The association of subjective fit perceptions, distress, emotional exhaustion, and work engagement, with work functioning problems: A cross-sectional study conducted among young construction project management professionals.

OBJECTIVES: To investigate the association of subjective fit perceptions, distress, emotional exhaustion, and work engagement, with work functioning, among young construction project management professionals (CPMPs).
METHODS: The research had a cross-sectional design. Dutch young CPMPs (142 participants, age range: 20 to 30 years of age) completed a questionnaire containing general questions recording their demographic characteristics, and instruments recording the following concepts: perceived person-organization fit, perceived person-job fit (including demands-abilities fit and needs-supplies fit), distress, emotional exhaustion, work engagement, and work functioning. Correlation analysis and multiple regression analysis were used to examine the association of fit perceptions, distress, emotional exhaustion, and work engagement, with work functioning.
RESULTS: The correlation analysis indicated that person-organization fit, needs-supplies fit, distress, emotional exhaustion, and work engagement correlated significantly with work functioning problems of young CPMPs. The multiple regression analyses corroborated that needs-supplies fit, distress, and emotional exhaustion related significantly to the work functioning problems of young CPMPs, with the standardized regression coefficients (β) of -0.28, 0.52, and 0.38 (P < .01), respectively. Other than would be expected, the multiple regression analyses also made clear that work engagement does not significantly relate to work functioning problems beyond distress and emotional exhaustion.
CONCLUSIONS: Incongruence between personal needs and job supplies, psychological distress, and emotional exhaustion are central correlates of the work functioning problems of young CPMPs. Occupational health professionals can use these insights to help young CPMPs at work.

INTRODUCTION

Work functioning refers to the health‐related capacity of the individual worker to meet work demands. , Construction management jobs are known to be physically and/or mentally demanding for workers because the work for instance involves strict deadlines, long working hours, and role conflicts. , Work stress and emotional exhaustion (an aspect of burnout), therefore, are prevalent among construction project management professionals (CPMPs), , which in turn can lead to work functioning problems. It may even be more serious for young CPMPs, for these younger workers are relatively new to the work and organization, and in case of adjustment issues (ie, trying to fit in) may suffer stress and resulting work functioning problems. Given this, young CPMPs, who still have their career ahead of them, may end their career in the construction sector prematurely and be forced to make a career switch and find employment elsewhere. This represents a human resource loss for construction organizations. It is even a problem for CPMPs and construction organizations across the globe. To help young CPMPs continue their career in the construction organization, it thus is imperative to address the factors that undermine, and promote, the health‐related ability to meet work demands (work functioning) of these workers.

Research on work functioning appeared about two decades ago. , Most studies on work functioning problems addressed the measurement properties of instruments relevant for recording work functioning. , , , To date, only a handful of studies have addressed correlates of work functioning, including personal factors such as self efficacy, health‐related factors such as emotional exhaustion, distress, fatigue, depressive, and cognitive syptoms, , , , as well as work‐related factors such as work engagement, job content, supervisor social support, and organizational support. , , These studies on predictors of work functioning problems of workers so far showed mixed results. Furthermore, the reseach so far showed that emotional exhaustion may be a predictor of work functioning problems. Furthermore, work engagement (ie, the positive work‐related psychological state of well‐being that is conceptualized by vigor, dedication and absorption ), as the distinct concept that is negatively related to burnout and the predictor of well‐being and work motivation demonstrated in many studies (eg, Christian et al ), was found to be only marginally related to work functioning problems by Abma and colleagues. , Accordingly, due to the mixed study findings so far it is important to conduct additional research on the predictors of the work functioning of workers. Furthermore, it is important to cross‐examine the contribution of work engagement as a motivational state to work functioning beyond health‐related variables, such as distress and emotional exhaustion, to have a better understanding of the relevance of work engagement to work functioning problems.

Furthermore, it is important to examine correlates of the work functioning of young workers in their own right, and a subjective fit approach may help. Young CPMPs who just transit from studies to work are relatively new to the work and organization. They thus may be struggling with their fit in the organization, their individual ability to meet the job demands, and the supplies provided by the job to meet their needs. Work‐related stressors, including evaluations of fit or (in)congruence, are known to affect the mental health of young workers. Specifically, fit theory makes clear that good ‘fit’ between, on the one hand, organizational characteristics, job requirements, and desired job benefits or “supplies”, and, on the other hand, the personal characteristics of workers (values, skills, reward preference) significantly affect positive attitudes and behaviors. A ‘good fit’ between personal characteristics of workers and the organization, work demands and abilities of workers, and needs of workers and job‐supplies can increase positive attitudes and outcomes, such as organizational identification, organizational citizenship behaviors, job satisfaction, and career motivation, , while poor perceived fit tends to result in mental health problems for workers. , Accordingly, perceived or subjective fit evaluations may relate to the work functioning problems of young CPMPs.

Overall, there still a lack of knowledge about the correlation of subjective fit perceptions, stress, emotional exhaustion, and work engagement, with work functioning problems, and no known study was found that has paid special attention to the work functioning problems of young workers. It is, therefore, essential to examine the correlates of work functioning problems of young CPMPs, to achieve a better understanding of the factors that may undermine, or promote, the work functioning of these workers. The aim of this research was thus to investigate among young CPMPs the association of subjective fit perceptions, distress, emotional exhaustion, and work engagement, with work functioning problems.

METHOD

Design, participants, and procedure

The research had a cross‐sectional design. Research participants were recruited via a Dutch construction sector stakeholder organization that has online plus direct access to construction workers in the Netherlands. The recruitment message invited construction project management professionals (CPMPs) who had recently started their career in the construction industry to participate in the survey research. The organization had published the recruitment message on its website and in its digital newsletter. After reading the recruitment message, those CPMPs interested in research participation self‐applied for research participation via an internet link that directed the participants to an information letter about the research, an informed consent form, and the questionnaire. After reading the information letter, and reading and signing the informed consent form, these CPMPs completed the questionnaire. After completion, the questionnaire was directly returned to the researchers via the secured digital survey system. Furthermore, to directly invite CPMPs for research participation, the construction sector stakeholder organization provided the researchers the contact details of 1000 CPMPs. Accordingly, an invitation to participate in the research plus accompanying materials (ie, general information about the research, an informed consent form, the questionnaire for completion after informed consent) were sent via regular mail to the home addresses of these CPMPs. Those CPMPs interested in research participation returned their completed informed consent form plus paper questionnaire to the researchers via a return envelope (response rate: 13.9%). In exchange for their research participation, the CPMPs received a lottery ticket that offered the chance to win a gift coupon. In total, 20 gift coupons of 10 euro each were raffled among the CPMPs who had completed the questionnaire and expressed interest in participation in the lottery. The CPMPs who had expressed interest in receiving a general overview of the research findings at the end of the research project received an overview of these results. The participants could also indicate to express no interest in receiving a general overview of the research findings or to receive information about the outcomes of the research via the organizations´ website discussing the research and its outcomes.

Ethics

The research was conducted in accordance with the Declaration of Helsinki. The Medical Ethics Committee of the Academic Medical Center judged (reference number: W18_162#18.200) that a comprehensive evaluation was not required since this study was not subject to the Medical Research Involving Human Subjects Act. Institutional procedures of the Academic Medical Center were used to respect the privacy of the research participants and the European law on data protection and privacy.

Measures

Subjective fit perceptions. Studies distinguish different types of fit perceptions, including person‐organization fit (P‐O fit), demands‐abilities fit (D‐A fit), and needs‐supplies fit (N‐S fit). P‐O fit is defined as the compatibility between people and organizations, and mainly includes value congruence, personality congruence, and need fulfillment. , D‐A fit describes the match between the demands of a job and the abilities of an individual, while N‐S fit refers to the fit between the needs of a person and the supplied attributes of a job, or the rewards that a particular job supplies in return for performance at work. P‐O Fit was measured with the Dutch version of the person‐organization fit instrument of Saks and Ashforth. This 4‐item instrument has a 5‐point scale (ie, 1 = To a very little extent, 5 = To a very large extent) and a high score suggests good person‐organization fit. Example items are as follows: ‘To what extent are the values of the organization similar to your own values?’ and ‘To what extent does your personality match the personality or image of the organization?’. D‐A Fit and N‐S Fit were recorded with the Dutch versions of the relevant fit scales of Cable and DeRue. Each instrument has three items and a 5‐point scale (ie, 1 = strongly disagree, 5 = strongly agree), and for each instrument a high score is suggestive of adequate fit. Example items, respectively, are ‘The match is very good between the demands of my job and my personal skills’ and ‘There is a good fit between what my job offers me and what I am looking for in a job’. These Dutch versions of validated instruments for recording the fit perceptions of employees in organizations have good internal consistency. ,

Distress was recorded with the 16‐item distress scale of the 4DSQ. An example item is as follows: ‘During the past week, did you feel tense?’. A high score is suggestive of distress. The recommended 5‐point answer scale was used for recording the responses of the participants (ie, ‘No’, ‘Sometimes’, ‘Regularly’, ‘Often’, and ‘Very often or Constantly’). After recording the responses of the participants, the answers of the participants were collapsed into a 3‐point scale (ie, ‘No’, ‘Sometimes’, and ‘Regularly to Very often or Constantly) per recommendations. The instrument has good psychometric properties.

Emotional exhaustion was measured with the Dutch emotional exhaustion subscale of the Utrecht Burnout Questionnaire (UBOS). , This subscale has 5 items and a 7‐point answer format (ie, ‘Never’, ‘A few times a year or less’, ‘Once a month or less’, ‘A few times a month’, ‘Once a week’, ‘A few times a week’, and ‘Every day’). An example item of the scale is ‘I feel used up at the end of the workday’. The UBOS has good psychometric qualities. ,

Work engagement, consisting of the domains ‘vigor’, ‘dedication’, and ‘absorption’, was recorded with the brief Dutch Utrecht Work Engagement Scale (UWES). Each aspect of work engagement was recorded with three items and the scales have a 7‐point answer format (ie, ‘Never’, ‘A few times a year or less’, ‘Once a month or less’, ‘A few times a month’, ‘Once a week’, ‘A few times a week’, and ‘Every day’). Example items are ‘At my job, I feel bursting with energy’ (ie, vigor), ‘I am enthusiastic about my job’ (ie, dedication), and ‘I am immersed in my work’ (ie, absorption). The instrument has good psychometric properties. ,

Work functioning covers four domains including capacity for work, quality and quantity of work, and costs of work, and was recorded with the use of the composite weighted work functioning method. This measurement method combines the participants’ capacity for work scores, quality and quantity of work scores, and costs of work scores, into a single overall work functioning score. A high score indicates work functioning problems. ‘Capacity for work’ was measured with the 9‐item mental‐interpersonal work demands subscale (eg, ‘Ability to think clearly’) plus the 6‐item physical work demands subscale (eg, ‘Ability to sit or stand more than 15 minutes’) of the Dutch version of the Work Limitations Questionnaire. ‘Quantity of work’ was assessed with the Dutch version of the output‐demands subscale (eg, ‘Ability to finish work on time’) of the Work Limitations Questionnaire. The answers of the respondents were recorded on a 6‐point scale (ie, 0 = Never difficult, 4 = always difficult, and 5 = not applicable to my job; was coded as missing value). ‘Costs of work’ was measured with the Dutch ‘need for recovery’ subscale. This instrument has 11 items and a dichotomous scale for recording the answers of the participants (ie, no/yes). An example item is as follows: ‘I find it hard to relax at the end of a working day’. Finally, ‘Quality of work’ was recorded with the Dutch in‐role (10 items, eg, ‘Providing good service’) and extra‐role (8 items, eg, ‘Participation in social activities of the organization’) subscales that record whether employees meet their formal and informal work responsibilities. A 3‐point scale was used for recording the responses of the participants (0 = more than usual, 1 = as much as usual, and 2 = less than usual). The composite weighted work functioning method has good convergent construct validity, moderate divergent construct validity, and good discriminative validity.

Data and analyses

The data collection period had started in October 2018 and ended at the end of January 2019. Pearson correlation analysis and multiple regression analysis were used to analyze the data. Specifically, Pearson correlation analysis was first used to examine the relations between variables under examination. Furthermore, the first multiple regression analysis model (Model 1) was to test whether the types of fit perceptions relate to work functioning problems while they control for each other. The second multiple regression analysis model (Model 2) was to test whether distress, emotional exhaustion, and work engagement relate to work functioning problems while they control for each other. In addition, as supplementary analysis, multiple regression models were also tested to examine whether types of fit perceptions relate to distress (Model 3), emotional exhaustion (Model 4), and work engagement (Model 5), respectively, while they control for each other. Pearson correlation analysis provides a first good insight into associations between variables under examination, while multiple regression analysis in the context of cross‐sectional data is relevant to apply for examining associations between, on the one hand, multiple variables controlling for each other (ie, independent variables, eg, distress, emotional exhaustion, and work engagement) and, on the other hand, one other variable of interest (ie, dependent variable, eg, work functioning problems). To be noted, variables with non‐significant Pearson correlation coefficients were not involved in the following multiple regression analyses. The regression coefficient of the independent variable indicates the strength of its association with the dependent variable when the other independent variables are held constant. The analyses were done with the use of the Statistical Package for the Social Sciences (SPSS).

RESULTS

One‐hundred and forty‐two young construction project management professionals completed the questionnaire (n = 142). The demographic characteristics of the participants are displayed in Table 1. The mean age of the participants was 26.1 years. They worked an average of 3.7 years for their current employer. Cronbach's α coefficients of the constructs under examination (ranging from 0.73 to 0.93, shown in Table 2) suggested good internal consistency of the measurement instruments. The mean values and standard deviations of three types of fit perceptions, distress, emotional exhaustion, work engagement, and work functioning problems of the participants can be found in Table 2 as well. The mean score of distress was 6.62, and in terms of the criteria or cutoff point of Van Rhenen et al, it was found that 22.9% of the participants reported severe distress (score above 11). The mean score of emotional exhaustion was 10.68, and in terms of the criteria or cutoff point of Schaufeli and Van Dierendonck, it was found that 40.4% of the participants reported average‐to‐high emotional exhaustion (scored above 13). The results suggested that distress and emotional exhaustion were prevalent within this sample of participants.

TABLE 1

Participant demographic characteristics

Mean Age (SD)	26.1 (2.4)
Mean number of years of work for current employer (SD)	3.7 (2.9)
Mean number of work hours per week (SD)	44.3 (7.1)
Enrolled in training program
No. full‐time employed	n = 117
Yes	n = 25
Organization size
0‐5 workers	n = 3
6‐15 workers	n = 6
16‐50 workers	n = 25
51‐100 workers	n = 28
101‐250 workers	n = 34
More than 250 workers	n = 46

Abbreviations: SD, standard deviation; n, number of subjects.

TABLE 2

Means, SD, Cronbach's α, and correlations of the constructs

	Construct	Mean (SD)	Min	Max	1	2	3	4	5	6	7	8	9	10	11
1	Person‐Organization fit	14.93 (2.09)	8.00	20.00	(0.80)
2	Demands‐Abilities fit	11.91 (1.51)	8.00	15.00	0.36***	(0.73)
3	Needs‐Supplies fit	11.01 (1.17)	5.00	15.00	0.54***	0.61***	(0.89)
4	Distress	6.62 (5.50)	0	28.00	−0.30***	−0.25**	−0.38***	(0.87)
5	Emotional exhaustion	10.68 (6.12)	0	26.00	−0.19*	−0.29***	−0.26**	0.55***	(0.91)
6	Work engagement	42.78 (7.79)	24.00	54.00	0.40***	0.44***	0.66***	−0.49***	−0.35***	(0.93)
7	Work functioning problems	19.1 (12.76)	0	56.45	−0.17*	−0.15	−0.29***	0.70***	0.64***	−0.33***	(0.91)
8	Capacity for work	13.2 (9.72)	0	43.63	−0.12	−0.18*	−0.23**	0.49***	0.29**	−0.30***	0.59***	(0.87)
9	Quantity of work	26.9 (20.57)	0	83.25	−0.04	−0.09	−0.18*	0.52***	0.51***	−0.20*	0.80***	0.51***	(0.92)
10	Costs of work	40.7 (32.47)	0	115.00	−0.16	−0.22**	−0.26**	0.62***	0.70***	−0.29**	0.83***	0.39***	0.51***	(0.83)
11	Quality of work	8.3 (19.45)	0	117.18	−0.22**	0.01	−0.21*	0.43***	0.18*	−0.21*	0.61***	0.23**	0.38***	0.25**	(0.80)

Cronbach's α coefficients are presented on the diagonal.

The measurements of the three types of fit have a 1‐5 scale. The measurement of distress has a 0‐2 scale with 16 items. The measurement of emotional exhaustion has a 0‐6 scale with 5 items. The measurement of work engagement has a 0‐6 scale. The composite weighted measurement of work functioning problems has a 0‐100 scale. The measurements of capacity for work and quantity of work have a 0‐4 scale. The measurement of costs of work has a 0‐1 scale. The measurement of quality of work has a 0‐2 scale. The subscale scores of work functioning problems were multiplied by their domain weights.

The mean values and SDs of summed scores were reported.

Abbreviation: SD, standard deviation.

P ≤ .05,

P ≤ .01,

P ≤ .001.

Correlation analysis

Pearson correlations among the construct scores of the participants are also displayed in Table 2. It was observed that person‐organization fit (r = −.17, P ≤ .05), needs‐supplies fit (r = −.29, P ≤ .001), distress (r = .70, P ≤ .001), emotional exhaustion (r = .64, P ≤ .001), and work engagement (r = −.33, P ≤ .001) correlated significantly with the work functioning problems of young CPMPs. Person‐organization fit only correlated significantly with the domain of quality of work (r = −.22, P ≤ .01). Demands‐abilities fit correlated significantly with the domains of capacity for work (r = −.18, P ≤ .05) and costs of work (r = −.22, P ≤ .01). Needs‐supplies fit correlated significantly with all four domains of work functioning problems, with the correlation coefficients ranging from −0.26 to −0.18. Distress and emotional exhaustion were found significantly and positively correlated with all the four domains of work functioning problems, with the correlation coefficients ranging from 0.18 to 0.70, while work engagement was significantly and negatively correlated with all the four domains, with the correlation coefficients ranging from −0.20 to −0.30.

In addition, the three types of fit perceptions were consistently found significantly and negatively correlated with distress and emotional exhaustion, respectively, with the correlation coefficients ranging from −0.38 to −0.19, and they were also found significantly and positively correlated with work engagement, with the correlation coefficients ranging from 0.41 to 0.66.

Multiple regression analyses

Multiple regression analysis models (Model 1 and Model 2) were subsequently tested to corroborate the association of person‐organization fit, needs‐supplies fit, distress, emotional exhaustion, and work engagement, with the work functioning problems of these young CPMPs (seen in Table 3). The results suggested that needs‐supplies fit (Model 1, β = −0.28, P ≤ .01), distress (Model 2, β = 0.52, P ≤ .001), and emotional exhaustion (Model 2, β = 0.38, P ≤ .001) related significantly to the work functioning problems of young CPMPs, while person‐organization fit and work engagement did not affect the work functioning problems of young CPMPs.

TABLE 3

Association of types of fit, distress, emotional exhaustion, and work engagement, with work functioning problems of young CPMPs yielded by regression analysis

constructs	Model 1		Model 2
	Work functioning		Work functioning
	β	P	β	P
Person‐Organization fit	−0.03	.796	—	—
Needs‐Supplies fit	−0.28**	.005	—	—
Distress	—	—	0.52***	.000
Emotional exhaustion	—	—	0.38***	.000
Work engagement	—	—	0.05	.429
Adjusted R square	0.072		0.59

P ≤ .01,

P ≤ .001.

Correlation analysis suggested that each type of fit perceptions of young CPMPs correlated significantly with the three psychological constructs (ie, work engagement, distress, and emotional exhaustion). A series of multiple regression analyses (Models 3, 4, and 5) was thus conducted to corroborate the correlations (seen in Table 4). It was revealed that only the needs‐supplies fit of the young CPMPs related significantly to the distress (Model 3, β = −0.30, P ≤ .01) and work engagement (Model 5, β = 0.59, P ≤ .001), while no significant effect of the types of fit on emotional exhaustion was found. Thus, the needs‐supplies fit of young CPMPs had a role in the distress and work engagement of these workers.

TABLE 4

Association of types of fit with distress, emotional exhaustion, and work engagement, yielded by regression analysis

Constructs	Model 3		Model 4		Model 5
	Distress		Emotional exhaustion		Work engagement
	β	P	β	P	β	P
Person‐Organization fit	−0.14	.143	−0.06	.566	0.08	.311
Demands‐Abilities fit	−0.01	.925	−0.21	.051	0.05	.587
Needs‐Supplies fit	−0.30**	.011	−0.10	.391	0.59***	.000
Adjusted R square	0.14		0.08		0.42

P ≤ .01.

P ≤ .001.

DISCUSSION

The aim of this research was to investigate the association of subjective fit perceptions, distress, emotional exhaustion, and work engagement, with work functioning, among young CPMPs. The findings of the research suggested that a) needs‐supplies fit related significantly to the work functioning problems of young CPMPs, while person‐organization fit and demands‐abilities fit had a minor role in the work functioning problems of young CPMPs; and b) distress and emotional exhaustion related significantly to the work functioning problems of young CPMPs, while work engagement of young CPMPs had a minor role in the work functioning problems. In addition, needs‐supplies fit was also found significantly related to the distress and work engagement of young CPMPs.

Implications of the research

The results showed that the incongruence between needs and supplies played a role in work functioning problems of young CPMPs. On the one hand, this finding contributes to the understanding of what young workers value during work and what this means for their health and functioning in the work context. Furthermore, this finding is in line with the argument of Cable and DeRue (2002) who pointed out that NS‐fit likely is the strongest predictor of work outcomes because most workers involve themselves in paid work to achieve (im)material benefits. While the current study pointed to the primary importance of NS‐fit for younger workers, it is acknowledged that it remains important to conduct research on the role of other types of subjective fit in the health and functioning of younger workers, including research on PO‐fit and DA‐fit.

In the current research, distress and emotional exhaustion were also identified as correlates of work functioning. This finding suggested that it is important to address distress and emotional exhaustion so as to maintain the sustainable work functioning of workers. Among a handful of existing studies that addressed the correlates of work functioning, only the study of Oude Hengel et al previously demonstrated an association between emotional exhaustion and the ability to continue working, and few studies have examined the relationship between distress and work functioning. In view of the current findings, construction companies are recommended to take measures to relieve the psychological distress and emotional exhaustion of young CPMPs in the organization.

Furthermore, work engagement was found to have an initial correlation (r = −0.33, P ≤ .001) with work functioning problems, but was found unrelated to work functioning problems when controlling for the effects of distress and emotional exhaustion in a multiple regression analysis. In the current research, work engagement was considered to be an innate motivational state, while distress and emotional exhaustion were considered innate health states. Hence, these three psychological states were included as simultaneous direct correlates of work functioning problems. However, it might be the case that work engagement primarily associates with work functioning problems through distress and emotional exhaustion and, thus, has an indirect association with work functioning. In line with the initial observation of Abma et al, the current research points out that work engagement may not have a strong direct association with work functioning problems. Yet, it is acknowledged that work engagement may contribute indirectly to the work functioning of workers and that this should be addressed in future research. Future research is, thus, recommended to examine the indirect association of work engagement with work functioning problems through distress and emotional exhaustion.

The results also demonstrated that needs‐supplies fit was significantly related to distress, and distress was significantly related to work functioning. This suggests that through distress, needs‐supplies fit may relate indirectly and significantly to work functioning problems of young CPMPs. Therefore, future research with a longitudinal design and mediation analysis as done by Radstaak et al is recommended to examine the mediating effect of distress.

Generally, health problems are more prevalent among middle‐aged workers, and for this reason most studies on work functioning were conducted among such workers. , , The current research suggests that the sustainable functioning of younger workers should be paid attention to as well, especially in stressful industries (eg, construction industry). Furthermore, existing studies on work functioning in the construction industry either focused on construction laborers or general construction workers (both bricklayers and supervisors). The findings in this study suggested that research attention should also be paid to the work functioning problems of construction management professionals.

Limitations and suggestions for future research

A limitation of the current research is that the data are cross‐sectional. The relationships among needs‐supplies fit, distress, and work functioning, thus, could not be interpreted as causal. Even so, longitudinal studies show causality among fit, stress, and psychological well‐being. , The current research showed significant associations between work functioning problems and its potential predictors, and future longitudinal research now is suggested to examine causality as a next step in this area of research. Second, the variables of this research were measured with self‐reported instruments, which can result in common method bias. However, non‐significant correlations were observed (ie, the correlation between work functioning problems and person‐organization fit, the correlation between work functioning problems and demands‐abilities fit, as shown in Tables 2 and 3). Since common method variance tends to inflate the size and significance of correlation coefficients, this may suggest that common method bias (if any) was not in play in the current research. Furthermore, to prevent method variance from occurring, measures were taken to counteract attenuation due to common method variance, as suggested by Podsakoff and colleagues. For example, the questionnaire survey was conducted anonymously to ensure that social desirability would not attenuate correlations. In addition, Spector addressed the effects of common method variance in research. It was concluded that common method variance may be in play in cross‐sectional research but that, regularly, it is not severe enough to inflate correlations from non‐significant to significant. Even so, future research on the fit of young CPMPs is recommended to include objective evaluations (eg, supervisor ratings about the fit of workers) and concrete outcomes (eg, information about whether work functioning standards were met) because this will further help to avoid common method bias. A third limitation is that the current research specifically focused on western young CPMPs. The generalizability of the research findings remains to be examined among CPMPs of all ages, other occupation groups, and non‐western cultures. Accordingly, future research is suggested to be conducted across occupations and countries to cross‐validate the results.

The current research also yields suggestions for new research. For instance, there are other types of fit, for instance, person‐group fit and person‐supervisor fit. It is worthwhile to examine whether these directly affect the work functioning problems of young CPMPs, or to examine whether these evoke stress in young CPMPs and, therefore, have a role in work functioning problems of young CPMPs. Future research is, thus, suggested to examine the role of other types of fit in predicting the work functioning problems of young CPMPs. Furthermore, it is also interesting to examine moderators of the effects of types of fit on health‐related outcomes relevant for young CPMPs. For example, social support at work can be a potential moderator because incongruence can become less stressful when young CPMPs cope with it with the support from, for instance, their supervisor or coworkers. In addition, more research should be conducted to identify other correlates of work functioning problems. Such research may help to better address the work functioning problems of workers. For instance, researchers may address the role of constructive (eg, being supportive) and destructive (eg, passive‐aggressiveness) behaviors of leaders (supervisors, managers, etc) in the work functioning problems of workers, or examine the contribution of non‐work factors (eg, having informal care responsibilities, family conflict, etc) to the work functioning problems of workers.

In conclusion

This study is the first to specifically address the work functioning problems of young workers, and the research identified the incongruence between personal needs and job supplies, psychological distress, and emotional exhaustion, as correlates of work functioning problems of young CPMPs.

DISCLOSURE

The Medical Ethics Committee of the Academic Medical Center judged (reference number: W18_162#18.200) that a comprehensive evaluation was not required since this study was not subject to the Medical Research Involving Human Subjects Act. Institutional procedures of the Academic Medical Center were used to respect the privacy of the research participants and the European law on data protection and privacy. The research was conducted in accordance with the Declaration of Helsinki, and informed consent was obtained from all research participants.

Registry and the Registration No. of the study/trial: N/A. Animal Studies: N/A.

Conflict of Interest: The authors declare no conflict of interests.

AUTHOR CONTRIBUTIONS

All authors met the four criteria for authorship of the ICMJE. Ziyang Song and Edwin J. Boezeman conceived the idea; Ziyang Song and Edwin J. Boezeman collected the data; Edwin J. Boezeman analyzed the data; Ziyang Song and Edwin J. Boezeman led the writing process; Karen Nieuwenhuijsen and Angela de Boer supervised the process of data analysis, helped with the interpretation of the data, and provided suggestions for revising the manuscript; and Xiaodong Li provided suggestions for revising the manuscript.