Selected Attributes of Human Resources Diversity Predicting Locus of Control from a Management Perspective

Abstract

Locus of control refers to the way in which people perceive whether they have control over situations in their lives or whether these situations are the result of external circumstances. Locus of control subsequently influences individuals’ motivation, decision-making, and ability to accept responsibility. How locus of control manifests itself in the behavior of a particular individual can be influenced by several factors. In this article, we focused on how elements of different dimensions of human resource diversity can influence locus of control. For the research, we chose a quantitative approach using a questionnaire measuring the locus of control, along with additional questions. The main aim of the presented research was to identify the relationship between sociodemographic variables and the locus of control orientation of individual groups of respondents. The research sample consisted of N = 384 participants who completed the reduced standardized Rotter locus of control scale. The results focused on differences in individuals’ locus of control in terms of age, gender, type of work experience, and marital status and to what extent these sociodemographic variables can be a predictor of individuals’ locus of control. Hypotheses testing was performed using IBM SPSS 23 software. Th theoretical application of the research findings lies in the discovery that the locus of control (LoC) is not influenced by simple characteristics but must be understood in a more complex way. The practical application lies in the fact that professional experience can influence how employees perceive their level of control over their ability to affect their work and outcomes.

1. Introduction

The locus of control (LoC) is a concept that expresses the extent to which individuals attribute the results of their behavior to their own actions, i.e., they perceive an internal locus of control, or to external circumstances, thus preferring an external locus of control. It represents an important framework for understanding whether people attribute responsibility to their successes and failures to their own abilities and decisions or to external circumstances, such as chance, luck, or the interventions of other people. The study of LoC has significant applications in various fields, especially psychological research. Its structure and functioning are related to the ways in which individuals respond to stress, plan their goals, cope with difficult situations, and regulate their behavior. LoC is thus an important factor in shaping life attitudes, motivation, and decision-making strategies. At the same time, it influences cognitive and emotional processes that shape the everyday perception of situations and adaptation to changing conditions. In the context of increasing uncertainty and workplace demands, understanding LoC is becoming particularly relevant for organizations, as it relates to motivation, decision-making, adaptability, and performance.

Despite the extensive research on LoC in clinical and educational settings, its role in work-related contexts and its connection to demographic and experiential variables remains insufficiently explored. The theoretical and empirical significance LoC also lies in its ability to mediate relationships between personality traits and behavior. Individuals with a predominant internal locus of control more often perceive their behavior as effective and meaningful, while individuals with an external locus of control may feel powerless over external circumstances. These differences have an impact on various life domains, from lifestyle and health to work performance and stress management. From a methodological point of view, LoC research is also important for its applicability in different population groups and cultural contexts and in conditions of changing social challenges. Its importance is growing especially in a period of increased demands for independence, flexibility, and the ability to navigate in uncertain situations. Based on the above, LoC represents not only a certain personality characteristic, but also a dynamic framework for understanding individual differences in approaches to the world, responsibility, and personal development. This study addresses this gap by examining the relationship between selected demographic variables and LoC within a working population. By doing so, it aims to contribute to the understanding of how life circumstances and job roles influence one’s sense of control. The originality of this study lies in its integration of individual and situational variables in the context of organizational behavior.

2. Theoretical Background

Locus of control (LoC) is a key psychological construct that reflects an individual’s belief in the degree of personal control over life situations. A distinction is made between internal and external locus of control. This construct was defined by Rotter (1966) in his work in such a way that if an individual perceives reinforcement as something that is not completely dependent on his actions, then this event is perceived as the result of luck, chance, fate, as something that is under the control of others, as something unpredictable. He refers to this as a belief in external control. If a person perceives that an event depends on his own behavior or his own relatively permanent characteristics, he refers to it as a belief in internal control. LoC can then be understood as a construct that distinguishes the extent to which an individual believes that the results of his behavior depend on his own actions (internal locus) or, conversely, on external forces (external locus). It is a person’s belief about whether he can influence the course of situations in his life (Schepisi, 2024; Lloyd & Hastings, 2009). It is a belief that outcomes in life depend either on one’s own actions or on the influence of external circumstances (Visdómine-Lozano & Luciano, 2006). This construct takes the form of a continuous spectrum, with individuals exhibiting different levels of internal or external control in different areas of life. The LoC continuum is illustrated in Figure 1.

The multidimensional nature of the locus of control construct is among the psychological constructs for which research has a tradition of more than 50 years. This construct primarily consists of two foci, namely internal control and external control (Figure 1), which are currently considered significant predictors of attitudes, behavior, and work outcomes, including motivation (Galvin et al., 2018). Originally, LoC was defined as an individual’s generalized expectation that the outcomes of their behavior are either the result of their own efforts or are influenced by external factors beyond their control (Rotter, 1966, 1975). LoC is also closely related to constructs such as self-efficacy and perceived control (Visdómine-Lozano & Luciano, 2006).

3. Literature Review

Research findings confirm the importance of the practical consequences of locus of control in various areas of life. Research shows that differences in the perception of control can affect overall psychological well-being, behavior in interpersonal relationships, and attitudes towards health or education. This makes LoC a key element in the design of interventions aimed at promoting personal responsibility, self-regulation, and the development of adaptive skills. Research also shows that successful manifestations of self-control, such as quitting smoking, are more often associated with an internal locus of control, which points to the importance of personal responsibility in changing behavior (Rosenbaum & Argon, 1979). Individuals with an internal locus of control reported better health (Botha & Dahmann, 2024). Some research suggests that LoC may also be related to physical health and self-perception in this area. Overweight or obese individuals have higher external locus of control scores, which may be related to the belief that they do not have sufficient control over certain aspects of their lives (Thomason, 1983). External locus of control is associated with higher levels of depression as it is related to lower self-esteem among college students (Yu & Fan, 2016). Studies suggest that an internal locus of control is associated with positive outcomes, such as academic success and resilience to negative behavior (Golding et al., 2019). An external locus of control is often associated with a belief in the power of others or chance, which can negatively affect perceptions of one’s own effectiveness—for example, in the area of economic decisions (Baguma & Chireshe, 2012; Ai et al., 2005). Previous research has often focused on LoC in relation to personality or mental health, but less attention has been paid to how demographic factors such as age, gender, marital status, or work experience shape individuals’ perception of control in professional settings.

Locus of control can vary depending on personality traits and specific situations (Ogunyemi, 2013). It can also vary depending on the area of life in which it is assessed (Graybill, 1978). The relationship between beliefs and conformity is further explored, with findings suggesting that control beliefs may mediate the relationship between needs and personality traits (Mussel, 2019). The connection between LoC and the environment is also confirmed by research that has shown that a disordered environment increases the tendency to cheat, especially in people with an external locus of control (Jansen et al., 2017). An internal locus of control is associated with greater immersion in an activity and lower anxiety (Mosing et al., 2012). In workplace bullying scenarios, an internal locus of control does not provide the expected protective effect against psychological distress, while an external locus of control may offer some benefits (Reknes et al., 2019). These findings support the view that LoC is a dynamic and context-sensitive construct that can be influenced by various personal and social characteristics.

The importance of locus of control is also evident in the context of organizations and careers. LoC is perceived as a control mechanism and is used in organizations, especially in the environment of flexible organizational cultures (Heinicke et al., 2016). Individuals with an internal locus of control are more motivated to engage in entrepreneurial activity and proactive behavior (Antwi-Boasiako, 2017). The relationship between LoC and behaviors such as conformity and entrepreneurial orientation is significant, with internal locus of control supporting positive entrepreneurial traits (Knezevic et al., 2021). A significant relationship between LoC and employability has been confirmed (Drazic et al., 2018). According to the study, career ambitions mediate the relationship between internal locus of control and employability (Lin & Ding, 2003). Individual’s LoC may develop in interactions with personal and contextual life experiences—such as the career stage, type of work experience, or family responsibilities.

Considering the review of studies focused on the investigation of LoC, it follows that LoC has a significant impact on the attitudes and subsequent behavior of individuals in certain situations. It is a certain personality trait that influences situationally conditioned behavior based on past experiences. In these cases, LoC is an independent variable that shapes attitudes and influences the behavior of individuals. Given that LoC is influenced by past experience, it is also necessary to examine it as a dependent variable, which may depend on several factors.

From this perspective, personality diversity plays an important role. Individual attributes of diversity contribute to the complexity of the perspective from which people perceive themselves, but also to the perspective from which they perceive others. The connection of individual dimensions contributes to the formation of values, priorities, and perceptions of each individual. Several authors define multidimensional models of diversity, in which they connect several levels of diversity, but in principle, we can distinguish primary and secondary diversity or otherwise referred to as internal and external dimensions of diversity (Vlas et al., 2022; Østergaard & Timmermans, 2023; Hulková, 2024; Verwijs & Russo, 2023). The primary or internal dimension is defined by attributes such as gender, age, race, ethnicity, mental and physical abilities, sexual orientation, and others. These are physical or social characteristics that are impossible or not easily changed. The secondary or external dimension of diversity represents attributes such as work experience, marital status, education, religion, language of communication, geographical location, work status, work style, military experience, and others. These are elements of personal identity that can be more easily changed. Both dimensions of diversity represent major areas of research or are considered an important factor in a wide range of research directions. Given the factors influencing locus of control, differences in LoC may also be manifested depending on age or life or work experience. Managers showed higher scores for internal locus of control, while the group of managerial employees can be assumed to be more experienced in terms of age, which suggests a possible relationship between age and locus of control (Harris & Hartman, 1992). LoC can therefore also be influenced by generation, as different social conditions have shaped different attitudes towards responsibility and control over life. In the workplace, differences in LoC have been identified according to position in the organizational hierarchy. Managers scored higher on the internal locus of control than non-managerial employees (Harris & Hartman, 1992). The results presented suggest that job classification may be related to preferred LoC. Regardless of gender, a tendency toward external locus of control has been shown to play a more significant role in shaping entrepreneurial intentions than internal LoC (Arkorful & Hilton, 2022). The association between LoC and marital quality is influenced by contextual factors such as the length of the marriage and the presence of marital instability. These findings suggest that an individual’s perceived effectiveness in managing interpersonal conflicts plays a key role in determining marital satisfaction (Sakotic-Kurbalija et al., 2017). Based on these insights, it can be assumed that marital status alone does not significantly influence LoC, as other contextual variables also appear to play an important role.

An important area of research is interventions aimed at supporting the internal locus of control. Targeted intervention programs can effectively strengthen the internal locus of control (Kaynak et al., 2024). Interventions aimed at promoting internal locus of control are effective (Williams et al., 2016). The importance of individually focused interventions in strengthening the internal locus of control has also been confirmed (Markovizky & Shafran, 2024). Another study confirmed that positive psychology interventions can effectively increase individuals’ internal locus of control (Choi & Heo, 2021).

In relation to individual characteristics, it was found that in certain situations, men were more conformist than women, suggesting a possible difference in beliefs about control over life situations depending on gender (Maadal, 2020). It can be assumed that sex (both biological and gender aspects) can have an impact on the perception of control and consequently on the behavior of individuals. The influence of the environment has also been shown in the family context. Young people with a positive family environment and supportive parenting practices showed higher scores for the internal locus of control (Ahlin & Antunes, 2015). The family environment or family status may be relevant in relation to emotional support, the perception of LoC, or other social factors, where the presence of a loved one may play a role.

Based on the theoretical background, the authors of the article subsequently derived the following four research hypotheses (RHs):

RH1: 

There is a statistically significant difference between age and the specified LoC.

RH2: 

There is a statistically significant difference between gender and the specified LoC.

RH3: 

There is a statistically significant relationship between the type of work experience and the specified LoC.

RH4: 

There is a statistically significant difference between current marital status and the specified LoC.

To test the hypotheses, the research methods and tools described in the following part of the paper were chosen. Figure 2 displays a model of the relationship between the primary and secondary dimensions of diversity and the locus of control variable, which serves as the basis for the formulation of research hypotheses RH1 to RH4. The model assumes that the variables age and gender (primary dimension of diversity) and marital status and type of work experience (secondary dimension of diversity) can influence the internal or external locus of control of an individual. Each of these four variables is directly linked to the LoC through a separate research hypothesis.

Figure 2 contains the structure of the research framework, where locus of control is the central element, potentially influenced by four variables representing diversity. At the bottom are the two primary dimensions of diversity: “Gender” and “Age”, linked by hypotheses RH2 and RH1. At the top are the secondary dimensions: “Type of work experience” and “Marital status”, linked by hypotheses RH3 and RH4. The research framework visually distinguishes between the two categories of diversity and their potential impact on LoC.

4. Materials and Methodology

The following part of the article is divided into two parts. The first part contains a description of the research collection instrument (questionnaire) and a brief description of the methods used in the research. The second part contains a description of the research sample.

4.1. Description of the Research Instrument and Methods Used

How individuals perceive their locus of control can be measured through several tests. The tests used are focused on mental health, e.g., Multidimensional Health Locus of Control scale (Kassianos et al., 2016), autonomy, e.g., Schepers’s Locus of Control Questionnaire (Schepers, 2004), mental well-being through The Ryff Scales of Psychological Well-being (Ryff & Keyes, 1995), or Rotter’s Locus of Control Scale (Rotter, 1966). Rotter developed the Internal-External Locus of Control Scale (I-E Scale), which was designed to measure individuals’ general belief that the outcomes of their actions are determined by their own efforts and abilities (internal locus) or by external forces such as luck, fate, or other people (external locus). The scale consisted of 29 items, of which 6 were filler items, and the remaining 23 items were used to assess the individual’s orientation. This scale or some modification of this scale has been used in several studies (Falco, 2007; Ojukwu & Onuoha, 2012; Botha & Dahmann, 2024). For the purposes of our research, we chose 10 items of this scale selected according to (Harris & Hartman, 1992). According to these authors and based on research focused on locus of control, several different types of behavior can be identified in internal and external individuals, as shown in

Table 1. Comparing the behavior of internal and external individuals (Harris & Hartman, 1992).

Inner Individual (I Control My Destiny)

External Individual (Factors in My Environment Control Me)

Is more satisfied with the results of personal efforts Feel more satisfied working under a participatory leader and less satisfied with directive leadership Sees a strong relationship between personal effort and personal performance Uses personal persuasion and rewards to influence others Will be more sensitive to situations that involve individual decisions Will be more open to environmental influences Will be more considerate of the needs of others

Is less satisfied with the results of personal efforts Feels less satisfied with a participative leader is more satisfied with a directive Sees a weak relationship between personal efforts and personal performance Will use coercive power to influence others Will be less confident in individual decisions Will be more concerned with changes in the environment Will be more concerned with personal well-being than the well-being of others

.

Table 1 shows that an internal individual should be more sensitive to motivational processes aimed at satisfying needs. Based on the above, we constructed a questionnaire that included, in addition to demographic questions, a 10-item reduced Rotter scale for measuring locus of control.

For research purposes, the authors of the article used a quantitative approach based on a standardized questionnaire tool, which is valid and reliable. Data collection was carried out in the form of an online questionnaire distributed via Google Forms. This method enabled simple and quick distribution of the questionnaire among respondents and at the same time ensured the automatic digitization of responses, thereby minimizing the risk of errors in manual data transcription. In order to minimize the potential bias of common methods during data collection, several procedural (methodological) measures were used. Before data collection, a measure was introduced to ensure the anonymity of respondents in order to minimize the pressure on respondents, as well as a measure that the questionnaire contained detailed instructions that ensured the minimization of common bias. The invitation to participate in the research also included an email contact for a scholar to whom respondents could direct their questions and any ambiguities. Another measure is that a standardized questionnaire was used, which is valid and reliable, and statistical methods (ANOVA, Chi-square tests, and Pearson correlation test) were used, which are suitable for testing due to the cross-sectional nature of the study to examine differences and associations in the locus of control between other variables. Data collection was carried out in the territory of the Slovak Republic using non-probability random sampling. We chose this type of sampling mainly because it is the fastest and easiest way to obtain a sample of respondents, does not require a large budget to reach a large number of respondents, and the research can be carried out even when it is not possible or practical to do a random sample. This method is also suitable when financial or human resources are limited. The questionnaire was distributed to a broad range of respondents without targeted selection. The collected data were subsequently exported to Microsoft Excel, where basic data quality control, aggregation, and preliminary descriptive analysis (calculation of frequencies, percentages, basic statistical indicators) were performed. The above-mentioned data processing phase was necessary to ensure data consistency and prepare data for statistical testing. For statistical analysis (evaluation of the stated research hypotheses), we used IBM SPSS Statistics version 23 software. We used the following statistical methods: descriptive statistics (arithmetic mean, standard deviation, relative and absolute frequency), Levene’s test of homogeneity of variances to verify the assumptions for the use of parametric tests, one-way analysis of variance (ANOVA) to test differences in mean values between multiple groups (e.g., by year of birth), Chi-square test of independence (Pearson test) to verify associations between categorized variables (e.g., type of control and gender or employment status).

4.2. Characteristics of the Research Sample

The research sample consisted of respondents selected randomly to ensure a diverse demographic structure of the research sample. The only condition for selecting the research sample was that the respondents were adults who confirmed their informed consent to participate in the research. The first sociodemographic question was the question that asked about the gender of the respondents. In

Table 2. Respondents’ gender (own elaboration, 2025).

Gender	Absolute Frequency	Relative Frequency [%]
Men	199	51.82
Women	185	48.18
Total	384	100.00

we can see the evaluation.

According to the Table 2, the research sample is gender-balanced. Out of the total set of 384 respondents, 199 were male (51.82%) and 185 were female (48.18%). The second question was a question that asked respondents about their year of birth. The results are presented in Figure 3.

Figure 3 shows the data of N = 384 respondents and their year of birth. The oldest respondent was a person born in 1969. On the other hand, the youngest person who participated in the research was a person born in 2002. In terms of generational affiliation, we can state that generation X (1961–1980) has a low representation of only 15 respondents (3.91%). Generation Y (1981–1995) has a representation of 177 respondents (46.09%). The most numerous groups of respondents were respondents who can be characterized as generation Z (1996–2010), which consisted of up to 50.00% of respondents (192 respondents). Due to the low representation of generation X, it is not possible to examine the differences between generational groups.

Another question that served to characterize the research sample was a question focused on the current marital status of the respondents. Respondents could indicate one of three answer options (married, single but in a relationship, and the last option single, not in a relationship). The results are provided in

Table 3. Marital status of respondents (own elaboration, 2025).

Marital Status	Absolute Frequency	Relative Frequency [%]
Married	59	15.37
Single, but in a relationship	198	51.56
Single, not in a relationship	127	33.07
Total	384	100.00

.

Table 3 above shows that the sample is unbalanced in terms of current marital status. The data show that the largest group in the sample was respondents who are single but currently in a relationship—represented by 198 respondents, what corresponds to 51.56% of the total. In second place were respondents who are single and without a partner, who were 127 (33.07%). The lowest representation was that of married people, who numbered 59, which represents 15.37%. This distribution indicates that the sample is significantly dominated by people who are not legally married, while more than half of them are currently in a partner relationship. The last socio-demographic question was a question focused on the respondents’ current work experience (

Table 4. Type of respondents’ work experience (own elaboration, 2025).

Employment Status	Absolute Frequency	Relative Frequency [%]
Employee/self-employed person	91	23.70
Working student	274	71.35
Unemployed	19	04.95
Total	384	100.00

), which offered three answer options.

Table 4 presents the distribution of respondents according to their current work experience. Of the total number of 384 respondents, the largest part of the sample was made up of working students, who represented 274 people, which corresponds to 71.35%. The second largest group was made up of respondents who are employed or self-employed—91 (23.70%). The least represented category was the unemployed, who numbered 19, which represents 4.95% of the respondents. The above distribution indicates that the research sample is strongly oriented towards the student population, who are also active in the labor market, which may have an impact on their lifestyle, self-regulation, and perception of locus of control.

5. Results

In the following part of the article, four research hypotheses formulated in the previous part of the article are evaluated.

RH1: 

There is a statistically significant difference between age and the specified LoC.

First, we created

Table 5. Descriptive statistics for LoC and year of birth (own elaboration, 2025).

Descriptives Statistics
LoC	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
I	273	1993.92	5.750	0.348	1993.24	1994.61	1969	2001
E	52	1994.38	6.402	0.888	1992.60	1996.17	1972	2002
B	59	1994.78	4.650	0.605	1993.57	1995.99	1978	2001
Total	384	1994.12	5.685	0.290	1993.55	1994.69	1969	2002

, which shows the descriptive statistics for LoC results in the context of age (year of birth). As we can see, there is no significant difference between the LoC results within the research sample in terms of average age and LoC results (I—internal control = 1993.92; E—external control = 1994.38; and B—balanced control = 1994.78).

Next, we proceeded to test the homogeneity of variances (Levene’s test), which showed that sig. = 0.313, which implies that the equality of variances is met, based on which we can proceed to the ANOVA test, the results of which are displayed in

Table 6. Levene’s test of homogeneity of variance (own elaboration, 2025).

Test of Homogeneity of Variances		Levene Statistic	df1	df2	Sig.
Year	Based on Mean	1.166	2	381	0.313
	Based on Median	0.825	2	381	0.439
	Based on Median and with adjusted df	0.825	2	366.143	0.439
	Based on trimmed mean	0.963	2	381	0.382

.

The last step was to perform ANOVA testing to show whether there was a statistically significant difference between year of birth and LoC score. The results are presented in

Table 7. ANOVA testing result for RH1 (own elaboration, 2025).

ANOVA
Year of Birth	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	39.899	2	19.949	0.616	0.541
Within Groups	12,337.828	381	32.383	-	-
Total	12,377.727	383	-	-	-

.

From the results according to Table 7, it can be concluded that there is no statistically significant difference in the average year of birth between the LoC results (I—internal control, E—external control, and B—balanced control) (F (2,381) = 0.616 and p = 0.541). In other words, the LoC (internal, external, or balanced control) does not depend on when the respondent was born, and therefore, we do not confirm the tested RH1.

RH2: 

There is a statistically significant difference between gender and the specified LoC.

Before the actual testing, we present the results of the descriptive statistics in

Table 8. LoC result by gender (own elaboration, 2025).

Result LoC/Gender	Result I—Internal Control		Result E—External Control		Result B—Balanced Control
	Absolute Frequency	Relative Frequency [%]	Absolute Frequency	Relative Frequency [%]	Absolute Frequency	Relative Frequency [%]
Men	143	52.38	22	42.31	34	57.63
Women	130	47.62	30	57.69	25	42.37
Total	273	100.00	52	100.00	59	100.00

below.

Based on the data in Table 8, the most common LoC result in the research sample for the male group is internal control (143 men), and the least common type of control is external control (22). For the female group, the most common type of control is internal control (130 women) and the least common type of control is balanced control (25 women). We then proceeded to statistical testing using SPSS 23, namely testing via the chi-square test, which can be seen in

Table 9. RH2 result using chi-square tests (own elaboration, 2025).

Chi-Square Tests	Value	df	Asymptotic Significance (2-Sided)
Pearson Chi-Square	2.716	2	0.257
Likelihood Ratio	2.723	2	0.256
Linear-by-Linear Association	0.068	1	0.794
N of Valid Cases	384	-	-
0 cells (0.0%) have expected count less than 5. The minimum expected count is 25.05.

. The initial analysis showed that all expected frequencies were sufficiently high (minimum expected frequency = 25.05), thus meeting the requirements for using the chi-square test.

As part of the evaluation, we tested RH2 (Table 9) that there is a statistically significant difference between gender and the result of LoC. For the analysis (we used SPSS 23 for testing), and specifically, we used the chi-square test of independence, the results of which are as follows: χ² (2) = 2.716, p = 0.257. The test result did not show a statistically significant difference between gender and the result of the LoC. In other words, gender does not have a significant effect on the type of control (I—internal, E—external and B—balanced). Based on these results, we do not confirm the second research hypothesis about a statistically significant difference between gender and LoC.

RH3: 

There is a statistically significant relationship between the type of work experience and the specified LoC.

Table 10. LoC results by type of work experience (own elaboration, 2025).

Result LoC/Employment Status	Result I—Internal Control		Result E—External Control		Result B—Balanced Control
	Absolute Frequency	Relative Frequency [%]	Absolute Frequency	Relative Frequency [%]	Absolute Frequency	Relative Frequency [%]
Employee/Self-employed person	72	26.37	7	13.46	12	20.33
Working student	191	69.96	41	78.85	42	71.19
Unemployed	10	03.67	4	07.69	5	08.48
Total	273	100.00	52	100.00	59	100.00

summarizes the descriptive statistics, which are presented ahead of the testing phase.

As displayed in Table 10, the distribution of control among employees and self-employed persons reveals that internal control is the most common type (72 respondents), with the same trend observed among matching students (191 respondents). The most numerous groups among the unemployed is also internal control (10 respondents). The results of statistical testing can be seen in

Table 11. Testing RH3 using the Pearson correlation test (own elaboration, 2025).

Correlations		Result LoC	Type of Work Experience
Result LoC	Pearson Correlation	1	0.354 *
	Sig. (2-tailed)	-	0.042
	N	384	384
Type of work experience	Pearson Correlation	0.354 *	1
	Sig. (2-tailed)	0.042	-
	N	0384	384

* Correlation is significant at the 0.05 level (2-tailed).

. Pearson correlation analysis was used to test the third hypothesis.

The results showed a positive statistically significant correlation between the variables “LoC scale score” and “type of work experience” (r = 0.354, p = 0.042, N = 384). The correlation coefficient can be considered a moderate dependence based on the standard interpretation (Cohen, 1988), with a p value < 0.05, which can be interpreted as a statistically significant relationship at the 5% significance level. The findings (Table 11) suggest that the type of work experience may be related, to some extent, to the tendency of individuals to prefer a certain type of control over situations in their lives (internal, external, or balanced locus of control). In other words, people with different work experiences may have different preferences in the way they attribute control over their own life or work outcomes.

RH4: 

There is a statistically significant difference between current marital status and the specified LoC.

Prior to conducting the actual testing,

Table 12. LoC results by type of current marital status (own elaboration, 2025).

Result LoC/Marital Status	Result I—Internal Control		Result E—External Control		Result B—Balanced Control
	Absolute Frequency	Relative Frequency [%]	Absolute Frequency	Absolute Frequency	Relative Frequency [%]	Absolute Frequency
Married	40	14.65	8	15.38	11	18.65
Single, but in a relationship	149	54.58	20	38.47	29	49.15
Single, not in a relationship	84	30.77	24	46.15	19	32.20
Total	273	100.00	52	100.00	59	100.00

below provides the descriptive statistics for LoC results by current marital status.

The results of the descriptive statistics in Table 12 illustrate that internal control prevails in all types of marital status. Similarly, in all three types of marital status, external control is the least numerous type of control. The results of the statistical testing of the fourth experimental hypothesis are in

Table 13. Testing RH4 using chi-square tests (own elaboration, 2025).

Chi-Square Tests	Value	df	Asymptotic Significance (2-Sided)
Pearson Chi-Square	5.924	4	0.205
Likelihood Ratio	5.772	4	0.217
Linear-by-Linear Association	0.037	1	0.847
N of Valid Cases	384	-	-
0 cells (0.0%) have expected count less than 5. The minimum expected count is 7.99.

. The initial analysis showed that all expected frequencies were sufficiently high (minimum expected frequency = 7.99), thus meeting the requirements for using the chi-square test.

As part of the evaluation, we tested the hypothesis (Table 13) that there is a statistically significant difference between current marital status and the result of the locus of control. For the analysis (testing, we used SPSS 23), and specifically, we used the chi-square test of independence, the results of which are as follows: χ² (2) = 5.924, p = 0.205. The test result did not show a statistically significant difference between current marital status and the result of the LoC. In other words, marital status does not have a significant effect on the type of control (I—internal, E—external, and B—balanced). Based on these results, we do not confirm the hypothesis.

6. Discussion

When formulating the research framework, we based our work on previously validated studies and findings that locus of control is understood as a continuum, with internal locus of control on one side and external locus of control on the other (Wu et al., 2020). Internal locus of control refers to the belief that individuals can influence their life situations through their actions, while external locus of control suggests that outcomes are determined by external factors (Henninger et al., 2012). Individuals with an internal locus of control attribute the outcomes of situations to their abilities, decisions, and effort, while those with an external locus of control perceive outcomes as the result of luck, chance, or external influences (Stones, 1983). The term “internal locus of control” is closely related to concepts such as “self-control,” “self-regulation,” and “ego depletion.” All these terms refer to how individuals perceive their ability to influence the outcomes of their lives and how effectively they can regulate their behavior and impulses. Self-control refers to the mental processes that enable an individual to suppress impulses and adapt behavior to the current demands of the situation (Inzlicht et al., 2014). However, this resource is not inexhaustible. The prolonged exercise of self-control can lead to psychological exhaustion, known as ego depletion, which in turn reduces the ability to exert further self-control (Moller et al., 2006; Kazén & Kuhl, 2022).

Nevertheless, there are situational self-control strategies that can effectively limit negative impulses by allowing the individual to purposefully change their environment and minimize the effects of temptations (Duckworth et al., 2016). Self-regulation, which is closely related to the concept of self-control, has a different nature, as it is often associated with the promotion of positive behavior rather than exhaustion, especially in goal-oriented individuals (Kazén & Kuhl, 2022). At the same time, it proves to be an important mediator in the formation of internal motives, for example in the field of education (Hanfstingl et al., 2010). The relationship between self-control demands and ego depletion is influenced by several factors, such as the satisfaction of basic psychological needs, which may mitigate the risk of self-control failure (Carey et al., 2019). These constructs suggested that LoC is influenced not only by individual predispositions, but also by situational factors. In our research, we focused on differences in individual dimensions of human diversity. Our assumptions were based on the premise that certain elements that shape personality diversity may influence how individuals perceive their LoC.

Our results confirmed that the relationships between locus of control and individual or situational factors are complex and cannot be predicted based on simple characteristics. We assumed that the result on the LoC scale could be influenced by age, gender, type of work experience, or marital status. These findings correspond with the results reported by the authors (Arkorful & Hilton, 2022; Sakotic-Kurbalija et al., 2017; Verwijs & Russo, 2023). Hypothesis RH1, which assumed a significant difference between year of birth and LoC, was not confirmed (p = 0.541, which is higher than the required value of p ≤ 0.05, which confirms the statistical insignificance of the difference between the investigated variables), indicating that there is no relationship between age and preferred LoC in our sample. This result is interesting considering the findings from previous studies, according to which age or experience can be related to higher internal control scores, especially among managers (Harris & Hartman, 1992).

Hypothesis RH2, that there is a difference between gender and LoC, was also not confirmed. Although some research points to possible differences in conformity or perception of control depending on gender (Maadal, 2020), our results do not confirm this relationship (p = 0.257, which means that it is higher than the required value of p ≤ 0.05 and thus confirms the statistical insignificance of the difference between the investigated variables). Hypothesis RH4 on the relationship between current marital status and locus of control was also not supported (p = 0.205, which is higher than the required value of p ≤ 0.05, which confirms the statistical insignificance of the difference between the investigated variables). This suggests that in our sample, marital status is not a significant factor influencing preferences in the area of control over life situations. On the contrary, hypothesis RH3 was confirmed (p = 0.042, and thus is lower than the required value of p ≤ 0.05, which confirms the statistical significance of the relationship between the investigated variables), which demonstrated a slightly statistically significant relationship between current job classification and LoC. This result corresponds to the findings that people with different work experience or positions in the organizational hierarchy may perceive control over their own outcomes differently (Harris & Hartman, 1992; Heinicke et al., 2016). This is consistent with the findings that LoC can be influenced by past experience, as experience with a certain type of supervisor or leadership style can influence how an individual perceives their ability to influence the outcome of their work or achieve work success. This may subsequently affect the preference for choosing a job in which the superior demonstrates a preferred management style, i.e., more authoritative for employees with external LoC and more participative for individuals with internal LoC. These findings may be beneficial for the field of management, since dissonance between employee expectations and the approach of the superior is often a reason for their resignation, leaving the organization.

Our findings also follow the broader framework of external locus of control research, which points to its multidimensional connection with various psychological factors, behavior, and cultural contexts. In summary, it can be stated that LoC as a psychological construct is closely related to the ability to self-control, perception of self-efficacy, and preferences of individuals in the area of regulating their behavior. At the same time, it is sensitive to environmental influences, job classification, and cultural and social factors. Our results confirm this complexity, pointing, in particular, to the connection between work experience and LoC, while individual characteristics such as age, gender, or marital status did not appear to be significant determinants in our sample.

7. Conclusions

Based on the obtained results, it can be concluded that age, gender, and marital status do not show a statistically significant relationship with the preferred locus of control, which indicates that these demographic variables are not a decisive factor influencing the perception of control over life situations in our sample. On the contrary, the results confirmed a statistically significant, moderately strong correlation between the current job title and the result based on the LoC scale. This points to a possible connection between the professional status of an individual and his tendency to attribute control over situations to himself or external circumstances. The findings also correspond to theoretical premises according to which higher job positions can support an internal locus of control. The results expand knowledge about the factors influencing LoC and underline the importance of work environment experiences in the context of the perception of control.

Theoretical implications: These findings contribute to the ongoing theoretical debate about the dynamic nature of LoC and its sensitivity to contextual and experiential variables. They support existing models that suggest LoC is not a static personality trait but a construct shaped by situational inputs, such as one’s role and responsibilities in the workplace. The results also invite further exploration of the mechanisms through which professional experience influences perceived control and psychological functioning. Specifically, the findings are consistent with social cognitive theory, which posits that self-efficacy and perceived control are shaped through experience, social modeling, and feedback. It also suggests that job position may act as a key experiential variable reinforcing these processes. Furthermore, the results challenge the exclusively trait-oriented understanding of internal locus of control, as they suggest that interventions targeting workplace structure and job role clarity can significantly influence this construct over time.

Practical implications: Organizations can use knowledge about the connection between job title and internal LoC to support employee development, build autonomy, and increase performance. Understanding how work roles shape perceptions of control can help design more effective leadership development programs, training interventions, and motivation strategies. In career counselling and occupational psychology, these insights can be applied to better assess client needs and tailor support for improving resilience, decision-making, and stress management. From a managerial perspective, specific measures can include the introduction of structured job rotation programs that expose employees to diverse responsibilities. Another measure can include providing targeted mentoring for employees in positions with low autonomy and introducing mechanisms that allow for effective feedback and strengthen employees’ sense of influence over results. Human resources departments, in collaboration with management, could also develop performance appraisal systems that take into account not only the results achieved, but also proactive problem solving, which ultimately strengthens the internal locus of control. In addition, leadership training can include support for employees’ independent decision-making, such as participatory decision-making, communication oriented towards strengthening competencies, and clear delegation of authority.

The presented research has several limitations that need to be taken into account when interpreting the results. First of all, the research sample consisted exclusively of respondents from Slovakia, which limits the possibilities of generalizing the findings to other cultural and social environments. Cultural norms, societal values, and labor market conditions can significantly influence individuals’ perception of control and their responses to internal or external stimuli. For example, locus of control may manifest differently in collectivist versus individualist cultures or in societies with varying levels of economic stability and institutional trust. As a result, the conclusions drawn from this study may not fully apply to populations in different national or regional contexts. Another limitation is the unbalanced generational representation of respondents, which could have affected the results in relation to the age variable. The research also worked with a relatively limited sample of 384 respondents, which reduces the statistical power of the analyses and may limit the accuracy of the conclusions. Another limitation of the research is the uneven representation of respondent generations (a predominance of Generation Z and Y), which may have an impact on the presented findings. This generational imbalance could limit the generalizability of the results, as it has a direct impact on career experiences, reactions, flexibility, and dynamism. Considering the above factors, it is recommended to supplement the research sample, which should be broader and more diverse. It would be appropriate to expand the research to the international level in order to verify whether the relationship between professional status and LoC is also manifested in other cultures with different social norms and work structures.

Since the current job title was the only variable with a statistically significant relationship to locus of control, this opens up the possibility of examining the impact of managerial approaches on the formation of LoC in employees. It is likely that leadership style, the degree of delegation of responsibility, or the provision of autonomy can significantly influence whether an employee perceives control over situations as internal or external. This also implies that employees’ expectations of management, such as the need for a directive versus supportive management style, may be conditioned by their LoC. Future research could therefore focus on the relationship between LoC and preferred management styles, as well as on the possibilities of influencing it through organizational interventions. Future research could also examine other factors, such as the level of education, type of work sector, or personality traits that may interact with the perception of control. Likewise, quantitative research could be complemented in the future with qualitative methods such as interviews or case studies, which could yield a deeper understanding of the mechanisms by which work experience influences LoC. Future studies could also benefit from using longitudinal research designs to observe changes in LoC over time or from conducting cross-cultural comparisons to examine the influence of different societal contexts. In future research, we want to look at the locus of control from a different perspective and focus on how it influences people’s behavior in critical situations. This could include examining its role in work environments and job positions with different levels of stress, in crisis decision-making, or in adapting to rapid organizational change. In addition, future work could examine how different organizational interventions (such as leadership coaching or job design changes) influence changes in LoC and whether these effects vary across industries, career stages, or demographic groups.