Next Article in Journal
Associations between Muscle-Tendon Morphology and Functional Movements Capacity, Flexibility, and Balance in Older Women
Previous Article in Journal
Digital Economy and Environmental Quality: Insights from the Spatial Durbin Model
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 19
Issue 23
10.3390/ijerph192316098
ijerph-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

A Latent Profile Analysis of PERMA: Associations with Physical Activity and Psychological Distress among Chinese Nursing College Students

by
Meiling Qi
1,2,†,
Qian Sun
3,†,
Xiangyu Zhao
1,
Yiming Gao
1,
Di Zhao
1,
Shiyu Shen
4,
Polat Zayidan
2,
Ziyang Xiu
2 and
Ping Li
1,*
1
School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
2
School of Nursing, College of Xinjiang Uyghur Medicine, Hetian 848099, China
3
School of Physical Education, Shandong University, Jinan 250012, China
4
Jinan Vocational College of Nursing, Jinan 250102, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2022, 19(23), 16098; https://doi.org/10.3390/ijerph192316098
Submission received: 26 October 2022 / Revised: 27 November 2022 / Accepted: 28 November 2022 / Published: 1 December 2022
(This article belongs to the Section Exercise and Health)
Browse Figure
Review Reports Versions Notes

Abstract

:
Background: The wellbeing of college students is an important concern for public health, and may have associations with insufficient physical activity and psychological distress. This study aimed to identify the latent classes of wellbeing based on the PERMA (i.e., positive emotions, engagement, relationships, meaning, and accomplishments) wellbeing framework, and to explore their associations with levels of physical activity and psychological distress. Methods: A cross-sectional online survey was conducted. A latent profile analysis was performed to characterize the different classes of wellbeing of nursing college students. Results: A group of 1741 nursing college students in China completed the study. Three wellbeing classes were identified in the final model (i.e., low-level wellbeing, moderate-level wellbeing, and high-level wellbeing). Significant differences were found between the three classes in terms of gender (p = 0.002) and year of study (p = 0.038). Low levels of physical activity participation were significantly associated with lower odds of being in the high-level wellbeing class compared with the moderate-level wellbeing class (OR = 1.398, 95%CI [1.023, 1.910], p = 0.035). Lower levels of psychological distress were also associated with greater wellbeing among the three wellbeing classes (p < 0.05). Conclusions: Effective strategies are needed to increase college students’ physical activity participation and decrease the severity of psychological distress to improve their health and wellbeing in China.

1. Introduction

Nursing college students often experience high learning pressure, and such life patterns can influence their wellbeing (e.g., psychological distress and depression) [1,2]. Other potential factors, such as a lack of correct family education, increasing fierce competition after graduation, and serious exposure to internet use also adversely affect college students’ mental health [3,4]. In this respect, studies have reported that more than 30% of college students suffer from psychological distress [5]. Furthermore, the existing literature has found that negative wellbeing and mental health are associated with reduced academic function, frustration, poor physical health conditions, and even a high risk of suicidal tendencies [5,6]. One previous study has also described that nursing students experience a higher prevalence of wellbeing disorders than students in other subjects [7]. Therefore, it is important to understand the multidimensional wellbeing of nursing college students in order to develop well-targeted public health interventions and policies and improve their wellbeing.
A growing body of empirical evidence suggests that wellbeing is mainly characterized by positive emotions, engagement, relationships, meaning, and accomplishments constituting a theoretical framework referred to as PERMA [8,9]. Specifically, positive emotions refer to the affective component or feeling well, with engagement referring to a deep psychological connection to a particular activity, relationship referring to social connection, meaning referring to purpose, and accomplishments referring to personal goals [10,11]. Wellbeing and flourishing have been examined using the PERMA wellbeing framework in adult workers [12], cancer survivors [13], and artists [14] across countries such as Korea, China, Brazil, and India. The PERMA wellbeing framework was also used in university contexts to examine the associations between wellbeing and the online learning environment [15], as well as health education [16]. However, these studies considered a single-dimensional approach in explaining the scores of five elements of PERMA wellbeing. Because the PERMA wellbeing profiler is used to calculate the mean scores of the five PERMA wellbeing elements, but not the categorical scores to classify different levels of wellbeing, limited studies have used the PERMA to explore different classes of wellbeing in nursing college students. To address this limitation, latent profile analysis (LPA) was suggested to be used to examine how the five PERMA wellbeing elements interact and to classify different classes of wellbeing of the nursing college students.
Previous studies have suggested that decreasing the psychological distress of nursing college students is critical for prevention and intervention to enhance their overall wellbeing [17]. This is because psychological distress (e.g., anxiety and depression) may contribute to an increased rate of mental disorders that have implications for nursing college students’ educational and career development [1]. In addition, protective factors, such as physical activity participation, are considered as effective approaches to improve nursing college students’ wellbeing [18]. Individuals who engage in regular physical activity are more likely to have an increased sense of wellbeing and a reduction in psychological distress [19]. Given the importance of developing differential interventions to enhance college students’ wellbeing, it is necessary to examine the associations between physical activity participation and psychological distress and different wellbeing classes in this population. Therefore, the first aim of this study was to use the LPA to identify classes of wellbeing based on the five-element PERMA wellbeing framework in Chinese college students. In addition, this study examined the impact of levels of physical activity participation and psychological distress on different classes of wellbeing in this population. This study hypothesized that there would be significant differences in physical activity participation and levels of psychological distress among different wellbeing classes.

2. Materials and Methods

2.1. Study Design

A cross-sectional study using an online survey design was performed in this study. Ethics approval for this study was received from the University Human Research Ethics Committee (2021-R-165). Completion and submission of the online survey implied consent to participate. This was declared to respondents at the commencement of the survey.

2.2. Participants and Recruitment

Using convenience sampling, nursing students from a large medical college in China were invited to participate. All nursing students who were willing to participate in this study were eligible to enroll. An email invitation with the help of the College Deputy Vice Administration Office was sent to all nursing students. The email invitation included the purpose of the study, inclusion and exclusion criteria, and the online survey link (https://www.wjx.cn (accessed on 10 October 2021)) to the questionnaire. A total of 1741 Chinese nursing college students were included for analysis in this study after removing those who reported more than 960 mins of total physical activity or sedentary time per day (n = 184, 9.6%). Participants were aged between 17 and 24 years (M = 19.38; SD = 1.02). Among these participants, most were female (n = 1366, 78.5%), and were in their second year of study (n = 765, 43.9%).

2.3. Data Collection

Data collection took place between 10 October and 30 December 2021. The study survey included participants’ demographic details (i.e., age, gender, and year of study), PERMA-Profiler, International Physical Activity Questionnaire—Short Form (IPAQ-SF), and an assessment of psychological distress.
The PERMA-Profiler Chinese version was used to evaluate individuals’ multidimensional wellbeing [20]. This study used the 15 items of the PERMA-Profiler to assess the five elements of wellbeing (i.e., positive emotions, engagement, relationships, meaning, and accomplishments). Three items assessed each PERMA element, and composite scores were averaged across the three items per element. Each item was scored on a Likert-type scale ranging from 0 to 10 (0 = not at all, 10 = completely; 0 = never, 10 = always; 0 = terrible, 10 = excellent), with higher scores indicating greater wellbeing. This tool demonstrated good internal consistency among Chinese nursing college students in this study (Cronbach’s α = 0.933).
The IPAQ-SF Chinese version was used to assess participants’ physical activity participation and average sitting time on weekdays and weekends during the past seven days [21]. There are two types of IPAQ scores for data processing and analysis: a categorical and a continuous score. The categorical score classified participants into three physical activity intensity levels (i.e., low, moderate, and high). The continuous score is expressed as the metabolic equivalent task (MET minutes per week) of energy expenditure. In addition, participants’ sitting time (i.e., hours per day) was also recorded on the IPAQ-SF. High validity and reliability for the IPAQ-SF have been established among Chinese adults with intraclass correlation coefficients above 0.84 [21].
The 10-item Kessler Psychological Distress Scale (K10), Chinese version, was used to assess psychological distress in the past month [22]. The K10 is a self-reported questionnaire containing ten questions with a score ranging from 1 to 5 to assess participants’ frequency of nonspecific psychological distress across the past month based on questions related to symptoms of anxiety and depression. Participants chose how often they felt or thought in a certain way: 1 = almost never, 2 = sometimes, 3 = fairly often, 4 = very often, and 5 = all the time. The total score was obtained by summing all 10 items, with a total score of 10–50. A score of 15 or less reflected no symptoms of distress, while low distress ranged from 16 to 21, moderate distress ranged from 22 to 29, and high distress ranged from 30 to 50. The K10 scale is a valid instrument with acceptable internal consistency, with Cronbach’s α over 0.954 in this study.

2.4. Statistical Analysis

Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 27.0 and the Mplus 8.3. Based on the data-cleaning rules for the IPAQ-SF, respondents who reported over 960 min of total physical activity or sedentary time per day were identified as over-reporting. The assumption is that individuals spend an average of 8 h of sleep per day [23]. Descriptive statistics were calculated using frequencies (i.e., percentages) for categorical variables and mean and standard deviations for continuous variables.
The LPA was used to determine the optimal number of wellbeing classes based on the PERMA wellbeing framework among Chinese nursing college students. Starting from the initial model (one category), the number of categories in the model is gradually increased until the model fits the data optimally. The optimal model was determined by a comprehensive consideration of fit indicators and theoretical values. The model fit indicators are the Log-likelihood test, Akaike’s information criterion (AIC), Bayesian information criterion (BIC), sample-size-adjusted Bayesian information criterion (ssaBIC), entropy (>0.8 is acceptable), and Lo–Mendell–Rubin (LMR), and the bootstrapped likelihood ratio test (BLRT). The smaller AIC, BIC, and ssaBIC are more desirable and represent the models with better fit and which are more parsimonious. Additionally, the sample size requirement was considered in the LPA, with a sample size of more than 5% in each class.
Differences in demographic characteristics and the five PERMA elements among the wellbeing classes within the final model were compared using analysis of variance (ANOVA) (i.e., age, PERMA elements) and chi-square tests (i.e., gender and year of study). Furthermore, multinomial logistics regression analyses were conducted to assess the association of levels of physical activity participation and psychological distress with the latent classes. Covariates (i.e., gender, year of study) with p values of <0.05 were included in the multinomial logistics regression. The significance level was set at 0.05.

3. Results

A majority of the participants had engaged in either moderate (n = 881, 50.6%) or high (n = 385, 22.1%) levels of physical activity in the past week. Almost half of the participants had reported no psychological distress in the past month (n = 769, 44.2%). The average scores of participants’ psychological distress scores and sitting time per day during workdays and weekdays were 18.67 (SD = 8.0), 6.56 (SD = 2.80), and 5.41(SD = 3.08), respectively. Additionally, participants’ average scores of the five PERMA wellbeing elements were more than 6.26 (SD range = 1.89–2.11) for each element (see Table 1).
Table 2 displays the fit statistics of latent classes of the PERMA wellbeing of Chinese nursing college students. LL, AIC, BIC, and adjusted BIC continued to decrease with an increase in the number of latent classes. The LMR test was not significant for the 5-class, indicating that the 5-class solution did not fit the data better than the 4-class solution. The model identification and entropy value indicated that the 3- or 4-class models were most suitable. This study selected a 3-class model considering the sample size of each class being > 5%, a high entropy value, and higher model identification in a 3-class model than a 4-class model. Based on the parsimony and interpretability of the classes, a 3-class model was selected.
There are significant differences in the five PERMA wellbeing elements across the three latent classes (p < 0.001) (see Table 3). The 1-class (5.4%) was labeled as low-level wellbeing, with the lowest mean scores of the five PERMA elements (M range = 1.91–2.42, SD range = 1.39–1.81). The 2-class made up 51.2% of the overall sample and was labeled as moderate-level wellbeing, as the mean scores of the five elements of PERMA in class 2 were in a middle level (M range = 5.31–6.22, SD range = 1.03–1.28). The 3-class (43.4%) was labeled as high-level wellbeing, with the highest mean scores of the five PERMA elements (M range 7.69–8.70, SD range = 1.02–1.36). The latent classes of PERMA wellbeing are shown in Figure 1.
Table 3 also describes differences in the three wellbeing classes on participants’ characteristics. No significant differences were found between the three classes in terms of age. However, compared to participants with low-level wellbeing, participants with moderate- and high-level wellbeing were more likely to be females (78.13 and 80.53 vs. 64.89%, p = 0.002), and less likely to be in the second year of study (43.18 and 44.47 vs. 46.81%) and third year of study (23.34 and 27.76 vs. 29.79%).
Table 4 shows the associations between levels of physical activity participation and psychological distress with the three wellbeing classes after adjusting for covariates (i.e., gender and year of study). When comparing the high-level wellbeing class relative to the moderate-level wellbeing class, having no distress (OR = 0.109, 95%CI [0.075, 0.160], p < 0.001) or low distress (OR = 0.296, 95%CI [0.199, 0.440], p < 0.001) was significantly associated with higher odds of being in the high-level wellbeing class. Adversely, engaging in a low level of physical activity was significantly associated with lower odds of being in the high-level wellbeing class (OR = 1.398, 95%CI [1.023, 1.910], p = 0.035).
When comparing the low-level wellbeing class relative to the high-level wellbeing class, physical activity participation did not differ significantly between the two classes. However, there was a trend that no distress (OR = 0.131, 95%CI [0.071, 0.242], p < 0.001), low distress (OR = 0.208, 95%CI [0.103, 0.419], p < 0.001) and moderate distress (OR = 0.408, 95%CI [0.188, 0.886], p = 0.024) were associated with increased odds of being in the high-level wellbeing class relative to the low-level wellbeing class.

4. Discussion

To our knowledge, this is the first study that has classified the latent classes of wellbeing using the PERMA wellbeing framework and measured associations between these wellbeing classes and levels of physical activity participation and psychological distress in Chinese nursing college students. Three latent classes were identified among nursing college students, including the low-level wellbeing class, moderate-level wellbeing class, and high-level wellbeing class.
This study demonstrated a significant difference in gender among the three wellbeing classes, which is in line with recent studies that the level of wellbeing among male students was lower than that among female students [24,25]. One potential reason suggested was that females report a higher frequency of online health information searching for health data and nutrition information, while males are more interested in smoking and online games via online health applications. Importantly, a higher percentage of participants in their second and third year of study seem to experience low-level wellbeing compared to moderate- and high-level wellbeing. This finding is not consistent with a similar study which indicated that senior students may accumulate more health information and enhanced health awareness than junior students to promote their health and wellbeing [24]. Specific reasons for these differences may be attributed to different major backgrounds of students and assessment tools of wellbeing. The implementation of clinical curriculum programs for nursing students in their second and third year of study may also contribute to the high prevalence of low-level wellbeing because of the risk of failure for nursing students in a professional clinical course [26]. In addition, increasing fierce competition after graduation may be a potential factor reducing the second-year and third-year nursing college students’ wellbeing [3]. Considered together, these findings suggest the implementation of health education among nursing college students may be an effective strategy to improve their wellbeing.
Although studies have demonstrated the benefits of physical activity on the health and wellbeing of college students [19,27], there was an increase in the physical inactivity and sedentary time in this demographic found in the current study. This study found that 27.3% of college students reported lower levels of physical activity participation. There are several potential factors that may contribute to insufficient physical activity in college students, such as prolonged sitting time, low awareness of the beneficial effects of physical activity, and lack of time and motivation [19,27]. This study also found that the average sitting time of college students was more than 6 h per day during workdays. Similar prolonged sedentary sitting time was also found in individuals in the university workplaces [28,29]. Previous studies have indicated that insufficient physical activity participation has the potential to decrease academic engagement and behavior among college students, and prolonged sitting time is also associated with high levels of psychological distress [30,31]. It is, therefore, important to increase levels of physical activity participation and decrease sedentary sitting time in the design of effective interventions for the health and wellbeing of nursing college students.
This study found that low levels of physical activity participation were associated with low levels of wellbeing among the moderate- and high-level wellbeing classes of nursing college students. The positive association between low levels of physical activity participation and wellbeing implies that insufficient physical activity participation may be a potential risk factor in developing wellbeing. Low physical activity participation may contribute to a low level of quality of life, academic performance, and mental health, which are positively associated with wellbeing [31,32]. Furthermore, a sedentary lifestyle was positively associated with students’ inactivity and long screen time, which have been identified as major public health issues that increase the risk of mental health problems (e.g., depression and anxiety) of college students [33]. Knowledge of the association between physical activity participation and wellbeing could help target interventions and direct resources to the college students [19]. Given the potential adverse effects of insufficient physical activity, there is a need to pay more attention to those nursing college students who engage in low levels of physical activity.
This study also found that moderate-to-high psychological distress accounted for 31.4%, which is to some extent in accordance with results of previous studies which found almost 24–35% of college students suffered from psychological issues, such as depression and anxiety [10,24]. A high level of psychological distress can result in a decline in college students’ quality of life, which may contribute to low levels of wellbeing [19]. However, only 5.1% of the nursing students reported low-level wellbeing in this current study. These findings suggest that other beneficial factors may reduce the risk of psychological distress and then positively influence nursing students’ wellbeing; for example, a high percentage of participants had moderate and high levels of physical activity participation in this current study (72.7%). Interestingly, compared with physical activity participation, the severity of psychological distress may be a more serious factor that influences college students’ wellbeing, as significantly negative associations between levels of psychological distress and the three latent classes were found. The results of the relationship between psychological distress and wellbeing are consistent with recent studies which indicated that negative emotion had a direct influence on early adults’ PERMA wellbeing elements [34,35]. This suggests that stress disorder syndrome was a potential predictor of low sleep health and sleep behavior, which may in turn influence wellbeing and quality of life. Another study also indicated that psychological distress can have an influence on the psychosocial functioning of quality of life and further reduce wellbeing [19]. Hence, relevant programs to reduce college students’ psychological distress are recommended to enhance their health and wellbeing in future studies.
Some limitations of this study should be considered. Firstly, some basic information about students, such as family background and education, were not investigated in this study, as students’ family background may have the potential to influence their wellbeing as indicated in the introduction chapter. Secondly, the gender distribution, with most respondents being females in this study, also limits the generalizability of the study results. Thirdly, using self-reported measures may also be a study limitation, as self-reported outcomes can lower the accuracy of the data and further affect the latent class results. Fourth, this current study is a convenience sample of nursing college students and is not representative of college students. Fifthly, this study enrolled nursing students, and group differences in the study variables between nursing students and students in other subjects are still unclear. Future studies might need to be conducted to compare different groups of wellbeing classes of students in other subjects and nursing and examine their associations with psychological distress and physical activity.

5. Conclusions

The LPA identified three classes of wellbeing based on the five elements of the PERMA wellbeing framework among Chinese nursing college students, including low-level wellbeing, moderate-level wellbeing, and high-level wellbeing. Considering the gender differences as the covariation, low levels of physical activity participation were associated with low levels of wellbeing between the moderate-level and high-level wellbeing classes. Furthermore, there were negative correlations between the levels of psychological distress and wellbeing among the three wellbeing classes of Chinese nursing students. These findings suggest that practice strategies to increase nursing college students’ physical activity participation and reduce the severity of their psychological distress may be effective to promote their health and wellbeing.

Author Contributions

M.Q.: Conceptualization, data curation, formal analysis, writing—original draft, and writing—review and editing. Q.S.: Conceptualization, data curation, formal analysis, and writing—original draft. X.Z.: Data curation, formal analysis, and writing—review and editing. Y.G.: Data curation, data interpretation, and writing—review and editing. D.Z.: Investigation, software, and writing—original draft. S.S.: Conceptualization, writing—review and editing, and visualization. P.Z.: Investigation, software, and writing—original draft. Z.X.: Investigation, software, and writing—original draft. P.L.: Writing—review and editing, visualization, supervision, and project administration All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Nature Science Foundation of China (grant number: 82272923) and the Shandong Province Social Science Planning Foundation (grant number: 21CSZJ30).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by Shandong University Human Research Ethics Committee (2021-R-165).

Informed Consent Statement

Completion and submission of the online survey implied consent to participate. This was declared to respondents at the commencement of the survey.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mindi, N.T.; Pa, H.; Anna Kawennison, F.; Perez-Chavez, J. College Student Psychological Distress: Relationship to Self-Esteem and Career Decision Self-Efficacy Beliefs. Career Dev. Q. 2019, 67, 282–297. [Google Scholar] [CrossRef]
  2. Mu, Y. A preliminary study on the cultivation Strategy of College students’ Health Psychology based on innovative ideological and political Education. Front. Educ. Res. 2019, 2, 149–154. [Google Scholar]
  3. Bi, W. Analysis on the Effect of Calisthenics Cooperative Innovation Teaching on College Students’ Mental Health. Front. Educ. Res. 2020, 3, 28–30. [Google Scholar] [CrossRef]
  4. Choi Gui, Y.; Ko Young, M.; Lee Sung, H. Influences of Factors Promoting Cigarette Smoking, Smoking Cognition, and Health Behaviors on Smoking among College Students: Gender Differences. Int. J. Adv. Nurs. Educ. Res. 2017, 1, 137–142. [Google Scholar] [CrossRef]
  5. William, G.; Julien, S.B.; Bruno, P.; Guay, F. Predicting college students’ psychological distress through basic psychological need-relevant practices by teachers, peers, and the academic program. Motiv. Emot. 2021, 45, 436–455. [Google Scholar] [CrossRef]
  6. Ahmed Abudallh, A.; Dheyaa Kadhim, J.; Mohammed, F. Effectiveness of social phobia on psychological Well-Being of Thi-Qar nursing college student. Indian J. Public Health Res. Dev. 2018, 9, 1168. [Google Scholar] [CrossRef]
  7. Belingheri, M.; Pellegrini, A.; Facchetti, R.; De Vito, G.; Cesana, G.; Riva, M.A. Self-reported prevalence of sleep disorders among medical and nursing students. Occup. Med. 2020, 70, 127–130. [Google Scholar] [CrossRef]
  8. Jonathan, D.B.; Matthew, P.I.; Aaron, J.; Karena, J.B.; Agteren, J.v. Evaluating the Psychometric Properties of the PERMA Profiler. J. Well-Being Assess. 2021, 4, 163–180. [Google Scholar] [CrossRef]
  9. Seligman, M.E. Flourish: A Visionary New Understanding of Happiness and Wellbeing; Simon and Schuster: New York, NY, USA, 2011. [Google Scholar]
  10. Ascenso, S.; Perkins, R.; Williamon, A. Resounding Meaning: A PERMA Wellbeing Profile of Classical Musicians. Front. Psychol. 2018, 9, 1895. [Google Scholar] [CrossRef]
  11. Carvalho, T.F.d.; Aquino, S.D.d.; Natividade, J.C. Flourishing in the Brazilian context: Evidence of the validity of the PERMA-profiler scale. Curr. Psychol. 2021. [Google Scholar] [CrossRef]
  12. Jimenez William, P.; Hu, X.; Garden, R.; Xiaofei, X. Toward a More PERMA(nent) Conceptualization of Worker Well-Being?:A Cross-Cultural Study of the Workplace PERMA Profiler. J. Pers. Psychol. 2021, 21, 94–100. [Google Scholar] [CrossRef]
  13. Luo, L.; Li, Y.; Zhou, Z.; Yang, S.; Qin, Y.; Peng, H.; Wang, Y.; Li, Z.; Tianqin, Y. Study on the Effect of Positive Psychological Intervention Based on PERMA Model on Perioperative Patients with AIDS Complicated with Breast Cancer. Comput. Math. Methods Med. 2022, 2022, 978122. [Google Scholar] [CrossRef] [PubMed]
  14. Jenkins, L.K.; Farrer, R.; Aujla, I.J. Understanding the impact of an intergenerational arts and health project: A study into the psychological well-being of participants, carers and artists. Public Health 2021, 194, 121–126. [Google Scholar] [CrossRef] [PubMed]
  15. Mustika, R.; Yo Edward, C.; Faruqi, M.; Tsania, Z.R. Evaluating the Relationship Between Online Learning Environment and Medical Students’ Wellbeing During COVID-19 Pandemic. Malays. J. Med. Sci. 2021, 28, 108–117. [Google Scholar] [CrossRef]
  16. Morgan, B.; Laura, S. A ’PERMA’ Response to the Pandemic: An Online Positive Education Programme to Promote Wellbeing in University Students. Front. Educ. 2021, 6, 642632. [Google Scholar] [CrossRef]
  17. Min-Suk, K.; Yun, S.-Y. A Study on the Influence of Nursing College Student’s Service Satisfaction on Moral and Psychological well-being. Indian J. Public Health Res. Dev. 2019, 10, 4374–4380. [Google Scholar] [CrossRef]
  18. Kim, C.; Song, Y.; YooJeong, J. The Effect of College Students’ Physical Activity Level on Depression and Personal Relationships. Healthcare 2021, 9, 526. [Google Scholar] [CrossRef]
  19. Zhang, T.; Xiang, P.; Gu, X.; Melanie, R. College Students’ Physical Activity and Health-Related Quality of Life: An Achievement Goal Perspective. Res. Q. Exerc. Sport 2016, 87, 182–190. [Google Scholar] [CrossRef]
  20. Butler, J.; Kern, M.L. The PERMA-Profiler: A Brief Multidimensional Measure of Flourishing. Int. J. Wellbeing 2016, 6, 1–48. [Google Scholar] [CrossRef] [Green Version]
  21. Lou, X.; He, Q. Validity and reliability of the International Physical Activity Questionnaire in Chinese hemodialysis patients: A multicenter study in China. Med. Sci. Monit. 2019, 25, 9402–9408. [Google Scholar] [CrossRef]
  22. Bougie, E.; Arim, R.G.; Kohen, D.E.; Findlay, L.C. Validation of the 10-item Kessler Psychological Distress Scale (K10) in the 2012 Aboriginal Peoples Survey. Health Rep. 2016, 27, 3–10. [Google Scholar] [PubMed]
  23. IPAQ. IPAQ Scoring Protocol. Available online: https://sites.google.com/site/theipaq/scoring-protocol (accessed on 8 August 2021).
  24. Huang, J.; Zheng, M.; Du, G.; Wei, P.; Shen, X.; Jin, J.; Han, Y.; Zhao, Y.; Yang, L.; Kong, L.; et al. Influence of contest on Chinese college students’ health literacy based on repeated cross-sectional studies. J. Am. Coll. Health 2020, 70, 1500–1507. [Google Scholar] [CrossRef] [PubMed]
  25. Sherine, H.; Masoud, O. Online health information seeking and health literacy among non-medical college students: Gender differences. J. Public Health 2020, 29, 1267–1273. [Google Scholar] [CrossRef]
  26. Rodger, K.S.; Juckes, K.L. Managing at risk nursing students: The clinical instructor experience. Nurse Educ. Today 2021, 105, 105036. [Google Scholar] [CrossRef] [PubMed]
  27. Wilson Oliver, W.A.; Panza Michael, J.; Evans, M.B.; Bopp, M. A Scoping Review on College Student Physical Activity: How Do Researchers Measure Activity and Examine Inequities? J. Phys. Act. Health 2021, 18, 728–736. [Google Scholar] [CrossRef]
  28. Qi, M.; Moyle, W.; Jones, C.; Weeks, B. Physical Activity and Psychological Well-Being in Older University Office Workers: Survey Findings. Workplace Health Saf. 2019, 67, 123–130. [Google Scholar] [CrossRef] [PubMed]
  29. Sun, Q.; Qi, M.; Moyle, W.; Jones, C.; Weeks, B.; Xie, Z.; Li, P. Physical Activity Participation and Psychological Wellbeing in University Office Workers in China and Australia: An Online Survey. Healthcare 2021, 9, 1618. [Google Scholar] [CrossRef] [PubMed]
  30. Dick, M.C.I.; Kelly, C.; Timothy, K.B.; Field, J.; Luna, C.; Elizabeth, T. Examining the Relationship between Physical Activity and Student Achievement and Behavior: Results from a Three-Year Intervention. J. Phys. Act. Res. 2018, 3, 109–117. [Google Scholar] [CrossRef]
  31. Jeric Escosio, S.; Saramie Suraya, B. Student Engagement as Influenced by Physical Activity and Student Motivation Among College Students. Int. J. Sports Sci. Phys. Educ. 2022, 7, 28. [Google Scholar] [CrossRef]
  32. Weiwei, X.; Zizhuo, W.; Yue, X. Experimental Research on the Intervention of Physical Education and Health Education on College Students’ Mental Health. Front. Sport Res. 2020, 2, 1–7. [Google Scholar]
  33. Xie, H.; Tao, S.; Zhang, Y.; Tao, F.; Wu, X. Impact of problematic mobile phone use and insufficient physical activity on depression symptoms: A college-based follow-up study. BMC Public Health 2019, 19, 1640. [Google Scholar] [CrossRef] [PubMed]
  34. Young, C.M. Mental and Physical Factors Influencing Wellbeing among South Korean Emergency Workers. Int. J. Environ. Res. Public Health 2020, 18, 70. [Google Scholar] [CrossRef]
  35. Saeideh, H.; Zita, O.; Timothy, R.B.; Robert, W.R. Assessing psychological well-being in early adulthood: Empirical evidence for the structure of daily well-being via network analysis. Appl. Dev. Sci. 2020, 26, 207–225. [Google Scholar] [CrossRef]
Ijerph 19 16098 g001 550
Figure 1. Standardized mean symptom scores by latent classes of wellbeing.
Figure 1. Standardized mean symptom scores by latent classes of wellbeing.
Ijerph 19 16098 g001
Table
Table 1. Demographic characteristics of participants (n = 1741).
Table 1. Demographic characteristics of participants (n = 1741).
VariablesM ± SD/N (%)
Age19.38 ± 1.02
Gender
Male375 (21.5%)
Female1366 (78.5%)
Year of study
First year530 (30.4%)
Second year765 (43.9%)
Third year446 (25.6%)
Physical activity participation
LPA475 (27.3%)
MPA881 (50.6%)
HPA385 (22.1%)
Average Sitting time per day on workdays(h/day)6.56 ± 2.80
Average sitting time per day on weekdays(h/day)5.41 ± 3.08
Psychological distress18.67 ± 8.00
No distress769 (44.2%)
Low distress425 (24.4%)
Moderate distress301 (17.3%)
High distress246 (14.1%)
Positive emotion6.92 ± 2.05
Engagement6.28 ± 1.89
Relationship7.10 ± 2.05
Meaning6.63 ± 2.11
Accomplishments6.26 ± 2.00
Notes: M = mean; SD = standard deviation; PA = physical activity; LPS = low physical activity; MPA = moderate physical activity; HPA = high physical activity.
Table
Table 2. Fit statistics of latent classes of PERMA (n = 1741).
Table 2. Fit statistics of latent classes of PERMA (n = 1741).
ModelKLLAICBICssaBICEntropyLMRBLRT
C110−8903.55317,827.10517,881.72717,849.958
C216−6847.83713,727.67513,815.07013,764.2400.859<0.0001<0.0001
C322−5644.62411,333.24811,453.41611,383.5250.9230.0193<0.0001
C428−4807.0779670.1539823.0959734.1420.9090.0004<0.0001
C534−4491.1969050.3929236.1079128.0920.8850.2359<0.0001
C640−4221.7358523.4698741.9588614.8810.8920.0033<0.0001
Notes: C = class; LL = log likelihood; AIC = Akaike’s information criterion; BIC = Bayesian information criterion; ssaBIC = Sample size adjusted Bayesian information criterion; LMR = Lo–Mendell–Rubin; BLRT = bootstrapped likelihood ratio test; bold letters indicate the best-fitting models.
Table
Table 3. Comparison of demographic characteristics and PERMA elements by latent classes (n = 1741).
Table 3. Comparison of demographic characteristics and PERMA elements by latent classes (n = 1741).
VariablesLow-Level
Wellbeing		Moderate-Level
Wellbeing		High-Level
Wellbeing		F/χ2p
Age19.49 ± 1.1119.34 ± 1.0419.41 ± 0.981.7080.182 a
Gender
Male33 (35.11%)194 (21.87%)148 (19.47%)12.2150.002 b
Female61 (64.89%)693 (78.13%)612 (80.53%)
Year of Study
First-year22 (23.40%)297 (33.48%)211 (27.76%)8.2690.038 b
Second-year44 (46.81%)383 (43.18%)338 (44.47%)
Third-year28 (29.79%)207 (23.34%)211 (27.76%)
Positive emotion2.18 ± 1.635.59 ± 1.108.65 ± 1.022154.291<0.001 a
Engagement2.16 ± 1.665.51 ± 1.037.69 ± 1.361211.396<0.001 a
Relationship2.42 ± 1.816.22 ± 1.288.70 ± 1.081544.464<0.001 a
Meaning1.91 ± 1.395.60 ± 1.148.40 ± 1.152018.922<0.001 a
Accomplishments2.04 ± 1.615.31 ± 1.067.90 ± 1.261604.456<0.001 a
Notes: a Value was calculated by one-way ANOVA; b value was calculated by a chi-square test; Bold numbers indicate significant differences (p < 0.05).
Table
Table 4. Multinomial logistic regression analysis of levels of PA participation and psychological distress on latent classes (n = 1741).
Table 4. Multinomial logistic regression analysis of levels of PA participation and psychological distress on latent classes (n = 1741).
VariablesHigh-Level vs. Moderate-Level WellbeingHigh-Level vs. Low-Level Wellbeing
pOR95%CIpOR95%CI
PA participation (Ref. = HPA)
LPA0.0351.398(1.023, 1.910)0.2471.341(0.787, 2.539)
MPA0.4671.107(0.841,1.458)0.3660.818(0.447, 1.346)
Psychological distress (Ref. = High distress)
No distress<0.0010.109(0.075, 0.160)<0.0010.131(0.071, 0.242)
Low distress<0.0010.296(0.199, 0.440)<0.0010.208(0.103, 0.419)
Moderate distress0.2440.768(0.492, 1.198)0.0240.408(0.188, 0.886)
Notes: PA = physical activity; LPS = low physical activity; MPA = moderate physical activity; HPA = high physical activity; Ref. = reference; analyses were adjusted for significant covariates (i.e., gender); Bold numbers indicate significant differences (p < 0.05).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Qi, M.; Sun, Q.; Zhao, X.; Gao, Y.; Zhao, D.; Shen, S.; Zayidan, P.; Xiu, Z.; Li, P. A Latent Profile Analysis of PERMA: Associations with Physical Activity and Psychological Distress among Chinese Nursing College Students. Int. J. Environ. Res. Public Health 2022, 19, 16098. https://doi.org/10.3390/ijerph192316098

AMA Style

Qi M, Sun Q, Zhao X, Gao Y, Zhao D, Shen S, Zayidan P, Xiu Z, Li P. A Latent Profile Analysis of PERMA: Associations with Physical Activity and Psychological Distress among Chinese Nursing College Students. International Journal of Environmental Research and Public Health. 2022; 19(23):16098. https://doi.org/10.3390/ijerph192316098

Chicago/Turabian Style

Qi, Meiling, Qian Sun, Xiangyu Zhao, Yiming Gao, Di Zhao, Shiyu Shen, Polat Zayidan, Ziyang Xiu, and Ping Li. 2022. "A Latent Profile Analysis of PERMA: Associations with Physical Activity and Psychological Distress among Chinese Nursing College Students" International Journal of Environmental Research and Public Health 19, no. 23: 16098. https://doi.org/10.3390/ijerph192316098

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