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Mental health and meaning in life in Chinese military personnel: a cross-lagged analysis

BMC Psychology volume 12, Article number: 426 (2024) Cite this article

Abstract

Background

The burgeoning field of research on the dual-factor model of mental health (DFM) has highlighted its significance, yet the applicability of the DFM in military personnel and its longitudinal relationships with different dimensions of meaning in life remains unclear. This study aimed to clarify the applicability of the DFM for military personnel and to investigate longitudinal relationships between the dual factors of mental health (negative factor, positive factor) and the two dimensions of meaning in life (presence of meaning, search for meaning) in military personnel.

Methods

In this study, data were collected in two waves (April and August 2023) from 227 Chinese military personnel. We constructed a dual-factor model with depression as the negative factor and subjective well-being as the positive factor, and we compared it with a single-factor model to determine if DFM could be applied to military personnel. We also constructed a cross-lagged model to investigate longitudinal relationships between depression, subjective well-being, presence of meaning, and search for meaning.

Results

According to the findings, military personnel fit better with the DFM than with the single-factor model. Cross-lagged analysis results revealed that both the presence of meaning and the search for meaning negatively predicted depression and positively predicted subjective well-being.

Conclusions

The DFM had good applicability among military personnel. Both the presence of meaning and the search for meaning could improve military mental health, suggesting that both dimensions of meaning in life may be potential targets for improving military mental health.

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Introduction

The dual-factor model of mental health

In recent years, with the increasing emphasis on mental health, the shortcomings of the traditional mental health model centered on psychopathology indicators have begun to emerge [1]. For example, the traditional mental health model was overly reliant on the single dimension of psychopathology, which led to the study of mental health being restricted to psychopathology and ignoring the individual’s ability to self-recovery and self-renewal [2], thus failing to comprehensively measure the level of mental health [3, 4]. In addition, traditional mental health models ran the risk of overestimating or underestimating mental health levels and failed to accurately assess the mental health level [5]. With the development of positive psychology, the dual-factor model of mental health (DFM) was proposed [5]. The model suggested that mental health not only included the absence of psychopathological symptoms (e.g., depression, anxiety, etc.), but also contained positive psychological states (e.g., high subjective well-being, high life satisfaction, etc.), and advocated that mental health should be comprehensively examined and understood in terms of both the negative and positive dimensional indicators [6]. Previous studies have demonstrated that the DFM has good applicability among Chinese adolescents [7], college students [8], and migrant workers [9].

Mental health in military personnel

Military personnel are responsible for the defense of the country, and their mental health, as an important part of the military’s combat effectiveness, is increasingly being emphasized [10]. However, most of the existing studies on military mental health used the traditional single-factor model, which focused on the single dimension of negative, and there was a lack of research related to the dual-factor model of military mental health. Due to the special nature of the profession, military personnel were frequently exposed to closed management, intensive training, and dangerous combat environments, resulting in a high incidence of psychological problems [11]. One study investigated 1138 Air Force recruits in the United States who were referred for mental health evaluation while undergoing basic military training, and the results demonstrated that the most frequent diagnosis was depressive disorders, accounting for 31% of all diagnoses [12]. Another study surveyed 1107 Chinese soldiers and found that 25.20% of them had depression symptoms [13]. Depression can adversely affect the physical and mental health and social functioning of military personnel, even leading to suicidal behavior [14]. Hence, previous studies frequently used depression as the representative indicator of the negative dimension of military mental health [15].

Subjective well-being is defined as the individual’s holistic assessment of the quality of life-based on his or her internalized standards [16]. Numerous studies have demonstrated the importance of subjective well-being for several outcomes such as mental health [17], disease recovery [18], health behavior [19], vocational success [20], and survival [21]. Therefore, the subjective well-being is considered the classic indicator of the positive dimension of mental health [22, 23]. Previous studies have found that the subjective well-being of military personnel was low and needed more attention [24]. Therefore, this study used depression as the negative factor and subjective well-being as the positive factor of mental health in military personnel.

The two-dimensional theory of meaning in life

Meaning in life is the individual’s comprehension and evaluation of himself and his life, which includes emphasizing the value of his existence, possessing goals and directions in life, and constantly pursuing his ideals [25]. Meaning in life can be categorized into independent cognitive and motivational dimensions [26], where the cognitive dimension, also known as the presence of meaning, refers to the degree that individuals perceive their lives to be meaningful and worthwhile [27], and the motivational dimension, also known as the search for meaning, refers to the degree of individuals’ investment in building and expanding their understanding of meaning in life [28]. Positive psychology believes that meaning in life could help individuals organize and interpret past experiences, discover what is significant in life, and guide them to achieve a sense of life satisfaction and a sense of self-transcendence [28, 29]. For military personnel, meaning in life could help them adapt to traumatic events, thereby reducing the incidence of adverse events such as post-traumatic stress disorder [30] and suicide [1], and it could help improve their physical health and reduce the incidence of physical illnesses and somatic problems [31]. Moreover, meaning in life was also considered to be an important protective factor for mental health, and previous studies found that meaning in life was significantly negatively correlated with psychotic symptoms such as depression [32,33,34], and significantly positively correlated with positive psychological states such as subjective well-being [35,36,37].

However, further studies have found that different dimensions of meaning in life may have different roles in mental health. On the one hand, the presence of meaning was steadily and positively associated with mental health [38], which was mainly manifested by the significantly negative correlation between the presence of meaning and psychotic symptoms [39, 40], and the significantly positive correlation with positive psychological states [39, 41, 42]. On the other hand, the relationship between the search for meaning and mental health is currently ambiguous. Some scholars argue that the search for meaning is beneficial to mental health [43]. Studies supporting this view suggest that the search for meaning in life leads to a sense of self-transcendence and fulfillment, which could promote mental health [29, 44]. Others hold that the search for meaning is harmful to mental health [45,46,47,48]. Research supporting this view suggests that the meaning-seeking process can be fraught with frustration and disappointment, which could be a threat to mental health [49]. Hence, the controversial point of current research lies in whether the search for meaning enhanced (Gain effect) or diminished (Discount effect) the contribution of the presence of meaning to mental health.

In summary, there are three issues that need to be further explored. Firstly, most of the studies on military mental health were single-factor models and mainly focused on the negative single dimension [50], so the applicability of the DFM in military personnel is unclear. Secondly, previous studies on the meaning in life regularly regarded it as a whole [32,33,34, 37], so the relationships between its two dimensions (presence of meaning, search for meaning) and mental health in military personnel were not yet clear. Lastly, most of the previous studies were cross-sectional [50], which limited further understanding of the longitudinal relationships among variables. Therefore, the present study aimed to clarify the applicability of the DFM for military personnel and to investigate the longitudinal relationship between the dual factors of mental health (depression, subjective well-being) and the two dimensions of meaning in life (presence of meaning, search for meaning) in military personnel.

Materials and methods

Participants

The cluster sampling method was used to select military personnel from a ministry in Shaanxi Province as participants, and a 4-month, 2-stage longitudinal survey was conducted on them. The first survey (Time1, T1) and the second survey (Time2, T2) were conducted on April 10, 2023 and August 10, 2023, with 240 and 236 valid questionnaires collected, respectively. Participants were required to complete a written questionnaire under the guidance of well-trained investigators, and the completed questionnaires were collected on the spot. It should be noted that the guidance proffered by the investigators did not pertain to the discussion of the content of the questionnaire, but only filled instructions for completing it, such as pointing out where to fill in the answers. The data from T1 and T2 were matched by basic information, and finally 227 data were used as the sample for analysis. In this study, all participants were male with a mean age of 22.93 ± 2.95 years. Informed consents were obtained from all participants for this study. This study has been reviewed and approved by the Ethics Committee of the First Affiliated Hospital of the Fourth Military Medical University (No.KY20202063-F-2).

Measures

Chinese meaning in life questionnaire (C-MLQ)

The scale was developed by Steger [26] and revised by Wang [51], and was mainly used to assess individuals’ perceptions of meaning in life. The scale consists of 10 items and can be categorized into two dimensions: presence of meaning (e.g., “I know my life meaning”) and search for meaning (e.g., “I’m looking for something that makes my life meaningful”). Items were rated on a 7-point scale (1 = completely disagree, 7 = completely agree). The score of each dimension is the sum of the scores of the items it contains, and the higher the score, the stronger the degree. The Cronbach’s α coefficients for the total scale were 0.832 (T1) and 0.788 (T2), the Cronbach’s α coefficients for the presence of meaning dimension were 0.914 (T1) and 0.875 (T2), and the Cronbach’s α coefficients for the search for meaning dimension were 0.833 (T1) and 0.773 (T2).

Patients’ health questionnaire depression scale-9 item (PHQ-9)

The PHQ-9 scale was developed based on the nine diagnostic criteria for depression disorder in the DSM-IV and was primarily used to assess the degree of depression symptoms [52]. The scale consists of 9 items and is rated on a 4-point scale (0 = never, 3 = almost every day). The total score is the sum of the scores of all the items, with a higher score representing more severe depression symptoms. The Cronbach’s α coefficients for the scale were 0.885 (T1) and 0.901 (T2).

Subjective well-being scale (SWB)

The scale was developed by Lyubomirsky [53] and revised by Bi [54]. Previous studies have demonstrated its good applicability in Chinese populations [55]. The scale consists of 4 items and is rated on a 7-point scale (1 = very unhappy, 7 = very happy). The sum of the scores for each item is the total score for the scale, with the higher total score indicating the higher subjective well-being. The Cronbach’s α coefficients for the scale were 0.756 (T1) and 0.734 (T2).

Statistical analysis

Data were analyzed using SPSS version 26.0 (IBM Corporation, Armonk NY, USA), and data were presented as n (%) for categorical variables and mean ± SD for numerical variables. The model fit comparisons and cross-lagged analysis were performed using Mplus version 8.0 (Muthen & Muthen, Los Angeles, CA, USA). To test the applicability of the DFM for military personnel and to demonstrate that the dual-factor model is better than the single-factor model, this study compared the fit of the two models with reference to the modeling strategy of Joreskog [56]. The single-factor model constructed a latent variable representing overall mental health, with test items for the positive dimension (subjective well-being) being positive factor loads, and test items for the negative dimension (depression) being negative factor loads. The dual-factor model constructed two latent variables, the positive and negative dimensions of mental health. The test items on subjective well-being were used as observable variables for the positive dimension, and the test items on depression were used as observable variables for the negative dimension, and two latent variables were correlated with each other. The model fit was evaluated using the chi-square (χ2), degrees of freedom (df), comparative fit index (CFI), standard root mean square (SRMR), and root mean square error of approximation (RMSEA) [57]. According to prior studies, χ2/df < 5, CFI greater than 0.90, and RMSEA and SRMR less than 0.08 indicated that the model fit was acceptable [58].

In addition, the cross-lagged analysis was performed to examine the longitudinal relationships between mental health and meaning in life in military personnel. Previous studies have shown that the presence of meaning may change with age [59] and that the subjective well-being may be affected by income [60]. Hence, this study constructed a cross-lagged model with age and income as covariates, and the presence of meaning, search for meaning, depression, and subjective well-being as observable variables. The cross-lagged model explicitly controls for autoregression among variables, known as stability. Put another way, after controlling for the variance associated with the effect of the preceding variable at T1, the residual variance in the change at T2 is attributed to other variables. Hence, the path coefficients demonstrating the cross-lagged relationships between variables are of substantial significance for interpretation. The correlations of the pairs of four variables at the same time were evaluated and a saturated model was assumed. The tested model is shown in Fig. 1.

Fig. 1
figure 1

The tested model. Notes T1: Time 1, T2: Time 2

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Results

Common method bias test

Since all the data in this study were obtained from the reports of the subjects, the study used Harman’s single-factor test for the common method bias test [61]. The test results of the two surveys showed that the factors with eigenvalues greater than 1 were 5 (T1) and 4 (T2), and the variance explanation rate of the first factor was 33.792% (T1) and 35.549% (T2), which was less than the critical criterion of 40% [61], therefore, there was no serious common method bias in this study.

Measurement invariance test

To examine for measurement invariance of the scale over time, this study tested the configural invariance model, metric invariance model, and scalar invariance model of the presence of meaning, search for meaning, depression, and subjective well-being [62]. Based on previous studies, ΔCFI < 0.02, and ΔRMSEA < 0.03 indicated that the variables have comparable measurement structures across time [63,64,65]. According to the fit indices, the configural, metric, and scalar invariance were all established. For the subsequent analyses, the constraints for scalar invariance were retained. The specific results are shown in Table 1.

Table 1 Measurement invariance test of variables
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The applicability test of the DFM in military personnel

To examine the applicability and rationality of the DFM for military personnel and to certify that the dual-factor model is better than the single-factor model for the measurement of military mental health, this study validated the two models using the testing strategy of the structural equation model. As shown in Table 2, the results showed that the fit indicators of the DFM were better than the single-factor model at both T1 and T2, and thus the dual-factor model has higher applicability.

Table 2 Comparisons of the single-factor model and dual-factor model of mental health
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Statistical description and correlation analysis

The results of correlation analysis showed that there was a significant longitudinal correlation between the measures across two time points: the presence of meaning (r = 0.70), search for meaning (r = 0.54), depression (r = 0.43), and subjective well-being (r = 0.53, p < 0.001, respectively) at T1 and T2, indicating that the variables were all stable. The results of the simultaneous correlation analysis showed that the presence of meaning, search for meaning, depression, and subjective well-being were significantly correlated with each other at T1, and the same results were found at T2, which indicated that the variables had good simultaneous correlations. The specific results are shown in Table 3. Therefore, the four variables of presence of meaning, search for meaning, depression, and subjective well-being were suitable for the cross-lagged analysis [66].

Table 3 Statistical description and correlation analysis
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Cross-lagged analysis

As shown in Fig. 2, the cross-lagged analysis results showed that T1 presence of meaning significantly predicted T2 presence of meaning (β = 0.56, p < 0.001), T1 search for meaning significantly predicted T2 search for meaning (β = 0.50, p < 0.001), T1 depression symptom significantly predicted T2 depression symptom (β = 0.27, p < 0.001), and T1 subjective well-being significantly predicted T2 subjective well-being (β = 0.19, p = 0.005). These results suggested that the presence of meaning, search for meaning, depression symptoms, and subjective well-being were stable.

And cross-lagged regression results showed that T1 presence of meaning significantly predicted T2 search for meaning (β = 0.22, p = 0.002), T2 depression symptom (β = -0.28, p < 0.001), and T2 subjective well-being (β = 0.15, p = 0.031); T1 search for meaning significantly predicted T2 presence of meaning (β = 0.13, p = 0.008), T2 depression symptom (β = -0.13, p = 0.026), and T2 subjective well-being (β = 0.15, p = 0.012); T1 depression symptom significantly predicted T2 subjective well-being (β = -0.26, p < 0.001), but did not significantly predict T2 presence of meaning (β = -0.07, p = 0.175) or T2 search for meaning (β = 0.06, p = 0.339); T1 subjective well-being significantly predicted T2 presence of meaning (β = 0.16, p = 0.002), but did not significantly predict T2 search for meaning (β = -0.03, p = 0.666) and T2 depression symptom (β = -0.02, p = 0.766). These results suggested that the presence of meaning and the search for meaning predicted each other; and that both the presence of meaning and the search for meaning negatively predicted depression and positively predicted subjective well-being, in other words, both the presence of meaning and the search for meaning positively predicted mental health of military personnel.

Fig. 2
figure 2

The cross-lagged model of the presence of meaning, search for meaning, depression, and subjective well-being in military personnel. Note T1 = Time 1, T2 = Time 2; *p < 0.05, **p < 0.01, ***p < 0.001; Solid lines represent relationships that are significant, and dashed lines represent relationships that are not significant. The numbers next to the solid lines represent the standardized coefficient (β). Non-significant values and covariates are not presented in the figure

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Discussion

Compared to the single-factor model of mental health, the DFM had a better fit in military personnel, which was consistent with the results of previous studies in the general population [32, 34]. Therefore, the DFM had good applicability to military personnel. Meanwhile, the results of this study also supported the premise of the DFM, which was that mental health consisted of two separate but interrelated constructs, positive and negative dimensions [67]. The results of this study suggested that when assessing the level of mental health of military personnel, both positive and negative aspects should be comprehensively assessed rather than simply focusing on the single negative aspect.

Results of cross-lagged analysis showed that the prior presence of meaning significantly negatively predicted later depression, and significantly positively predicted later subjective well-being, indicating that the presence of meaning was beneficial to military mental health, which was consistent with previous research [38]. The presence of meaning emphasized the understanding and perception of meaning in life [68], and was considered as a basic psychological need in daily life, the satisfaction of which brought positive emotional experiences such as subjective well-being to individuals [69]. It has been found that the presence of meaning can enhance individuals’ positive emotions [70]. According to the broaden-and-build theory of positive emotions, positive emotions can promote the accumulation of resources [71], which can improve individuals’ subjective well-being and prevent the occurrence of depression [72]. In addition, the presence of meaning has been found to be positively correlated with positive coping styles (e.g., problem solving, positive reappraisal) and negatively correlated with negative coping styles (e.g., denial, avoidance, and substance dependence) [73, 74]. When confronting negative events, individuals with a high presence of meaning tended to adopt positive coping styles, which could effectively help individuals reduce negative emotions such as anxiety and depression [75]. Research also showed that individuals with a high presence of meaning experienced less psychological conflict when making health-related decisions, and tended to self-regulate for better mental health [76]. Therefore, the presence of meaning was an important protective factor for the mental health of military personnel.

The results also showed that prior search for meaning also negatively predicted later depression and positively predicted later subjective well-being, meaning that the search for meaning was similarly beneficial to military mental health. In other words, the search for meaning reinforced the promotional effects of the presence of meaning on the mental health of military personnel, demonstrating the gain effect. Some researchers argued that the search for meaning can be equivalent to a cognitive schema that enhances the role of meaning experience in individuals’ assessment of positive psychological states such as life satisfaction [43]. Interestingly, the positive or negative effect of the search for meaning on the presence of meaning seems to be related to cultural contexts. Previous studies found that the search for meaning and presence of meaning showed negative correlations in samples from the United States and Australia [61, 62], and positive correlations in samples from China and Japan [35, 60]. Thus, it seems that the two dimensions of meaning in life are mutually reinforcing in collectivistic cultures and mutually antagonistic in individualistic cultures [40]. Second, studies have found that a higher presence of meaning can also expand and enrich the foundational parts of meaning in life, thus allowing individuals to have higher subjective well-being and lower depression in their search for meaning [77]. In addition, Steger [78] categorized meaning in life into four basic types based on different combinations of the presence of meaning and the search for meaning, including meaning diffusion (low presence of meaning and low search for meaning), meaning exclusion (high presence of meaning and low search for meaning), meaning extension (high presence of meaning and low search for meaning), and meaning acquisition (high presence of meaning and high search for meaning). Significant differences in indicators of psychological functions such as depression and hope have been found among individuals with different life meaning types [46, 79], with the negative effects of search for meaning manifested primarily in individuals with a low presence of meaning, and positive effects manifested in primarily individuals with high presence of meaning [80]. As a noble profession, military personnel bore the responsibility of protecting the country and had high social statuses, their presence of meaning may be higher, so the search for meaning may mainly play the gain effect on the military personnel.

However, there were also the following limitations in this study. Firstly, the participants in this study were all male military personnel, and there was a lack of data on female military personnel, so it may not be a comprehensive representation of the military population, thus subsequent studies could add female military personnel to enhance the applicability of the findings to the military population. Secondly, only two time points of data were collected in this study, which prevented the researcher from explaining the mediating role of the variables, and subsequent studies could collect data from three time points to test whether any variables play a mediating role. Lastly, the positive and negative dimensions of mental health belonged theoretically to artificially synthesized composite indicators, and only using depression as the negative dimension and subjective well-being as the positive dimension may not comprehensively reflect the mental health of military personnel. Therefore, future research could incorporate more observational indicators in each of the two dimensions to more comprehensively reflect the mental health of military personnel.

Conclusion

In summary, this study verified the applicability of DFM for military personnel and investigated the longitudinal relationship between the dual factors of mental health and the two dimensions of meaning in life in military personnel. We found that the DFM had better applicability in military personnel compared to the single-factor model, suggesting that both negative and positive dimensions should be investigated in order to comprehensively assess the mental health of military personnel. Meanwhile, this study found that both the cognitive and motivational dimensions of meaning in life can positively predict military mental health, which offered potential improvement targets. Therefore, when improving the mental health of military personnel in the future, mental health workers could consider starting from the perspective of the meaning of life. By improving the level of presence of meaning (e.g., by increasing the respect of the whole society for the military profession, and by improving the level of the quality of life of the military personnel), as well as encouraging the military personnel to seek more meaning (e.g., by encouraging military personnel to develop their hobbies, and by encouraging military personnel to pursue honors), it will ultimately promote the overall improvement of the military mental health.

Data availability

The datasets generated and/or analyzed in this study are not available, but may be available from the corresponding author on reasonable request.

Abbreviations

DFM:

Dual-factor model of mental health

C-MLQ:

Chinese meaning in life questionnaire

PHQ-9:

Patients’ health questionnaire depression scale-9 item

SWB:

Subjective well-being scale

CFI:

Comparative fit index

SRMR:

Standard root mean square

RMSEA:

Root mean square error of approximation

References

  1. Keyes CLM, Lopez SJ. Toward a science of mental health: positive directions in diagnosis and interventions. Handbook of positive psychology. edn. New York, NY, US: Oxford University Press; 2002. pp. 45–59.

    Google Scholar 

  2. Suldo SM, Shaffer EJ. Looking beyond psychopathology: the dual-factor model of mental health in youth. School Psychol Rev. 2008;37(1):52–68.

    Article  Google Scholar 

  3. Cowen EL. The enhancement of psychological wellness: challenges and opportunities. Am J Community Psychol. 1994;22(2):149–79.

    Article  PubMed  Google Scholar 

  4. Keyes CL. Promoting and protecting mental health as flourishing: a complementary strategy for improving national mental health. Am Psychol. 2007;62(2):95–108.

    Article  PubMed  Google Scholar 

  5. Greenspoon PJ, Sasklofske DH. Toward an integration of subjective well-being and psychopathology. Soc Indic Res. 2001;54(1):81–108.

    Article  Google Scholar 

  6. Antaramian S. Assessing psychological symptoms and well-being: application of a dual-factor mental health model to understand college student performance. J Psychoeducational Assess. 2015;33(5):419–29.

    Article  Google Scholar 

  7. Clark KN, Malecki CK. Adolescent mental health profiles through a latent dual-factor approach. J Sch Psychol. 2022;91:112–28.

    Article  PubMed  Google Scholar 

  8. Xiao R, Zhang C, Lai Q, Hou Y, Zhang X. Applicability of the Dual-Factor Model of Mental Health in the Mental Health Screening of Chinese College Students. Front Psychol. 2020;11:549036.

    Article  PubMed  Google Scholar 

  9. Zhang Q, Lu J, Quan P. Application of the dual-factor model of mental health among Chinese new generation of migrant workers. BMC Psychol. 2021;9(1):188.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Dunbar MS, Schuler MS, Meadows SO, Engel CC. Associations between Mental and Physical Health conditions and Occupational impairments in the U.S. military. Mil Med. 2022;187(3–4):e387–93.

    Article  PubMed  Google Scholar 

  11. Bin Zubair U, Mansoor S, Rana MH. Prevalence of depressive symptoms and associated socio-demographic factors among recruits during military training. J R Army Med Corps. 2015;161(2):127–31.

    Article  PubMed  Google Scholar 

  12. Cigrang JA, Carbone EG, Todd S, Fiedler E. Mental health attrition from Air Force basic military training. Mil Med. 1998;163(12):834–8.

    Article  PubMed  Google Scholar 

  13. Xiong H, Zhang X, Zhang Y, Ma F, Li Y, Li L. An investigation of the prevalence of depressive symptoms in soldiers during military training. Prev Med. 2005;41(2):642–5.

    Article  PubMed  Google Scholar 

  14. Moore MJ, Shawler E, Jordan CH, Jackson CA. Veteran and Military Mental Health Issues. In: StatPearls edn. Treasure Island (FL) ineligible companies. Disclosure: Evan Shawler declares no relevant financial relationships with ineligible companies. Disclosure: Christopher Jordan declares no relevant financial relationships with ineligible companies. Disclosure: Christopher Jackson declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC.; 2024.

  15. Greenberg J, Tesfazion AA, Robinson CS. Screening, diagnosis, and treatment of depression. Mil Med. 2012;177(8 Suppl):60–6.

    Article  PubMed  Google Scholar 

  16. Jorm AF, Ryan SM. Cross-national and historical differences in subjective well-being. Int J Epidemiol. 2014;43(2):330–40.

    Article  PubMed  Google Scholar 

  17. Bolier L, Haverman M, Westerhof GJ, Riper H, Smit F, Bohlmeijer E. Positive psychology interventions: a meta-analysis of randomized controlled studies. BMC Public Health. 2013;13:119.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Howell RT, Kern ML, Lyubomirsky S. Health benefits: Meta-analytically determining the impact of well-being on objective health outcomes. Health Psychol Rev. 2007;1(1):83–136.

    Article  Google Scholar 

  19. Boehm JK, Kubzansky LD. The heart’s content: the association between positive psychological well-being and cardiovascular health. Psychol Bull. 2012;138(4):655–91.

    Article  PubMed  Google Scholar 

  20. Lyubomirsky S, King L, Diener E. The benefits of frequent positive affect: does happiness lead to success? Psychol Bull. 2005;131(6):803–55.

    Article  PubMed  Google Scholar 

  21. Lamers SM, Bolier L, Westerhof GJ, Smit F, Bohlmeijer ET. The impact of emotional well-being on long-term recovery and survival in physical illness: a meta-analysis. J Behav Med. 2012;35(5):538–47.

    Article  PubMed  Google Scholar 

  22. Diener E. Subjective well-being. The science of happiness and a proposal for a national index. Am Psychol. 2000;55(1):34–43.

    Article  PubMed  Google Scholar 

  23. Steinmayr R, Wirthwein L, Modler L, Barry MM. Development of Subjective Well-being in Adolescence. Int J Environ Res Public Health 2019, 16(19).

  24. Bulmer S, Drain JR, Tait JL, Corrigan SL, Gastin PB, Aisbett B, Rantalainen T, Main LC. Quantification of Recruit Training Demands and subjective wellbeing during Basic Military Training. Int J Environ Res Public Health 2022, 19(12).

  25. Steger MF. Experiencing meaning in life: optimal functioning at the nexus of well-being, psychopathology, and spirituality. The human quest for meaning: theories, research, and applications. 2nd ed. New York, NY, US: Routledge/Taylor & Francis Group; 2012. pp. 165–84.

    Google Scholar 

  26. Steger MF, Frazier P, Oishi S, Kaler M. The meaning in life questionnaire: assessing the presence of and search for meaning in life. J Couns Psychol. 2006;53(1):80–93.

    Article  Google Scholar 

  27. McKnight PE, Kashdan TB. Purpose in life as a system that creates and sustains health and well-being: an integrative, testable theory. Rev Gen Psychol. 2009;13(3):242–51.

    Article  Google Scholar 

  28. Frankl VE. Man’s search for meaning: an introduction to logotherapy. 4th ed. Boston, MA, US: Beacon Press; 1992.

    Google Scholar 

  29. Steger MF. Meaning in life. Oxford handbook of positive psychology. 2nd ed. New York, NY, US: Oxford University Press; 2009. pp. 679–87.

    Google Scholar 

  30. Fischer IC, Shanahan ML, Hirsh AT, Stewart JC, Rand KL. The relationship between meaning in life and post-traumatic stress symptoms in US military personnel: a meta-analysis. J Affect Disord. 2020;277:658–70.

    Article  PubMed  Google Scholar 

  31. Czekierda K, Banik A, Park CL, Luszczynska A. Meaning in life and physical health: systematic review and meta-analysis. Health Psychol Rev. 2017;11(4):387–418.

    Article  PubMed  Google Scholar 

  32. Haugan G. Meaning-in-life in nursing-home patients: a correlate with physical and emotional symptoms. J Clin Nurs. 2014;23(7–8):1030–43.

    Article  PubMed  Google Scholar 

  33. Volkert J, Harter M, Dehoust MC, Ausin B, Canuto A, Da Ronch C, Suling A, Grassi L, Munoz M, Santos-Olmo AB, et al. The role of meaning in life in community-dwelling older adults with depression and relationship to other risk factors. Aging Ment Health. 2019;23(1):100–6.

    Article  PubMed  Google Scholar 

  34. Zhou JJ, Zhang Y, Ren QZ, Li T, Lin GD, Liao MY, Chen SH, Tong P, Gao YL. Mediating effects of meaning in life on the relationship between family care, depression, and quality of life in Chinese older adults. Front Public Health. 2023;11:1079593.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Xu X, Xu Y, Zhao J, Ye P, Yu M, Lai Y, Wang J, Huang Q. Good personality and subjective Well-Being: Presence of meaning in Life and Perceived Social Support as mediators. Int J Environ Res Public Health 2022, 19(21).

  36. Arslan G, Allen KA. Exploring the association between coronavirus stress, meaning in life, psychological flexibility, and subjective well-being. Psychol Health Med. 2022;27(4):803–14.

    Article  PubMed  Google Scholar 

  37. Zika S, Chamberlain K. On the relation between meaning in life and psychological well-being. Br J Psychol. 1992;83(Pt 1):133–45.

    Article  PubMed  Google Scholar 

  38. Aftab A, Lee EE, Klaus F, Daly R, Wu TC, Tu X, Huege S, Jeste DV. Meaning in Life and its Relationship with Physical, Mental, and cognitive functioning: a study of 1,042 Community-Dwelling adults across the Lifespan. J Clin Psychiatry 2019, 81(1).

  39. Abu-Raiya H, Sasson T, Russo-Netzer P. Presence of meaning, search for meaning, religiousness, satisfaction with life and depressive symptoms among a diverse Israeli sample. Int J Psychol. 2021;56(2):276–85.

    Article  PubMed  Google Scholar 

  40. Szczesniak M, Falewicz A, Strochalska K, Rybarski R. Anxiety and depression in a non-clinical sample of young Polish adults: Presence of meaning in life as a Mediator. Int J Environ Res Public Health 2022, 19(10).

  41. Zhang Q, Yang Y, Zhang GL. Influence of life meaning on Subjective Well-Being of Older people: serial multiple mediation of Exercise Identification and amount of Exercise. Front Public Health. 2021;9:515484.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Hallford DJ, Mellor D, Cummins RA, McCabe MP. Meaning in life in earlier and later Older-Adulthood: Confirmatory Factor Analysis and correlates of the meaning in Life Questionnaire. J Appl Gerontol. 2018;37(10):1270–94.

    Article  PubMed  Google Scholar 

  43. Steger MF, Oishi S, Kesebir S. Is a life without meaning satisfying? The moderating role of the search for meaning in satisfaction with life judgments. J Posit Psychol. 2011;6(3):173–80.

    Article  Google Scholar 

  44. Li X, Jia X. The Effect of Boredom on College Students’ Meaning in Life: A Longitudinal Mediation Model. Int J Environ Res Public Health 2022, 19(19).

  45. Lin L, Chan HW. When is search for meaning in life beneficial for well-being? A cross-national study. Int J Psychol. 2021;56(1):75–84.

    Article  PubMed  Google Scholar 

  46. Dezutter J, Waterman AS, Schwartz SJ, Luyckx K, Beyers W, Meca A, Kim SY, Whitbourne SK, Zamboanga BL, Lee RM, et al. Meaning in life in emerging Adulthood: a person-oriented Approach. J Pers. 2014;82(1):57–68.

    Article  PubMed  Google Scholar 

  47. Schwartz SJ, Beyers W, Luyckx K, Soenens B, Zamboanga BL, Forthun LF, Hardy SA, Vazsonyi AT, Ham LS, Kim SY, et al. Examining the light and dark sides of emerging adults’ identity: a study of identity status differences in positive and negative psychosocial functioning. J Youth Adolesc. 2011;40(7):839–59.

    Article  PubMed  Google Scholar 

  48. Steger MF, Kashdan TB, Sullivan BA, Lorentz D. Understanding the search for meaning in life: personality, cognitive style, and the dynamic between seeking and experiencing meaning. J Pers. 2008;76(2):199–228.

    Article  PubMed  Google Scholar 

  49. Triandis HC. The self and social behavior in differing cultural contexts. Psychol Rev. 1989;96(3):506–20.

    Article  Google Scholar 

  50. Valladares-Garrido MJ, Picon-Reategui CK, Zila-Velasque JP, Grados-Espinoza P, Vera-Ponce VJ, Pereira-Victorio CJ, Valladares-Garrido D, Failoc-Rojas VE. Depression and anxiety in Peruvian military personnel during the pandemic context: a cross-sectional study. BMC Public Health. 2023;23(1):691.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wang M, Dai X. Chinese meaning in Life Questionnaire revised in College Students and its reliability and validity test. Chin J Clin Psychol. 2008;16(5):459–61.

    Google Scholar 

  52. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Lyubomirsky S, Lepper HS. A measure of subjective happiness: preliminary reliability and construct validation. Soc Indic Res. 1999;46(2):137–55.

    Article  Google Scholar 

  54. Bi C, Huang X. Development and initial validation of the youth self-confidence inventory. Acta Physiol Sinica. 2009;41(5):444–53.

    Google Scholar 

  55. Peng H, Sheng L, Qiu F, Zhou Z, Xin S. Psychological Burden reduction starts from dealing with Boredom: the influencing mechanism of Boredom Proneness on Subjective Well-being among adolescents. Psychol Dev Educ. 2023;39(6):895–902.

    Google Scholar 

  56. Jöreskog KG, Sörbom D. LISREL 8 user’s reference guide. Chicago, IL: Scientific Software International; 1996.

    Google Scholar 

  57. Shi C, Wang S, Tang Q, Liu X, Li Y. Cross-lagged relationship between anxiety, depression, and sleep disturbance among college students during and after collective isolation. Front Public Health. 2022;10:1038862.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Hou X, Wang G, Wang H, Liu J, Liu W, Ji S, Wang E, Qu D, Hu J. Which came first? Bulimia and emotional symptoms: a cross-lagged panel analysis. Int J Clin Health Psychol. 2022;22(3):100320.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Sutin AR, Luchetti M, Stephan Y, Terracciano A. Meaning in life and risk of cognitive impairment: a 9-Year prospective study in 14 countries. Arch Gerontol Geriatr. 2020;88:104033.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Ngamaba KH, Panagioti M, Armitage CJ. Income inequality and subjective well-being: a systematic review and meta-analysis. Qual Life Res. 2018;27(3):577–96.

    Article  PubMed  Google Scholar 

  61. Zhou H, Long L. Statistical remedies for common method biases. Adv Psychol Sci. 2004;12(06):942–942.

    Google Scholar 

  62. Wang X, Qiao Y, Wang S. Parental phubbing, problematic smartphone use, and adolescents’ learning burnout: a cross-lagged panel analysis. J Affect Disord. 2023;320:442–9.

    Article  PubMed  Google Scholar 

  63. Chen FF. Sensitivity of goodness of fit indexes to lack of Measurement Invariance. Struct Equation Modeling: Multidisciplinary J. 2007;14(3):464–504.

    Article  Google Scholar 

  64. Lv S, Wang H. Cross-lagged analysis of problematic social media use and phubbing among college students. BMC Psychol. 2023;11(1):39.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Rutkowski L, Svetina D. Assessing the Hypothesis of Measurement Invariance in the context of large-scale international surveys. Educ Psychol Meas. 2013;74(1):31–57.

    Article  Google Scholar 

  66. Kim GS, Kim N, Won CW, Shim MS, Park MK, Kim M, Lee S. Cross-lagged panel analysis between physical Frailty, cognitive function, and Falls by Sex. J Am Med Dir Assoc. 2023;24(10):1541–e15481541.

    Article  PubMed  Google Scholar 

  67. Wang X, Zhang D, Wang J-L. Dual-factor model of Mental Health: surpass the traditional Mental Health Model. Psychology 2011, 2.

  68. Steger M, Oishi S, Kashdan T. Meaning in life across the life span: levels and correlates of meaning in life from emerging adulthood to older adulthood. J Posit Psychol. 2009;4:43–52.

    Article  Google Scholar 

  69. Hadden B, Smith C. I gotta say, today was a good (and meaningful) day: daily meaning in life as a potential Basic Psychological need. J Happiness Stud 2019, 20.

  70. Miao M, Gan Y. How does meaning in life predict proactive coping? The self-regulatory mechanism on emotion and cognition. J Pers. 2019;87(3):579–92.

    Article  PubMed  Google Scholar 

  71. Fredrickson BL. Chapter One - Positive Emotions Broaden and Build. In: Advances in Experimental Social Psychology. Volume 47, edn. Edited by Devine P, Plant A: Academic Press; 2013: 1–53.

  72. Sin NL, Lyubomirsky S. Enhancing well-being and alleviating depressive symptoms with positive psychology interventions: a practice-friendly meta-analysis. J Clin Psychol. 2009;65(5):467–87.

    Article  PubMed  Google Scholar 

  73. Halama P. Meaning in Life and Coping: Sense of Meaning as a Buffer Against Stress. In: Meaning in Positive and Existential Psychology edn. Edited by Batthyany A, Russo-Netzer P. New York, NY: Springer New York; 2014: 239–250.

  74. Krok D. Sense of coherence mediates the relationship between the religious meaning system and coping styles in Polish older adults. Aging Ment Health. 2016;20(10):1002–9.

    Article  PubMed  Google Scholar 

  75. Zhang Y, An H, Xu L, Tao N. Relationship between depression, the family environment, and the coping styles of military recruits: a cross-section study. Med (Baltim). 2020;99(38):e22027.

    Article  Google Scholar 

  76. Kang Y, Strecher VJ, Kim E, Falk EB. Purpose in life and conflict-related neural responses during health decision-making. Health Psychol. 2019;38(6):545–52.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Park N, Park M, Peterson C. When is the search for meaning related to life satisfaction? Appl Psychology: Health Well-Being. 2010;2:1–13.

    Google Scholar 

  78. Steger M, Frazier P, Oishi S, Kaler M. The meaning in Life Questionnaire: assessing the Presence of and search for meaning in life. J Couns Psychol 2006, 53.

  79. Burrow AL, O’Dell AC, Hill PL. Profiles of a developmental asset: youth purpose as a context for hope and well-being. J Youth Adolesc. 2010;39(11):1265–73.

    Article  PubMed  Google Scholar 

  80. Steger MF, Kawabata Y, Shimai S, Otake K. The meaningful life in Japan and the United States: levels and correlates of meaning in life. J Res Pers. 2008;42(3):660–78.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank all participants for their contribution to this study.

Funding

This work was supported by the National Social Science Foundation of China (No. 2022SKJJC040).

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Author notes

  1. Bin Liu and Mingxuan Zou contributed equally to this work.

Authors and Affiliations

  1. Department of Military Medical Psychology, Air Force Medical University, Xi’an, 710032, China

    Bin Liu, Mingxuan Zou, Qun Yang & Fengzhan Li

  2. Public Health School, Shaanxi University of Chinese Medicine, Xi’an, 712046, China

    Mingxuan Zou

  3. Frontier Medical Service Training Brigade, Army Medical University, Hutubi, 831200, China

    Hongxiang Bao

  4. Air Force Bureau of Trainee Pilot Selection (Nanjing Central Division), Nanjing, 210018, China

    Xiang Xu

  5. Department of Psychology, NO. 986 Hospital of Air Force, Xi’an, 710054, China

    Xiaohui Liu

  6. 1st Group of the Sixth Regiment, First Training Base of Air Force Aviation University, Changchun, 130022, China

    Bing Zhang

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Contributions

BL and MXZ designed of the study, collected and analyzed the data, interpreted the study results, drafted, revised, and approved the final manuscript. HXB, XX, XHL, and BZ collected the data, conducted preliminary data analysis, revised and approved the final manuscript. QY and FZL conceived and designed the study, revised and approved the final manuscript. All authors read and approved the final study manuscript.

Corresponding authors

Correspondence to Qun Yang or Fengzhan Li.

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Ethics approval and consent to participate

This study has been reviewed and approved by the Ethics Committee of the First Affiliated Hospital of the Fourth Military Medical University (No.KY20202063-F-2). Informed consents were obtained from all participants for this study.

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Not applicable.

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The authors declare no competing interests.

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Liu, B., Zou, M., Bao, H. et al. Mental health and meaning in life in Chinese military personnel: a cross-lagged analysis. BMC Psychol 12, 426 (2024). https://doi.org/10.1186/s40359-024-01932-1

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BMC Psychology

ISSN: 2050-7283

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