA are (and hence should be referred to as) multidirectional, that is, include both positive and negative aspects of ageing (cf. Wurm et al. 2017). This idea is linked to the issue of complexity, referring to multidimensionality (Diehl and Wahl 2010; Diehl et al. 2014) or domain specificity of VoA (Kornadt and Rothermund 2011, 2015). Modern approaches, such as the Awareness of Age-Related Change (AARC) concept, assume that VoA vary on a continuum ranging from sub- or pre-conscious (implicit) to conscious (explicit; Diehl et al. 2014). Whereas the latter is thought to increase across the life span, subconscious processing decreases (Wurm et al. 2017). A lifespan perspective affords the idea of diachronicity in VoA: VoA point to the future in younger people, whereas ageing starts to become part of the present towards middle-age, when age-related experiences become part of one’s self-concept. For their evaluations in old age, by contrast, people compare the present to the past (cf. Kornadt et al. 2019).

The latter conceptions of VoA seem to be in stark contrast to the classical way of assessing VoA. Measures such as the Attitudes Toward Own Aging (ATOA) subscale of the Philadelphia Geriatric Center Morale Scale (PGCMS; Lawton 1975) as well as the Riegel Scale (Riegel and Riegel 1960) or Palmore’s Facts On Aging Quiz (1977) conceptualise VoA as a unidimensional construct, characterised by unidirectional losses. Through the lack of reference to time and limited measurement invariance of items, most classical approaches to measure VoA face limited applicability to different age groups. ‘Age’ and ‘ageing’ mean different semantic categories for a 5-year-old or a 30-year-old or a 70-year-old, for example. Also, scales such as Attitudes Toward Older People (Tuckman and Lorge 1953), Attitudes Towards Old Age (Eisdorfer and Altrocchi 1961), or Old People (Kogan 1961) emphasise cognitive facets, that is, they largely disregard affective and behavioural aspects and thus seem to hardly map onto the multifaceted and highly individual nature of experiences and perceptions of ageing.

Since the beginning of the assessment of VoA in the 1950s, a wide array of measures has become available to capture them. Most of these had been developed for the purpose of addressing VoA not earlier than in middle adulthood, such as the AgeCog Scales being applied to adults aged 40 years and above (Steverink et al. 2001; Wurm et al. 2007). The present study aimed to review and systematise available measures of VoA to provide answers to the question of how VoA are commonly conceptualised and assessed. This overview reveals which tools of which quality are available for which purpose. Based on the results of this analysis of self-report measures, alternative formats and approaches are considered in terms of their feasibility for supplementation and extension of the established self-report means to assess VoA.

Methods

Search strategy

Experts from the DFG Scientific Network Images of Aging were consulted in a focus group to define a preliminary collection of assessment tools or instruments for capturing VoA (n = 42) as well as a list of common VoA terms that describe the main concepts (the following 12 in alphabetical order: age anxiety, age identity, age stereotypes, ageing awareness, ageing expectations, ageism, attitudes to ageing, beliefs about ageing, images of ageing, perceptions of ageing, subjective age, and views on ageing). For each of these main concepts, a systematic basic search (topics) in the Web of Science Core Collection electronic database was conducted in combination with an AND operation of ‘assessment OR questionnaire OR measure’. Searches were run from 5 September to 10 October 2018 with no time restriction. In all cases, a comprehensive list of variations (e.g. felt age, desired age, ideal age), synonyms, and MeSH terms (e.g. age/ageing, anxiety/fear, old/older people/adults/elderly/senior), as well as spelling variants and truncations were used. Backwards search for references to potentially relevant measurement tools in the articles was also conducted.

Inclusion criteria and study selection

Articles, reviews, and book chapters were included as document types (i.e. proceedings and meeting abstracts were excluded). They had to include at least one item or scale on VoA which had not been published elsewhere (in cases where measures were referred to that were not already part of our collection, backwards search was conducted to retrieve the original source and review it for inclusion). Measures in all languages were included if the papers were written in English. The measure had to be publicly available, either free to view through journal subscriptions or provided by the authors on request (n = 31, i.e. 7% out of 435 full texts selected through abstract screening were not available). Also, basic psychometric information had to be available, that is, reliability (for multi-item instruments) and at least one validation criterion (e.g. factorial validity, convergent or divergent validity, predictive validity). Inclusion of articles through the literature search was qualified by a second reviewer (V.K. and M.G.). In case of disagreement, records and measures were discussed until consensus was reached.

Data extraction and analysis

Data extraction and data analysis focused on items, questionnaires, and rating scales developed to capture VoA. A data extraction sheet was developed by the group of authors, and data were extracted from the records of measures accordingly. Besides measure (title or name), authors, and year of publication, the following information was extracted: country of origin, number of citations (Web of Science) as an indicator of frequency of use, number of subscales, names of subscales, number of items (per subscale if applicable), target age group, and purpose (for which the measure was developed). Furthermore, psychometric information on reliability (i.e. Cronbach’s alpha, test–retest, specified other) and validity (i.e. factorial, predictive, divergent, convergent, specified other) was recorded.

A taxonomy to characterise VoA comprising eight dimensions with two to four levels each was developed by the expert panel of the DFG Scientific Network Images of Aging according to conceptualisations of VoA in the literature (see introduction). The first dimension ‘Ecosystem’ entails a two-step differentiation. The first step addresses the observer level, that is, the differentiation between individual and society (Whose VoA are addressed, those of the person asked or those of the social context or society as a whole?). In a second step, at the individual level, the target level of observation is further differentiated into self and others (Who are the VoA about, my own age and ageing or other people’s ageing and/or the group of older people in general?). Metastereotypes (see above) are a special case in the latter category.

The second dimension ‘Dynamics’ defines whether VoA refer to the status of being old (i.e. VoA refer to a more or less clearly defined situation at a certain point in time or point in life and/or the associations with being a certain age) or the process of getting old (i.e. VoA focus on what changes or remains stable as people grow older). The third dimension ‘Manifestation’ distinguishes the four levels on which VoA reflect in a person: VoA at the cognitive level entail thoughts, knowledge, and/or reasoning regarding age, ageing, or older people. On the affective level, there are feelings regarding age, ageing, or older people, and also emotional responses to age cues. On the physiological level bodily responses to ageing occur, in particular to age cues. On the behavioural level actions and conduct associated with own age and ageing (e.g. health behaviour or preparatory behaviour), behaviour directed at other (older) people, or behavioural responses to age cues (e.g. discriminative action) can be differentiated.

The fourth dimension ‘Stability’ distinguishes between malleable or stable VoA. On the one hand, changes or fluctuations in VoA reflect differences resulting from distinct states in particular situations (e.g. a phase in life or as a result of acute events and experiences). On the other hand, VoA are assumed to be (relatively) stable, individual characteristics that are part of the personal attitude and value system, that is, traits of personality (cf. Spuling et al. 2019). The fifth dimension ‘Complexity’ targets uni- versus multidimensionality of VoA, that is whether these are construed as overarching attitudes on a general level or as specific facets of age and ageing at different levels (e.g. physical, social, psychological) or as divergent VoA in different domains (e.g. work, family, leisure, etc.). The sixth dimension ‘Balance’ separates unidirectional from multidirectional VoA conceptions, that is, whether only one valence direction (i.e. age-associated negative aspects/changes or losses) or whether multiple valence directions are considered (i.e. both developmental potentials, gains or neutral phenomena, aside from losses).

The seventh dimension ‘Awareness’ differentiates implicit associations of age and ageing and subconscious processes from explicit attitudes. Since implicit VoA cannot be addressed by direct questions that obviously target VoA, more subtle approaches are required, such as indirect assessments (e.g. level of knowledge, consent to prejudice) or behavioural observations (e.g. ignorance, social rejection, age-offensive behaviour). Explicit VoA, by contrast, can be captured by asking straightforward questions about age and ageing without veiling the target (e.g. “older people typically are”, “with my advancing age, I…”). Finally, the eighth dimension ‘Time’ defines whether a reference to a certain time is made. Following a lifespan perspective, VoA can refer to the future, the present, or the past. Future-oriented VoA are directed at anticipated age-related events and/or expectations regarding age and ageing, whereas present-oriented VoA deal with people’s current awareness, their prevailing perceptions and experiences of getting and/or being older. Finally, past-oriented VoA refer to memories or perceptions of things being better or worse and/or different from previously held expectations.

Based on this systematisation, the authors developed a classification scheme with the eight dimensions as main categories and the levels as subcategories, adding a “mixed” subcategory for Awareness as well as “mixed (separate subscales)” and “mixed (within one scale)” as subcategories for Ecosystem, Manifestation, Dynamics, Time, and Stability. For Ecosystem, statements on social demands, such as how society should deal with ageing or treat older adults, were coded as ‘societal’, whereas opinions on how older people are treated in society were categorised as metastereotypes and thus coded as ‘other’. For Stability, assessments targeting VoA in a certain ‘state’ are often indicated by signal words referring to the current time such as ‘now’, ‘at the moment’, ‘today’, ‘during the last days/weeks/months’. This subcategory usually applies together with the subcategory ‘present’ of Time. Of note here is that the three subcategories of future, past, and present are obviously not mutually exclusive: If assessments vary in or mix up time perspectives (e.g. by different items), these are coded in more than one category. For Awareness, we coded items that obviously and transparently asked for VoA as explicit, whereas tools that only indirectly (and less apparently for the respondents) assessed VoA, such as Palmore’s Facts on Aging Quiz (1977), for example, were coded as implicit means.

Results

Selection of measures

Consistent application of the inclusion criteria resulted in the exclusion of five instruments from the preliminary compilation of assessment tools to capture VoA, hence the final collection entailed 37 instruments stemming from the expert consultations. A further 52 instruments were added as a result of the Web of Science searches (see Fig. 1). Thus, the final collection comprised 89 instruments in total (cf. Tables 2, 3, 4, 5).

Fig. 1
figure1

Flowchart for selection of measures based on Web of Science searches and focus groups. Note VoA = views on ageing

Characteristics of the measures were recorded using the data extraction sheet and subjected to coding based on the taxonomy as outlined above. Inter-rater agreement was calculated from codings of 50% of the instruments (n = 43). Within the eight dimensions, inter-rater agreement ranged from Krippendorff’s α = .74 for Manifestation to α = .90 for Complexity (bootstrapping n = 1000).

Global characteristics of measures

Two-thirds (n = 59) of the instruments published between 1953 (Attitudes toward older people scale; Tuckman and Lorge 1953) and 2018 (Awareness of Age-Related Change; Brothers et al. 2018) were developed and/or validated in the USA. About two-thirds of the instruments, that is, 32.5% and 31.5%, respectively, either targeted samples of young people under the age of 30 years (mostly students) or included people from adulthood up to old age (i.e. 65 or 85 years and older). The remaining third addressed target samples of 40 + years of age with 21.3% being 60 + year-old samples.

Given the inclusion criteria, basic psychometric criteria were available for all selected measures. Cronbach’s alpha was reported for the vast majority (79%) of instruments (n = 70); test–retest reliability was available for 18% of the tools (n = 16). More than two-thirds (69%) reported on predictive validity (such as predicting performance, motivation, behaviour, health or well-being); for 47% (n = 42), there was information about factorial validity, and reports of divergent and/or convergent validity were available for 34% and 30%, respectively. On average, 15.9 years had passed since publication (median = 11 years) and publications were cited 51.7 times on average (median = 21) with maxima of 2212 Web of Science citations for the broader Stereotype Content Questionnaire (Fiske et al. 2002) used for ratings on diverse target groups and 783 citations for the prominent paper by Lawton (1975) on the Philadelphia Geriatric Center Morale Scale with the well-known Attitudes Toward Own Aging subscale. The number of subscales ranged from zero (i.e. single items or single scale only) to 13.

Data synthesis on the taxonomy of VoA

Dimensionality of VoA

The codings on the eight dimensions defined by the taxonomy are summarised in Table 1. It becomes clear that in currently available self-report assessment tools, VoA are represented in a relatively imbalanced way across most dimensions. Almost 90% of the tools address VoA in an explicit way on its conscious level. Hence, the implicit nature of VoA—being a central attribute of stereotypes—is highly neglected. The vast majority (61%) of the measures addresses VoA on the level of thinking (i.e. cognitive); all measures in the mixed categories of Manifestation include cognitive aspects, 68% have a concurrent affective component, and 77% also address behavioural aspects, while only one measure considers physiological matters (i.e. ‘senses’ in the Adults’ Perception of Ages, Montepare 1996a). Two-thirds of the instruments recognise that VoA are multidirectional and, consequentially, also specify age-associated positive aspects and developmental potentials aside from losses. Slightly more than half of the instruments acknowledge the multidimensionality of VoA (56%); however, this means that 44% of the measures give preference to a unidimensional operationalisation of VoA. In terms of Dynamics, again two-thirds of the assessments regard VoA as a status quo concept, and only 12% pursue a clear (non-mixed) process perspective. This coincides with 75% of the instruments in which one does not find a time reference. Hence the diachronicity concept is widely disregarded among the instruments. Finally, 88% of the measures regard VoA as a trait.

Table 1 Frequencies of VoA dimensions addressed by the selected instruments (N = 89)

Agents and targets of VoA

Whereas one-third of the instruments assesses a mixture of thinking about others’ age and ageing or old people as a group with thinking about own age and ageing, 43% solely assess responses referring to other (old) people and only 20% are exclusively dedicated to one’s own age and ageing. This individual-level perspective is juxtaposed with at least a quarter of assessments that reflect VoA on the societal level (i.e. n = 23, being 26% when counting both pure societal VoA measures and mixed categories).

Contrasting of the groups of instruments rating either only oneself (n = 18) to those addressing rating of only others (n = 38) for the remaining dimensions underlined that ratings about oneself mean greater introspection. Consequently, despite always entailing a cognitive manifestation, more than 60% of the measures about the ageing self were mixed, entailing also manifestations on the affective (n = 6), behavioural (n = 6), or physiological level (n = 1). For ratings of others, 84% of the measures were purely cognitive, which was a significant difference from self-ratings, χ2(4) = 19.09, p = .001. Also, a process perspective was more likely for ratings referring to the self (44% of process and 44% of status in contrast to 82% of pure status ratings and only 3% of process perspectives reflected in the ratings referring to other people), χ2(3) = 18.84, p < .001. Complexity (i.e. dimensionality) and Balance, (i.e. gains-losses perspective), however, did not differentiate self-ratings and ratings of others. Consistent with the predominant status concept of VoA, instruments addressing ratings of other people had no time reference at all (100%) and regarded VoA as a trait (97%). Measures referring to self-assessments, however, often referred to the future (28%), the past, or the present (17% each), or mixed these perspectives (22%). In stark contrast to the other-directed measures, only 16% of the self-ratings had no time reference, χ2(4) = 43.25, p < .001. Similarly, different from ratings of other’s age and ageing or old people, only 50% of the ratings referring to one’s own age and ageing regarded VoA as a trait, instead of being a state (28%) or at least mixed state-trait (17%), χ2(3) = 18.99, p < .001.

VoA measures across time

Comparing measures published in the last 5 (n = 22) or 10 years (n = 42) with those of the earlier years did not reveal significant changes regarding the taxonomy profile. There is a tendency of measures having become more process-oriented: 17% of the measures of the last 10 years as opposed to 8.5% of the older instruments. Furthermore, there were tendencies for the measures of the last 5 years to provide slightly more separate subscales to assess manifestations on different (psychological) levels (13.6% vs. 3% for the older measures) and fewer subscales mixing manifestations (31.3% vs. 22.7%), χ2(4) = 7.81, p = .10. Also, of those published in the last 5 years, none continued to mix items with and without time references, compared to 16% of the measures published more than 5 years ago and 21% of the measures older than 10 years, χ2(2) = 7.33, p = .026. Although this trend meant slightly higher proportions of measures with time references in the last 5 years (18% as opposed to only 10% in the older measures), it also coincided with more measures that did not refer to time at all (82% compared to 73% in the instruments of the preceding years).

Further, we explored whether taking into account how much measures are recognised in the scientific community (as indicated by citation frequency) would change the findings regarding the taxonomy profile of measures. Adjusting scores by the mean citation frequency per year did not change results substantially (cf. Table 1). In terms of complexity, the ratio changed slightly, reflecting that unidimensional measures tended to be cited more often than multidimensional measures (the difference was not statistically significant due to the high variability in citation frequencies).

Clustering of measures

To identify an overarching structure in how the self-report measures included in this review map on the taxonomy of VoA, a two-step cluster analysis was run using log-likelihood estimation with automatic determination of clusters (max = 15) and model selection via Akaike information criterion (AIC). The resulting four clusters could be differentiated by the way VoA were issued and conceptualised, respectively: Measures in Cluster 1 addressed “VoA as cognitive other-directed multidimensional and multidirectional traits” (n = 23 published between 1953 and 2017). Instruments in Cluster 2 covered “VoA as self-directed complex time referenced process” (n = 14 published between 1972 and 2018), whereas those in Cluster 3 conceptualised “VoA as mixed multidimensional traits” (n = 24 published between 1962 and 2017) and those in Cluster 4 issued “VoA as cognitive unidimensional traits” (n = 28 published between 1961 and 2018; see Tables 2, 3, 4, 5).

Table 2 Descriptives of instruments in cluster 1 (n = 23)
Table 3 Descriptives of instruments in cluster 2 (n = 14)
Table 4 Descriptives of instruments in cluster 3 (n = 24)
Table 5 Descriptives of instruments in cluster 4 (n = 28)

Specifically, measures in Cluster 1 conceptualised VoA as 100% explicit, cognitive, multidimensional traits without any time reference (see Table 6). The vast majority addressed views on other people’s age and ageing (83%), were multidirectional (i.e. focussed both on gains and losses; 96%), and framed the issue of age or being old as a status (87%). Cluster 2 contained the—mostly explicit (93%)—measures addressing people’s own age and ageing (100%). Subsumed measures comprised both unidimensional and multidimensional approaches (43% and 57%), and fewer unidirectional, solely loss-oriented (36%) than multidirectional (64%) as well as fewer status-oriented (36%) than process-oriented means (57%). Unlike other clusters, items reflected the manifold manifestations of VoA on the individual levels of cognition, affect, and behaviour (71% codings in the mixed categories). All of these instruments referred to diverse time perspectives, that is, past (21%), present (21%), future (36%); and, in some cases, also in a less differentiated mixed manner (21%). Likewise—and in contrast to the other clusters—measures reflected the state and trait proportions of VoA (both 35%), again eventually in a less distinct (21% mixed) or even unclear (7%) way.

Table 6 Proportions of VoA dimensions addressed in the four VoA instrument clusters (Ntotal = 89)

The “mixed multidimensional traits” Cluster 3 contained most measures that coevally focused on different levels of the Ecosystem. The 83% mixed codings reflected combinations of VoA directed at the self (60%), others (95%), and society (90%). Furthermore, even more mixed manifestations (83%) on the joint cognitive (100%), affective (70%), and behavioural (95%) level appeared. Despite the high amount of explicit measures in the total collection, Cluster 3 had the highest proportion of implicit means (17%), and those with mixed status and process (42%) or different time perspectives (33%). While 79% of the measures were multidimensional, Cluster 3 had the highest proportion of solely loss-oriented unidirectional means (46%).

In stark contrast to the other three clusters, measures in Cluster 4 were exclusively (100%) time unreferenced and unidimensional with a predominant cognitive (86%) focus on other people (57%) and also VoA on the level of society (14% plus 21.5% measures with mixed focus on the different Ecosystem levels). Similar to Clusters 1 and 3, measures mostly framed age as a status (75%), of which people have stable assessments (93% trait).

Mean years since publication ranged from 19.8 (median = 14) for Cluster 1, 15.8 (median = 11) for Cluster 3, 14.8 (median = 11.5) for Cluster 2 to 13.8 (median = 9) for Cluster 4. Mean number of citations (mean citations weighted per years since publication in parentheses) ranged from 89.9 (4.51, median = 2.58) for Cluster 2 and 58.4 (4.49, median = 2.10) for Cluster 4 to 40.3 (2.39, median = 1.22) for Cluster 1 and 32.7 (2.96, median = 2.08) for Cluster 3. Hence, by tendency—since these variations were non-significant—Clusters 2 and 4 include somewhat “younger”, well-referenced measures.

Prototypical examples of Cluster 1 are the Attitudes Toward Older People Scale (Tuckman and Lorge 1953) and the Aging Semantic Differential (Rosencranz and McNevin 1969), which congruently capture in an explicit way (i.e. people are aware of what the measure aims at) the multidimensional and multidirectional trait-like status of being old. Both measures refer to (other) older people on the purely cognitive level without any specific time reference (see Table 2).

Examples of Cluster 2 are the established ATOA subscale of the PGCMS (1975) as well as Kastenbaum’s et al. (1972) Subjective Age (SA) measure. Both of these are unidimensional, unidirectional means targeting self-assessment. Whereas ATOA is a classical explicit, cognitive evaluation tool of the ageing process as a mixture of state and trait, SA is an implicit tool whose assessments of the current state are shaped by not only cognitive but also affective representations (in the sense of “feeling” young or old). Both instruments are time referenced: ATOA refers to the past, whereas SA refers to the present status (see Table 3). Prototypical measures collated in Cluster 3 are the Fraboni Scale of Ageism (1990) as well as the Anxiety About Aging Scale (Lasher and Faulkender 1993) for whom the mixture of cognitive but also affective and behavioural manifestation of multidimensional VoA traits is characteristic (see Table 4). They differ, however, in that Fraboni’s scale implicitly targets negative views on other (old) people and loss-oriented societal VoA with no time reference, whereas Lasher and Faulkender’s scale is an explicit one targeting self and others regarding both gains and losses referring to past, present, and future.

Finally, Cluster 4 comprises Kogan’s (1961) Old people Scale, Palmore’s Facts on Aging Quiz, and the more recent Löckenhoff et al. (2009) bisected measure. All of these are unidimensional means addressing purely cognitive, non-time referenced reflections on other (old) people or VoA on the level of society (see Table 5). In contrast to Kogan’s and Löckenhoff’s scale, Palmore’s scale does not capture explicit VoA and works with “wrong” answers (and was therefore also coded as implicit and unidirectional).

Discussion

The eight-dimensional categorisation of VoA assessment instruments revealed that for some dimensions, existing VoA instruments mostly fall onto one level, whereas for others, different levels of that dimension are already represented within the existing VoA instruments. The latter is the case for Complexity and Balance as well as for the individual levels of Ecosystem. Depending on the purpose and target of the assessment, the pool of self-report measures provides instruments that conceptualise VoA as unidimensional or multidimensional as well as unidirectional or multidirectional and put the focus on either the ageing self and/or other people. This contrasts significantly with the dimensions of Awareness, Manifestation, and Time Perspective, and—at least to a certain degree—Dynamics and Stability.

These patterns of central foci of assessment are mirrored in the clusters which map VoA instruments based on co-occurring dimensions. Whilst there is divergence concerning Ecosystem, Balance (esp. Cluster 1), Stability, Dynamics (esp. Cluster 2), and Complexity (esp. Cluster 4), there is little to no differentiation concerning Awareness (all explicit), Manifestation (prevailingly cognitive), and Time Reference (three quarters of the instruments do not refer to time). This hints at where the current assessment of VoA should be extended.

Buzz and balance for self-report assessments of VoA

Overall, the collection of instruments works perfectly well for the assessment of individual VoA on the explicit and cognitive level. There are differentiated measures to capture self-views as well as one’s way of thinking about other people’s age and ageing or old people as a group (age stereotypes, in particular). There are tools to capture rough and global VoA or very well elaborated and validated ones that allow studying domain-specific, multidimensional VoA. Two-thirds of the instruments reflect the idea that age and ageing infer both gains and losses; a minority of the instruments includes just one valence direction. There are some decent options for mapping changes in VoA, such as lifelong dynamics (i.e. the process of ageing) or fluctuations (i.e. states as opposed to stable trait-like VoA). The finding, however, that the vast majority of the measures regard VoA as a trait is particularly remarkable against the background of current attempts to find effective ways of intervening to dissolve traditional age stereotypes and allow for more differentiated VoA in terms of productive development (e.g. Beyer et al. 2019). These efforts are based on the idea that VoA are indeed malleable and thus, at least in part, reflect a state.

What the collection seems to miss are means to capture the implicit aspects of VoA, their manifestation in affect, physiology, and behaviour as well as their societal representation. Also, regarding VoA as a lifelong phenomenon (see Kornadt et al. 2019) cannot forego consideration of its diachronicity: Depending on life phase VoA are differentially tied to one’s past, present, or future. Yet the vast majority of self-report measures neglect to include time references. Instruments exclusively targeting one’s own age and ageing were somewhat more differentiated in terms of manifestation on distinct levels, considering the malleability of VoA (VoA also as states), referring to ageing as a process, and regarding time references. This finding is limited, however, by the fact that the instruments purely targeting one’s own age and ageing (n = 18, i.e. 32%) were outnumbered by those on others’ age and ageing (n = 38, i.e. 68%). Similarly, the most recently published means tended to be less mixed (i.e. using separate subscales to differentiate diverse manifestations, including references to time) and slightly more process-oriented. Measures with such a profile were among the highly cited ones in Cluster 2. Meanwhile, none of the measures published over the last 5 years were implicit.

The inclusion criteria chosen for the selection of instruments for our systematisation may have contributed to certain aspects being underrepresented: We exclusively considered self-report questionnaire measures. This format might lead to approaching phenomena on the explicit and cognitive level and focus on the individual—both as perceiver and as target. In contrast, linguistic and literature content analyses are much more common in sociological research traditions (Ng et al. 2015). Moreover, other forms of psychological assessment typically used in basic research, such as reaction time tasks like implicit association tests (Greenwald et al. 1998) or subliminal priming (Elgendi et al. 2018) are specially thought to address phenomena on implicit and affective levels. Diary entries for the natural occurrence of ageing experiences (Miche et al. 2014b), or ecological momentary assessments (Kotter-Gruehn et al. 2015) allow capturing intra-individual variability and systematically operationalising time references. A review of methodological alternatives to pure self-report and classic questionnaire measures could indicate to what extent these may provide useful extensions for filling the gaps found.

Thinking outside the box for innovative extensions

Most of the alternative measures that are addressed in this section do not fall under the labels commonly used to describe ‘views on ageing’ as outlined above. Hence, these suggestions are not meant as definitive recommendations. The actual suitability of these approaches in supplementing the self-report instruments systematised in the present study would be subject to future research.

What became clear is that the implicit part of VoA as well as their manifestations on the affective and behavioural level appear underrepresented in self-report measures. Additionally, means of time reference and possibly those that allow depicting the lifelong ageing processes as well as fluctuations in people’s VoA over time would be worth a closer look. The classical tool for studying phenomena on the subconscious, that is, implicit and affective level, is the Implicit Association Test (IAT; Greenwald et al. 1998), a very popular method in experimental research. Frequently combined with psychophysiological measures, which allow capturing pre- and sub-conscious processes as well, the IAT compares reaction times as responses to pairings of specific concepts (e.g. old vs. young) with certain attributes (e.g. positive vs. negative; Hummert et al. 2002). A version for children has also been developed (Babcock et al. 2016). Another reaction time-based method for assessing VoA, specifically age stereotypes, is the so-called contradiction paradigm. Here, participants’ reading times for sentences with content that is either consistent or inconsistent with negative age stereotypes are compared (Lassonde et al. 2012). In terms of the VoA dimensions presented in the present review, these tests target the implicit level on the Awareness dimension as well as affective and—depending on the concrete operationalisation—physiological levels of Manifestation. The same is true for experiments using priming, which additionally often target the behavioural consequences of VoA. As such, experiments examine people’s performance in cognitive testing and daily functioning (e.g. driving) after being exposed to negative age stereotypes (e.g. Chapman et al. 2014; Hagood and Gruenewald 2018; Mazerolle et al. 2012). Another approach involves manipulating people’s subjective age and examining the influence of the manipulation on various outcomes (Eibach et al. 2010).

Diverse stimuli related to age, ageing, and older people are used in related paradigms. Photographs of younger and older faces are used, for instance, to study relationships to ratings of attractiveness or intelligence or associations between negative/positive expressed emotions and age ratings (Kotter-Gruehn and Hess 2012; Palumbo et al. 2017). Voice samples (Montepare et al. 2014) and vignettes (Schroyen et al. 2016) are also popular stimuli to study age stereotypes on an implicit level, while—depending on design—also allowing observation of affective, physiological, and behavioural manifestations.

Ageing simulation takes a somewhat different approach to address ageing in a holistic way on different levels of Awareness and Manifestation. Younger and middle-aged adults are made to experience “ageing” or their “older selves”. This includes simulated ageing exercises, in which participants wear ageing suits or other apparel to let them experience sensory and physical changes while studying their affect, behaviour, and cognitions (Green and Dorr 2016). Similarly, virtual reality experiments allow participants to see and interact with an aged version of their self and measure their reactions and behaviours, that is, how close they feel to their future aged self or how much money they allocate to retirement funds, for example (Hershfield et al. 2011). These approaches also entail a Time Reference, in that they make participants experience aspects of their possible future.

A method that also relies on self-report, but not on the classical questionnaire format, are diary studies, in which participants report, for example, on experiences related to age and ageing on a daily basis (Miche et al. 2014b). In the age of digitalisation, sophisticated ecological momentary assessments (Kotter-Gruehn et al. 2015) provide an excellent tool to explicitly separate state-trait proportions of VoA (the Stability dimension) as well as—if set up as longitudinal studies—to study lifespan ageing processes in combination with changes in VoA over time (the Dynamics dimension). These tools also allow for an elaborated study of diachronicity phenomena of VoA across the life span (the Time Reference dimension), being highly parsimonious and user friendly at the same time.

Last but not least, taking a more sociological perspective on VoA both in terms of theory and assessment might help supplement overly individualistic assessments of VoA. There are studies relying on interview techniques (Horton et al. 2008), content analyses of media, such as site descriptions on social media like Facebook (Levy et al. 2014), analyses of linguistic databases (Ng et al. 2015), identification of adjectives used to describe “typical” older people (Chen and King 2002; Wehr and Buchwald 2007), or generation of words describing older people’s activities (Wurtele 2009), to name just a few. Like self-report measures, these approaches are language-based but instead mostly address a combination of implicit and explicit VoA on both individual and societal levels and allow studying societal trends and dynamics in VoA. Recently, photographs about ageing taken by different age groups were used as an indicator of VoA in everyday life (Klusmann 2020).

As mentioned above, this list of alternative approaches is not exhaustive. A fertile extension of self-report measures of VoA might also involve methods from disciplines even further remote than those described. What becomes clear, however, is that overcoming disciplinary boundaries seems promising for the development of innovative extensions to assess VoA dimensions in a more complete way.

Limitations and outlook

One of the major strengths of this review is that its taxonomy and categorisation is theory-based and goes far beyond other recent efforts to collect and report on VoA measures, both in scope and in content (e.g. Ayalon et al. 2019; Faudzi et al. 2019). Furthermore, it relies on an extensive search that combines multiple approaches and sources, i.e. focus groups with experts as well as a systematic literature search. This comprehensive search strategy resulted in a collection of 89 instruments that allows for a valid and high-quality overview of how VoA have been measured over decades.

Although Web of Science is a database that covers a wide range of disciplines, a literature search in several different databases could have helped to reach even higher certainty that truly all existing VoA measures have been considered for inclusion in the review. Furthermore, whereas the search terms for VoA were quite comprehensive, the use of additional keywords representing ‘instrument’ (e.g. screening, inventory, tool, profile) might have led to the identification of a few more VoA measures. Adding these terms to two of the search’s subsets on main concepts as outlined in the methods section, however, did not reveal any further hits.

In considering the strengths and limitations of this review, one also has to keep in mind that strict inclusion and exclusion criteria also always mean trade-off decisions. The criterion to only include tools with basic psychometric information available meant that 81 instruments were excluded; these were mostly developed ad hoc to study ageing attitudes as endpoints of research. Including these in our classification may have changed the answer to our question of how VoA are measured. Nevertheless, in our view, the systematisation and categorisation reported here along with considerations about innovative extensions and combinations of measures with tools that typically do not run under the label of VoA allow for a sound overview of available instruments to assess VoA, maybe even across the whole life span.

Given that roughly two-thirds of the instruments in our collection originate in the USA, it is likely that the included instruments reflect mostly Western, and particularly North American ideas with regards to VoA (Löckenhoff et al. 2009; Voss et al. 2018). Furthermore, two-thirds of the instruments included here have been validated with adult and older adult samples only. As outlined in the introduction, not all of these measures seem appropriate for straightforward use with other age groups and would need adaptations because ‘age’ and ‘ageing’ have different meanings for a 70-year-old than a 30-year-old or a child. Hence, there is a need for validated measures that can be used across the life span.

Conclusion

This review provides an overview of self-report instruments to assess VoA and categorises them such that researchers and practitioners can choose the appropriate instrument for their project. We found that VoA are already being measured on a wide range of dimensions. That is, we have well-validated tools to assess VoA both in terms of either thinking about oneself as ageing or being old as well as evaluations of other people being old or getting old. There are tools to study VoA in a parsimonious unidimensional way in the form of global ratings, but also elaborated measures that allow considering the multidimensional nature of both ageing and VoA by differentiating specific domains. Most instruments reflect that ageing encompasses both gains and losses and is not a unidirectional phenomenon. There are also means to regard ageing as a process and some tools that refrain from regarding VoA as stable traits, but provide options to assess changes in VoA. However, we saw that the issue of time frames in which VoA develop and occur is underdeveloped—a phenomenon that seems tied to the observation that only recently have researchers started to regard VoA from a lifespan perspective. We have learned that widening the focus to approaches that do not typically come under the label of VoA might enable us to assess a more complete range of dimensions than the current self-report measures of VoA do. Hence, the predominant focus on explicit individual VoA manifested on the cognitive level might be extended to include also the implicit proportions of VoA along with their affective, behavioural, and maybe also physiological manifestations. Societal VoA might become a stronger issue and—following the idea of a lifelong role of VoA—time references across the life span could be emphasised, along with taking a process perspective and considering situation-specific variations of VoA.

References

*Studies included in the review. †Studies including versions of the measures included in the review

  1. Alwin DF (1997) Feeling thermometers versus 7-point scales: which are better? Sociol Method Res 25:318–340. https://doi.org/10.1177/0049124197025003003

    Article  Google Scholar 

  2. *Anderson K, Harwood J, Hummert ML (2005) The grandparent-grandchild relationship: implications for models of intergenerational communication. Hum Commun Res 31:268–294. https://doi.org/10.1093/hcr/31.2.268

    Article  Google Scholar 

  3. †Arnhoff FN, Leon HV, Lorge I (1964) Cross-cultural acceptance of stereotypes towards aging. J Soc Psychol 63:41–58. https://doi.org/10.1080/00224545.1964.9922212

    Article  Google Scholar 

  4. †Axelrod S, Eisdorfer C (1961) Attitudes toward old people: an empirical analysis of the stimulus-group validity of the Tuckman–Lorge questionnaire. J Gerontol 16:75–80. https://doi.org/10.1093/geronj/16.1.75

    Article  Google Scholar 

  5. Ayalon L et al (2019) A systematic review of existing ageism scales. Ageing Res Rev 54:100919. https://doi.org/10.1016/j.arr.2019.100919

    Article  Google Scholar 

  6. Babcock RL, MaloneBeach EE, Hannighofer J, Woodworth-Hou B (2016) Development of a children’s IAT to measure bias against the elderly. J Intergenerational Relatsh 14:167–178. https://doi.org/10.1080/15350770.2016.1195245

    Article  Google Scholar 

  7. *Bai X, Lai DWL, Guo A (2016) Ageism and depression: perceptions of older people as a burden in china. J Soc Issues 72:26–46. https://doi.org/10.1111/josi.12154

    Article  Google Scholar 

  8. Baltes PB (1987) Theoretical propositions of life-span developmental psychology: on the dynamics between growth and decline. Dev Psychol 23:611–626. https://doi.org/10.1037/0012-1649.23.5.611

    Article  Google Scholar 

  9. *Barker M, O’Hanlon A, McGee HM, Hickey A, Conroy RM (2007) Cross-sectional validation of the aging perceptions questionnaire: a multidimensional instrument for assessing self-perceptions of aging. BMC Geriatr 7:9. https://doi.org/10.1186/1471-2318-7-9

    Article  Google Scholar 

  10. *Bernardes SF, Marques S, Matos M (2015) Old and in pain: enduring and situational effects of cultural aging stereotypes on older people’s pain experiences. Eur J Pain 19:994–1001. https://doi.org/10.1002/ejp.626

    Article  Google Scholar 

  11. Beyer A-K, Wolff JK, Freiberger E, Wurm S (2019) Are self-perceptions of ageing modifiable? Examination of an exercise programme with vs. without a self-perceptions of ageing-intervention for older adults. Psychol Health 34:661–676. https://doi.org/10.1080/08870446.2018.1556273

    Article  Google Scholar 

  12. *Bousfield C, Hutchison P (2010) Contact, anxiety, and young people’s attitudes and behavioral intentions towards the elderly. Educ Gerontol 36:451–466. https://doi.org/10.1080/03601270903324362

    Article  Google Scholar 

  13. Bowen CE, Noack MG, Staudinger UM (2011) Aging in the work context. In: Schaie KW, Willis SL (eds) Handbook of the psychology of aging, 7th edn. Academic Press, San Diego, pp 263–277. https://doi.org/10.1016/B978-0-12-380882-0.00017-6

    Chapter  Google Scholar 

  14. *Braithwaite V, Lynd-Stevenson R, Pigram D (1993) An empirical study of ageism: from polemics to scientific utility. Aust Psychol 28:9–15. https://doi.org/10.1080/00050069308258857

    Article  Google Scholar 

  15. Bronfenbrenner U, Crouter A (1983) The evolution of environmental models in developmental research. In: Mussen P-H (ed) Handbook of child psychology, history, theory, and methods, vol I, 4th edn. Wiley, New York, pp 357–414

    Google Scholar 

  16. *Brothers A, Gabrian M, Wahl HW, Diehl M (2018) A new multidimensional questionnaire to assess awareness of age-related change (AARC). Gerontologist 59:141–151. https://doi.org/10.1093/geront/gny006

    Article  Google Scholar 

  17. *Cary LA, Chasteen AL, Remedios J (2017) The ambivalent ageism scale: developing and validating a scale to measure benevolent and hostile ageism. Gerontologist 57:27–36. https://doi.org/10.1093/geront/gnw118

    Article  Google Scholar 

  18. *Chalabaev A, Emile M, Corrion K, Stephan Y, Clement-Guillotin C, Pradier C, d’Arripe-Longueville F (2013) Development and validation of the aging stereotypes and exercise scale. J Aging Phys Act 21:319–334

    Article  Google Scholar 

  19. *Chan W et al (2012) Stereotypes of age differences in personality traits: universal and accurate? J Personal Soc Psychol 103:1050–1066. https://doi.org/10.1037/a0029712

    Article  Google Scholar 

  20. Chapman L, Sargent-Cox K, Horswill MS, Anstey KJ (2014) The impact of age stereotypes on older adults’ hazard perception performance and driving confidence. J Appl Gerontol 35:642–652. https://doi.org/10.1177/0733464813517505

    Article  Google Scholar 

  21. Chen Y, King BE (2002) Intra- and intergenerational communication satisfaction as a function of an individual’s age and age stereotypes. Int J Behav Dev 26:562–570. https://doi.org/10.1080/01650250143000553

    Article  Google Scholar 

  22. *Cherry KE, Palmore E (2008) Relating to older people evaluation (ROPE): a measure of self-reported ageism. Educ Gerontol 34:849–861. https://doi.org/10.1080/03601270802042099

    Article  Google Scholar 

  23. *Cheung C-K, Lee I-J, Chan C-M (1994) Self-esteem and perceptions of the elderly. Soc Behav Pers 22:279–289. https://doi.org/10.2224/sbp.1994.22.3.279

    Article  Google Scholar 

  24. *Chopik WJ, Giasson HL (2017) Age differences in explicit and implicit age attitudes across the life span. Gerontologist 57:169-S177. https://doi.org/10.1093/geront/gnx058

    Article  Google Scholar 

  25. *Chumbler NR (1994) The development and reliability of a stereotypes toward older people scale. Coll Stud J 28:220–229

    Google Scholar 

  26. *Chumbler NR (1996) The development of a brief scale on attitudes toward treating elderly patients. Gerontol Geriatr Educ 16:39–51. https://doi.org/10.1300/J021v16n01_05

    Article  Google Scholar 

  27. *de Gracia Blanco M, Olmo JG, Arbonès MM, Bosch PM (2004) Analysis of self-concept in older adults in different contexts: validation of the subjective aging perception scale (SAPS). Eur J Psychol Assess 20:262–274. https://doi.org/10.1027/1015-5759.20.4.262

    Article  Google Scholar 

  28. Diehl M, Wahl HW, Barrett AE et al (2014) Awareness of aging: theoretical considerations on an emerging concept. Dev Rev 34:93–113. https://doi.org/10.1016/j.dr.2014.01.001

    Article  Google Scholar 

  29. Diehl MK, Wahl HW (2010) Awareness of age-related change: examination of a (mostly) unexplored concept. J Gerontol B Psychol Sci Soc Sci 65:340–350. https://doi.org/10.1093/geronb/gbp110

    Article  Google Scholar 

  30. Eibach RP, Mock SE, Courtney EA (2010) Having a “senior moment”: induced aging phenomenology, subjective age, and susceptibility to ageist stereotypes. J Exp Soc Psychol 46:643–649. https://doi.org/10.1016/j.jesp.2010.03.002

    Article  Google Scholar 

  31. Eisdorfer C, Altrocchi J (1961) A comparison of attitudes toward old age and mental illness. J Gerontol 16:340–343. https://doi.org/10.1093/geronj/16.4.340

    Article  Google Scholar 

  32. Elgendi M, Kumar P, Barbic S, Howard N, Abbott D, Cichocki A (2018) Subliminal priming—state of the art and future perspectives. Behav Sci 8:54. https://doi.org/10.3390/bs8060054

    Article  Google Scholar 

  33. *Fan T-HD (2007) Beliefs about aging and later life health and well-being among the elderly in Taiwan. Dissertation, University of Texas at Austin

  34. Faudzi FNM, Armitage CJ, Bryant C, Brown LJE (2019) A systematic review of the psychometric properties of self-report measures of attitudes to aging. Res Aging 41:549–574. https://doi.org/10.1177/0164027518825117

    Article  Google Scholar 

  35. *Fiske ST, Cuddy AJC, Glick P, Xu J (2002) A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition. J Personal Soc Psychol 82:878–902. https://doi.org/10.1037/0022-3514.82.6.878

    Article  Google Scholar 

  36. *Fraboni M, Saltstone R, Hughes S (1990) The Fraboni scale of ageism (FSA): an attempt at a more precise measure of ageism. Can J Aging 9:56–66. https://doi.org/10.1017/S0714980800016093

    Article  Google Scholar 

  37. *Gething L (1994) Health professional attitudes towards ageing and older people: preliminary report of the reactions to ageing questionnaire. Aust J Ageing 13:77–81. https://doi.org/10.1111/j.1741-6612.1994.tb00646.x

    Article  Google Scholar 

  38. Gilbert CN, Ricketts KG (2008) Children’s attitudes toward older adults and aging: a synthesis of research. Educ Gerontol 34:570–586. https://doi.org/10.1080/03601270801900420

    Article  Google Scholar 

  39. †Gluth S, Ebner NC, Schmiedek F (2010) Attitudes toward younger and older adults: the German aging semantic differential. Int J Behav Dev 34:147–158. https://doi.org/10.1177/0165025409350947

    Article  Google Scholar 

  40. *Goebel BL (1984) Age stereotypes held by student nurses. J Psychol 116:249–254. https://doi.org/10.1080/00223980.1984.9923644

    Article  Google Scholar 

  41. Green SL, Dorr N (2016) Changing attitudes toward older adults through a simulated aging exercise: implications for family therapy. Women Ther 39:69–85. https://doi.org/10.1080/02703149.2016.1116314

    Article  Google Scholar 

  42. Greenwald AG, McGhee DE, Schwartz JLK (1998) Measuring individual differences in implicit cognition: the implicit association test. J Personal Soc Psychol 74:1464–1480. https://doi.org/10.1037/0022-3514.74.6.1464

    Article  Google Scholar 

  43. Hagood EW, Gruenewald TL (2018) Positive versus negative priming of older adults’ generative value: do negative messages impair memory? Aging Ment Health 22:257–260. https://doi.org/10.1080/13607863.2016.1239063

    Article  Google Scholar 

  44. Hershfield HE, Goldstein DG, Sharpe WF, Fox J, Yeykelis L, Carstensen LL, Bailenson JN (2011) Increasing saving behavior through age-progressed renderings of the future self. J Mark Res 48:23–37. https://doi.org/10.1509/jmkr.48.SPL.S23

    Article  Google Scholar 

  45. Hess TM (2006) Attitudes toward aging and their effects on behavior. In: Birren JE, Schaie KW, Abeles RP, Gatz M, Salthouse TA (eds) Handbook of the psychology of aging, 6th edn. Academic Press, Burlington, pp 379–406. https://doi.org/10.1016/B978-012101264-9/50020-3

    Chapter  Google Scholar 

  46. *Hollar D, Roberts E, Busby-Whitehead J (2011) COCOA: a new validated instrument to assess medical students’ attitudes towards older adults. Educ Gerontol 37:193–209. https://doi.org/10.1080/03601277.2010.532063

    Article  Google Scholar 

  47. Horton S, Baker J, Côté J, Deakin JM (2008) Understanding seniors’ perceptions and stereotypes of aging. Educ Gerontol 34:997–1017. https://doi.org/10.1080/03601270802042198

    Article  Google Scholar 

  48. *Hostetler AJ (2012) Community involvement, perceived control, and attitudes toward aging among lesbians and gay men. Int J Aging Hum Dev 75:141–167. https://doi.org/10.2190/AG.75.2.c

    Article  Google Scholar 

  49. Hummert ML, Garstka TA, O’Brien LT, Greenwald AG, Mellott DS (2002) Using the implicit association test to measure age differences in implicit social cognitions. Psychol Aging 17:482–495. https://doi.org/10.1037/0882-7974.17.3.482

    Article  Google Scholar 

  50. *Huy C, Schneider S, Thiel A (2010) Perceptions of aging and health behavior: determinants of a healthy diet in an older German population. J Nutr Health Aging 14:381–385

    Article  Google Scholar 

  51. †Intrieri RC, von Eye A, Kelly JA (1995) The aging semantic differential: a confirmatory factor analysis. Gerontologist 35:616–621. https://doi.org/10.1093/geront/35.5.616

    Article  Google Scholar 

  52. *Isaacs LW, Bearison DJ (1986) The development of children’s prejudice against the aged. Int J Aging Hum Dev 23:175–194. https://doi.org/10.2190/8GVR-XJQY-LFTH-E0A1

    Article  Google Scholar 

  53. *Jopp DS, Jung S, Damarin AK, Mirpuri S, Spini D (2017) Who is your successful aging role model? J Gerontol B Psychol Sci Soc Sci 72:237–247. https://doi.org/10.1093/geronb/gbw138

    Article  Google Scholar 

  54. *Kafer RA, Rakowski W, Lachman M, Hickey T (1980) Aging opinion survey: a report on instrument development. Int J Aging Hum Dev 11:319–333. https://doi.org/10.2190/jqf5-xdcv-h1ah-3e1y

    Article  Google Scholar 

  55. *Kane MN (2007) Social work and criminal justice students’ perceptions of elders. J Soc Ser Res 34:13–26. https://doi.org/10.1300/J079v34n01_02

    Article  Google Scholar 

  56. *Kang SK, Chasteen AL (2009) The development and validation of the age-based rejection sensitivity questionnaire. Gerontologist 49:303–316. https://doi.org/10.1093/geront/gnp035

    Article  Google Scholar 

  57. *Kastenbaum R, Derbin V, Sabatini P, Artt S (1972) “The ages of me”: toward personal and interpersonal definitions of functional aging. Int J Aging Hum Dev 3:197–211. https://doi.org/10.2190/tujr-wtxk-866q-8qu7

    Article  Google Scholar 

  58. *Kilty KM, Feld A (1976) Attitudes toward aging and towards the needs of older people. J Gerontol 31:586–594. https://doi.org/10.1093/geronj/31.5.586

    Article  Google Scholar 

  59. *Kim H, Abell N, Cheatham L, Paek I (2017a) Development and validation of the attitudes toward education for older adults (AEOA) scale. Educ Gerontol 43:341–355. https://doi.org/10.1080/03601277.2017.1296298

    Article  Google Scholar 

  60. *Kim J, Lee J, Sims OT (2017b) The productive aging concept and social work students’ perceptions toward an older population. J Soc Ser Res 43:149–155. https://doi.org/10.1080/01488376.2016.1202878

    Article  Google Scholar 

  61. *Kliegel M, Zimprich D (2005) Predictors of cognitive complaints in older adults: a mixture regression approach. Eur J Ageing 2:13–23. https://doi.org/10.1007/s10433-005-0017-6

    Article  Google Scholar 

  62. *Kline DW, Scialfa CT, Stier D, Babbitt TJ (1990) Effects of bias and educational experience on two knowledge of aging questionnaire. Educ Gerontol 16:297–310. https://doi.org/10.1080/0380127900160307

    Article  Google Scholar 

  63. Klusmann V (2020) Aging is in the eye of the beholder: images of aging captured in photographs by younger and older adults (Manuscript in preparation)

  64. *Klusmann V, Evers A, Schwarzer R, Heuser I (2012) Views on aging and emotional benefits of physical activity: effects of an exercise intervention in older women. Psychol Sport Exerc 13:236–242. https://doi.org/10.1016/j.psychsport.2011.11.001

    Article  Google Scholar 

  65. Klusmann V, Sproesser G, Wolff JK, Renner B (2019) Positive self-perceptions of aging promote healthy eating behavior across the life span via social-cognitive processes. J Gerontol B Psychol Sci Soc Sci 74:735–744. https://doi.org/10.1093/geronb/gbx139

    Article  Google Scholar 

  66. *Knox VJ, Gekoski WL, Kelly LE (1995) The age group evaluation and description (AGED) Inventory: a new instrument for assessing stereotypes of and attitudes toward age groups. Int J Aging Hum Dev 40:31–55. https://doi.org/10.2190/8CUC-4XK8-M33K-07YD

    Article  Google Scholar 

  67. *Kogan N (1961) Attitudes toward old people: the development of a scale and an examination of correlates. J Abnorm Soc Psychol 62:44–54. https://doi.org/10.1037/h0048053

    Article  Google Scholar 

  68. *Kornadt AE (2016) Do age stereotypes as social role expectations for older adults influence personality development? J Res Personal 60:51–55. https://doi.org/10.1016/j.jrp.2015.11.005

    Article  Google Scholar 

  69. Kornadt AE, Rothermund K (2011) Contexts of aging: assessing evaluative age stereotypes in different life domains. J Gerontol B Psychol Sci Soc Sci 66:547–556. https://doi.org/10.1093/geronb/gbr036

    Article  Google Scholar 

  70. *Kornadt AE, Rothermund K (2012) Internalization of age stereotypes into the self-concept via future self-views: a general model and domain-specific differences. Psychol Aging 27:164–172. https://doi.org/10.1037/a0025110

    Article  Google Scholar 

  71. *Kornadt AE, Rothermund K (2015) Views on aging: domain-specific approaches and implications for developmental regulation. Annu Rev Gerontol Geriatr 35:121–144. https://doi.org/10.1891/0198-8794.35.121

    Article  Google Scholar 

  72. Kornadt AE, Kessler E-M, Wurm S, Bowen CE, Gabrian M, Klusmann V (2019) Views on ageing: a lifespan perspective. Eur J Ageing. https://doi.org/10.1007/s10433-019-00535-9

    Article  Google Scholar 

  73. Kotter-Gruehn D (2015) Changing negative views of aging: implications for intervention and translational research. Annu Rev Gerontol Geriatr 35:167–186. https://doi.org/10.1891/0198-8794.35.167

    Article  Google Scholar 

  74. Kotter-Gruehn D, Hess TM (2012) So you think you look young? Matching older adults’ subjective ages with age estimations provided by younger, middle-aged, and older adults. Int J Behav Dev 36:468–475. https://doi.org/10.1177/0165025412454029

    Article  Google Scholar 

  75. Kotter-Gruehn D, Neupert SD, Stephan Y (2015) Feeling old today? Daily health, stressors, and affect explain day-to-day variability in subjective age. Psychol Health 30:1470–1485. https://doi.org/10.1080/08870446.2015.1061130

    Article  Google Scholar 

  76. *Kruse A, Schmitt E (2006) A multidimensional scale for the measurement of agreement with age stereotypes and the salience of age in social interaction. Ageing Soc 26:393–411. https://doi.org/10.1017/S0144686X06004703

    Article  Google Scholar 

  77. *Lai DWL (2009) Older chinese’ attitudes toward aging and the relationship to mental health: an international comparison. Soc Work Health Care 48:243–259. https://doi.org/10.1080/00981380802591957

    Article  Google Scholar 

  78. *Laidlaw K, Power MJ, Schmidt S (2007) The attitudes to ageing questionnaire (AAQ): development and psychometric properties. Int J Geriatr Psychiatry 22:367–379. https://doi.org/10.1002/gps.1683

    Article  Google Scholar 

  79. †Laidlaw K, Kishita N, Shenkin SD, Power MJ (2018) Development of a short form of the attitudes to ageing questionnaire (AAQ). Int J Geriatr Psychiatry 33:113–121. https://doi.org/10.1002/gps.4687

    Article  Google Scholar 

  80. Lasher KP, Faulkender PJ (1993) Measurement of aging anxiety: development of the anxiety about aging scale. Int J Aging Hum Dev 37:247–259. https://doi.org/10.2190/1U69-9AU2-V6LH-9Y1L

    Article  Google Scholar 

  81. Lassonde KA, Surla C, Buchanan JA, O’Brien EJ (2012) Using the contradiction paradigm to assess ageism. J Aging Stud 26:174–181. https://doi.org/10.1016/j.jaging.2011.12.002

    Article  Google Scholar 

  82. *Lawton MP (1975) The Philadelphia geriatric center morale scale: a revision. J Gerontol 30:85–89. https://doi.org/10.1093/geronj/30.1.85

    Article  Google Scholar 

  83. †Lee M, Reuben DB, Ferrell BA (2005) Multidimensional attitudes of medical residents and geriatrics fellows toward older people. J Am Geriatr Soc 53:489–494. https://doi.org/10.1111/j.1532-5415.2005.53170.x

    Article  Google Scholar 

  84. *Lee JE, Kahana B, Kahana E (2017) Successful aging from the viewpoint of older adults: development of a brief successful aging inventory (SAI). Gerontology 63:359–371. https://doi.org/10.1159/000455252

    Article  Google Scholar 

  85. Levy BR (2003) Mind matters: cognitive and physical effects of aging self-stereotypes. J Gerontol B Psychol Sci Soc Sci 58:203–211. https://doi.org/10.1093/geronb/58.4.P203

    Article  Google Scholar 

  86. Levy BR (2009) Stereotype embodiment: a psychosocial approach to aging. Curr Dir Psychol Sci 18:332–336. https://doi.org/10.1111/j.1467-8721.2009.01662.x

    Article  Google Scholar 

  87. *Levy BR, Kasl SV, Gill TM (2004) Image of aging scale. Percept Mot Skills 99:208–210. https://doi.org/10.2466/pms.99.1.208-210

    Article  Google Scholar 

  88. Levy BR, Chung PH, Bedford T, Navrazhina K (2014) Facebook as a site for negative age stereotypes. Gerontologist 54:172–176. https://doi.org/10.1093/geront/gns194

    Article  Google Scholar 

  89. †Liang J, Bollen KA (1983) The structure of the Philadelphia geriatric center morale scale: a reinterpretation. J Gerontol 38:181–189. https://doi.org/10.1093/geronj/38.2.181

    Article  Google Scholar 

  90. *Lineweaver TT, Roy A, Horth M (2017) Children’s stereotypes of older adults: evaluating contributions of cognitive development and social learning. Educ Gerontol 43:300–312. https://doi.org/10.1080/03601277.2017.1296296

    Article  Google Scholar 

  91. Löckenhoff CE, De Fruyt F, Terracciano A et al (2009) Perceptions of aging across 26 cultures and their culture-level associates. Psychol Aging 24:941–954. https://doi.org/10.1037/a0016901

    Article  Google Scholar 

  92. *Lowe PA, Reynolds CR (2006) Examination of the psychometric properties of the adult manifest anxiety scale-elderly version scores. Educ Psychol Meas 66:93–115. https://doi.org/10.1177/0013164405278563

    Article  Google Scholar 

  93. *Macdonald JL, Levy SR (2016) Ageism in the workplace: the role of psychosocial factors in predicting job satisfaction, commitment, and engagement. J Soc Issues 72:169–190. https://doi.org/10.1111/josi.12161

    Article  Google Scholar 

  94. *Macia E, Lahmam A, Baali A, Boëtsch G, Chapuis-Lucciani N (2009) Perception of age stereotypes and self-perception of aging: a comparison of French and Moroccan populations. J Cross Cult Gerontol 24:391. https://doi.org/10.1007/s10823-009-9103-0

    Article  Google Scholar 

  95. Martens A, Goldenberg JL, Greenberg J (2005) A terror management perspective on ageism. J Soc Issues 61:223–239. https://doi.org/10.1111/j.1540-4560.2005.00403.x

    Article  Google Scholar 

  96. Mazerolle M, Régner I, Morisset P, Rigalleau F, Huguet P (2012) Stereotype threat strengthens automatic recall and undermines controlled processes in older adults. Psychol Sci 23:723–727. https://doi.org/10.1177/0956797612437607

    Article  Google Scholar 

  97. *Mendoza-Núñez VM, Sarmiento-Salmorán E, Marín-Cortés R, Martínez-Maldonado MDlL, Ruiz-Ramos M (2018) Influence of the self-perception of old age on the effect of a healthy aging program. J Clin Med 7:106. https://doi.org/10.3390/jcm7050106

    Article  Google Scholar 

  98. †Miche M, Elsässer VC, Schilling OK, Wahl H-W (2014) Attitude toward own aging in midlife and early old age over a 12-year period: examination of measurement equivalence and developmental trajectories. Psychol Aging 29:588–600. https://doi.org/10.1037/a0037259

    Article  Google Scholar 

  99. Miche M, Wahl H-W, Diehl M, Oswald F, Kaspar R, Kolb M (2014) Natural occurrence of subjective aging experiences in community-dwelling older adults. J Gerontol B Psychol Sci Soc Sci 69:174–187. https://doi.org/10.1093/geronb/gbs164

    Article  Google Scholar 

  100. Miche M, Brothers A, Diehl M, Wahl H-W (2015) The role of subjective aging within the changing ecologies of aging: perspectives for research and practice. Annu Rev Gerontol Geriatr 35:211–245. https://doi.org/10.1891/0198-8794.35.211

    Article  Google Scholar 

  101. *Mock SE, Eibach RP (2011) Aging attitudes moderate the effect of subjective age on psychological well-being: evidence from a 10-year longitudinal study. Psychol Aging 26:979–986. https://doi.org/10.1037/a0023877

    Article  Google Scholar 

  102. *Montepare JM (1996a) An assessment of adults’ perceptions of their psychological, physical, and social ages. J Clin Geropsychol 2:117–128

    Google Scholar 

  103. *Montepare JM (1996b) Variations in adults’ subjective ages in relation to birthday nearness, age awareness, and attitudes toward aging. J Adult Dev 3:193–203. https://doi.org/10.1007/bf02281963

    Article  Google Scholar 

  104. Montepare JM, Kempler D, McLaughlin-Volpe T (2014) The voice of wisdom: new insights on social impressions of aging voices. J Lang Soc Psychol 33:241–259. https://doi.org/10.1177/0261927X13519080

    Article  Google Scholar 

  105. Ng R, Allore HG, Trentalange M, Monin JK, Levy BR (2015) Increasing negativity of age stereotypes across 200 years: evidence from a database of 400 million words. PLoS ONE 10:e0117086. https://doi.org/10.1371/journal.pone.0117086

    Article  Google Scholar 

  106. *Ng R, Allore HG, Monin JK, Levy BR (2016) Retirement as meaningful: positive retirement stereotypes associated with longevity. J Soc Issues 72:69–85. https://doi.org/10.1111/josi.12156

    Article  Google Scholar 

  107. *North MS, Fiske ST (2013) A prescriptive intergenerational-tension ageism scale: succession, identity, and consumption (SIC). Psychol Assess 25:706–713. https://doi.org/10.1037/a0032367

    Article  Google Scholar 

  108. *Oberleder M (1962) An attitude scale to determine adjustment in institutions for the aged. J Chronic Dis 15:915–923. https://doi.org/10.1016/0021-9681(62)90060-7

    Article  Google Scholar 

  109. *Palmore E (1977) Facts on aging: a short quiz. Gerontologist 17:315–320. https://doi.org/10.1093/geront/17.4.315

    Article  Google Scholar 

  110. †Palmore E (1981) More on Palmore’s facts on aging quiz. Gerontologist 21:115–116. https://doi.org/10.1093/geront/21.2.115

    Article  Google Scholar 

  111. Palmore EB (1988) The facts of aging quiz: a handbook of uses and results. Springer, New York

    Google Scholar 

  112. *Palmore E (2001) The ageism survey: first findings. Gerontologist 41:572–575. https://doi.org/10.1093/geront/41.5.572

    Article  Google Scholar 

  113. Palumbo R, Adams RB, Hess U, Kleck RE, Zebrowitz L (2017) Age and gender differences in facial attractiveness, but not emotion resemblance, contribute to age and gender stereotypes. Front Psychol 8:1704. https://doi.org/10.3389/fpsyg.2017.01704

    Article  Google Scholar 

  114. *Parnell V, Worthington M, Nursing R, Bender M (2001) My body is ugly because it is old: ageism and its internalization. PSIGE Newsl 74:12–18

    Google Scholar 

  115. *Pinquart M (2002) Good news about the effects of bad old-age stereotypes. Exp Aging Res 28:317–336. https://doi.org/10.1080/03610730290080353

    Article  Google Scholar 

  116. *Polizzi KG (2003) Assessing attitudes toward the elderly: Polizzi’s refined version of the aging semantic differential. Educ Gerontol 29:197–216. https://doi.org/10.1080/713844306

    Article  Google Scholar 

  117. *Reuben DB, Lee M, Davis JW Jr, Eslami MS, Osterweil DG, Melchiore S, Weintraub NT (1998) Development and validation of a geriatrics attitudes scale for primary care residents. J Am Geriatr Soc 46:1425–1430. https://doi.org/10.1111/j.1532-5415.1998.tb06012.x

    Article  Google Scholar 

  118. *Rich PE, Myrick RD, Campbell C (1983) Changing children’s perceptions of the elderly. Educ Gerontol 9:483–491. https://doi.org/10.1080/0380127830090512

    Article  Google Scholar 

  119. Riegel KF, Riegel RM (1960) A study on changes of attitudes and interests during later years of life. Vita Humana 3:177–206. https://doi.org/10.1159/000269403

    Article  Google Scholar 

  120. *Rittenour CE, Cohen EL (2016) Viewing our aged selves: age progression simulations increase young adults’ aging anxiety and negative stereotypes of older adults. Int J Aging Hum Dev 82:271–289. https://doi.org/10.1177/0091415016641690

    Article  Google Scholar 

  121. *Rosencranz HA, McNevin TE (1969) A factor analysis of attitudes toward the aged. Gerontologist 9:55–59. https://doi.org/10.1093/geront/9.1.55

    Article  Google Scholar 

  122. *Rothermund K, Brandtstädter J (2003) Age stereotypes and self-views in later life: evaluating rival assumptions. Int J Behav Dev 27:549–554. https://doi.org/10.1080/01650250344000208

    Article  Google Scholar 

  123. †Rupp DE, Vodanovich SJ, Crede M (2005) The multidimensional nature of ageism: construct validity and group differences. J Soc Psychol 145:335–362. https://doi.org/10.3200/socp.145.3.335-362

    Article  Google Scholar 

  124. *Rust TB, Kwong See ST (2010) Beliefs about aging and Alzheimer’s disease in three domains. Can J Aging 29:567–575. https://doi.org/10.1017/S0714980810000590

    Article  Google Scholar 

  125. *Sanders GF, Montgomery JE, Pittman JF, Balkwell C (1984) Youth’s attitudes toward the elderly. J Appl Gerontol 3:59–70. https://doi.org/10.1177/073346488400300107

    Article  Google Scholar 

  126. *Sarkisian CA, Hays RD, Berry S, Mangione CM (2002) Development, reliability, and validity of the expectations regarding aging (ERA-38) survey. Gerontologist 42:534–542. https://doi.org/10.1093/geront/42.4.534

    Article  Google Scholar 

  127. †Sarkisian CA, Steers WN, Hays RD, Mangione CM (2005) Development of the 12-item expectations regarding aging survey. Gerontologist 45:240–248. https://doi.org/10.1093/geront/45.2.240

    Article  Google Scholar 

  128. Schooler KK (1970) Effect of environment on morale. Gerontologist 10:194–197. https://doi.org/10.1093/geront/10.3_part_1.194

    Article  Google Scholar 

  129. Schroyen S, Missotten P, Jerusalem G, Gilles C, Adam S (2016) Ageism and caring attitudes among nurses in oncology. Int Psychogeriatr 28:749–757. https://doi.org/10.1017/S1041610215001970

    Article  Google Scholar 

  130. †Sexton E, King-Kallimanis BL, Morgan K, McGee H (2014) Development of the Brief Ageing Perceptions Questionnaire (B-APQ): a confirmatory factor analysis approach to item reduction. BMC Geriatr 14:44. https://doi.org/10.1186/1471-2318-14-44

    Article  Google Scholar 

  131. *Sindi S, Juster RP, Wan N, Nair NPV, Ying Kin N, Lupien SJ (2012) Depressive symptoms, cortisol, and cognition during human aging: the role of negative aging perceptions. Stress 15:130–137. https://doi.org/10.3109/10253890.2011.599047

    Article  Google Scholar 

  132. Spuling SM, Klusmann V, Bowen CE, Kornadt AE, Kessler E-M (2019) The uniqueness of subjective ageing: convergent and discriminant validity. Eur J Ageing. https://doi.org/10.1007/s10433-019-00529-7

    Article  Google Scholar 

  133. Staudinger UM (2015) Images of aging: outside and inside perspectives. Annu Rev Gerontol Geriatr 35:187–209. https://doi.org/10.1891/0198-8794.35.187

    Article  Google Scholar 

  134. *Steverink N, Westerhof GJ, Bode C, Dittmann-Kohli F (2001) The personal experience of aging, individual resources, and subjective well-being. J Gerontol B Psychol Sci Soc Sci 56:364–373. https://doi.org/10.1093/geronb/56.6.p364

    Article  Google Scholar 

  135. *Stremmel AJ, Travis SS, Kelly-Harrison P (1996) Development of the intergenerational exchanges attitude scale. Educ Gerontol 22:317–328. https://doi.org/10.1080/0360127960220402

    Article  Google Scholar 

  136. *Sun JK, Smith J (2017) Self-perceptions of aging and perceived barriers to care: reasons for health care delay. Gerontologist 57:216–226. https://doi.org/10.1093/geront/gnx014

    Article  Google Scholar 

  137. †Thiel A, Gomolinsky U, Huy C (2009) Altersstereotype und Sportaktivität in der Generation 50 + [Stereotypes of ageing and exercise in the over-50 s]. Z Gerontol Geriatr 42:145–154. https://doi.org/10.1007/s00391-008-0556-5

    Article  Google Scholar 

  138. *Thompson AE, O’Sullivan LF, Byers ES, Shaughnessy K (2014) Young adults’ implicit and explicit attitudes towards the sexuality of older adults. Can J Aging 33:259–270. https://doi.org/10.1017/S0714980814000208

    Article  Google Scholar 

  139. *Tuckman J, Lorge I (1953) Attitudes toward old people. J Soc Psychol 37:249–260

    Google Scholar 

  140. *Van Dalen HP, Henkens K, Schippers J (2010) Productivity of older workers: perceptions of employers and employees. Popul Dev Rev 36:309–330. https://doi.org/10.1111/j.1728-4457.2010.00331.x

    Article  Google Scholar 

  141. *Vauclair C-M, Abrams D, Bratt C (2010) Measuring attitudes to age in Britain: reliability and validity of the indicators. Department for Work and Pensions Working Paper No 90. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/214388/WP90.pdf. Last Access 6 Nov 2019

  142. Voss P, Kornadt AE, Hess TM, Fung HH, Rothermund K (2018) A world of difference? Domain-specific views on aging in China, the US, and Germany. Psychol Aging 33:595–606. https://doi.org/10.1037/pag0000237

    Article  Google Scholar 

  143. *Wagner LS, Luger TM (2017) Assessing positive attitudes toward older and younger adults. Educ Gerontol 43:147–165. https://doi.org/10.1080/03601277.2016.1272890

    Article  Google Scholar 

  144. Wehr T, Buchwald F (2007) Subjektive Vorstellungen über ältere Menschen und das Altern [Subjective concepts about older people and ageing]. Z Sozialpsychologie 38:163–177. https://doi.org/10.1024/0044-3514.38.3.163

    Article  Google Scholar 

  145. *Weiss D (2018) On the inevitability of aging: essentialist beliefs moderate the impact of negative age stereotypes on older adults’ memory performance and physiological reactivity. J Gerontol B Psychol Sci Soc Sci 73:925–933. https://doi.org/10.1093/geronb/gbw087

    Article  Google Scholar 

  146. *Weiss D, Lang FR (2012) “They” are old but “I” feel younger: age-group dissociation as a self-protective strategy in old age. Psychol Aging 27:153–163. https://doi.org/10.1037/a0024887

    Article  Google Scholar 

  147. Westerhof GJ, Wurm S (2018) Subjective aging and health. In: Knight BG, Wahl HW (eds) Oxford research encyclopedia of psychology. Oxford University Press, Oxford. https://doi.org/10.1093/acrefore/9780190236557.013.4

    Chapter  Google Scholar 

  148. Wolff JK, Warner LM, Ziegelmann JP, Wurm S (2014) What do targeting positive views on ageing add to a physical activity intervention in older adults? Results from a randomised controlled trial. Psychol Health 29:915–932. https://doi.org/10.1080/08870446.2014.896464

    Article  Google Scholar 

  149. Wurm S, Tesch-Römer C, Tomasik MJ (2007) Longitudinal finding aging-related cognitions, control beliefs, and health in later life. J Gerontol B Psychol Sci Soc Sci 62:156–164. https://doi.org/10.1093/geronb/62.3.P156

    Article  Google Scholar 

  150. Wurm S, Diehl M, Kornadt AE, Westerhof GJ, Wahl H-W (2017) How do views on aging affect health outcomes in adulthood and late life? Explanations for an established connection. Dev Rev 46:27–43. https://doi.org/10.1016/j.dr.2017.08.002

    Article  Google Scholar 

  151. Wurm S, Wiest M, Wolff JK, Beyer A-K, Spuling SM (2019) Changes in views on aging in later adulthood: the role of cardiovascular events. Eur J Ageing. https://doi.org/10.1007/s10433-019-00547-5

    Article  Google Scholar 

  152. Wurtele SK (2009) “Activities of older adults” survey: tapping into student views of the elderly. Educ Gerontol 35:1026–1031. https://doi.org/10.1080/03601270902973557

    Article  Google Scholar 

  153. *Yilmaz DV, Terzioglu F (2011) Development and psychometric evaluation of ageism attitude scale among the university students. Turk Geriatri Dergisi 14:259–268

    Google Scholar 

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Acknowledgements

Open Access funding provided by Projekt DEAL. This work is a result of the Scientific Research Network “Images of Aging: Via a dynamic life span model to new perspectives for research and practice”, funded by the German Research Foundation (KL 3072/1-1) awarded to V.K.. The authors thank all members and guests of the network for their valuable support and the discussions.

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Klusmann, V., Notthoff, N., Beyer, AK. et al. The assessment of views on ageing: a review of self-report measures and innovative extensions. Eur J Ageing 17, 403–433 (2020). https://doi.org/10.1007/s10433-020-00556-9

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Keywords

  • Views on ageing
  • Age stereotypes
  • Subjective ageing
  • Self-perceptions of ageing
  • Assessment
  • Review