Interaction of Depressive Status and Cognitive Ability Predicts Psychological Resilience of Young Adults in Taiwan

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Interaction of Depressive Status and Cognitive Ability Predicts Psychological Resilience of Young Adults in Taiwan

https://doi.org/10.21203/rs.3.rs-2437174/v1

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Associations among cognitive ability, depressive symptoms, and psychological resilience have been found, but the interaction among these variables remains unclear, especially for young adults. The current study aimed to investigate how these variables interact in young adults in Taiwan. A total of 192 participants (97 female) with a mean age of 21.84 years (range 19–30 years) were analyzed for this study. Participants’ cognitive ability was assessed by the Taiwanese version of the Montreal Cognitive Assessment. Depressive status was evaluated by the revision of Beck Depression Inventory-II. Participants with a score of 14 or above were defined as mild-to-severe-depressed (MSD). Otherwise, they were defined as minimal-depressed (MD). For the psychological resilience measurement, a Chinese version of the Resilience Scale for Adults (RSA) was used. A linear regression model was applied to investigate the interaction of cognitive ability and depressive status on psychological resilience after adjusting for the covariates of gender and age. The interaction of BDI-II and MoCA was significantly associated with the RSA score (B = -6.519, p = .044) and other effects were not significant. The results indicated that a negative relationship between cognitive ability and psychological resilience was only observed in MSD young adults but not in MD. This study had a limited number of participants in the MSD group. Young adults with higher cognitive ability reported lower psychological resilience when they had mild-to-severe depression. In contrast, cognitive ability does not relate to psychological resilience among young adults with minimal depression.

Health sciences/Health care/Quality of life

Biological sciences/Psychology/Human behaviour

Depression

Cognitive ability

Resilience

Young adults

Mental health.

In Taiwan, people in early adulthood (around the age of 20 to 30) encounter a number of issues when graduating from school, beginning full-time jobs, and taking responsibility for their own life. During this transition period, they invariably experience stressful events. For example, making crucial and important life decisions regarding intimacy, marriage, family, and other major commitments involving career and life goals. People encountering these stressful events may experience problems in their mental health or existing problems may worsen into psychiatric disorders ¹. For example, if an individual has trouble managing feelings of stress, they are likely to suffer from mental illness, such as anxiety ² or depression ³. It is therefore important to help young adults develop psychological resilience, an important factor that can determine an individual's psychological recovery from stressful experiences ⁴.

Although the definition of psychological resilience remains inconsistent, recent research suggests that psychological resilience is a dynamic process that attenuates or disrupts the adverse effects of traumatic event ⁵. This process plays a crucial role in the prognosis of stress-related psychiatric disorders as well as the maintenance of mental health during stressful events ^6,7. Low psychological resilience is associated with several mental health problems, such as anxiety, depression, and stress ^8–10. In contrast, people with high psychological resilience adapt well and maintain a high level of psychological function even after the exposure to severely risky experiences ¹¹. Understanding the contexts in which young adults can maintain good psychological resilience can provide them or a professional helper with a direction for working through adversity caused by stressful events during this transition period ¹².

Recently, an increasing number of studies have sought to understand the relationship between individuals’ cognitive abilities and psychological resilience. Wolf, et al. ¹³ conducted a longitudinal study of cognitively healthy elderly individuals in Germany and found that individuals with lower resilience capacities (measured by educational attainments, which is the highest level of education that an individual has completed) exhibited stronger amyloid-related cognitive decline. In South Korea, researchers differentiated the degree of cognitive abilities between resilient individuals and non-resilient individuals in cross-sectional and longitudinal settings ^14,15. They defined the “resilient group” as the participants who had at least one negative experience without any depressive syndromes in the past two weeks, and those who did not report any negative experience and had no depression were designated as the “reference group”. They used the Mini-Mental State Examination MMSE, an index of cognitive ability; ¹⁶ to evaluate an individual’s general cognitive ability (i.e., visuospatial, executive functioning, naming, memory, attention, language, abstraction, and orientation). The results demonstrated that the resilient group showed high MMSE scores compared to the reference group regardless of their age ¹⁵. In addition to finding an association between general cognitive ability and resilience, several studies have found a positive correlation between resilience and specific cognitive components (i.e., working memory, WM, or executive function) in people who experience adverse situations ¹⁷. However, a recent study by Bemath, et al. ¹⁸ found a null relationship between individuals’ cognitive abilities and psychological resilience when they investigated the role of working memory in the resilience of South African emerging adults from disadvantaged backgrounds. In general, the association between general cognitive ability and resilience has been established, despite inconsistent findings in the examination of the association between resilience and working memory.

There are several factors that could explain the inconsistent findings. First, studies vary in how they define and measure an individual’s resilience, such as a participant’s education attainments ¹³, and participants experienced negative events without depression ^14,15. Second, some studies focused on adults (ages 30 to 64) in adverse circumstances ^14,15, and findings from these studies may not be generalized to young adults (age of 20 to 30). Finally, the relationship between resilience and general cognitive function has been found to be contingent upon individuals’ depressive status ¹⁵ measured by the Beck's Depression Inventory II BDI-II, an index of one’s depressive status; ¹⁹.

To investigate the relationship between cognitive ability and resilience, we conducted this study with three different approaches from the previous studies. First, since resilience is considered a dynamic process and conceptualized at multiple levels ⁵, an individual's resilience should be conceptualized and measured in multiple aspects together. We therefore measure resilience using the Resilience Scale for Adults (RSA) ²⁰, a valid and reliable measurement that captures an individual’s resilience in six aspects including, (1) perception of the self, (2) planned future, (3) social competence, (4) family cohesion, (5) social resources, and (6) structured style ^20–22. Second, previous studies have shown that one’s adverse experience would influence their cognitive ability, including events associated with high social and family risks ²³, low socioeconomic status ²⁴, and environmental safety ²⁵, and maternal depression ²⁶. Thus, in the current study, we recruited young adults and examined the relationship between resilience and cognitive ability regardless of their exposure to adverse circumstances. Third, since previous studies have demonstrated that depression was negatively correlated with resilience ^27,28 and the depressive symptoms was a predictor of resilience ²⁹, we stratified the analysis by groups of different depressive statuses in young adults to investigate how depressive status modulates the association between cognitive ability and resilience. While we expect that depressive status is negatively associated with resilience and that cognitive ability is positively associated with resilience, we also expect that individuals’ depressive status and their cognitive ability will have an interactive effect in predicting their resilience.

In sum, this study had two main purposes. First, the study aimed to measure psychological resilience directly using an existing measurement and recruited young adults to investigate the association between cognitive ability and psychological resilience in this population. Second, to understand under what circumstances young adults can resist adversity caused by stressful events during this transition period, how cognitive ability and depressive status interact to predict an individual’s psychological resilience was investigated.

2.1 Participants

This study recruited a total of 208 participants from the National Cheng Kung University community through online advertisement. The study was conducted in accordance with the Helsinki Declaration as revised in 1989. Ethical approval for this study was obtained from the Ethics Committee of the Department of Psychology at National Cheng Kung University (ethics code 108 − 072) (Tainan, Taiwan), and all experimental protocol was carried out in accordance with relevant guidelines and regulations. All participants were well informed of the details and risks of this study and signed written consent. Participants received feedback of NT$ 160 per hour after finishing the whole experiment. Additionally, 16 participants were excluded from further statistical analysis due to missing data or invalid answers (i.e., unrecognizable responses). Therefore, 192 participants (97 females) were included in the current study, and they had a mean age of 21.84 ± 1.99 years (range 19–30 years).

2.2 Measurement of depressive status

In this study, depressive status was measured with the revised Beck’s Depression Inventory-II (BDI-II) ¹⁹, which was consistent with that used by Yang, et al. ¹⁵ in their study. BDI-II was revised in 1996 in response to the publication of DSM-IV which changed the diagnostic criteria for Major Depressive Disorder. The BDI-II contains 21 items on a 4-point scale from 0 (symptoms absent) to 3 (severe symptoms). A score of 0–13 indicates minimal depression, and a score of 14 or above indicates mild-to-severe depression. The BDI-II is a reliable and validated measure of depression with a high level of internal consistency (α = .91) ³⁰.

2.3 Measurement of general cognitive ability

In this study, the Montreal Cognitive Assessment (MoCA) was used instead of the MMSE used by Yang, et al. ¹⁵ in their study to measure the participants’ cognitive ability. The MoCA has been widely identified as superior to the MMSE in the detection of mild cognitive impairment ³¹ and is still widely used in recent studies to assess the cognitive ability ^32,33. Furthermore, the MoCA showed differences in cognitive profiles, even in those performing in the normal range on the MMSE ³⁴. Thus, more variances among our participants were identified. The MoCA is a 30-point test that can be completed in approximately 10 minutes. There are 8 tasks in this assessment, and each task evaluates different domains of cognitive ability, including visuospatial, executive functioning, naming, memory, attention, language, abstraction, and orientation. The assessment is a validated scale with a Cronbach’s α score of .903 that represents high reliability ³⁵.

2.4 Measurement of psychological resilience

In this study, we would like to realize an individual’s current resilient state, so we used the traditional Chinese version of the Resilience Scale for Adults (RSA) to be a measurement of an individual’s resilience that has been widely used in the recent studies across different regions ^36–38. It is a self-reporting measurement evaluating six different domains of resilience in adults: (1) Perception of the Self, (2) Planned Future, (3) Social Competence, (4) Family Cohesion, (5) Social Resources, and (6) Structured Style ^20–22. It is a reliable scale with Cronbach’s α scores ranging from .67 to .81, and .88 for the total score. The stability of the scale was also verified by a test re-test with Pearson r scores ranging from .73 to .80, and .84 for the total score ³⁹.

2.5 Statistical analysis

Descriptive and inferential analyses were completed using IBM SPSS Statistics (Version 22.0). The purpose of this study was to explore how depressive status and cognitive ability interact to influence the psychological resilience of young adults; thus, a linear regression model was used to test this interaction effect. Participants’ gender and age were used as covariates, which were added along with the independent variables, as predictors in the linear regression analysis. A p-value less than 0.05 was considered statistically significant for all analyses.

Participants with a BDI-II score less than 14 were defined as minimal-depressed (MD). Otherwise, they were defined as mild-to-severe-depressed (MSD) (Beck et al., 1996). The research examined the differentiation of the association between cognitive ability and psychological resilience between the two depression groups. Participants in the MD group were coded as 0, and the participants in the MSD group were coded as 1. Two linear regression models were tested in the current study, and the statistical diagrams of these two models are shown in Fig. 1. The first model examined how BDI-II and MoCA scores are associated with the RSA score. For the second model, how the interaction of the BDI-II score and MoCA score are associated with the RSA score was examined.

In this study, data was collected from 192 participants (97 female), with a mean age of 21.84 ± 1.991 years. Table 1 summarizes the demographic characteristics, as well as the data collected from the participants. Table 2 displays the correlation among the observed variables. The relationships between RSA scores and MoCA scores of the MD group and MSD group are represented in Fig. 2.

The standardized results in model one showed that the BDI-II score negatively influenced the RSA score (β=-.407, SE = 3.987, p < .001, 95% CI [-32.181, -16.449]). However, the MoCA score had no significant effect on the RSA score (β=-.014, SE = 1.102, p = .834, 95% CI [-2.406, 1.944]). The linear regression results are summarized in Table 3.

In the non-standardized results of Model 2, the interaction of BDI-II score and MoCA score (represented as the product of the scores of these two variables) negatively influenced the RSA score (B=-6.519, SE = 3.218, p = .044, 95% CI [-12.867, -0.171]). Nevertheless, the RSA score was not significantly influenced by the MoCA score (B = .586, SE = 1.165, p = .615, 95% CI [-1.713, 2.886]) or the BDI-II score (B = 160.979, SE = 91.552, p = .080, 95% CI [-19.635, 341.594]). The linear regression results are summarized in Table 3.

This is the first study to use linear regression models to investigate the effect of the interaction of cognitive ability and depressive status on psychological resilience in young adults. The hypotheses were generally supported. The results showed that depressive status was negatively associated with psychological resilience, whereas cognitive ability was not associated with psychological resilience (see Table 3, Model 1). More importantly, the interaction of cognitive ability and depressive status was significantly associated with psychological resilience (see Table 3, Model 2), and the results suggested that cognitive ability was negatively correlated with psychological resilience when participants encountered mild-to-severe depression, while the psychological resilience of participants with minimal depression remained consistent regardless of their cognitive ability. The results underscore the critical role of the interaction of cognitive ability and depressive status in evaluating psychological resilience in young adults.

Most studies in elderly (60 years or older) groups ⁴¹ and patient groups ⁴² have demonstrated an inverse relationship between depression and resilience. A few studies using adults with no mental illness have also found this inverse relationship. Petros, et al. ⁴³ used the 25-item Connor-Davidson Resilience Scale CD-RISC; ⁴⁴ and the 10-item Center for Epidemiologic Studies Depression Scale CES-D-10; ⁴⁵ to separately assess resilience and depressive symptoms in non-clinical adults. Their results showed that resilience was inversely associated with depressive symptoms. In the current study, although the focus was on young adults (from ages 20 to 30) and different types of measurement tools (RSA and BDI-II) were used to assess resilience and depressive status, a strong inverse relationship was still found. The current findings reinforce previous findings that depression is inversely associated with resilience, regardless of an individual's age or physical health.

Recent studies considering the association between cognitive ability and resilience have produced inconsistent findings. For example, some studies have shown that resilience is positively associated with general cognitive ability ^13,46 or specific cognitive components ¹⁷, but Bemath, et al. ¹⁸ found no association between cognitive ability and resilience. The inconsistent findings may result from these studies defining an individual’s resilience by using single index (e.g., participant’s education attainments ¹³, participants showed no depression when experiencing the negative events ^14,15 and focusing on adults who experienced adverse events in their childhood where their cognitive abilities may be influenced. In the current study a self-report measurement tool (RSA) was used to define an individual’s resilience, and adults were recruited without experiencing adverse events. The results show that one’s cognitive ability was not correlated with their resilience. This finding suggests that the previous studies that considered the correlation between cognitive ability and resilience might be confounded by the correlation between their experience of adverse events in their childhood and their depressive status when adverse events were experienced. Once the experience of adverse events and depressive status were controlled, the relationship between cognitive ability and resilience vanished.

Yang, et al. ¹⁵ found that the association between cognitive ability and resilience differed significantly across different genders, with resilient males showing a significant association between cognitive ability and resilience, while no significant association was found in resilient females. They provided several possible explanations to justify this finding, such as different depressive statuses were found in different resilient genders, or different characteristics of resilience were found in the male resilience group and the female resilience group (e.g., males chose social experiences as a negative life event, while females tended to select items about personal experiences). In the current study, two methods were used to avoid confounding results with the gender variable. First, the relationship between cognitive ability and resilience in different depressive status groups by using gender as a covariate to avoid the influence of gender effects was examined. Second, an identical measurement tool (e.g., RSA) to assess resilience across genders was used. Thus, resilience assessments were not affected by gender-specific characteristics (e.g., social experiences and personal experiences). When controlling for gender-related variables, the findings suggest that the association between an individual’s cognitive ability and resilience was modulated by depressive status, with a negative association when the individual had mild-to-severe depression, and no association when the individual exhibited only mild depression.

According to the results of the current study, the association between depressive status and resilience was not statistically significant (p = .08) when considering the interaction effect of cognitive ability and depressive status. This finding was inconsistent with most previous findings suggesting an inverse association between depression and resilience ^41,42. The nonsignificant result may be due to the different number of samples of the two groups with different depressive statuses, with the MD group (N = 155) having a larger sample size than the MSD group (N = 37). This finding needs to be further examined in future studies using an equivalent number of samples between these two groups.

This study has a number of limitations. First, as mentioned above, the sample size of the MSD group was much smaller than the sample size of the MD group. Further research is required with a larger sample size in the MSD group ⁴⁷, equalizing the sample size between the MD group and MSD group, to determine the reliability and validity of this regression model. Second, the current research focuses on young adults, and the findings are difficult to generalize to other age groups. Future studies could recruit individuals of different ages to validate this regression model and make comparisons between different age groups. Third, only the effect of individual level variables (cognitive ability and depressive status) on an individual's resilience was examined. The current research trend of psychological resilience has focused on conceptualizing resilience at multiple levels, from the biological to the social structural level ⁵. For example, Narayanan ⁴⁸ suggested that low socioeconomic status was a significant predictor of resilience. Further research should include dimensions ranging from the individual level to the larger social context to examine how these variables influence an individual’s resilience. Finally, the constructs we choose in the current study (cognitive ability, depressive symptoms and psychological resilience) can be differentiated into different categories. For example, cognitive ability can be grouped into distinct cognitive components (such as attention, memory, and executive function) ⁴⁹ or non-inclusive categories (such as rational evaluation or irrational rumination of information) ⁵⁰; depressive symptoms can be caused by different situations, such as those related to failing to achieve someone else's goals or failing to achieve one's own defined goals ³; resilience can either be hopeful or not ⁵¹. Whether psychological resilience holds promise depends on how individuals interpret the threats they encounter. Future studies could include the type of above-mentioned differentiations that can be made, and the associations between these structures can be further explored.

In summary, this study is the first to examine the interaction of depressive status and cognitive ability influencing the psychological resilience of young adults. The findings demonstrated that young adults with mild-to-severe depression show low psychological resilience when they have good cognitive ability. In contrast, young adults with minimal depression maintain consistent levels of psychological resilience regardless of the variation in cognitive ability. To extend this model, more levels should be considered in future studies. The current research provides a useful model for professional assistants to help young adults overcome adversity caused by stressful events and remain resilient during this transitional period.

MMSE

Mini-Mental State Examination

RSA

Resilience Scale for Adults

BDI-II

Beck’s Depression Inventory-II

MoCA

Montreal Cognitive Assessment

Minimal-depressed

MSD

Mild-to-severe-depressed

Acknowledgments

We would like to thank co-principle investigators of the Brain Science Project - Prof. Sheng Hsiang Lin, Prof. Joshua Goh Oon Soo, Prof. Meng-Che Tsai, Prof. Yun-Hsuan Chang, Prof. Kuan-Pin Su, as well as all research assistants of the project for their support and insightful comments.

Author Contributions

S. -H Lin: Investigation, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing - review & editing.

T. -Y Huang: Data curation, Writing & editing.

Y. -C Liao: Data curation, Validation, Writing - review & editing.

C. -H Wu: Data curation, Validation, Writing - review & editing.

S. Hsieh: Conceptualization, Funding acquisition, Resources, Project administration, review & editing.

C. -T Yang: Investigation, Conceptualization, Funding acquisition, Resources, Project administration, Validation, Writing - review & editing.

Funding

This research was funded in part by Higher Education Sprout Project, Ministry of Education to the Headquarters of University Advancement at National Cheng Kung University (NCKU) to C.-T.Yang, Ministry of Science and Technology (grant number MOST 108-2321-B-006-022-MY2, 110-2321-B-006-004, and 111-2321-B-006-008) to S. Hsieh and C.-T.Yang, and a faculty research grant of Soochow University College of Science (Official letter Issue No. 1102602326) awarded to S.-H. Lin. In addition, this research was, in part, supported by the Ministry of Education, Taiwan, Republic of China, the Aim for the Top University Project to the National Cheng Kung University (NCKU).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Data availability

The data that support the findings of this study are available from the corresponding author

upon reasonable request. The data sharing adopted by the authors comply with the

requirements of the funding institute and with institutional ethics approval.

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Table 1. Descriptive characteristics of participants (N=192)

Characteristics	All (N = 192)	MD (N = 155)	MSD (N = 37)
Age (years)	21.84 ± 1.99	21.92 2.10	21.51 1.43
Sex
Male	95 (49.5%)	80 (51.61%)	15 (40.54%)
Female	97 (50.5%)	75 (48.39%)	22 (59.46%)
MoCA	28.21 ± 1.46	28.15 1.51	28.46 1.19
BDI-II	8.14± 6.87	5.48 3.92	19.24 5.25
RSA	147.19± 23.62	151.88 21.61	127.51 21.67

Values are presented as N (%) or mean ± SD. (MD: Minimal-depressed; MSD: Mild-to-severe-depressed; MoCA: Montreal Cognitive Assessment; BDI-II: Beck Depression Inventory-II; RSA: Resilience Scale for Adults)

Table 2. Pearson’s correlation coefficients (r) among observed variables (N = 192)

Variable	BDI-II		MoCA		RSA		*MoCABDI-II**
1. BDI-II		—	0.142	*	-0.464	***	0.796	***
2. MoCA		p = 0.049	—		-0.064		0.101
3. RSA		p < .001	p = 0.379		—		-0.414	***
*4. MoCABDI-II**		p < .001	p = 0.165		p < .001		—
Control variable: age, sex; * p < .05, p < .01, * p < .001; the lower panel displays p-value (p); the upper panel gives the corresponding Pearson correlation coefficient, with text size proportional to its absolute value. BDI-II: Beck Depression Inventory-II; MoCA: Montreal Cognitive Assessment; RSA: Resilience Scale for Adults

Table 3. Linear regression coefficients for Models 1 & 2

	Model 1			Model 2
	β	SE	p-value	B	SE	p-value
MoCA	-.014	1.102	.834	.586	1.165	.615
BDI-II	-.407	3.987	.000	160.979	97.552	.08
MoCA*BDI-II	-	-	-	-6.519	3.218	.044

MoCA: Montreal Cognitive Assessment; RSA: Resilience Scale for Adults

No competing interests reported.

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Interaction of Depressive Status and Cognitive Ability Predicts Psychological Resilience of Young Adults in Taiwan

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1 Introduction

2 Materials And Methods

2.1 Participants

2.2 Measurement of depressive status

2.3 Measurement of general cognitive ability

2.4 Measurement of psychological resilience

2.5 Statistical analysis

3 Results

4 Discussion

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