Socialinė teorija, empirija, politika ir praktika ISSN 1648-2425 eISSN 2345-0266
2025, vol. 30, pp. 99–116 DOI: https://doi.org/10.15388/STEPP.2025.30.6

Changing Perceived Life Control: Intergenerational Insights from Lithuania

Aida Savicka
Lithuanian Culture Research Institute
Department of Contemporary Lithuanian Culture, Vilnius
E-mail: aida.savicka@gmail.com
ORCID: https://orcid.org/0000-0002-4290-1005

Abstract. A substantial body of research underscores that greater perceived control over one’s life not only enhances the individual quality of life but also, at an aggregate level, fosters economic efficiency, social inclusion, and civic participation. Perceived control also plays a crucial role in enhancing resilience during crises. At the individual level, it helps to develop more effective coping mechanisms and mitigate psychological distress, engage in more proactive problem-solving strategies and maintain better health outcomes. At the societal level, it strengthens community cohesion that enhances mutual support, collaborative problem-solving and more coordinated crisis responses.

Thus, effective strategies to maintain or increase perceived control can significantly buffer against the adverse effects of crises. However, social preconditions for the formation of perceived control and its broader societal implications remain insufficiently explored. This study examines the dynamics of perceived control in Lithuanian society through the lens of generational replacement, by utilizing the data from the European Values Survey which has been conducted in the country for almost three decades. The findings reveal notable differences in this attitude across social generations. Yet, a multilevel Age-Period-Cohort (APC) analysis indicates that, while generational shifts contribute to an overall societal increase in perceived control, the primary driver is a profound cultural transformation that cuts across all generations.

Keywords: perceived control, social generations, age-period-cohort (APC) analysis, European Values Study.

Received: 2024 12 01. Accepted: 2025 06 04.
Copyright © 2025 Aida Savicka. Published by Vilnius University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Introduction

Perceived life control1 is a person’s subjective belief that he or she has the ability to control or significantly influence the circumstances and events that affect one’s life and to achieve the desired outcomes (Grob and Flammer, 1999). Perceived control over one’s own life (henceforth perceived control) was initially attributed by early researchers to dispositional personality traits, given its relative stability across time and various life domains (Phares, 1976). Over time, however, it has increasingly been conceptualized as a cognitive attitude that can be modified. While the objective possibilities for control are determined by the resources, abilities, and means available to influence one’s life events, perceived control is not reducible to these factors. Instead, it reflects a subjective assessment of one’s own abilities and available resources, as well as expectations for success (Dweck, 2013). This subjective belief is shaped by prior experiences, feedback and evaluations from others, and observations of similar individuals, often referred to as ‘comparable others’ (Bandura, 1978). The development of perceived control is thus influenced by a dynamic interplay between individual psychological factors – such as cognitive style, resilience, and coping skills – and broader sociocultural influences, including cultural values, social environments, and processes of socialization (Bandura, 1997). Rooted in Julian Rotter’s concept of internal and external locus of control within the social learning theory (Phares, 1976; Rotter, 1966), perceived control has inspired a rich body of psychological research. More recently, the self-determination theory has provided a significant framework for exploring this concept, while emphasizing the roles of autonomy, competence, choice, social connectedness, and feedback – both positive and negative – in shaping motivation, self-efficacy, and perceived control in human behavior (Ryan and Deci, 2017).

Perceived control serves as a valuable resource at both individual and societal levels, playing a pivotal role in shaping human attitudes, subjective evaluations, and behavior. At an individual level, it facilitates effective coping with obstacles and stressful events by framing them as challenges to overcome rather than insurmountable threats. This perspective encourages active, consistent, flexible, and creative problem-solving strategies (Skinner and Zimmer-Gembeck, 2010; Taylor and Stanton, 2007; Weiner, 2010) and crisis resilience (Koltai and Stuckler, 2020), positively impacting mental and physical health (Infurna et al., 2011; Lachman et al., 2009; Strickland, 1978)2009; Strickland, 1978. On a societal scale, researchers have explored the interplay between socio-cultural factors – such as cultural values, religion, the social status, and political or economic systems – and individuals’ sense of control. This relationship significantly shapes societal outcomes, by fostering social empowerment, enhancing community and civic engagement (Cattan et al., 2011; Lakomý, 2021), building trust in institutions, and bolstering resistance in times of various turmoil (Bandura, 1997).

The socio-cultural dimensions of perceived control, central to this paper, underscore its profound implications for both individual well-being and societal dynamics. The aim of the present study is to analyze the dynamics of perceived control in Lithuanian society from the perspective of generational replacement2, assessing the level of perceived control in Lithuanian society and its development in the broader context of European countries and identifying the relative impact of two potential factors driving the change – the natural process of generational replacement within the population, or a gradual shift in attitudes occurring across all generationals over time.

Methodology

This paper examines perceived control by using data from the European Values Study (EVS)3, which has been conducted in Lithuania for almost three decades4. The dataset offers a unique opportunity to explore perceived control across various population groups based on individual characteristics, compare these indicators across European societies, and investigate shifts in this attitude from an intergenerational perspective. The latter task requires a complex analysis to distinguish between the effects of period, ageing and generational replacement, which is methodologically challenging. The repeated nature of the EVS data is particularly significant in this context, as only long-term data allow for an attempt to disentangle these effects by comparing the perceived control of individuals from different generations at the same age, as captured across the four waves of the EVS.

In the subsequent analysis, the following aspects will be examined: first, the long-term dynamics of perceived control within Lithuanian society; second, how the perceived control of individuals from the same generation changes as they transition from one life stage to another; third, how the perceived control differs between individuals of the same age belonging to different generations. Finally, the study will assess which factor contributes more significantly to changes in perceived control at the societal level: the intra-generational dynamics of this attitude, reflecting shifts in values among all or certain generations over time, or the natural generational replacement.

The main dependent variable in the present analysis is self-reported perceived control. Although self-reported indicators of perceived control are commonly employed in both psychological and sociological research, they are susceptible to certain biases – most notably those arising from conceptual ambiguity and divergent individual interpretations: some respondents may interpret the construct as referring primarily to internal control over personal behavior, while others may emphasize external control over environmental circumstances. To mitigate such interpretive variability, the EVS employs the following question wording in order to ensure a more precise operationalization: “Some people feel they have completely free choice and control over their lives, and other people feel that what they do has no real effect on what happens to them. Please use the scale to indicate how much freedom of choice and control you feel you have over the way your life turns out?”. This variable from the EVS data file was included in the analysis without being transformed: 1 = none at all (low perceived control), 10 = a great deal (high perceived control).

The independent variables used in the analysis include the survey wave, country, the year of birth of a respondent, age group and generation. The first three variables were directly utilized from the EVS dataset without modification, while the latter two were derived by recoding the age variable and categorizing the respondents into six distinct age groups (15–24, 25–34, 35–44, 45–54, 55–64, 65 and above) and six social generations:

● Interwar generation (born 1918–1940);

● First Soviet generation (born 1941–1959);

● Second Soviet generation (born 1960–1969);

● Last Soviet generation (born 1970–1979);

● Transition generation (born 1980–1989);

● First Independence generation (born 1990–2000).

This generational classification of the Lithuanian population has been proposed by L. Zilinskiene, M. Ilic, and their co-authors (Zilinskiene and Ilic, 2021) taking into account the specific political, economic, and social development characteristics of the country. Their classification has been extended in other studies by including the generation that has just reached adulthood (First Independence); and it has proven to be well aligned with empirical data regarding the differentiation of value orientations among various population groups in the country (Savicka, 2023; Savicka and Žiliukaitė, 2023).

It is important to acknowledge that generational differentiation is a complex task due to the lack of universally superior criteria for defining generational boundaries. In Lithuania, however, the non-evolutionary nature of historical transformations – such as wars, occupations, political regime changes, mass repression, the national revival, the restoration of independence, and EU accession, as well as cultural, economic, and technological developments – provides clear temporal markers that aid in distinguishing generations. The Interwar generation, for example, was shaped by the traumas of war, armed resistance, emigration, deportation, mass collectivization, and intense urbanization (Davoliūtė, 2014). The First Soviet generation matured under postwar scarcity, totalitarianism, and Soviet modernization. The life course of the Second Soviet generation was shaped by institutionalized upbringing and followed a rather standardized course, leading to less risk but also fewer life choices (Kraniauskienė and Damaševičiūtė, 2025). The Last Soviet generation grew up during late socialism and matured during the national revival and early societal transformation. Members of the Transitional generation, by contrast, have virtually no direct experience of the Soviet regime, growing up amid rapid economic change and normative uncertainty, yet developing stronger self-agency (Žilinskienė, 2025). Meanwhile, the First Independence generation was raised in an environment saturated with digital technologies and smart devices from early childhood, and, as a result, its members tend to identify with global generations shaped by global events and information flows. The diverse generational experiences of Lithuanians may have led to varying perceptions of life control among their members. Older generations, marked by war, repression, and totalitarianism, often faced constrained choices and limited agency, while younger generations – particularly those raised after the restoration of independence – grew up in conditions fostering greater personal autonomy and self-efficacy. Although studies on value shifts among Lithuanian generations reveal patterns similar to those observed in other Western societies, especially among the young (including growing individualism, orientation towards greater self-expression and personal agency), direct cross-cultural comparisons remain insufficient without accounting for Lithuania’s distinct historical context. Thus, the analysis that follows employs a locally grounded generational classification to better capture these unique trajectories.

The data on the dynamics of perceived control were examined through a combination of descriptive statistics, non-parametric tests using the Kruskal-Wallis (K-W) criterion, and regression modeling. The analysis was carried out using the IBM SPSS Statistics software.

Dynamics of Perceived Control in Western Societies

Cross-cultural research of perceived control offers valuable insights into how cultural, religious, social, economic, and political factors shape individuals’ sense of agency. The prevailing locus of control – whether internal or external – varies between cultures and significantly influences individual attitudes through socialization processes. In individualistic cultures, which prioritize autonomy, independence, and self-reliance, individuals tend to feel a greater sense of personal control over their lives. By contrast, in collectivistic cultures, where institutional control, social integration, contextual self-concepts, and holistic thinking are emphasized, personal control over one’s environment is less culturally valued and less commonly experienced. Instead, these cultures place a stronger focus on adapting to external conditions (Cheng et al., 2013; Morling et al., 2002; Ryan and Deci, 2017). Different studies provide mixed evidence on the long-term dynamics of perceived levels of control in Western societies. For instance, a meta-analysis of data on children and adolescents from 1960 to 2002 revealed a decline in perceived control, attributed to the profound and rapid social changes during this period (Twenge et al., 2004). Conversely, other studies have reported an increase in perceived control in Western contexts, linking this trend to a growing emphasis on autonomy and the pursuit of self-development (Gatz and Karel, 1993). These findings underscore the multifaceted nature of perceived control and its responsiveness to shifting cultural and societal values.

When examining the dynamics and differences in perceived control at the national level across Europe, EVS provides an exceptionally valuable dataset due to its broad geographic coverage and extended observation period. These data indicate that, throughout the studied period, Northern European countries consistently exhibit high levels of perceived control (based on country means), as illustrated in Figure 1. These countries are characterized by higher levels of individual autonomy, a long-standing tradition of democratic governance, and robust social welfare systems that foster a sense of personal independence. Conversely, countries from the former socialist bloc, such as Azerbaijan, Bulgaria, Latvia, Russia, Georgia, and Ukraine, report the lowest levels of perceived control. This disparity is linked to political and economic instability and the legacy of authoritarian regimes, which often emphasized collectivist indoctrination.

Over the observation period, perceived control levels increased in nearly all European countries, with the most significant positive changes occurring in Ukraine, Belarus, Bulgaria, Romania, Slovenia, and Russia – i.e., in those countries that initially reported relatively low levels. In contrast, perceived control remained relatively stable in Finland, Sweden, Slovakia, and Latvia, and decreased only in Austria. Despite a narrowing of regional differences over time, these disparities remained statistically significant. These findings align with prior research on the differences in perceived control levels between individualistic and collectivist societies, reaffirming that perceived control is not merely an individual characteristic but also a cultural attribute of society.

Figure 1. Dynamics of the level of perceived control in the European countries that participated in the corresponding waves of EVS (mean on a scale from 1 to 10)

In this context, an assessment of the perceived control levels among the Lithuanian population reveals that, in 1990, these levels were slightly higher than those observed in other post-communist countries participating in the study (with the exception of the Czech Republic and Slovakia) and were nearly equal to the average of the European countries included in the research. When examining later periods, a significant decline was recorded in 1999 (the trend was also observed in other Baltic states), followed by a fairly rapid increase in 2008 and 2017 (see Figure 2). Thus, the decline in the average perceived control level in 1999 can be considered a short-term reaction to the transitional challenges faced by the country, such as high unemployment, inflation, social norm uncertainty, and other factors. However, the long-term trend indicates a strengthening perception of control at the societal level, leading to levels in 2008 and 2017 that slightly exceeded the average for European countries participating in the corresponding waves of the EVS.

Figure 2. Dynamics of the level of perceived control in Lithuanian society in 1990–2017 (mean on a scale from 1 to 10 with 95% confidence interval)

Comparison of Social Generations

Upon reviewing the dynamics of perceived control on a societal scale, we arrive at the primary question of this study: what is the driving force behind the strengthening societal attitudes observed across the society – whether it is the strengthening of these attitudes within all generational groups or the natural generational replacement? Before proceeding to the presentation of empirical data analysis results, let us briefly discuss the key assumptions and methodological challenges in research concerning intergenerational attitude differences.

Generational studies examine the impact of the unique historical context during the formation period of different generations, as well as long-term political, social, economic, and technological changes, and parenting strategies, on individuals’ sense of responsibility, autonomy, and life circumstances control. In Western societies, it is observed that the Baby Boomers (born circa 1946–1964) developed a relatively high level of perceived control over life, shaped by their experiences of post-war economic growth, relative job security, and social stability. In contrast, Generation X (born circa 1965–1980), facing economic downturns, rising divorce rates, and an increase in dual-income households, developed more skepticism. This generation exhibits a moderate level of perceived control. Generation Y (born circa 1981–1996), growing up amidst the digital revolution and economic instability, demonstrates weaker perceived control, despite the new opportunities presented by technological advances. Meanwhile, Generation Z (born circa 1997–2012), increasingly immersed in social life and growing up amidst rapidly changing technologies, is concerned about climate change and more attuned to global issues such as inequality and social justice. Current research on this generation suggests that, while it is still in its early stages, it is likely that Generation Z possesses a weaker sense of control over broad societal issues (e.g., climate change, political instability). However, its members feel more in control of their personal expression and choices in personal and professional life (Howe and Strauss, 2007; Inglehart and Welzel, 2005; McCrindle, 2018; Scholz, 2019; Twenge et al., 2012). In this context, the data from an international study conducted in 1992–1993, which involved both Eastern European countries (Bulgaria, Czech Republic, Poland, Romania, Russia, Transylvania, Hungary) and Western countries (USA, Norway, France, Finland, Switzerland, Germany), are particularly interesting. The study showed that while lower well-being indicators were observed among adolescents (aged 14–20) in Eastern European countries, they exhibited a stronger sense of perceived control. This can be explained by the social comparison effect: in societies transitioning to democratic systems, young people feel they have more control over their lives compared to the older generations who lived under authoritarian regimes in their countries (Grob, 2000).

As for the methodological challenges in cross-generational value research, one must address the issue of identifying the effects of age, period, and cohort on the value orientations of individuals from different social generations. The age effect is caused by both the physiological changes that occur with ageing and social role changes associated with these life stages; thus, it arises from both biological and social processes characteristic of the human life course. The generational effect is related to the natural change of generations shaped by distinct socialization experiences (Mannheim, 1952). Meanwhile, the period effect stems from the response to historical events or environmental phenomena and processes that affect all generations simultaneously. These three factors influencing people’s value orientations are closely interrelated, and, as a result, their effects are often combined rather than additive. In empirical studies, insufficient attention is often paid to the complexity of the interrelationship between these effects, which may lead to unwarranted conclusions.

The so-called Age-Period-Cohort (APC) analysis deals with an unsolvable problem due to the linear dependency between age, period, and cohort effects, often referred to as the identification problem5. After decades of attempts to resolve this issue, it is increasingly acknowledged that, at least for now, there is no solution to the identification problem that does not require deep prior knowledge of at least one of the evaluated APC effects (Bell, 2020). Therefore, it is always recommended to conduct APC analysis alongside a comprehensive descriptive data analysis, which provides a general understanding of the impact of age, period, and cohort on values, primarily by assessing the effect of different pairs of factors (Yang and Land, 2016). Therefore, in order to address the identification problem and analyze the effects of age, period, and generation on perceived control, this paper first examines the influence of the period paired with age and with generation. It then compares the levels of perceived control across generations at the same age to explore the age–generation relationship, using visual analysis and mean comparisons. Next, a regression model estimates changes in perceived control as a function of the survey year and the birth year to evaluate whether generational replacement or intragenerational change drives variation more strongly. The model’s coefficients (𝐵) represent the expected change in perceived control per unit change in each variable, holding the other constant. To compare the impact of each process, 𝐵 is multiplied by the range over which the process operates: for generational replacement, the difference in mean birth years; for intragenerational change, the difference in survey years. While this enables comparison of the two rates, it does not clarify whether intragenerational change stems from aging or broader societal shifts – which is an issue addressed by earlier parts of the analysis. Such step-by-step analysis allows for an examination of the driving forces behind the observed value changes in society: if the rate of value changes across generations largely matches the overall pace of societal change, one can talk about a cultural transition for the entire society. However, if no or very slow value changes are observed in older generations compared to the general societal change, it can be inferred that the overall change is driven by a generational replacement. In real life, changes are usually driven by both of these causes, and studies typically aim to assess their relative significance. Although the desire to precisely separate these effects is practically unachievable, certain insights can be gained if statistical analysis is based on clearly formulated theoretical assumptions and the results of previous studies on the interrelationship of the analyzed factors from different perspectives.

Figure 3. Perceived control in different age groups 1990–2017 (mean on a scale of 1 to 10)

Considering the outlined methodological limitations and their proposed solutions, let us first examine the interaction effects of different factor pairs – the period and age, the period and social generations, as well as social generations and age – on the perceived control of Lithuanians. The analysis of the interaction between the period and age reveals long-term trends in the level of perceived control across different age groups: in all age groups, a decrease in perceived control is evident in 1999, followed by a significant increase in later EVS waves. The only exception to this trend is the oldest age group, where the level of perceived control slightly decreased in 2017 (see Figure 3). It is likely that this weakening of perceived control in the oldest age group is at least partly related to difficulties in adapting to rapid technological changes, which, particularly in recent years, have permeated all areas of life (including public services) and altered the traditional ways of functioning in the public sphere. However, verifying this hypothesis would require a more detailed study.

A similar analysis of the influence of the period and social generation interaction on people’s attitudes makes it possible to identify periods that affect the attitudes of all generations in the same way, as well as periods that affect them differently. Here, again, we can see the effect of 1999 and the drop in the level of perceived control of the oldest – Interwar – generation in 2017 (see Figure 4). It is important to note that, although the trends and conclusions depicted in Figures 3 and 4 seem very similar, they present different information: in the first case, respondents of the same age who participated in different EVS waves represented different generations; whereas, in the second case, representatives of the respective generations participating in different EVS waves were at different stages of their life course. Therefore, in both cases, some important information remains unrepresented.

Figure 4. Perceived control across generations 1990–2017 (mean on a scale of 1 to 10)

As discussed, in research on changes in value orientations, it is essential to consider not only the period effect but also the influence of age. This involves evaluating whether the importance of different value attitudes remains relatively stable throughout a person’s life, shaped by their socialization experiences, or whether a universal trend emerges in the course of life. Data from previous studies on changes in perceived control with age are ambiguous: some longitudinal studies indicate that perceived control remains relatively stable across life (Gatz and Karel, 1993); others suggest an increase in perceived control up to ages 30–40, followed by a decline and a subsequent rise after approximately 60 years (Specht et al., 2013). Other studies indicate a trajectory dynamic where perceived control strengthens as individuals transition into adulthood, peaks in middle age, and then declines, which is linked to differences in actual competencies, opportunities for control, and the likelihood of control-limiting situations across different age cohorts (Lachman et al., 2009; Mirowsky and Ross, 2007), as well as age-related stereotypes (Levy, 2003). The discrepancies in findings across different studies on the dynamics of perceived control at various life stages may be partly due to the different life domains associated with control that are the focus of the research (Brandtstädter and Rothermund, 1994).

The analysis of EVS data reveals a fairly consistent pattern of differences in perceived control levels across age groups, similar in all four study waves: older individuals tend to exhibit lower levels of perceived control compared to younger individuals (see Figure 5). Notably, the oldest age group (65 years and older) stands out: in 1990, 1999, and 2008, perceived control in this group was slightly higher than in the 55–64 age group. However, in 2017, among those reaching retirement age, significantly lower levels of perceived control were recorded compared to the 55–64 age group, which may be related to the previously mentioned difficulties in adapting to the rapidly changing and increasingly digitalized social environment.

Figure 5. Perceived control in different age groups 1990–2017 (mean on a scale of 1 to 10)

After conducting a comprehensive analysis of the interaction between the life stage and social cohort effects on perceived control, it is necessary to assess whether the variations in the attitude are more significantly influenced by the effects of age or generations. This is done by comparing perceived control across individuals from different generations at the same age. Regarding the variation in perceived control within cohorts, different trajectories are observed as individuals move from one life stage to another. In the youngest generations, the attitude consistently strengthens, while, in the Second Soviet and Interwar generations, it weakens and then strengthens again over the course of life (the 1999 effect is clearly visible here). In the First Soviet Generation, however, the attitude fluctuates in a statistically insignificant manner (see Figure 6). When evaluating the attitudes of individuals from different cohorts at the same age, a general trend is observed across all age groups: each subsequent generation shows a stronger perception of control (some inconsistencies can again be explained by the 1999 effect), and these differences are statistically significant (see Table 1). It may seem that separating the effects of age and generation leads to slightly different conclusions compared to comparing the attitudes of people of different ages during specific periods: here, no decline in attitude levels is observed in the oldest age group within any generation, but this is because, in the earlier analysis, the decline was specific to the attitudes recorded in 2017. In this case, the perceived control of the oldest age group includes data from not only the final EVS wave (for example, regarding the Interwar generation, some of its representatives reached the age of 65 by the 1990 study, and Figure 6 reflects the combined rates from various EVS waves).

Figure 6. Perceived control in different social generations as they move from one age group to another in 1990–2017 (mean on a scale from 1 to 10)

An unresolved question remains regarding which change is occurring at a faster rate: that due to generational replacement or due to the shift in attitudes within individual generations? To address this, a regression model was developed to examine the relationship between perceived control and both the year of the study and the respondent’s birth year (see Table 2). The regression results indicate that both regressors have a statistically significant positive effect on perceived control. This confirms that (1) over time, this attitude strengthens when controlling for the respondents’ birth years, and that (2) individuals born later tend to exhibit stronger perceived control, regardless of the year in which the study was conducted.

Table 1. Perceived control of different generations in different age groups 1990–2017 (mean on a scale of 1 to 10)

Generation	Age group						K-W test results for each generation
	18–24	25–34	35–44	45–54	55–64	≥65
Interwar	-	-	-	6.42	5.94	6.52	p = 0.021, H(2) = 7.768
First Soviet	-	6.72	6.73	6.51	6.77	6.76	p = 0.658, H(4) = 2.424
Second Soviet	7.20	6.68	6.63	7.10	7.38	-	p = 0.001, H(4) = 18.625
Last Soviet	6.94	6.97	7.46	7.73	-	-	p = 0.000, H(3) = 18.481
Transition	7.16	7.34	8.01	-	-	-	p = 0.013, H(2) = 8.728
First Independence	7.58	7.74	-	-	-	-	p = 0.475, H(1) = 0.510
K-W test results for each age group	p = 0.019, H(3) = 9.986	p = 0.000, H(4) = 21.479	p = 0.000, H(3) = 40.165	p = 0.000, H(3) = 33.491	p = 0.000, H(2) = 30.469	p = 0.213, H(1) = 1.551

Table 2. Multilevel regression of perceived control on study year and respondents’ birth year

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	-63.785	6.275		-10.165	.000
	Study year	.019	.003	.087	5.707	.000
	Year of birth	.017	.002	.140	9.133	.000

The unstandardized 𝐵 coefficients in the regression model indicate the expected change in the dependent variable for a one-unit increase in the corresponding independent variable, while holding other model variables constant. Therefore, in order to assess the relative pace of change in both processes, it is necessary to multiply the unstandardized effect coefficient 𝐵 by the corresponding process’s operational range for each process. To evaluate the impact of generational replacement, we multiply the calculated difference in the respondents’ average birth years between the first and the last waves of the study (18.67) by the unstandardized coefficient estimate for the birth year variable in the regression model (0.017), resulting in a product of 0.32. Similarly, to evaluate the impact of within-generational change, we multiply the difference between the last and the first wave of the study years (27) by the unstandardized coefficient estimate for the study year variable (0.019), yielding a product of 0.516. These results suggest that, although significant change in perceived control occurs due to generational replacement, the relatively faster (1.6 times) strengthening of perceived control at the societal level over the 27-year period is driven by the internal increase in perceived control within generations. However, these data alone do not answer the question of whether the within-generational change in the attitude is taking place due to the ageing of its members or the gradual effect of a widespread cultural transformation syndrome affecting society as a whole. Nonetheless, given previous data indicating that, across all four EVS waves, the Lithuanian society exhibited a weakening of perceived control with age (see Figure 5), it can be argued that the strengthening of perceived control within generations is occurring in spite of the ageing effect. This suggests that perceived control is increasing due to a deeper cultural shift across generations.

Conclusions

Perceived control constitutes a vital societal resource, closely associated with key phenomena such as subjective well-being, trust in state institutions, political and civic engagement, crisis resilience, and the internalization of personal responsibility – which are factors integral to the development of civil society and the consolidation of the welfare state. In this context, the present study’s findings – indicating a positive long-term trajectory in perceived control across Lithuanian society – are notably promising. According to this measure, Lithuania has consistently equaled or outperformed the average levels observed in the participating countries of the corresponding EVS wave, positioning itself as a leader among former socialist states. Although all Lithuanian generations exhibit a comparable long-term trajectory of increasing perceived control, distinct generational differences are evident, with successive generations reporting progressively higher levels of perceived control. These results align with research conducted in other Western contexts, indicating that the political, social, economic, technological, and cultural conditions prevailing during formative periods play a critical role in shaping individuals’ perceptions of control over significant life events. Importantly, the data suggest that the societal shift is driven less by generational replacement and more by the amplification of this attitude within each generation over time. These empirical findings, which reveal generational differences in perceived control and underscore a broader cultural transformation as the primary catalyst for its increase, entail several important implications.

From the perspective of societal resilience to crises, these developments are promising, as they indicate a faster pace of change in perceived control driven by cultural dynamics rather than generational replacement alone. The broader cultural shift reflects a reframing of autonomy, self-efficacy, and responsibility as normative ideals. This is especially crucial amid contemporary conditions of uncertainty, such as economic volatility, climate crises, and geopolitical instability. A society where individuals across generations increasingly believe they can influence their life circumstances is better positioned to collectively respond to crises. Still, in confronting contemporary societal challenges, the continuous cultivation of individual and collective agency emerges as a critical measure for resilience and adaptive response. The findings are also positive in this respect, as intragenerational growth confirms that perceived control is not a fixed trait, but rather that it can increase over the course of an individual’s life under favorable conditions. Theoretical and empirical research emphasizes the importance of creating enabling infrastructures and relational contexts that empower individuals to view themselves as active contributors to societal processes (Bandura, 2023). Effective empowerment strategies can substantively modulate individuals’ perceived sense of control and efficacy (Perkins and Zimmerman, 1995). This can be achieved by multifaceted approaches, including participatory educational frameworks (Skinner et al., 1998), institutional designs that support inclusive decision-making, and community-based initiatives aimed at fostering strong and cohesive social identities (Greenaway et al., 2015). In social work, interventions can be tailored to enhance personal agency in groups with lower perceived control (e.g., elderly, marginalized social groups, migrants, long-term unemployed), by using approaches that promote self-directed goal-setting and participatory decision-making. Such interventions not only strengthen psychological resilience in the face of adversity but also enhance the overall well-being. Therefore, enhancing perceived control should become a key objective of both individual and collective efforts aimed at improving the quality of personal and societal life, as well as strengthening preparedness for crisis situations.

The present study also advances the general understanding of societal change mechanisms by comparing the relative pace of value attitude shifts driven by intragenerational change and generational replacement. In assessing its constraints, it is crucial to give due consideration to the conceptual underpinnings of intergenerational categorization. Defining distinct generational cohorts inherently assumes internal uniformity and sharply defined boundaries between groups. These assumptions risk obscuring the nuanced, often continuous dynamics of social and cultural change, as well as the overlapping life experiences that cut across generational divides – which are factors that must be carefully considered when interpreting the results. Furthermore, the study primarily concentrates on intergenerational differences in perceived control, approached through the prism of value orientations shaped by formative socio-historical contexts. While this cultural-experiential perspective provides important insights into the role of collective memory and socialization processes, it does not account for structural and socio-economic variables – such as levels of education, employment trajectories, and class positions – that also contribute significantly to differences in perceived control across generations. The exclusion of these dimensions represents a deliberate analytical focus rather than a conceptual oversight. Despite these limitations, the study remains valuable for its contribution to understanding how value orientations mediate intergenerational differences in perceived control. By foregrounding the role of historically situated experiences in shaping generational worldviews, the research offers a culturally grounded perspective that complements and can inform future structural analyses. This approach enables a more comprehensive conceptualization of intergenerational change, emphasizing that generational membership is not solely a demographic marker but is also a culturally constructed and historically contingent phenomenon.

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1. 1 Perceived life control is often considered synonymous with locus of control or fatalism, although it is a slightly broader concept. People have a sense of perceived control when they believe that most events that are important to them are caused by their personal actions (called internal locus of control) and that they have the skills to perform the actions necessary to achieve their goals (called self-efficacy). Perceived control is considered as one aspect of life control, along with closely related attitudes such as self-confidence, self-esteem, perceived competence and causal linking (Abeles, 1991; Judge et al., 2002; Skinner and Zimmer-Gembeck, 2010).

2. 2 Henceforth, the term generation will be understood in the context of a social generation, as articulated within the Mannheimian tradition. This refers to a cohort of individuals born within a specific time frame, united by shared experiences of significant events, a collective historical memory, and a generational self-concept shaped by these factors, while also navigating unique opportunities and constraints arising from their social conditions.

3. 3 More information on the study is available at https://europeanvaluesstudy.eu/. The data file used in the study presented in this paper is publicly available in the GESIS data archive: EVS (2022). EVS Trend File 1981–2017. GESIS, Cologne. ZA7503 Data file Version 3.0.0, https://doi.org/10.4232/1.14021

4. 4 The representative EVS surveys in Lithuania were carried out in 1990 (EVS2), 1999 (EVS3), 2008 (EVS4) and 2017 (EVS5), with 1,000, 1,018, 1,500 and 1,448 respondents respectively.

5. 5 The identification problem in APC analysis stems from the fact that any of these independent variables can be accurately estimated by knowing the other two: Age = Period - Cohort. This linear dependence makes it impossible to mathematically separate the effects of age, period and cohort without certain restrictions or assumptions.

6. 6 For a detailed account of this APC analysis, see the exposition provided by Abigail-Kate Reid and Nick Allum (Reid and Allum, 2019).