Next Article in Journal
Research on Financial Early Warning Based on Combination Forecasting Model
Previous Article in Journal
Modeling Urban Freeway Rear-End Collision Risk Using Machine Learning Algorithms
Previous Article in Special Issue
Analysis of Socially Vulnerable Communities and Factors Affecting Their Safety and Resilience in Disaster Risk Reduction
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 19
10.3390/su141912048
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Sustainable Reservists’ Services: The Effect of Resilience on the Intention to Remain in the Active Military Reserve Using a Parallel Mediating Model

by
Svajone Bekesiene
1,*,
Rosita Kanapeckaitė
1,2,
Rasa Smaliukienė
1,
Olga Navickienė
1,
Ieva Meidutė-Kavaliauskienė
1 and
Ramutė Vaičaitienė
1
1
General Jonas Zemaitis Military Academy of Lithuania, Silo 5a, LT-10322 Vilnius, Lithuania
2
Institute of Psychology, Vilnius University, Universiteto g. 9/1, LT-01513 Vilnius, Lithuania
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(19), 12048; https://doi.org/10.3390/su141912048
Submission received: 17 August 2022 / Revised: 7 September 2022 / Accepted: 19 September 2022 / Published: 23 September 2022
(This article belongs to the Special Issue Security Challenges in the Context of Sustainability)
Browse Figures
Versions Notes

Abstract

:
The high priority of military training programs in the army is to improve the resilience of its professional and reserve soldiers. In addition, resilience helps to maintain the optimal cognitive and physical performances necessary for mission success; it also has other positive effects that have not yet been studied. Therefore, the purpose of the current study is to understand the effect of psychological resilience (PRE) on the intention of reservists to remain in the active reserve (FMT) after the completion of combat training. In addition, we focus on the motivation (prosocial motivation (PRM) and intrinsic motivation (IMT)) and psychological capital (passion in the pursuit of long-term goals (LTGs), proactivity (PRO), and capability to harness the circumstances (SEF)), and achieved a level of competence after the completion of training (ACH). Building on the perspective of training sustainable reserve soldiers’ capabilities and the theory of psychological resilience, we hypothesize and assess the effect of psychological resilience on the intention of reservists to remain in the active reserve for future military training, as well as the mediating role of psychological capital, motivation, and the obtained training ratings. The study hypotheses are tested on a sample of 345 Lithuanian reserve soldiers. The mediating effects are tested by employing the PROCESS v3.5 macro program developed by Hayes, and bootstrap 10,000. The main findings propose that the total impact of psychological resilience is highly positive (β = 0.659, t = 7.670, p < 0.001) and influences the decision of the reservists to extend their capabilities in future military training. Furthermore, intrinsic motivation (β = 0.691, p < 0.001, and 58.6% of the total effect) and the achieved rating of completed training (β = 0.136, p < 0.01, and 21.2% of the total effect) positively mediate the relationship between psychological resilience and the intention to remain in the active reserve. Selected bootstrap confidence interval and Sobel test statistics with two-tailed probability values evidence the robustness of the mediating results. The significance of the theoretical and practical implications is discussed.

1. Introduction

The reservist service is an important capacity of the military; therefore, an emphasis has always been placed on the maintenance of the intention of reserve soldiers to stay active in the military. Considering that reserve soldiers mainly work in the civilian labor market [1], they constantly move between military and civilian fields [2], where competing fields test their psychological resilience. Reservists’ intentions to stay active in the military, i.e., actively participate in the training and take part in military deployments, has become more relevant than ever in a changing geopolitical environment. Some countries in Europe, such as Sweden and Lithuania, have returned conscription, and the importance of reservist service has started to rise. The preparation of reserve soldiers for military service is a key for countries that heavily rely on reserve units for defense or other operational needs. Additionally, it can be stated that reservists play an extensive role in military operations around the world, and some countries base significant portions of their defense strategy on their reserves. In many countries, the reserve component in the military comprises a greater amount of military manpower available in that country. Accordingly, countries that rely, to a great extent, on reserve units for their primary defense focus on collecting knowledge-based information about what affects the readiness of the service of reservists [3] and their willingness to stay active in the military.
Due to the difficult security situation and operational requirements, the leading research in the field of study of reserve forces has been conducted in Israel, the UK, and the US [4,5,6]. These studies mostly focus on the identity of reservists [7,8,9] and questions concerning their attitudes [10]. Similarly, researchers in Finland and Estonia conducted research on their conscripts and reservists [11]. As is known from previous studies, the sociological segregation between reservists and soldiers is considerable, and their experiences of military life are very different. Unlike their active-duty colleagues, their training does not occur on a regular basis as they only train periodically. As a result, many reserve soldiers experience stress and frustration regarding military service, and their virtues or values that the military strives to establish are not as strong as those of their active-service counterparts. It should also be mentioned that reserve soldiers are continuously moving between civilian and military fields as transmigrants [12] and assume negative life events that can cause a psychological health problem. Furthermore, the reserve soldiers have different reasons to be in the military than their active counterparts, as most reservists cannot use the military as their sole means of recruitment.
The extensive research conducted on military services demonstrates that psychological resilience is important for coping with stress during military activities and switching between civilian and military life [13]. Psychological resilience has also been observed to help a person continue functioning and meet the ongoing demands under highly challenging conditions [14]. The importance of resilience as a phenomenon is discussed very extensively. Researchers in recent years have confirmed that resilience can be expressed by multidimensional characteristics that vary depending on internal and external stressors and individual life environments [15,16,17]. Resilience can be expressed as a very multi-faceted construct [18], and can be observed as a characteristic [19], a process [20], or a result [21]. Therefore, psychological resilience has an impact on the readiness and adherence of reservists towards military values and standards [22], as well as their persistence to continue with military service.
Using the theory of psychological resilience [23,24,25], our objective is to extend the simple interrelationship models of (a) psychological resilience and motivation [26], (b) psychological resilience and personal characteristics (psychological capital) [26], and (c) psychological resilience and performance [27], which are dominant in military research literature. With this study, our aim is to explain how the indirect effects of psychological resilience can impact the soldiers’ intentions to stay in the active reserve after conducting training through three variable clusters: motivation, psychological capital, and performance.
The research is significant in terms of the circumstance that resilience is, to a high degree, a controllable process, and the elements that are essential can be influenced and highlighted. Therefore, knowing the effect of resilience, we can develop military training programs that train individuals for high psychological resilience and lead toward a greater intention to stay in the military’s active reserve.

1.1. The Effect of Psychological Resilience

Resilience, the capacity to overcome the negative effects of setbacks and focus on performance, is a complex process involving not only an individual’s physiology and psychology, but also the influence of factors, such as sex, environment, and training. Resilience can be introduced as a ‘polysemantic’ construct [28] that includes numerous explanations that show some parallels between the individual’s ability to overcome misfortune and the skill to bounce back [29]. Researchers and practitioners have paid close attention to defining the concept of resilience [30,31], and it has become important in all measures of human wellbeing [32] representing individual or organizational psychology [33].
In the general context, resilience refers to the ability of individuals to adapt to major disasters to maintain good mental and physical wellbeing. The resilience paradigm over the past three decades has evolved from a stable feature-oriented approach to a process- or result-oriented approach. Most scientists recently agreed on the complexity of the term and consider resilience to be a dynamic process that leads to health, adaptation, and positive functioning [34,35].

1.2. Research Focus and Hypotheses

In general, resilience is fundamentally a multilevel construct that is revealed through individual capacities and groups so as to foster, engage, and sustain positive social relationships, as well as to suffer and recover from stressors and social isolation. Both identifying the characteristics of individuals, their relationships, group structures, and norms that promote resilience, and determining the effective interventions to build resilience represent some of the most important challenges facing the military and contemporary behavioral science [36,37].
Scholars show that there is evidence that resilience can be taught [36,37,38]. However, almost all the research conducted on the effects of military training shows that it is a vital learning process for the motivation and achievement of soldiers. It should also be noted that different studies measure resilience differently in that, just as there is no single agreed-upon metric for measuring resilience, each study infers individual resilience based on other measures, such as better mental health, better cognitive skills, more efficient work, and better outcomes [36,37,38]. Those studies that observe resilience in the military domain focus on whether military training can help improve skills, leading to better outcomes [39].
The studies related to soldier resilience can therefore be found. Additionally, it is clear that there is a need to better understand the relationships between different clusters of intrapersonal and interpersonal variables associated with psychological resilience and determine those that contribute most to the soldier’s decision to stay and continue to serve in the army wherein the exposure to trauma and adversity is an inevitable part of military life [40].
Starting from motivation variables, it can be pointed out that motivation is a construct that has been broadly studied and valued in the field of psychology, mainly due to its significance. In particular, motivation leads individuals to action, thus providing direction and intention [41]. According to the self-determination theory, when people engage in a task or action, they may have many different reasons for doing so, and these reasons have an impact on the quality of their behavior and wellbeing [41]. Hence, motivation can be intrinsic, which implies doing something for its own good and reflects the individual’s true nature to be challenged, explore, and develop social or cognitive competencies, and extrinsic concepts (e.g., prosocial motivation), which are experienced in situations where the individual acts according to external regulations [42]. Thus, militaries made up of individuals who choose to join the army out of a sense of patriotism or opportunities for self-development reveal an intrinsic, more autonomous motivation, because this decision reflects an inherent satisfaction that does not depend on external contingencies [43].
Moreover, personality traits can be considered to describe the essential character of a person [44], while self-efficacy describes how the person controls his/her behavior in a specific situation [37]. The scholars proved that coping is also very important and can produce the behavioral efforts of an individual to control problems and regulate the mental health of military personnel [45,46]; it can be an important mediating and regulating factor in the process of psychological stress as well [47].
In fact, properly implemented training can make soldiers better at tactics, teamwork, critical decision making, all essential elements of the concept of human dimensions, and, more importantly, keys to success on the battlefield [48].
Taking into account the nonlinear dependency between resilience and the individual characteristics of reserve soldiers in this study, a parallel mediation model is proposed to test the mediating role of variables representing three clusters: motivation with prosocial motivation (PRM) and intrinsic motivation (IMT); psychological capital represented by passion in the pursuit of long-term goals (LTGs), proactivity (PRO), and the ability to exploit the circumstances (SEF); and experience characterized by completed training scores achieved (ACH) in the association between reservist psychological resilience and an intention to stay in the active reserve (see Figure 1).
Specifically, the direct and indirect effects were examined by the following hypotheses raised:
Hypothesis H1.
 Reservists’ psychological resilience can be directly associated with an intention to stay in the active reserve.
Hypotheses H2a–f.
Reservists’ psychological resilience can be associated with reservist motivation, psychological capital, and perceived training results.
Hypotheses H3a–f.
Reservist motivation (M1 and M2), psychological capital (M3, M4 and M5), and experience (M6) can significantly mediate the relationship between psychological resilience and intention to stay in the active reserve.

2. Research Methodology

2.1. Participants and Data Collection Procedure

For this study, participants who contributed to a five-week reserve training course were selected. These participants actually represented the soldiers of the Active Army Personnel Reserve (AAPR) of the Lithuanian Armed Forces, and they were on the list of reserve. All the soldiers chosen for our study participated in military training on programmer tasks, which was organized by the Lithuanian Armed Forces School (LAFS). These platoon-level field tactical exercises started in August and ended in September 2021. Exercises in the training area focused on training individual warfare skills and to extend the team-work experience of the soldiers by increasing their psychological resilience. Additionally, it can be mentioned that all participants accomplished the obligatory tasks and operations with the supervision of professional LAFS instructors. The soldiers completed various classes and exercises according to a pre-planned daily schedule. During these training courses, all the participants remained in the same training area (without going home) and spent five weeks in the barracks considering the additional restrictions due to the COVID-19 pandemic.
Our survey included 375 soldiers from the Active Army Personnel Reserve (AAPR). These soldiers completed a special military training course lasting five weeks. Approximately 97% (N = 365) filled-out questionnaires were returned. The quality analysis of the collected data sets indicated 3% of the inappropriate quality and was not included in this study sample. All in all, the data set of 354 questionnaires of Active Army Personnel Reserve soldiers was finally analyzed. The sociodemographic profiles of the participants are presented in Table A1 (see Appendix A, Table A1).

2.2. Measurement Instruments

Eight constructs made up the measurement instrument. The paper–pencil survey provided data based on self-assessment scales. The encouragement of reserve soldiers to stay in active reserve (FMT) after completing AAPR training was evaluated through the effect of psychological resilience (PRE) on the reservists’ opinions. Additionally, we focused on a few specifical aspects of the self-determination theory [49] where motivation was a vital perception of behavioral transformation. Therefore, this study included two motivation aspects, intrinsic motivation (IMT) and prosocial motivation (PRM); three constructs that represent psychological capital, a passion for the pursuit of long-term goals (LTGs), proactivity (PRO), and capability to control the circumstances (SEF); and military training judgment scores as achieved competence level after completing the training (ACH). The chosen items showed good reliability in the study sample. Starting from Cronbach’s alpha coefficients for each construct, the values were high and varied from 0.852 to 0.953. Furthermore, the extracted average variance (AVE) and composite reliability (CR) indexes were analyzed to fit the discriminant validity for the prevention of multicollinearity problems. All of the assessed AVE (ranging from 0.605 to 0.878) and CR (ranging from 0.892 to 0.985) were considered. The final version of the questionnaire contained a total of fifty-eight questions.
Psychological resilience (PRE) affects military readiness and is crucial to coping with physiological stressors during military operations. To measure the psychological resilience of the reservists, ten items of the Connor–Davidson resilience scale were chosen [50]. The reservists’ answers were assessed by the five-point Likert scale, where 0 = “Not true at all” and 4 = “True nearly all the time” [51]. The final score was indicated by the sum of the responses for each of the ten items, and the highest sum of scores indicated the highest level of resilience. Construct values varied in the interval from 0 to 40, where a higher value indicated greater resilience. The calculated Cronbach’s alpha was 0.932; CR was 0.938; and AVE was 0.605.
Reserve soldiers’ intentions to stay in the active reserve (FMT) after completing the AAPR training was assessed by three items: Fmt1—“I want to update my military skills and serve Lithuania”; Fmt2—“After completing the training, I intend to continue to be an active personnel reserve soldier, and when called to exercises, I intend to participate in them again”; and Fmt3—“After completing the training, I intend to continue actively contributing to the defense of the country”. The items’ measurement scales varied in the interval [1–5], where 1 = “Strongly disagree” and 5 = “Strongly agree”. The construct values varied in the interval from 5 to 15, where a higher value indicated a positive mindset. The calculated Cronbach’s alpha was 0.852; CR was 0.906; and AVE was 0.764.
Intrinsic motivation (IMT) was measured to understand the soldier’s behavior for its inherent satisfaction, rather than for some separable consequences. In particular, human behavior is influenced by emotions, and thus intrinsically motivated behavior is driven by feelings for competence and autonomy. We used the following list of items: Imt1—“I like military service”; Imt2—“I think it’s fun to serve in the military”; Imt3—“The military profession inspires me”; Imt4—“I think military service is satisfying me”; Imt5—“I see opportunities to realize myself as a citizen of Lithuania”; Imt6—“These trainings will help me to constantly deepen my knowledge of warfare and improve myself”; Imt7—“These trainings will help you improve your personal qualities”; Imt8—“Military activities are in line with my personal values”; and Imt9—“I am satisfied with my decision to serve Lithuania”. These items were selected from Ryan et al.’s questionnaire [52]. The construct values varied in the interval from 0 to 40, where a higher value indicated greater resilience. The calculated Cronbach’s alpha was 0.932; CR was 0.938; and AVE was 0.605.
Prosocial motivation (PRM) was measured to create perceptions about reservists’ desires to expend effort in order to benefit other people. To measure prosocial motivation, four items from the Grant scale [53] were used: Prm1—“I care that my participation in these trainings to be useful to others”; Prm2—“With my participation, I want to help fellow students to improve as individuals”; Prm3—“I want to make a positive impact on others”; and Prm4—“It is important for me to do good for society”. The items’ measurement scale varied in the interval [1–5], where 1 = “Strongly disagree” and 5 = “Strongly agree”. The construct values varied in the interval from 0 to 40, where a higher value indicated greater resilience. The calculated Cronbach’s alpha was 0.901; CR was 0.935; and AVE was 0.783.
The passion for the pursuit of long-term goals (LTGs) was measured with the idea to demonstrate the great importance for the soldiers’ psychological growth during military training, which is socially, physically, and psychologically demanding. This study included only four items from the Short Grit Scale (Grit-S) [54] and assessed the reservists’ efforts: Ltg1—“New ideas and projects sometimes distract me from the ones I started earlier”; Ltg2—“Failures do not deter me”; Ltg3—“I finish everything I start”; and Ltg4—“I am hardworking”. The items’ measurement scale varied in the interval [1–5], where 1 = “Not like me at all” and 5 = “Very much like me”. These items were selected from Duckworth et al.’s questionnaire [54]. The construct values varied in the interval from 0 to 40, where a higher value indicated greater resilience. The calculated Cronbach’s alpha was 0.702; CR was 0.892; and AVE was 0.675.
Proactivity (PRO) as proactive personality style was measured using a shortened, six-item scale version of that of Claes et al. [55]. The six items included to assess the reservists’ proactivity were: Pro1—“If I see something I don’t like, I fix it”; Pro2—“If I believe in an idea, no obstacle will prevent me from making it happen”; Pro3—“I love being a champion for my ideas, even against others’ opposition; Pro4—“No matter what the odds, if I believe in something I will make it happen”; Pro5—“I am always looking for better ways to do things”; and Pro6—“I excel at identifying opportunities”. The items’ measurement scale varied in the interval [1–5], where 1 = “Strongly disagree” and 5 = “Strongly agree”. The construct values varied in the interval from 6 to 30, where a higher value indicated a soldier’s greater proactivity levels. The calculated Cronbach’s alpha was 0.883; CR was 0.953; and AVE was 0.786.
The situational exploitation ability (SEF) was measured to demonstrate the importance of soldiers’ functions through cognitive, motivational, affective, and decision-making processes. The self-efficacy scale included six items [56]: Sef1—“I am a person who can complete the training of active personnel reserve soldiers”; Sef2—“I will be able to mobilize and find the necessary strength to do the hard work of training”; Sef3—“I will be able to endure the most difficult moments of training exercises”; Sef4—“I will be able to complete training”; Sef5—“I will achieve results that I can be proud of”; and Sef6—“I will strengthen my martial skills”. The items’ measurements on the Likert scale varied in the interval [1–5], where 1 = “Strongly disagree” and 5 = “Strongly agree”. The construct values varied in the interval from 6 to 30, where a higher value indicated a greater capability to control the circumstances. The calculated Cronbach’s alpha was 0.923; CR was 0.933; and AVE was 0.824.
The level of competence achieved following the completion of the training (ACH) was measured using fourteen elements to evaluate all types of educational processes that were involved in the modules used in the Lithuanian Armed Forces training. Therefore, the ACH scale represents the self-reported achievements in military competence developed during the five-week military training and demonstrates the effort and expertise of reserve soldiers following the completion of the training. The achievements of the soldiers were judged on a five-point scale: 1—“Unsatisfactory, when judgement values vary in the interval [1–2]”, 2—“Weakly, when judgement values vary in the interval [3–4]”, 3—”Satisfactory, when judgement values vary in the interval [5–6]”, 4—“Well, when judgement values vary in the interval [7–8]”, and 5—“Very well, when judgement values vary in the interval [9–10]”. Similarly, military skills were measured in the previous study where respondents had to evaluate their handling of military challenges after a military performance [57]. The construct values varied in the range from 14 to 70, where a higher value indicated higher achievement. The calculated Cronbach’s alpha was 0.942; CR was 0.944; and AVE was 0.628.
Additionally, the description of the convergent validity of the constructs included in this study is presented in Table 1.

2.3. Data Analysis Methodology

The preliminary data analysis started with descriptive statistics. The means and standard deviations for the continuation variables and the percentages for the collected demographic measures were calculated. The relations between factors were weighed by Pearson’s bivariate correlation, and the strength of these relationships was classified by the following judgment: around 0.10 were in ‘small’ relationships, close to 0.30 were presented ‘medium’ correlations, and 0.50 or higher were in ‘large’ relationships [58].
The scales of these eight constructs were assessed using confirmatory factor analysis (CFA) to measure the convergence validity, and the confirmed theoretical model. CFA helped us estimate the factor loading values that had to be greater than 0.5 [59]. Furthermore, discriminant validity and confidence intervals were chosen to disclose evidence of the discriminant validity between two constructs [60,61]. In case we planned to test the mediating effects, we used the bias-corrected bootstrap method, which represents the most precise confidence interval (CI) estimation and presents the highest statistical effectiveness [62,63].
Few steps were taken to test the hypothesis of the mediation model. First, the direct relationships between two variables were tested; the psychological resilience (PRE) as an independent variable was regressed to FMT as a dependent variable (Hypothesis H1). Second, RES as an independent variable was regressed to all six mediators (Hypotheses H2a–f). Third, mediation using a multiple mediation model was tested. The mediation effects were confirmed simultaneously on multiple variables in case they were more accurate and parsimonious than conducting several simple mediation models [64]. Therefore, the specific macro-model 4 of PROCESS v3.5 was chosen, with psychological resilience (PRE) as the independent variable and the intention to remain in active reserve (FMT) as the outcome variable. The following six factors were chosen as mediators: prosocial motivation (PRM), intrinsic motivation (IMT), passion for the pursuit of long-term goals (LTGs), proactivity (PRO), and capability to harness the circumstances (SEF), and achieved scores of completed training (ACH). As such, we simultaneously evaluated whether independent variables’ prosocial motivation (PRM), intrinsic motivation (IMT), passion for the pursuit of long-term goals (LTGs), proactivity (PRO), and capability to harness the circumstances (SEF), and the level of competence achieved after the completion of training (ACH) mediates the relationship between psychological resilience (PRE) and the intention to stay in the active reserve (FMT) following the completion of combat training (Hypotheses H3a–f). The results of the modeling determine the comparative degrees of indirect effects related to each mediator [51]. Additionally, the effects of the six mediators were compared to conclude which should be given more weight. In our case, mediation was tested using a 95% confidence interval by obtaining 10,000 bootstrap samples using the biased-corrected method. The bootstrapping method was used to test mediation to increase power and maintain a sensible control for type-1 error rates [65]. The indirect effect was considered statistically significant if the 95% bias-corrected CI did not contain zero [66].
In the current study, a modeling analysis was performed using SPSS 27v with macro-PROCESS v3.5 as an additional possibility for data analysis [67]. Additionally, the Sobel test was used to test the robustness of the results of mediating relationships [68].

3. Results

3.1. Preliminary Data Analysis

As was mentioned above, this study focused on reserve soldiers’ preparation issues, so all participants were men (100%), and the average age of the participants was 28.5 years. The majority were single (53.9%) and had a vocational education level (39.2%). More than 71% before this training program were working as specialists, and only 15.8% indicated that they were managers who had subordinates. Additionally, 33.1% of participants had been previously trained in different kinds of military training. More detailed characteristics of the collected data that represent the sample background are presented in Table A1 (see Appendix A).
First, descriptive data analysis was performed to measure the means and standard deviations of all constructed variables. Then, the relationships were evaluated by correlation analysis. Finally, a discriminant validity evaluation was conducted to ensure that the latent constructs used to measure the causal relationships under study were truly distinct from each other. The results are presented in Table 2.
In general, the discriminant validity assessment indicated that all variables can be accepted for this measurement model in case they support the discriminant validity between the constructs. Descriptive statistics and Pearson’s correlations for all evaluated variables are presented in Table 2. Specifically, the psychological resilience of reserve soldiers was positively and highly associated with proactivity (PRO and PRE, r = 0.737, p < 0.01), which represents the intention of the individuals to perform more in their jobs, and then work for longer hours to achieve greater results and self-efficacy (SEF and PRE, r = 0.646, p < 0.01), which typically represents the person’s ability to take advantage of the circumstances that influence their life. Similarly, a positive and highly statistically significant relationship was observed between the intention of reserve soldiers to stay in the active reserve and IMT (IMT and FMT, r = 0.858, p < 0.01).

3.2. Results of the Parallel Mediation Modeling

The data modeling analysis began from testing psychological resilience (PRE) effects on six variables (see H2a–f, Figure 1): prosocial motivation (PRM); intrinsic motivation (IMT); passion for the pursuit of long-term goals (LTGs); proactivity (PRO); capability to harness the circumstances (SEF), and achieved scores of completed training (ACH). The conducted analysis allowed us to identify the high statistically significant and positive effect of psychological resilience (PRE) on the study variables: PRM, β = 0.684, t = 7.514, p < 0.01 (see Hypothesis H2a, Table 3); IMT, β = 0.701, t = 9.652, p < 0.001 (see Hypothesis H2b, Table 2); LTG, β = 0.400, t = 9.600, p < 0.001 (see Hypothesis H2c, Table 3); PRO, β = 0.739, t = 19.767, p < 0.001 (see Hypothesis H2d, Table 2); SEF, β = 0.757, t = 15.329, p < 0.001 (see Hypothesis H2e, Table 3); and ACH, β = 0.621, t = 10.797, p < 0.001 (see Hypothesis H2f, Table 3). According to the modeling results, the direct effect of psychological resilience on the intention to stay in the active reserve (see Hypothesis H1, Table 3) is statistically significant; β = 0.659, t = 7.670, p < 0.001. The detailed descriptions of the seven regression models that focused on testing hypotheses H1 and H2a–f are presented in Table 3.
Continuing with the modeling analysis on the reserve soldiers’ decisions to repeat military training in the future also has to be discussed, including the model that was constructed to test how seven independent variables (PRE, PRM, IMT, LTG, PRO, SEF, and ACH) can predict FMT as an outcome variable. The detailed descriptions of the bootstrap results for the regression model parameters with FMT as an outcome variable are presented in Table 4.
The results obtained from the study suggest that the intention to remain in the active reserve for future military training (FMT) is significantly predicted by three variables, such as intrinsic motivation, β = 0.9864, t = 22.191, p < 0.001; capability to toughen the circumstances, β = −0.1711, t = −2.2665, p < 0.05; and the scores achieved from completing the training, β = 0.219, t = 1.426, p < 0.05. The direct effect of psychological resilience was observed to be insignificant; β = 0.0147, t = 0.1861, p > 0.1. Furthermore, the discussed modeling results as unstandardized coefficients are presented schematically in Figure 2.
The macro-model 4 of PROCESS v3.5 allowed us to test the indirect effects by the parallel mediation analysis. These modeling results demonstrate that psychological resilience indicates the impact on the decision of reserve soldiers to remain in the active reserve (FMT) through six mediators (PRM, IMT, LTG, PRO, SEF, and ACH). The direct and indirect effects of the six factors that represent the motivation and ability of the soldiers to complete specific tasks on the relationship between psychological resilience and the intention to stay in the active reserve are presented in Table 5.
Furthermore, the indirect effect of psychological resilience on the intention to remain in the active reserve through IMT was significant; β = 0.691, SE = 0.081, 95% CI (0.527, 0.845). The mediation effect (PRE →IMT →FMT) was reported to be 58.6.% of the total effect. Consequently, the ability to exploit the circumstances (SEF) mediated the relationship between psychological resilience and FMT (SEF, β = 0.130, SE = 0.047, 95% CI (−0.164, −0.0007)), and the achieved military training outcomes (ACH, β = 0.136, SE = 0.039, 95% CI (0.096, 0.287)) mediated the relationship between psychological resilience and intention to stay in the active reserve. The mediation effect accounting for SEF (PRE → SEF →FMT) was 20.2% and for ACH (PRE → ACH →FMT) was 21.2% of the total effect.
However, the indirect effect of psychological resilience on the intention to remain in the active reserve through three mediators was not significant: prosocial motivation (PRM, β = 0.0008, SE = 0.034, 95% CI (− 0.065, 0.067); passion for the pursuit of long-term goals (LTGs, β = 0.0076, SE = 0.0657, 95% CI (−0.1216, 0.1368)); and proactivity (PRO, β = −0.0691, SE = 0.077, 95% CI (−0.220, 0.082)).
Meanwhile, the modeling results indicate the statistical significance of three of six indirect effects that included the mediator effect of intrinsic motivation (IMT), the ability to harness circumstances (SEF), and achievement of military training outcomes (ACH) in the relationship between psychological resilience (PRE) and the intention of the reserve soldiers to stay in the active reserve for future training (FMT). It was important to examine whether these specific indirect effects were significantly different in the mediation.
There was a significant difference between the mediating effects of IMT and LTGs; β = 0.407, SE = 0.057, 95% CI (0.292, 0.514). Furthermore, there were significant differences between the mediating effects of ITM and PRO, β = 0.439, SE = 0.065, 95% CI (0.311, 0.565); the mediating effect of SEF, β = 0.417, SE = 0.064, 95% CI (0.290, 0.540); and the mediating effect of ACH, β = 0.410, SE = 0.059, 95% CI (0.285, 0.517). Consequently, the mediating effect of prosocial motivation was weaker than the mediating effect of intrinsic motivation; β = −0.409, SE = 0.056, 95% CI (−0.514, −0.294).
In addition, the Sobel test was conducted to assess whether a mediator variable significantly carried the influence of an independent variable on a dependent variable. Therefore, the indirect effect of the psychological resilience of the independent variable (PRE) on the intention of the dependent variable to stay in the active reserve for future military training (FMT) through the mediator variables was tested using the Sobel test statistics (SOBT), and two-tailed probability values were chosen to represent the robustness of obtaining mediating results for three effects: intrinsic motivation as a strong, direct effect on individual self-management (IMT, SOBT = 9.272, p < 0.001); capability to harness the circumstances (SEF, SOBT= −2.625, p < 0.01); and achieved military training results (ACH, SOBT = 3.959, p < 0.001).
The significance of the theoretical and practical consequences of obtaining the modeling results is discussed in the subsequent section.

4. Discussion

The purpose of our study was to measure the effect of psychological resilience (PRE) on the intention of the reservists to remain in the active reserve (FMT), taking into account a variety of other psychological factors, such as the motivation of the reservists’ inspiration (prosocial motivation (PRM) and intrinsic motivation (IMT)), psychological capital (passion for the pursuit of long-term goals (LTGs), proactivity (PRO), and the ability to exploit the circumstances (SEF)), and achievement level of competence after the completion of the training (ACH).
The results of the study demonstrate that the mediating effects of psychological resilience and intrinsic motivation contribute to the intention of the reservists to stay in the active reserve for future military activities. These results are consistent with a previous study.
Firstly, we observed that psychological resilience was a significant predictor of continuing professional duties as a soldier, which was also observed in a previous study [69]. This shows that soldiers who present a greater psychological capital and motivation tend to continue their military service. Furthermore, our results support our hypotheses H2a–f that the psychological resilience of reservists can be associated with the motivation of reservists (PRM, β = 0.684, p < 0.01; IMT, β = 0.701, p < 0.001), psychological capital (LTG, β = 0.400, p < 0.001; PRO, β = 0.739, p < 0.001; SEF, β = 0.757, p < 0.001), and perceived training results (ACH, β = 0.621, p < 0.001). Naturally, training results can represent a possible underlying mechanism that could partially explain how psychological resilience is linked to the intentions of the reservists. The associations between psychological resilience, motivation, and intention to remain in the active reserve after completing combat training can be explained by the previous research model that signified the impact of the psychological resilience of reserve soldiers on sustainable military competences [64]. For example, researchers observed that the emphasis on resilience helped to build military-relevant skills; the same skills can both help and hinder individuals as they transition back to civilian life [55]. In the same way, soldiers with high levels of resilience before training who received drill sergeant training showed the greatest improvements in knowledge [70].
Together, these observations suggest that soldiers who are more psychologically resilient have the capability to harness the circumstances and tend to continue their military service. Therefore, these reserve soldiers are highly motivated and will have a greater intention of being selected for additional military training in the future.
Second, in agreement with the self-determination theory [71], we identified the mediating role of intrinsic motivation (IMT, 58.6% of the total effect), achieved the level of competence after completing military training (ACH, 21.2% of the total effect), and the ability to hardness circumstances (SEF, 20.2% of the total effect) in the association between psychological resilience and the intention of the reservists to stay in the active reserve after training. In other words, seeking to enhance and sustain soldiers’ readiness, we needed to enhance the training programs as a way to build resilience. According to the previous studies [68,72,73], training can help build resilience by helping military personnel to be prepared to act in uncertain, dynamic, and changing operational situations. Soldiers with a high level of resilience are more likely to have the confidence to deal with adversity and challenges, and to be able to cope with difficulties [74,75]; soldiers tend to assess their self-perception of mental wellbeing with a positive attitude. This is in line with the results obtained by Chopik et al. [76] that pre-deployment perceived resilience predicted post-deployment emotions among US Army soldiers.
Third, in terms of our findings for parallel mediation, psychological resilience increases the intention of soldiers to remain in the active reserve by increasing their intrinsic motivation, achieving high scores in completed training and decreased self-efficacy. At first, this may appear to be a controversial result; however, as was observed in the previous studies, perfectionism and self-efficacy do not correlate positively with performance [77,78]. Additionally, the military competence among soldiers (i.e., performance) was modified by intrinsic motivation, which can be understood as the participation in military training programs due to inherent satisfactions [79]. In other words, psychological resilience can play a vital role in the military training scores of reservists. Additionally, resilience provides a great contribution to increasing soldiers’ goal planning.
The novelty of this study was the non-linear approach toward the psychological factors that drive the intention of people to continue with challenging activities. To our knowledge, the parallel mediation model was used to investigate the effect of psychological resilience on the impact of decision making by reserve soldiers for the first time. The intention of the soldiers to remain in the active military reserve was explained as a multidimensional intention that was affected by the person’s psychological resilience, intrinsic and prosocial motivations, psychological capital, and the level of competence achieved following the completion of training. In the same way, previous studies reliably verified that intrinsic motivation and the search for high achievements can positively influence the resilience of soldiers and subsequently increase the effect of perceived military competence [64]. Furthermore, based on the resilience framework, soldiers who experienced fewer negative emotions were more likely to regulate their behavior, focusing on a problem that can encourage the development of resilience [80].
This study had limitations that should be mentioned. First, the constructed models could not support the causal inferences about the relationships between the study variables, despite the fact that the presented results clearly support the existence of such a relationship. Longitudinal studies are needed to further investigate the causality of the relationships identified in the current study. Second, our results cannot be generalized to the all-complex military environment. Thus, future studies could use more extended models, which can include an additional focus on instructor support and the influence of the support from colleagues. In fact, it has been shown that as a coping strategy, social support has had a positive impact on military performance [80,81]. The future work should therefore investigate the influence of instructor’s professional support and colleagues’ support during military training.
Despite the identified limitations, this study contributed to the existing research on the relationship between psychological resilience and the intention of reservists to remain in the active reserve after completing combat training, at least in Lithuania, and shed light on similar topics in other cultures. Our findings provide evidence that psychosocial resilience training is valuable not only for re-military preparedness, but also for the greater reservist intention to stay in the active military reserve and, by doing that, to contribute to sustaining military personnel. Furthermore, our results support the interpretation that psychological resilience plays an important role in the association between intrinsic motivation and decision making. Therefore, military training programs should also encourage the development of reservist resilience through emotional-regulation programs and courses related to goal planning, which would increase their psychological resilience.

5. Conclusions

This study included eight constructs that are dominant in the military research literature. Furthermore, the simple models of the interrelationships of psychological resilience were extended to show the indirect effect of relationships between the personal characteristics, motivation, and performance of the soldiers.
Additionally, our results in modeling support the argument that the psychological resilience of reserve soldiers has significant, direct, positive implications for the motivation and performance of soldiers. The findings of estimated indirect effects through these constructs, achievements in military training, intrinsic motivation, and the ability to harness the circumstances, suggest that psychological resilience affects the intention of soldiers to remain in the active reserve. Furthermore, these three mediators could be considered as the main triggers for the decision-making process of reservists.
Moreover, this study supported the argument that perceived intrinsic motivation and AAPR training through how reserve soldiers evaluated their level of achievement in AAPR training challenges and worth may strengthen their motivations to stay in the active reserve, leading to an upward spiral that cultivates greater resilience and preparedness for uncertainties among the reservists.

Author Contributions

Conceptualization, R.K., S.B., R.S., O.N., I.M.-K. and R.V.; methodology, R.K., S.B., R.S., O.N., I.M.-K. and R.V.; software, S.B.; validation, R.K., R.S., R.V. and S.B.; formal analysis, S.B., O.N. and R.K.; investigations, R.K. and S.B.; resources, R.K. and S.B.; data curation, R.K. and S.B.; writing for original draft preparation, R.K., R.S. and S.B.; writing for review and editing, R.K., S.B., R.S., O.N., I.M.-K. and R.V.; visualization, S.B.; supervision, S.B.; project administration, S.B.; funding acquisition, S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Research Council of Lithuania (LMTLT) under project agreement No S-LU-22-9; principal investigator of the grant: Svajone Bekesiene. The funders did not contribute to the design of the study or to the compilation, analysis or clarification of data, or to writing a manuscript or making a decision to publish the results.

Institutional Review Board Statement

The study was approved by the Vilnius University Research Ethics Committee protocol, No. 35/(1.13E)250000-KT-5).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data supporting the reported results are archived in the National Open Access Research Data Archive (MIDAS) at www.midas.lt (accessed on 10 May 2022).

Conflicts of Interest

The authors declare no conflict of interest. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table
Table A1. Sociodemographic profiles of reserve soldiers’ datasets.
Table A1. Sociodemographic profiles of reserve soldiers’ datasets.
CharacteristicsIndicate Value
Age, average in years (SD)28.40 (1.287)
Gender, n (%)
Male354 (100%)
Education, n (%)
1. University54 (15.6)
2. High school (non-university)49 (14.1)
3. Vocational school136 (39.2)
4. Secondary100 (28.8)
5. Unfinished secondary8 (2.3)
Marital status, n (%)
1. Single187 (52.8)
2. Married84 (23.7)
3. Widower, widow2 (0.6)
4. Divorced2 (0.6)
5. Partnership79 (22.3)
Position in the labor market, n (%)
1. Manager, I have subordinates46 (13)
2. Specialist208 (58.8)
3. Other100 (28.2)
Previously had been trained, n (%)
1. Participated in the military trainings120 (33.9)
2. Other234 (66.1)
Notes: N = 354 for all variables; DS—standard deviation.

References

  1. Figinski, T.F. The Effect of Potential Activations on the Employment of Military Reservists: Evidence from a Field Experiment. ILR Rev. 2017, 70, 1037–1056. [Google Scholar] [CrossRef]
  2. Laanepere, T.; Kasearu, K. Military and Civilian Field–Related Factors in Estonian Reservists’ Military Service Readiness. Armed Forces Soc. 2021, 47, 690–709. [Google Scholar] [CrossRef]
  3. Bonanno, G.A. Resilience in the Face of Potential Trauma. Curr. Dir. Psychol. Sci. 2016, 14, 135–138. [Google Scholar] [CrossRef]
  4. Rein-Sapir, Y.; Ben-Ari, E. The Israel Reserve Law: The Duality of Reservists and Transformed Military Autonomy. Armed Forces Soc. 2020, 47, 710–731. [Google Scholar] [CrossRef]
  5. Bury, P.; Catignani, S. Future Reserves 2020, the British Army and the Politics of Military Innovation during the Cameron Era. Int. Aff. 2019, 95, 681–701. [Google Scholar] [CrossRef]
  6. Rice, V.; Liu, B. Personal Resilience and Coping Part II: Identifying Resilience and Coping among U.S. Military Service Members and Veterans with Implications for Work. Work 2016, 54, 335–350. [Google Scholar] [CrossRef]
  7. Cacace, S.; Smith, E.J.; Cramer, R.J.; Meca, A.; Desmarais, S.L. Military Self-Stigma as a Mediator of the Link between Military Identity and Suicide Risk. Mil. Psychol. 2022, 34, 237–251. [Google Scholar] [CrossRef]
  8. Griffith, J.; Ben-Ari, E. Reserve Military Service: A Social Constructionist Perspective. Armed Forces Soc. 2021, 47, 635–660. [Google Scholar] [CrossRef]
  9. Gazit, N.; Lomsky-Feder, E.; Ari, E.B. Military Covenants and Contracts in Motion: Reservists as Transmigrants 10 Years Later. Armed Forces Soc. 2020, 47, 616–634. [Google Scholar] [CrossRef]
  10. Kirby, S.N.; Naftel, S. The Impact of Deployment on the Retention of Military Reservists. Armed Forces Soc. 2000, 26, 259–284. [Google Scholar] [CrossRef]
  11. Estonian Parliament, ‘National Security Concept of Estonia’. 2017. Available online: https://www.kmin.ee/sites/default/files/elfinder/article_files/national_security_concept_of_estonia_0.pdf (accessed on 16 May 2022).
  12. Lomsky-Feder, E.; Gazit, N.; Ben-Ari, E. Reserve soldiers as transmigrants: Moving between the civilian and military worlds. Armed Forces Soc. 2008, 34, 593–614. [Google Scholar] [CrossRef]
  13. Nindl, B.C.; Castellani, J.W.; Warr, B.J.; Sharp, M.A.; Henning, P.C.; Spiering, B.A.; Scofield, D.E. Physiological Employment Standards III: Physiological Challenges and Consequences Encountered during International Military Deployments. Eur. J. Appl. Physiol. 2013, 113, 2655–2672. [Google Scholar] [CrossRef] [PubMed]
  14. Bonanno, G.A. Loss, Trauma, and Human Resilience: Have We Underestimated the Human Capacity to Thrive After Extremely Aversive Events? Am. Psychol. 2004, 59, 20–28. [Google Scholar] [CrossRef] [PubMed]
  15. Bowes, M.A.; Ferreira, N.; Henderson, M. The Influence of Psychosocial Factors in Veteran Adjustment to Civilian Life. Clin. Psychol. Psychother. 2018, 25, 583–600. [Google Scholar] [CrossRef] [PubMed]
  16. Hughes, J.M.; Ulmer, C.S.; Hastings, S.N.; Gierisch, J.M.; Workgroup, M.A.V.M.; Howard, M.O. Sleep, resilience, and psychological distress in United States military Veterans. Mil. Psychol. 2018, 30, 404–414. [Google Scholar] [CrossRef]
  17. van Voorhees, E.E.; Wagner, H.R.; Beckham, J.C.; Bradford, D.W.; Neal, L.C.; Penk, W.E.; Elbogen, E.B. Effects of Social Support and Resilient Coping on Violent Behavior in Military Veterans. Psychol. Serv. 2018, 15, 181–190. [Google Scholar] [CrossRef] [PubMed]
  18. Oshio, A.; Taku, K.; Hirano, M.; Saeed, G. Resilience and Big Five Personality Traits: A Meta-Analysis. Personal. Individ. Differ. 2018, 127, 54–60. [Google Scholar] [CrossRef]
  19. Southwick, S.M.; Bonanno, G.A.; Masten, A.S.; Panter-Brick, C.; Yehuda, R. Resilience Definitions, Theory, and Challenges: Interdisciplinary Perspectives. Eur. J. Psychotraumatol. 2014, 5, 25338. [Google Scholar] [CrossRef]
  20. Crestani Calegaro, V.; Canova Mosele, P.H.; Lorenzi Negretto, B.; Zatti, C.; Miralha da Cunha, A.B.; Machado Freitas, L.H. The Role of Personality in Posttraumatic Stress Disorder, Trait Resilience, and Quality of Life in People Exposed to the Kiss Nightclub Fire. PLoS ONE 2019, 14, e0220472. [Google Scholar] [CrossRef]
  21. Stainton, A.; Chisholm, K.; Kaiser, N.; Rosen, M.; Upthegrove, R.; Ruhrmann, S.; Wood, S.J. Resilience as a Multimodal Dynamic Process. Early Interv. Psychiatry 2019, 13, 725–732. [Google Scholar] [CrossRef] [Green Version]
  22. Masten, A.S. Global perspectives on resilience in children and youth. Child Dev. 2014, 85, 6–20. [Google Scholar] [CrossRef]
  23. Bolton, K.W.; Hall, J.C.; Blundo, R.; Lehmann, P. The Role of Resilience and Resilience Theory in Solution-Focused Practice. J. Syst. Ther. 2017, 36, 1–15. [Google Scholar] [CrossRef]
  24. Spanner, L. Resilient and Entrepreneurial Military Spouses: Neoliberalization Meets Militarization. Crit. Mil. Stud. 2022, 8, 233–253. [Google Scholar] [CrossRef]
  25. Tranter, H.; Brooks, M.; Khan, R. Emotional Resilience and Event Centrality Mediate Posttraumatic Growth Following Adverse Childhood Experiences. Psychol. Trauma 2021, 13, 165–173. [Google Scholar] [CrossRef]
  26. Bartone, P.T. Resilience Under Military Operational Stress: Can Leaders Influence Hardiness? Mil. Psychol. 2006, 18, S131–S148. [Google Scholar] [CrossRef]
  27. Beckner, M.E.; Main, L.; Tait, J.L.; Martin, B.J.; Conkright, W.R.; Nindl, B.C. Circulating biomarkers associated with performance and resilience during military operational stress. Eur. J. Sport Sci. 2022, 22, 72–86. [Google Scholar] [CrossRef]
  28. Whitten, S.M.; Hertzler, G.; Strunz, S. How Real Options and Ecological Resilience Thinking Can Assist in Environmental Risk Management. J. Risk Res. 2012, 15, 331–346. [Google Scholar] [CrossRef]
  29. Chadwick, S. Social and emotional resilience. In Impacts of Cyberbullying, Building Social and Emotional Resilience in Schools; Springer: Cham, Switzerland, 2012; pp. 31–55. [Google Scholar] [CrossRef]
  30. Brown, N.A.; Rovins, J.E.; Feldmann-Jensen, S.; Orchiston, C.; Johnston, D. Exploring Disaster Resilience within the Hotel Sector: A Systematic Review of Literature. Int. J. Disaster Risk Reduct. 2017, 22, 362–370. [Google Scholar] [CrossRef]
  31. Béné, C.; Newsham, A.; Davies, M.; Ulrichs, M.; Godfrey-Wood, R. Review Article: Resilience, Poverty and Development. J. Int. Dev. 2014, 26, 598–623. [Google Scholar] [CrossRef]
  32. Harms, P.D.; Brady, L.; Wood, D.; Silard, A. Resilience and well-being. In Handbook of Well-Being; DEF Publishers: Salt Lake City, UT, USA, 2018. [Google Scholar]
  33. Salanova, M.; Llorens, S.; Martínez, I.M. Contributions from positive organizational psychology to develop healthy and resilient organizations. Pap. Psicólogo 2018, 37, 177–184. [Google Scholar]
  34. Bryce, C.; Ring, P.; Ashby, S.; Wardman, J.K. Resilience in the Face of Uncertainty: Early Lessons from the COVID-19 Pandemic. J. Risk Res. 2020, 23, 880–887. [Google Scholar] [CrossRef]
  35. Praetorius, G.; Hollnagel, E.; Dahlman, J. Modelling Vessel Traffic Service to Understand Resilience in Everyday Operations. Reliab. Eng. Syst. Saf. 2015, 141, 10–21. [Google Scholar] [CrossRef]
  36. Lee, J.E.C.; Sudom, K.A.; Zamorski, M.A. Longitudinal analysis of psychological resilience and mental health in Canadian military personnel returning from overseas deployment. J. Occup. Health Psychol. 2013, 18, 327–337. [Google Scholar] [CrossRef]
  37. Zhao, X.; Wang, J.; Shi, C. The Influence of Mental Resilience on the Positive Coping Style of Air Force Soldiers: A Moderation- Mediation Model. Front. Psychol. 2020, 11, 550. [Google Scholar] [CrossRef] [PubMed]
  38. Cacioppo, J.T. Building Social Resilience in Soldiers: A Double Dissociative Randomized Controlled Study. J. Personal. Soc. Psychol. 2015, 109, 90–105. [Google Scholar] [CrossRef]
  39. McCrory, P.; Cobley, S.; Marchant, P. The effect of psychological skills training (PST) on self-regulation behavior, self-efficacy, and psychological skill use in military pilot-trainees. Mil. Psychol. 2013, 25, 136–147. [Google Scholar] [CrossRef]
  40. Sanborn, A.J.B.; Yalch, M.M.; Bongar, B. The effect of military service and trauma exposure on resilience. Traumatology 2021, 1–4. [Google Scholar] [CrossRef]
  41. Ryan, R.M.; Deci, E.L. Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemp. Educ. Psychol. 2000, 25, 54–67. [Google Scholar] [CrossRef]
  42. Deci, E.L.; Ryan, R.M. Self-determination theory: A macrotheory of human motivation, development, and health. Can. Psychol./Psychol. Can. 2008, 49, 182. [Google Scholar] [CrossRef]
  43. Chambel, M.J.; Castanheira, F.; Oliveira-Cruz, F.; Lopes, S. Work context support and Portuguese soldiers’ well-being: The mediating role of autonomous motivation. Mil. Psychol. 2015, 27, 297–310. [Google Scholar] [CrossRef]
  44. Parmak, M.; Tyfa, D.A. The Link Between Conscription Experience and Conscripts’ Attitude Toward National Military Service at the End of Training: An Example from Estonia. Armed Forces Soc. 2022. [Google Scholar] [CrossRef]
  45. Parmak, M.; Mylle, J.J.; Euwema, M.C. Personality and the perception of situation structure in a military environment: Seeking sensation versus structure as a soldier. J. Appl. Soc. Psychol. 2013, 43, 1040–1049. [Google Scholar] [CrossRef]
  46. Parmak, M.; Mylle, J.J.; Euwema, M.C. Sensation Seeking and Perceived Need for Structure Moderate Soldiers’ Well-Being Before and After Operational Deployment. Mil. Behav. Health 2014, 2, 75–81. [Google Scholar] [CrossRef]
  47. Folkman, S.; Lazarus, R.S.; Gruen, R.J.; Delongis, A. Appraisal, coping, health status, and psychological symptoms. J. Pers. Soc. Psychol. 1986, 50, 571–579. [Google Scholar] [CrossRef] [PubMed]
  48. Adler, A.B.; Bliese, P.D.; Pickering, M.A.; Hammermeister, J.; Williams, J.; Harada, C.; Csoka, L.; Holliday, B.; Ohlson, C. Mental skills training with basic combat training soldiers: A group-randomized trial. J. Appl. Psychol. 2015, 100, 1752–1764. [Google Scholar] [CrossRef]
  49. Flannery, M. Self-Determination Theory: Intrinsic Motivation and Behavioral Change. Oncol. Nurs. Forum 2017, 44, 155–156. [Google Scholar] [CrossRef]
  50. Notario-Pacheco, B.; Martínez-Vizcaíno, V.; Trillo-Calvo, E.; Pérez-Yus, M.; Serrano-Parra, D.; García-Campayo, J. Validity and Reliability of the Spanish Version of the 10-Item CD-RISC in Patients with Fibromyalgia. Health Qual. Life Outcomes 2014, 12, 14. [Google Scholar] [CrossRef]
  51. Vongsirimas, N.; Thanoi, W.; Yobas, P.K. Evaluating psychometric properties of the Connor–Davidson Resilience Scale (10-Item CD-RISC) among university students in Thailand. Nurs. Sci. J. Thail. 2017, 35, 25–35. [Google Scholar]
  52. Ryan, R.M.; Deci, E.L. Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. Am. Psychol. 2000, 55, 68–78. [Google Scholar] [CrossRef]
  53. Grant, A.M. The Significance of Task Significance: Job Performance Effects, Relational Mechanisms, and Boundary Conditions. J. Appl. Psychol. 2008, 93, 108–124. [Google Scholar] [CrossRef]
  54. Duckworth, A.L.; Peterson, C.; Matthews, M.D.; Kelly, D.R. Grit: Perseverance and Passion for Long-Term Goals. J. Pers. Soc. Psychol. 2007, 92, 1087–1101. [Google Scholar] [CrossRef] [PubMed]
  55. Claes, R.; Beheydt, C.; Lemmens, B. Unidimensionality of Abbreviated Proactive Personality Scales across Cultures. Appl. Psychol. 2005, 54, 476–489. [Google Scholar] [CrossRef]
  56. Buch, R.; Säfvenbom, R.; Boe, O. The Relationships between Academic Self-Efficacy, Intrinsic Motivation, and Perceived Competence. J. Mil. Stud. 2015, 6, 19–35. [Google Scholar] [CrossRef]
  57. Moldjord, C.; Laberg, J.C.; Rundmo, T. Stressors, Social Support and Military Performance in a Modern War Scenario. J. Mil. Stud. 2015, 6, 1–18. [Google Scholar] [CrossRef]
  58. Smaliukienė, R.; Bekesiene, S.; Mažeikienė, A.; Larsson, G.; Karčiauskaitė, D.; Mazgelytė, E.; Vaičaitienė, R. Hair Cortisol, Perceived Stress, and the Effect of Group Dynamics: A Longitudinal Study of Young Men during Compulsory Military Training in Lithuania. Int. J. Environ. Res. Public Health 2022, 19, 1663. [Google Scholar] [CrossRef]
  59. Bekesiene, S.; Hošková-Mayerová, Š.; Diliunas, P. Identification of Effective Leadership Indicators in the Lithuania Army Forces. In Mathematical-Statistical Models and Qualitative Theories for Economic and Social Sciences; Hošková-Mayerová, Š., Maturo, F., Kacprzyk, J., Eds.; Studies in Systems, Decision and Control; Springer: Cham, Switzerland, 2017; p. 104. [Google Scholar] [CrossRef]
  60. Bekesiene, S.; Hoskova-Mayerova, S.; Diliunas, P. Structural Equation Modeling Using the Amos and Regression of Effective Organizational Commitment Indicators in Lithuanian Military Forces. In Proceedings of the Aplimat—16th Conference on Applied Mathematics Proceedings, Bratislava, Slovakia, 31 January–2 February 2017; pp. 91–102. [Google Scholar]
  61. Bekesiene, S.; Smaliukiene, R. Personal Growth under Stress: Mediating Effects of Unit Cohesion and Leadership during Mandatory Military Training. Sustainability 2022, 14, 10389. [Google Scholar] [CrossRef]
  62. Bekesiene, S.; Hoskova-Mayerova, S. Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators. J. Math. Fundam. Sci. 2018, 50, 121–141. [Google Scholar] [CrossRef]
  63. Smaliukiene, R.; Bekesiene, S. Towards Sustainable Human Resources: How Generational Differences Impact Subjective Wellbeing in the Military? Sustainability 2020, 12, 10016. [Google Scholar] [CrossRef]
  64. Kanapeckaitė, R.; Bekesiene, S.; Bagdžiūnienė, D. Reserve Soldiers’ Psychological Resilience Impact to Sustainable Military Competences: On the Mediating Role of Psychological Skills (Effort, Self-Efficacy, Proactivity). Sustainability 2022, 14, 6810. [Google Scholar] [CrossRef]
  65. MacKinnon, D.P.; Lockwood, C.M.; Hoffman, J.M.; West, S.G.; Sheets, V. A Comparison of Methods to Test Mediation and Other Intervening Variable Effects. Psychol. Methods 2002, 7, 83–104. [Google Scholar] [CrossRef]
  66. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis. A Regression-Based Approach; The Guilford Press: New York, NY, USA, 2013. [Google Scholar]
  67. Meule, A. Contemporary Understanding of Mediation Testing. Meta-Psychology 2019, 3, 1–7. [Google Scholar] [CrossRef]
  68. Fitzwater, J.P.J.; Arthur, C.A.; Hardy, L. “The Tough Get Tougher”: Mental Skills Training with Elite Military Recruits. Sport Exerc. Perform. Psychol. 2018, 7, 93–107. [Google Scholar] [CrossRef]
  69. Adrian, A.L.; Adler, A.B.; Thomas, J.L.; Britt, T.W. Integrating New Soldiers: The Role of Leaders and Unit Members. Mil. Psychol. 2018, 30, 131–141. [Google Scholar] [CrossRef]
  70. Gutierrez, I.A.; Kincaid, M.; Best, A.; Adler, A.B. Resilience Training Efficacy by Instructor Specialization: A Program Evaluation with Army Recruits. Mil. Behav. Health 2021, 9, 324–334. [Google Scholar] [CrossRef]
  71. Huang, J.; Li, X.; Zhao, J.; An, Y. Relations among Resilience, Emotion Regulation Strategies and Academic Self-Concept among Chinese Migrant Children. Curr. Psychol. 2021. [Google Scholar] [CrossRef]
  72. Morgan, J.K.; Brown, J.; Bray, R.M. Resilience as a Moderating Factor between Stress and Alcohol-Related Consequences in the Army National Guard. Addict. Behav. 2018, 80, 22–27. [Google Scholar] [CrossRef]
  73. Bartone, P.T.; Bowles, S.V. Coping with Recruiter Stress: Hardiness, Performance and Well-Being in US Army Recruiters. Mil. Psychol. 2020, 32, 390–397. [Google Scholar] [CrossRef]
  74. Mažeikienė, A.; Bekesiene, S.; Karčiauskaitė, D.; Mazgelytė, E.; Larsson, G.; Petrėnas, T.; Kaminskas, A.; Songailienė, J.; Utkus, A.; Vaičaitienė, R.; et al. The Association between Endogenous Hair Steroid Hormones and Social Environmental Factors in a Group of Conscripts during Basic Military Training. Int. J. Environ. Res. Public Health 2021, 18, 12239. [Google Scholar] [CrossRef]
  75. Bekesiene, S.; Smaliukiene, R.; Vaicaitiene, R.; Mažeikien, E.A.; Larsson, G.; Karˇciauskaite, D.; Mazgelyte, E. Three-Faceted Approach to Perceived Stress: A Longitudinal Study of Stress Hormones, Personality, and Group Cohesion in the Real-Life Setting of Compulsory Basic Military Training. Sustainability 2022, 14, 1046. [Google Scholar] [CrossRef]
  76. Chopik, W.J.; Kelley, W.L.; Vie, L.L.; Oh, J.; Bonett, D.G.; Lucas, R.E.; Seligman, M.E.P. Development of Character Strengths across the Deployment Cycle among U.S. Army Soldiers. J. Pers. 2021, 89, 23–34. [Google Scholar] [CrossRef]
  77. Vancouver, J.B.; Kendall, L.N. When Self-Efficacy Negatively Relates to Motivation and Performance in a Learning Context. J. Appl. Psychol. 2006, 91, 1146–1153. [Google Scholar] [CrossRef] [PubMed]
  78. Myrseth, H.; Hystad, S.W.; Säfvenbom, R.; Olsen, O.K. Perception of Specific Military Skills—The Impact of Perfectionism and Self-Efficacy. J. Mil. Stud. 2018, 9, 34–48. [Google Scholar] [CrossRef]
  79. Miller, G.; Blau, G.; Campbell, D. Are Chapter 31 Military Veterans Returning to College More Likely to Choose Intrinsically-Oriented Versus Extrinsically-Oriented Majors? J. Educ. Learn. 2020, 10, 1. [Google Scholar] [CrossRef]
  80. Riolli, L.; Savicki, V.; Spain, E. Positive Emotions in Traumatic Conditions: Mediation of Appraisal and Mood for Military Personnel. Mil. Psychol. 2010, 22, 207–223. [Google Scholar] [CrossRef]
  81. Overdale, S.; Gardner, D. Social Support and Coping Adaptability in Initial Military Training. Mil. Psychol. 2012, 24, 312–330. [Google Scholar] [CrossRef]
Sustainability 14 12048 g001 550
Figure 1. Conceptual diagram for study analysis. Direct (H1, H2a, H2b, H2c, H2d, H2e, and H2f) and indirect (H3a, H3b, H3c, H3d, H3e, and H3f) effects are examined. The psychological resilience of the independent variable (IV) (PRE) and the intention of the dependent variable (DV) to stay in active reserve for future military training (FMT). The mediated variable motivations: M1 = prosocial motivation (PRM) and M2 = intrinsic motivation (IMT); psychological capital: M3 = passion for the pursuit of long-term goals (LTGs), M4 = proactivity (PRO), and M5 = ability to exploit the circumstances (SEF); and M6 = completed training scores achieved (ACH).
Figure 1. Conceptual diagram for study analysis. Direct (H1, H2a, H2b, H2c, H2d, H2e, and H2f) and indirect (H3a, H3b, H3c, H3d, H3e, and H3f) effects are examined. The psychological resilience of the independent variable (IV) (PRE) and the intention of the dependent variable (DV) to stay in active reserve for future military training (FMT). The mediated variable motivations: M1 = prosocial motivation (PRM) and M2 = intrinsic motivation (IMT); psychological capital: M3 = passion for the pursuit of long-term goals (LTGs), M4 = proactivity (PRO), and M5 = ability to exploit the circumstances (SEF); and M6 = completed training scores achieved (ACH).
Sustainability 14 12048 g001
Sustainability 14 12048 g002 550
Figure 2. This is a scheme of a parallel mediation model to present the seven variables and psychological resilience in the relationship between resilience (PRE) and intention to stay in the active reserve (FMT). The mediated variable motivations: M1 = prosocial motivation (PRM) and M2 = intrinsic motivation (IMT); psychological capital: M3 = passion for the pursuit of long-term goals (LTGs), M4 = proactivity (PRO), and M5 = capability to harness the circumstances (SEF); and M6 = achieved scores of completed training (ACH). The unstandardized coefficients are presented. The total effect of psychological resilience is shown in parentheses. Course results represent reserve soldiers’ (N = 354) achievements after conducting military training. Statistical significance of coefficients is indicated by ** p < 0.05, *** p < 0.001.
Figure 2. This is a scheme of a parallel mediation model to present the seven variables and psychological resilience in the relationship between resilience (PRE) and intention to stay in the active reserve (FMT). The mediated variable motivations: M1 = prosocial motivation (PRM) and M2 = intrinsic motivation (IMT); psychological capital: M3 = passion for the pursuit of long-term goals (LTGs), M4 = proactivity (PRO), and M5 = capability to harness the circumstances (SEF); and M6 = achieved scores of completed training (ACH). The unstandardized coefficients are presented. The total effect of psychological resilience is shown in parentheses. Course results represent reserve soldiers’ (N = 354) achievements after conducting military training. Statistical significance of coefficients is indicated by ** p < 0.05, *** p < 0.001.
Sustainability 14 12048 g002
Table
Table 1. The background of variables included in the study.
Table 1. The background of variables included in the study.
Model Variable CodeConstruct Measurement DescriptionCronbach’s Alpha
Dependent variable:
Intention to stay in active reserveFMT3 items concerning the respondent’s insights into how they perceived military service after completing the training, planned to continue to be an active personnel reserve soldier, and intended to participate again. The insights of the reserve soldiers were evaluated using the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study scores differ in the interval [1–5], and the importance of the construction elements varies in the interval [0.65–0.89].0.85
Independent variable:
Psychological resilience PRE10 items concerning the improved abilities on a Likert scale ranging from 1—strongly disagree to 5—strongly agree; study scores differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.76–0.85].0.93
Mediators of motivation:
Prosocial
motivation (M1) 		PRM4 items concerning the reservist’s perceived social impact during military training measured by the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study scores differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.87–0.91].0.90
Intrinsic
motivation (M2)		IMT9 items concerning the inherent satisfaction of reservists measured by the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study scores differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.86–0.99]. 0.95
Mediators of psychological capital:
Passion for the pursuit of long-term goals (M3)LTG4 items to assess the reservists’ efforts on extensive features of personality characteristic using the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study values differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.78–0.88].0.70
Capability to control the circumstances (M4)SEF6 items measuring the attitude to follow long-term goals and effort over time measured by the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study values differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.82–0.86].0.92
Proactivity (M5)PRO6 items for proactivity measured by the Likert scale ranging from 1—strongly disagree to 5—strongly agree; study values differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.88–0.94].0.88
Mediator of experience:
Military competence achievements (M6)ACH14 items on the military training module assessments as expectancies before deployment and self-assessment after deployment. Construct values measured by five-point Likert scale, the study values differ in the interval [1–5], and construct items’ importance weights vary in the interval [0.67–0.85].0.94
Notes: N = 354 for all items.
Table
Table 2. The descriptive statistics, discriminant validity, and Pearson’s correlations between the study variables.
Table 2. The descriptive statistics, discriminant validity, and Pearson’s correlations between the study variables.
Variable
Code		DescriptiveDiscriminant
Validity		Correlations
MSDCRAVE12345678
1: PRE 3.9150.6550.938 0.605 0.778
2: FMT3.0081.1060.906 0.764 0.390 **0.874
3: PRM3.8171.1680.935 0.783 0.383 **0.479 **0.885
4: IMT 3.3580.9740.985 0.878 0.470 **0.858 **0.561 **0.937
5: LTG 3.4020.5590.892 0.6750.468 **0.193 **0.156 **0.236 **0.822
6: PRO 3.9080.6550.953 0.786 0.737 **0.330 **0.342 **0.417 **0.472 **0.887
7: SEF 4.3640.7670.933 0.824 0.646 **0.493 **0.479 **0.593 **0.292 **0.622 **0.908
8: ACH 4.0460.7940.944 0.628 0.512 **0.412 **0.395 **0.481 **0.289 **0.508 **0.572 **0.795
Notes: PRE = psychological resilience; FMT = intention to stay in active reserve; PRM = prosocial motivation; IMT = intrinsic motivation; LTG = passion for the pursuit of long-term goals; PRO = proactivity; SEF = capability to harness the circumstances; and ACH = achieved scores of completed training. **Pearson’s correlation is significant at the 0.01 level (2-tailed). M = means; SD = standard deviations.
Table
Table 3. The effect of psychological resilience separately evaluated by regression models.
Table 3. The effect of psychological resilience separately evaluated by regression models.
Description Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H1Model 1 (H1)Intercept0.4270.341 1.2530.211−0.2441.098
PRE → FMTPRE0.6590.0860.3907.6700.0000.4900.828
Model 1
Summary		RR-sqMSEFdf1df2p
0.3900.1521.04258.8321.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2aModel 2 (H2a)
PRE → PRM		Intercept1.1390.362 3.1500.0020.4281.850
PRE0.6840.0910.3837.5140.0000.5050.864
Model 2
Summary		RR-sqMSEFdf1df2p
0.3830.1471.17156.4581.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2bModel 3 (H2b)Intercept0.6160.288 2.1380.0330.0491.182
PRE →IMTPRE0.7010.0730.4709.6520.0000.5580.843
Model 3
Summary		RR-sqMSEFdf1df2p
0.4700.2210.74493.1671.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2cModel 4 (H2c)Intercept1.8360.166 11.0940.0001.5102.161
PRE → LTGPRE0.4000.0420.4689.6000.0000.3180.482
Model 4
Summary		RR-sqMSEFdf1df2p
0.4680.2190.24592.1631.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2dModel 5 (H2d)Intercept1.0180.148 6.8630.0000.7261.310
PRE → PROPRE0.7390.0370.73719.7670.0000.6650.812
Model 5
Summary		RR-sqMSEFdf1df2p
0.7370.5440.197390.7501.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2eModel 6 (H2e)Intercept1.4010.196 7.1450.0001.0151.787
PRE → SEFPRE0.7570.0490.64615.3290.0000.6600.855
Model 6
Summary		RR-sqMSEFdf1df2p
0.6460.4170.345234.9731.000328.0000.000
Coeff.SESt. Coeff.tpLLCIULCI
Hypothesis H2fModel 7 (H2f)Intercept1.6170.228 7.0860.0001.1682.066
PRE → ACHPRE0.6210.0580.51210.7970.0000.5080.734
Model 7
Summary		RR-sqMSEFdf1df2p
0.5120.2620.467116.5641.000328.0000.000
Notes: Model 1 = outcome variable FMT; Model 2 = outcome variable PRM; Model 3 = outcome variable IMT; Model 4 = outcome variable LTG; Model 5 = outcome variable PRO; Model 6 = outcome variable SEF; Model 7 = outcome variable ACH. R = correlation coefficient and R-sq = correlation coefficient in square. LLCI = lower bound of 95% confidence interval; ULCI = upper bound of 95% confidence interval.
Table
Table 4. Total bootstrap results for regression model parameters with reserve soldiers’ decisions to stay in the active reserve as an outcome variable.
Table 4. Total bootstrap results for regression model parameters with reserve soldiers’ decisions to stay in the active reserve as an outcome variable.
Model DescriptionCoeff.SESt. CoefftpLLCIULCI
Independent
variables		Intercept−0.13600.2433 −0.55910.5765−0.61470.3427
PRE0.01470.07900.00870.18610.8525−0.14071.701
PRM0.00080.03360.00080.02340.9814−0.06530.669
IMT0.98640.04440.869622.19100.00000.89891.0738
LTG0.00760.06570.00380.11540.9082−0.12161.368
PRO−0.06910.0768−0.0410−0.90030.3686−0.22020.0819
SEF−0.17110.0642−0.0119−2.26650.0390−0.2435−0.007
ACH0.21930.05140.01571.42620.04670.17910.4241
Model
Summary		RR-sqMSE Fdf1df2p
0.85920.73820.3276c 129.70297.000322.0000.000
Notes: outcome variable = intention to stay in active reserve (FMT). PRE = psychological resilience; PRM = prosocial motivation; IMT = intrinsic motivation; LTGs = passion for the pursuit of long-term goals; PRO = proactivity; SEF = capability to harness the circumstances; and ACH = achieved scores of completed training. R = correlation coefficient and R-sq. = correlation coefficient in square. LLCI = lower bound of 95% confidence interval; ULCI = upper bound of 95% confidence interval.
Table
Table 5. The estimated pathways’ summaries for parallel mediation model when psychological resilience influences the intention to stay in the active reserve.
Table 5. The estimated pathways’ summaries for parallel mediation model when psychological resilience influences the intention to stay in the active reserve.
Estimated PathwaysEstimated Effects
(β)		Boot-SEBootstrapped CI (95%)
LLCIULCI
Direct effect
PRE →FMT0.01470.079− 0.14070.1701
Indirect effects
PRE → PRM →FMT0.00050.0225−0.03970.0565
PRE →IMT →FMT0.6910 ***0.08100.52740.8448
PRE → LTG →FMT0.00300.0280−0.05170.0584
PRE → PRO →FMT−0.05110.0630−0.17850.0087
PRE → SEF →FMT− 0.1301 **0.0467− 0.1644−0.0007
PRE → ACH →FMT0.1363 **0.03920.09570.2868
Total indirect effect0.6441 ***0.10360.43720.8434
Notes: PRE = psychological resilience; PRM = prosocial motivation; IMT = intrinsic motivation as strong, direct effect on individual self-management; LTGs = passion for the pursuit of long-term goals; PRO = proactivity; SEF = capability to harness the circumstances; ACH = achieved military training outcomes; FMT = intention to stay in the active reserve for future military training. Statistical significance marks: ** p < 0.05, *** p < 0.001.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Bekesiene, S.; Kanapeckaitė, R.; Smaliukienė, R.; Navickienė, O.; Meidutė-Kavaliauskienė, I.; Vaičaitienė, R. Sustainable Reservists’ Services: The Effect of Resilience on the Intention to Remain in the Active Military Reserve Using a Parallel Mediating Model. Sustainability 2022, 14, 12048. https://doi.org/10.3390/su141912048

AMA Style

Bekesiene S, Kanapeckaitė R, Smaliukienė R, Navickienė O, Meidutė-Kavaliauskienė I, Vaičaitienė R. Sustainable Reservists’ Services: The Effect of Resilience on the Intention to Remain in the Active Military Reserve Using a Parallel Mediating Model. Sustainability. 2022; 14(19):12048. https://doi.org/10.3390/su141912048

Chicago/Turabian Style

Bekesiene, Svajone, Rosita Kanapeckaitė, Rasa Smaliukienė, Olga Navickienė, Ieva Meidutė-Kavaliauskienė, and Ramutė Vaičaitienė. 2022. "Sustainable Reservists’ Services: The Effect of Resilience on the Intention to Remain in the Active Military Reserve Using a Parallel Mediating Model" Sustainability 14, no. 19: 12048. https://doi.org/10.3390/su141912048

APA Style

Bekesiene, S., Kanapeckaitė, R., Smaliukienė, R., Navickienė, O., Meidutė-Kavaliauskienė, I., & Vaičaitienė, R. (2022). Sustainable Reservists’ Services: The Effect of Resilience on the Intention to Remain in the Active Military Reserve Using a Parallel Mediating Model. Sustainability, 14(19), 12048. https://doi.org/10.3390/su141912048

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop