Assessing longitudinal change of and dynamic relationships among role stressors, job attitudes, turnover intention, and well-being in neophyte newcomers

Assessing longitudinal change of and dynamicrelationships among role stressors, job attitudes,turnover intention, and well-being in neophytenewcomers

CHRISTIAN VANDENBERGHE1*, ALEXANDRA PANACCIO1,

KATHLEEN BENTEIN2, KARIM MIGNONAC3 AND PATRICE ROUSSEL3

1Management Department, HEC Montreal, Montreal, Quebec, Canada2Ecole des sciences de la gestion, Universite du Quebec a Montreal, Montreal, Quebec, Canada3Centre de recherche en management, Universite Toulouse 1 Capitole, Toulouse, France

Summary Using a latent growth modeling (LGM) approach, this paper examines the trajectories of change in rolestressors (ambiguity, conflict, and overload), job attitudes (affective commitment and job satisfaction), andturnover intention and psychological well-being among neophyte newcomers, as well as the relationshipsamong these changes. Based on a sample of 170 university alumni surveyed three times during the firstmonths of employment, we found that role conflict and role overload increased, affective commitment and jobsatisfaction declined, and turnover intention increased over the course of the study. Role ambiguity and well-being did not change. The initial levels of affective commitment, job satisfaction, and well-being werepositively related to the increase in role overload, while the initial level of turnover intention was related to areduced increase in role overload over time. We also found that the increase in role overload and role conflictwas associated with a decline in affective commitment and job satisfaction, respectively, and that the decreasein affective commitment and satisfaction was related to an increase in turnover intention. We discuss theimplications of these findings. Copyright # 2010 John Wiley & Sons, Ltd.

Keywords: role stressors; change; job attitudes; turnover intention; well-being

Introduction

The early stages of the employment relationship are a period of adjustment during which newcomers ‘‘learn the

ropes’’ and, if the socialization process is successful, become fully functional organizational members. As such, this

stage is critical for organizations. By definition a transitional period (Ashforth, 2001), the year following entry is

characterized by changes in employees’ beliefs toward the organization and in characteristics of the work context

(Wanous & Reichers, 2000). However, despite the prevalence of change during this stage of the employment

relationship, few studies have sought to measure these changes and their implications directly. The present study

aims to address this shortcoming by examining the trajectories of change – that is, the direction and magnitude of

within-person change occurring across time – in indicators of newcomer adjustment (perception of stressors

[role overload, ambiguity, and conflict]) and socialization outcomes (job attitudes [affective commitment and job

Journal of Organizational Behavior, J. Organiz. Behav. 32, 652–671 (2011)

Published online 20 December 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/job.732

*Correspondence to: Christian Vandenberghe, HEC Montreal, 3000, Chemin de la Cote Sainte-Catherine, Montreal, Quebec, Canada H3T2A7.E-mail: [email protected]

Copyright # 2010 John Wiley & Sons, Ltd.Received 13 August 2009

Revised 27 September 2010, Accepted 9 October 2010

satisfaction], turnover intention, and psychological well-being) during organizational entry, and the way these

changes relate to one another.

Given the high demands facing newcomers, stress is an important aspect of organizational entry. In recent

years, a great deal of research has been conducted on stress in organizations, but little of this research has focused

on newcomers. Similarly, job satisfaction and affective commitment are well-established socialization

outcomes (Saks, Uggerslev, & Fassina, 2007); these attitudes are also indicators of the relative inclination of

job incumbents to remain with their organization (Tett & Meyer, 1993) and, because they make the work experience

more enjoyable, may play a role in the maintenance of well-being (Schaufeli, 2004). However, despite calls for

accounting for change in examining these variables (e.g., Bauer, Bodner, Erdogan, Truxillo, & Tucker, 2007), few

have adopted a dynamic approach to their study. Our first goal is thus to examine the trajectories of change in these

indicators of newcomer adjustment (role stressors) and socialization outcomes (job attitudes, turnover intention, and

well-being).

Workplace stressors constitute examples of ‘‘events’’ which, according to Affective Events Theory (AET; Weiss

& Cropanzano, 1996), lead to emotional responses, thereby impacting attitudes and behaviors (Rodell & Judge,

2009). Therefore, a second goal of this study is to examine the relationships between the trajectories of change in role

stressors and the trajectories of change in socialization outcomes. Finally, given that the first months of employment

can cause rapid changes in job attitudes, as a result of unmet expectations (Boswell, Boudreau, & Tichy, 2005),

accounting for time in studying these constructs should also allow us to better capture the true nature of their

relationships. Accordingly, our third goal is to examine the relationships between change trajectories of newcomers’

job attitudes and change trajectories of turnover intention and well-being.

This study uses a latent growth modeling (LGM) approach to disentangle the static (initial status) and dynamic

(change) components of socialization variables measured at three occasions during organizational entry in a sample

of neophyte newcomers. In the next few sections, we develop our hypotheses regarding change in socialization over

time and how the static and dynamic components of socialization variables relate to one another. In doing so, we rely

on Lazarus and Folkman’s (1984) stress theory in which individuals’ reactions are conceived as resulting from the

combination of the appraisal of threats in the environment (primary appraisal) and of the resources to cope with them

(secondary appraisal). As we highlight below, newcomers’ initial commitments to the situation make them confident

in their resources to cope with role stressors, yet due to a more realistic assessment of their coping capacities over

time, their perceptions of role stress should increase over time and ultimately engender decreased commitment,

satisfaction, and well-being and increased turnover intentions.

Change During Organizational Entry

The months following organizational entry correspond to a transition phase (Ashforth, 2001) characterized by

changes in employees’ perceptions, attitudes, and behaviors. These changes are due in part to newcomers making a

more realistic assessment of their environment following an initial period of overly positive perceptions and attitudes

– a phenomenon known as the honeymoon-hangover effect (Boswell et al., 2005; Boswell, Shipp, Payne, &

Culbertson, 2009). This may occur because (a) newcomers are initially bound by their initial commitments into the

relationship, are immune to negative outcomes and discard negative information from the environment (Fichman &

Levinthal, 1991) and (b) organizations tend to present their most favorable side to potential employees (Boswell

et al., 2009). After a fewmonths, newcomers have touched basewith the organization’s values and gained knowledge

of their roles (e.g., Bauer et al., 2007; Kammeyer-Mueller &Wanberg, 2003; Morrison, 1993a), and are hence more

realistic in their appraisal of demands from the environment and the resources to cope with them. This process

suggests predictable patterns of change in our study variables that we describe below.

Copyright # 2010 John Wiley & Sons, Ltd. J. Organiz. Behav. 32, 652–671 (2011)

DOI: 10.1002/job

CHANGE IN STRESSORS, ATTITUDES, AND WELL-BEING 653

Role stressors

Individuals engage in constant evaluations of their environment, and specifically, of what their ‘‘relationship to the

environment implies for [their] personal well-being’’ (Smith & Lazarus, 1993, p. 234). This cognitive appraisal leads

to certain aspects of the environment being identified as stressors, i.e., perceived threats to well-being. Research has

shown that certain stressors tend to be appraised in a consistent manner by employees (Wallace, Edwards, Armold,

Frazier, & Finch, 2009), and role ambiguity, role conflict, and role overload have been identified as three critical

sources of workplace stress. Role ambiguity results from having insufficient information regarding the expectations

associated with one’s role and role conflict reflects employee’s perception of having to meet inconsistent

expectations (Rizzo, House, & Lirtzman, 1970), while role overload is experienced when the demands of one’s

work role are perceived to exceed the time and resources available to meet them (Kahn, Wolfe, Quinn,

Snoek, & Rosenthal, 1964). Given their prevalence in the stress literature, these stressors were retained in the current

study.

It has been suggested that individuals further categorize stressors as being either challenging, when they are

perceived to be manageable, and thus presenting an opportunity for personal growth, or hindering, when they are

perceived as constraining personal development (e.g., LePine, Podsakoff, & LePine, 2005; Wallace et al., 2009).

While role ambiguity and conflict are typically considered to be hindrance stressors (e.g., LePine et al., 2005; Rodell

& Judge, 2009), the situation is less clear with regards to role overload: Challenge stressor for some (e.g., McCauley,

Rudennan, Ohlott, & Morrow, 1994), it is considered by others to be a hindrance stressor (e.g., LePine et al., 2005).

Similarly, it has been suggested that a heavy workload, a concept closely related to role overload, could be

categorized as either a challenge or a hindrance (Rodell & Judge, 2009). Drawing from transactional stress theory

(Lazarus & Folkman, 1984), we contend that this appraisal as either a challenge or a hindrance stressor depends on

one’s assessment of having resources to meet the demand. A heavy workload may thus be a challenge stressor if the

employee perceives having resources at her disposal to face it, or a hindrance stressor if she perceives this demand to

exceed available resources. In this case, the workload becomes overwhelming, corresponding to a situation of role

overload.

Even though role overload is endemic in organizations, newcomers are thought to minimize negative elements and

overemphasize positive ones upon organizational entry (Ashforth, 2001), and therefore may initially lack conscious

awareness of a discrepancy between the demands put upon them and the resources available for meeting them.

Newcomers may thus initially view a heavy workload as falling within the range of stimuli which offer an

opportunity for development and growth (i.e., a challenge stressor), particularly because their a priori beliefs

concerning their job are positive (Fichman & Levinthal, 1991). As time passes by and reality sets in, they will likely

become increasingly aware of this discrepancy and develop a more realistic evaluation of their environment, leading

to a more accurate perception of role overload. In sum, what was initially perceived as having ‘‘a lot of work’’ will

become having ‘‘too much work’’ as newcomers settle into their jobs. Thus, we predict an increase in newcomers’

role overload in this study:

Hypothesis 1a: During the time period of the study, an increasing trajectory of change will occur in employees’

perceptions of role overload.

The socialization process involves the development of social identifications, which emerge through interactions

with various entities (Ashforth, 2001; Bauer et al., 2007). As the number of entities with which an employee interacts

likely increases during the first months of employment (the department, the union, the work group, etc.) and as these

entities’ goals and values have been reported as potentially conflicting (Reichers, 1986), employees may find

themselves increasingly torn between the demands of various groups to which they identify, and thus experience an

increase in perceptions of role conflict. Prior research has indeed found perceptions of role conflict to increase in the

months following organizational entry (e.g., Ashforth & Saks, 1996). Based on this, the following hypothesis is

proposed:


DOI: 10.1002/job

654 C. VANDENBERGHE ET AL.

Hypothesis 1b: During the time period of the study, an increasing trajectory of change will occur in employees’

perceptions of role conflict.

Socialization is also a process of uncertainty reduction, as employees seek to increase the predictability of

interactions with organizational members, and an important aspect of this process consists in the clarification of

one’s role within the organization (Bauer et al., 2007). In other words, newcomers act proactively and seek

information to clarify expectations of them (Morrison, 1993b). This process is thought to reduce role ambiguity

(Thomas & Anderson, 1998). Accordingly, empirical evidence suggests that perceptions of role ambiguity tend to

decline in the months following organizational entry (e.g., Ashforth & Saks, 1996; Meyer & Allen, 1988; Morrison,

1993a). We thus expect employees’ perceptions of role ambiguity to decline over the course of the study.

Hypothesis 1c: During the time period of the study, a decreasing trajectory of change will occur in employees’

perceptions of role ambiguity.

Job attitudes

In addition to changes in the levels of perceived role stressors, we expect affective organizational commitment and

job satisfaction to evolve during the course of the study. While research has shown that organizational commitment

can take multiple forms, the current investigation focuses on its affective component as it has consistently emerged

as the strongest predictor of both turnover intention and stress/well-being (e.g., Meyer, Stanley, Herscovitch, &

Topolnytsky, 2002). In the current study, we expect affective organizational commitment and job satisfaction to

decline, due to progressive wearing off of the ‘‘honeymoon’’, as early expectations are not met (Boswell et al., 2005;

Meyer & Allen, 1988). This phenomenon is common, as expectations are often unrealistic in the beginning,

especially among neophyte newcomers (Wanous, 1980). Another potential explanation for the decline of affective

commitment is that employees, as they socialize over time, become committed to groups and entities whose goals

and values may conflict with those of the organization (Reichers, 1986). Increased salience and commitment to these

groups may decrease the overall satisfaction with one’s job and lead employees to reconsider their affective

commitment to the global organization. In accordance with this, prior empirical evidence shows that affective

organizational commitment (Lance, Vandenberg, & Self, 2000; Meyer & Allen, 1988) and job satisfaction

(e.g., Ashforth & Saks, 1996; Maier & Brunstein, 2001) tend to decline over time during the first few months of

employment. However, as past research has relied on static approaches to the phenomenon, there is a potential

confound between individuals’ absolute levels on commitment and satisfaction and the trajectory of change they

experience on these variables across time. Our objective is to demonstrate that whatever the initial level of affective

commitment and job satisfaction at entry, newcomers will experience a drop over time, as a result of disillusionment.

We thus propose the following hypotheses:

Hypothesis 2a: During the time period of the study, a decreasing trajectory of change will occur in employees’

affective commitment.

Hypothesis 2b: During the time period of the study, a decreasing trajectory of change will occur in employees’ job

satisfaction.

Turnover intentions and well-being

Turnover cognitions tend to increase in the months following organizational entry (e.g., Saks & Ashforth, 2000).

This is likely another facet of the reality shock described above: Disillusioned newcomers may feel that another

organization could better fulfill their expectations, and thus consider leaving their current employer. If organizational

socialization truly engenders a progressively more realistic evaluation of the positive and negative aspects of the

work environment, a withdrawal trend should emerge over time. This should be illustrated by an increasing


DOI: 10.1002/job


trajectory of change in turnover intention that is independent from the initial level of turnover intention. The

following hypothesis is thus proposed:

Hypothesis 2c: During the time period of the study, an increasing trajectory of change will occur in employees’

turnover intention.

It has been proposed that individuals have a set point in well-being, the level of which is explained by individual

characteristics (Diener & Diener, 1996), and that specific circumstances such as a job change may cause a temporary

shift (positive or negative) in well-being (Boswell et al., 2005). The organizational entry period typically generates

such circumstances, as it is stressful and engenders anxiety (Saks, 1994). Further, the protecting function of the

honeymoon effect is likely to be short-lived and quickly followed by a hangover effect. Consequently, and in line

with the existing evidence from research that measured well-being-related variables at different points in time using

a static design (e.g., Ashforth & Saks, 1996), we expect individual well-being to depart from its set point and to drop

during the entry period. This leads to the following hypothesis:

Hypothesis 3: During the time period of the study, a decreasing trajectory of change will occur in employees’

well-being.

Relationships Among Initial Status and Change Variables

We have thus far proposed hypotheses concerning the expected trajectories of change for the study variables over the

course of the study. However, the LGM approach also allows for examining relationships among change trajectories.

More precisely, it allows for identifying two components or variables: (a) the initial status or static component (i.e.,

the value of the variable at the point of entry to the job) and (b) the change variable (i.e., the rate of increase or

decrease on the target variable over the period of the study – although we assume change to be linear, this will be

tested). The following sets of hypotheses thus concern relationships between either two change variables, or between

an initial status and a change variable.

Relationships among changes in role stressors and job attitudes

As AET (Weiss & Cropanzano, 1996) suggests, workplace stressors represent ‘‘events’’ (Rodell & Judge, 2009) that

likely impact attitudes and behaviors. Research further suggests that hindrance stressors such as role ambiguity,

conflict and overload have negative relationships with commitment and satisfaction (Podsakoff, LePine, & LePine,

2007). Drawing from transactional stress theory (Lazarus & Folkman, 1984), we proposed that a heavy workload

may initially be perceived rather favorably – i.e., as a challenge stressor. This is because newcomers have initial

positive commitments to the job which result in appraising having the resources to cope with it. Over time, a clearer

perception of a discrepancy between demands and resources emerges and the heavy workload – now perceived as

overload – may lead to frustration directed toward the organization (Ashforth & Saks, 2000). Indeed, role overload

will likely be attributed to the organization’s doing (e.g., understaffing, inadequate workload distribution), which

should result in employees expressing their frustration through disengagement – that is, reducing their level of

commitment – from the employment relationship. Affective commitment is, indeed, a form of reciprocation for

positive experiences perceived to be offered by the organization (Meyer et al., 2002); negative experiences for which

the organization is thought to be responsible should cause a drop in commitment. Experiencing work overload may

also make the immediate work environment less pleasant. As job satisfaction is a reaction directed toward the

immediate work environment, an increase in role overload may precipitate the decline in job satisfaction. To


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summarize, we expect a positive association between the rate of change in role overload and the rates of change in

affective commitment and job satisfaction. As role overload is expected to increase and commitment and satisfaction

to decrease, the following hypotheses are proposed:

Hypothesis 4a: The greater the rate of increase in role overload, the greater the rate of decline in affective

commitment.

Hypothesis 4b: The greater the rate of increase in role overload, the greater the rate of decline in job satisfaction.

By contrast, employees are less likely to invest time and energy ‘‘fighting’’, or attempting to overcome, stressors

that are perceived as hindrance stressors from the beginning, because they do not perceive having the resources to

face these sources of stress; in other words, they do not perceive to have any control over them (LePine et al., 2005).

Further, the organization is less likely to be perceived as being responsible for these stressors, as role conflict

oftentimes results from distinct entities within the organization imposing conflicting demands on employees, and

role ambiguity may be perceived as resulting from a lack of guidance from more proximal entities, such as the

supervisor and/or colleagues. Therefore, we do not expect employees to react to increases in these hindrance

stressors with disengagement from the organization as a way of ‘‘restoring the balance’’. Such changes, however, can

be expected to affect individuals’ level of job satisfaction, an attitude which represents the employee’s enjoyment of

the job (Tett & Meyer, 1993) as opposed to an affective bond with the organization. Further, as role conflict and role

ambiguity constrain employees’ ability to perform and be effective in their jobs, these stressors may impact

negatively their capacity to earn rewards (Schaubroeck, Cotton, & Jennings, 1989). Not being able to perform to

one’s full potential likely reduces enjoyment derived from the job (job satisfaction), but may not impact the strength

of the emotional attachment to the employing organization. For these reasons, we expect change in role conflict and

ambiguity to relate to change in job satisfaction, but not change in organizational commitment. As role conflict was

expected to increase and role ambiguity to decrease over time, the following hypotheses are proposed:

Hypothesis 4c: The greater the rate of increase in role conflict, the greater the rate of decline in job satisfaction.

Hypothesis 4d: The greater the rate of decrease in role ambiguity, the lower the rate of decline in job satisfaction.

Relationship of commitment’s initial status with change in role overload

While prior research has generally considered role stressors as predictors of job attitudes (e.g., Podsakoff et al.,

2007), attitudes may also influence stressors. Indeed, drawing from the idea that individuals with a certain

disposition may adopt behaviors which ‘‘create’’ stressors (Spector, Zapf, Chen, & Frese, 2000), newcomers who

experience high affective commitment at the time of entry may construe their organizational role more broadly,

which may predispose them to experiencing role overload over time. This is because employees enact, in addition to

the ‘‘job-holder role’’ (prescribed duties), an ‘‘organizational-member role’’, which encompasses ‘‘extra-role’’

behaviors (Welbourne, Johnson, & Erez, 1998). A highly committed employee is more likely to define her

organizational-member role more broadly than an employee who is less committed (Morrison, 1994), because she

identifies with the organization’s values and goals, and seeks to advance the organization’s interests. In support for

this view, empirical evidence shows that committed employees are more likely to engage in organizational

citizenship behaviors (e.g., Meyer et al., 2002). This, over time, may lead to overload, because of the resources

required to adequately carry out these extra tasks. We thus predict that newcomers who experience high initial levels

of affective commitment will tend to experience a greater increase in role overload. This leads to the following

hypothesis:

Hypothesis 4e: The higher the initial status of affective commitment, the greater the rate of increase in role

overload.


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Relationships between change in role stressors and change in well-being

A basic assumption of organizational stress theories is that work-related stressors cause strains. Accordingly,

empirical evidence shows that stressors relate negatively to employee well-being (Beehr, Jex, Stacy, & Murray,

2000). However, as past research has relied on static designs to establish these relationships, the single conclusion

one can draw at this point is that the static components of role stressors and well-being should be positively

associated in this study. Nonetheless, we predict that the pattern of these relationships should extend to their change

components, because well-being arguably deviates from its set point during circumstances generating events that

strongly impact individuals (Boswell et al., 2005). As argued in a previous section, the organizational entry period is

an ideal window during which individuals can be influenced by their environment (Louis, 1980), and new entrants

are particularly sensitive to role stressors. Given that role overload and role conflict were expected to increase during

the study period, and role ambiguity and well-being, were expected to decline, the following hypotheses are

proposed:

Hypothesis 5a: The greater the rate of increase in role overload, the greater the rate of decline in employee well-being.

Hypothesis 5b: The greater the rate of increase in role conflict, the greater the rate of decline in employee well-being.

Hypothesis 5c: The greater the rate of decrease in role ambiguity, the lower the rate of decline in employeewell-being.

Relationships among changes in job attitudes, turnover intention, and well-being

Affective commitment and job satisfaction have been reported to relate negatively to turnover intention (e.g., Meyer

et al., 2002; Tett & Meyer, 1993). Indeed, as affective commitment reflects the strength of the emotional bond

between an individual and her organization and job satisfaction refers to affective attachment to the job; the less

attached an employee is to her organization or job, the more she will feel free to consider leaving. Given that turnover

cognitions are thought to evolve in part in response to job attitudes, we expect changes in job attitudes to relate to

changes in turnover intention. Indeed, newcomers, especially neophyte newcomers, should easily translate decreases

in commitment and satisfaction into exit intention because the cost of leaving is generally low during the first months

of employment. We thus expect the rate of (negative) change in affective commitment and satisfaction to relate

negatively to the rate of (positive) change in turnover intention.

Hypothesis 6a: The greater the rate of decline in affective commitment, the greater the rate of increase in turnover

intention.

Hypothesis 6b: The greater the rate of decline in job satisfaction, the greater the rate of increase in turnover

intention.

Finally, empirical evidence suggests that commitment and satisfaction are positively related to psychological

well-being (e.g., Galais & Moser, 2009; Meyer et al., 2002), likely because these attitudes engender positive

emotions, which contribute to well-being. Given the prevalence of unmet expectations during organizational entry

(Wanous, Poland, Premack, & Davis, 1992), negative changes in attitudes may become the norm (Vandenberg &

Self, 1993). Further, as negative changes in commitment and satisfaction can result in frustration and negative

emotions, well-being may drop as well. The following hypotheses are proposed:

Hypothesis 7a: The greater the rate of decrease in affective commitment, the greater the rate of decrease in well-

being.

Hypothesis 7b: The greater the rate of decrease in job satisfaction, the greater the rate of decrease in well-being.


DOI: 10.1002/job


Organizational Context

The sample consisted of business and engineering ‘‘Master’’ graduates from prestigious business schools and

universities in France. Data collection began in October 2007, a time when the unemployment rate in France was the

lowest it had been in about 25 years (7.5%; Institut National de la Statistique et des Etudes Economiques, 2010). In

this context, it is likely that organizations tended to create a positive picture of the organization and job in order to

attract respondents, which may have contributed to them having high expectations upon entry. Academic

socialization may have also contributed to respondents having high expectations, as graduating from a prestigious

school is highly valued in French culture. Having attended such schools, respondents likely expected to find

interesting, rewarding jobs upon graduating. These factors make it likely that respondents experienced a honeymoon

period.

Method

Sample and procedure

With the agreement of faculty deans, a sample of university alumni who graduated from different universities located

in France was first contacted during their last school year, 2006–2007, and asked if they would be willing, after

graduating, to participate in a study on attitudes and behaviors of organizational newcomers. Those who agreed to

participate were surveyed about 5 months after the end of classes, then twice more at 3-month intervals, which

ensured that data would be collected for most respondents during the first year of employment, considered critical in

the socialization literature (Fischer, 1986). Online questionnaires were used for the three waves of surveys. The

questionnaires included measures of role stressors, affective commitment, job satisfaction, turnover intention, and

well-being. Names and email addresses were used to match respondents across time. Of the 783 alumni who were

contacted at Time 1, 376 (48%) responded; among them, 262 (69%) responded at Time 2, and 217 (83%) at Time 3.

We excluded 57 respondents who changed organizations during the study (42 between Time 1 and Time 2, and 15

between Time 2 and Time 3). We did so because most of these individuals probably left for reasons unrelated to

dissatisfaction with the organization. In fact, many respondents had fixed-term rather than permanent employment

contracts. Indeed, given the high level of protection guaranteed by French and European labor regulations to

employees hired under permanent employment contracts, the use of fixed-term contracts is frequent in France as in

many other European countries (OECD, 2009; Poinas, 2010). The usage of fixed-term contracts, which is prevalent

in the hiring of young workers (Poinas, 2010), lowers firing costs and provides organizations with greater flexibility.

A large portion of the 57 individuals who left may thus have changed organizations because their fixed-term contract

was not renewed or may have decided to move to another organization to avoid facing possible unemployment at the

end of their term. Excluding these individuals, our final sample across the three measurements comprised 170

individuals, with average age and tenure at Time 1 being 25.42 years and 2.3 months, respectively, and 44% being

female.

To determine whether subject attrition led to non-random sampling, we tested whether the probability of

remaining in the sample at Time 2 (N¼ 262) and at Time 3 (N¼ 217) among Time 1 respondents (N¼ 376) could be

predicted by demographics and substantive variables (Goodman & Blum, 1996). The first logistic regression

predicting the probability of remaining in the sample at Time 2, with age, sex, organizational tenure and our seven

substantive variables measured at Time 1 as predictors, was non-significant (x2 [9]¼ 13.23, ns). Only sex


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significantly predicted the probability of remaining in the sample at Time 2. The second logistic regression

predicting the probability of remaining in the sample at Time 3, with age, sex, organizational tenure and our seven

substantive variables measured at Time 1 and Time 2 as predictors, was also non-significant (x2 [16]¼ 9.09, ns).

None of the variables significantly predicted the probability of remaining in the sample at Time 3. Thus, respondent

attrition appeared to be essentially random.

Measures

All measures were translated from English to French by one translator and then back-translated independently by a

second translator. Minor discrepancies among translated versions were resolved by a short discussion among

translators. A 5-point Likert-type scale (1, strongly disagree; 5, strongly agree) was used for all items.

Role stressors

Role ambiguity was measured using five items from Rizzo et al.’s (1970) scale (e.g., ‘‘I know what my

responsibilities are’’), and reversing scores. We assessed role conflict using a slightly revised version of Rizzo et al.’s

(1970) 8-item scale (e.g., ‘‘At work, I receive incompatible requests from two or more people’’). Lastly, wemeasured

role overload using a slightly revised version of Schaubroeck et al.’s (1989) 3-item scale (e.g., ‘‘I never seem to have

enough time to get everything done at work’’).

Affective commitment

The French version (Bentein, Vandenberg, Vandenberghe, & Stinglhamber, 2005) of Meyer, Allen, and Smith’s

(1993) affective commitment scale was used (six items; e.g., ‘‘I feel like part of the family at my organization’’).

Job satisfaction

We assessed job satisfaction via Mignonac’s (2008) French translation of two items adapted from Hackman and

Oldham’s (1980) Job Diagnostic Survey (e.g., ‘‘Generally speaking, I’m satisfied with my current job’’).

Turnover intention

Turnover intention was measured with two items adapted from Hom and Griffeth (1991) and Jaros (1997) (e.g., ‘‘I

often think about quitting this organization’’).

Well-being

The six negative items from Warr’s (1990) scale were used to measure employee well-being (‘‘During the past few

weeks, to what extent have you felt the following emotions when thinking about your job?’’: e.g., ‘‘Tense’’).

Results

Descriptive statistics and correlations

As can be seen from Table 1, all variables displayed an acceptable reliability, exceeding the 0.70 threshold with the

exception of Time 1 and Time 2measures of job satisfaction, which fell slightly short of this threshold (as¼ 0.69 and

0.66, respectively). Interestingly, most of the time, commitment correlated positively with role overload. In contrast,

role ambiguity and role conflict correlated negatively with commitment and satisfaction, and positively with

turnover intention, on most occasions. Commitment and satisfaction correlated negatively with turnover intention


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Table

1.Descriptivestatistics

andcorrelationsforthestudyvariables

Variable

MSD

12

34

56

78

910

11

12

13

14

15

16

17

18

19

20

21

1.Role

overload

(T1)

2.691.04

0.90

2.Role

overload

(T2)

2.891.05

0.62

0.91

3.Role

overload

(T3)

2.931.04

0.57

0.57

0.92

4.Role

conflict(T1)

2.240.79

0.39

0.23

0.21

0.86

5.Role

conflict(T2)

2.470.86

0.36

0.33

0.29

0.66

0.88

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conflict(T3)

2.550.83

0.30

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0.38

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ambiguity(T1)

3.430.89

0.17

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ambiguity(T2)

3.370.87

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Note.N

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lphacoefficientsarereported

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orrelationsator>0.21aresignificantatp<0.01andthose

>0.15at

p<0.05,two-tailed.


DOI: 10.1002/job


while well-being correlated negatively with stressors, and positively with satisfaction, yet was unrelated with

commitment on most occasions.

Modeling analyses

LGM analyses were carried out in three phases: (1) tests of measurement invariance between Time 1, 2, and 3 for all

variables; (2) nested model comparisons of alternate univariate second-order factor (SOF) LGM models to

determine the basic form of the growth trajectory for each variable; and (3) multivariate first-order factor (FOF)

LGM models to examine the associations between stressors, affective commitment, job satisfaction, turnover

intention and well-being, in one model, and of commitment and satisfaction to turnover intention and well-being in

another. The first two phases were conducted on the final study sample (N¼ 170), and the third phase on the 319

subjects who at least responded at Time 1 (i.e., 376 minus the 57 turnover cases). This larger sample for the third

phase was obtained from applying the full information maximum likelihood estimation procedure to impute the

Time 2 and Time 3 missing data (Ployhart & Vandenberg, 2010) given that missing data reduced statistical power to

estimate parameters in our (complex) multivariate models. This procedure was justified by the absence of systematic

response bias in our data. For the same reason, we opted for FOF LGM models in estimating multivariate models.

Models were estimated using LISREL 8.54 (Joreskog, Sorbom, Du Toit, & Du Toit, 2001). The following fit indices,

commonly used in the literature, were used: (a) the chi-square test; (b) the comparative fit index (CFI); (c) the non-

normed fit index (NNFI); (d) the standardized root mean square residual (SRMR); and (e) the root mean square error

of approximation (RMSEA). To compare the fit of nested models, the x2 difference test was used.

Measurement invariance

Nested model comparisons were first performed to test measurement equivalence. Results indicated that the

assumption of configural (i.e., the nature of the construct that is operationalized by measured variables remains

unchanged across measurement occasions) and metric (i.e., the relations between measures and their corresponding

constructs are invariant across measurement occasions) invariance was met for all focal variables. Thus, invariance

constraints were incorporated in LGM analyses.

Univariate SOF LGM analyses

Nested univariate SOF LGM models were then tested for each variable to examine the form of longitudinal change

and the structure of FOFs’ residuals – in other words, the change trajectory for each variable. Model 0 was a ‘‘no

growth’’ model, Model 1 featured a linear change and homoscedastic residuals, Model 2 involved a linear change

and heteroscedastic residuals. Models 3 and 4 presented an optimal growth trajectory factor with FOF residuals

being either homoscedastic (Model 3) or heteroscedastic (Model 4). We compared nested models (homoscedastic vs.

heteroscedastic; linear vs. nonlinear) in order to select the SOF LGM model that most parsimoniously described the

change trajectory of each variable.

Table 2 presents the results of these analyses. As the contrast (Dx2) between Model 0 and Model 1 or 2 was non-

significant for role ambiguity and well-being, these variables displayed a flat trajectory of change across time.

Therefore, Hypotheses 1c and 3 were not supported. For all the other variables (role overload, role conflict, affective

commitment, job satisfaction, and turnover intention), nested model comparisons showed that a linear change model

(Model 1 or 2) provided a significant improvement over a no-growth model (Model 0). In addition, comparisons

between Model 1 and Model 2 and between Model 3 and Model 4 showed that allowing residuals to display a

heteroscedastic structure did not improve model fit for these variables. Therefore, the more parsimonious

homoscedastic structure for residuals should be preferred. Additional contrasts between Model 1 and Model 3 and

between Model 2 and Model 4 for role overload, role conflict, affective commitment, job satisfaction, and turnover

intention showed that models including an optimal change function did not improve significantly over models that


DOI: 10.1002/job


displayed a linear change function. Thus, on the basis of parsimony, the linear trajectory of change model was

selected as the model best depicting intraindividual change over time for these variables.

To more precisely determine the shape of the growth trajectories (positive vs. negative) for the variables in

question, we examined the SOF LGM parameter estimates (factor means and variances) for the initial status and

change factors of the selected models. Results are presented in Table 3. In support for Hypotheses 1a and 1b, the

change factor mean was positive and significant for role overload and role conflict (mCH¼ 0.11, p< 0.01, and 0.14,

p< 0.001, respectively), indicating that these variables increased linearly across time. Further, results also show

interindividual variations in both the initial status (s2IS¼ 0.66, p< 0.001, and 0.39, p< 0.001, respectively) of, and

change (s2CH¼ 0.03, p< 0.10, and 0.03, p< 0.10, respectively) in, role overload and role conflict, suggesting that

Table 2. Univariate SOF latent growth models: Tests of alternative SOF LGM specifications

Changefunction

FOF residualsstructure x2 df CFI NNFI SRMR RMSEA

Role overload Model 0 No change 72.84 29 0.98 0.97 0.08 0.09Model 1a Linear Homoscedastic 63.00 28 0.98 0.98 0.08 0.08Model 2 Linear Heteroscedastic 62.42 26 0.98 0.97 0.08 0.09Model 3 Optimal Homoscedastic 62.10 27 0.98 0.98 0.08 0.08Model 4 Optimal Heteroscedastic 60.80 25 0.98 0.97 0.08 0.09

Role conflict Model 0 No change 520.18 264 0.96 0.96 0.09 0.07Model 1a Linear Homoscedastic 491.42 263 0.97 0.96 0.08 0.06Model 2 Linear Heteroscedastic 487.63 261 0.97 0.96 0.08 0.06Model 3 Optimal Homoscedastic 489.26 262 0.97 0.96 0.08 0.06Model 4 Optimal Heteroscedastic 486.66 260 0.97 0.96 0.07 0.06

Role ambiguity Model 0a No change 163.97 96 0.98 0.98 0.08 0.06Model 1 Linear Homoscedastic 161.59 95 0.98 0.98 0.08 0.06Model 2 Linear Heteroscedastic 159.57 93 0.98 0.98 0.08 0.06Model 3 Optimal Homoscedastic 159.72 94 0.98 0.98 0.08 0.06Model 4 Optimal Heteroscedastic 160.47 92 0.98 0.98 0.08 0.06

Affective commitment Model 0 No change 280.15 143 0.98 0.98 0.10 0.07Model 1a Linear Homoscedastic 268.46 142 0.99 0.98 0.10 0.07Model 2 Linear Heteroscedastic 267.67 140 0.99 0.98 0.10 0.07Model 3 Optimal Homoscedastic 268.39 141 0.99 0.98 0.10 0.07Model 4 Optimal Heteroscedastic 272.78 139 0.98 0.98 0.10 0.07

Job satisfaction Model 0 No change 35.16 9 0.95 0.92 0.06 0.13Model 1a Linear Homoscedastic 8.64 8 1.00 1.00 0.03 0.02Model 2 Linear Heteroscedastic 6.88 6 1.00 1.00 0.02 0.03Model 3 Optimal Homoscedastic 4.80 7 1.00 1.00 0.03 0.00Model 4 Optimal Heteroscedastic 4.43 5 1.00 1.00 0.02 0.00

Turnover intention Model 0 No change 77.27 9 0.92 0.86 0.09 0.20Model 1a Linear Homoscedastic 15.59 8 0.99 0.98 0.04 0.07Model 2 Linear Heteroscedastic 14.90 6 0.99 0.97 0.04 0.09Model 3 Optimal Homoscedastic 15.34 7 0.99 0.98 0.05 0.08Model 4 Optimal Heteroscedastic 14.87 5 0.92 0.86 0.09 0.20

Well-being Model 0a No change 377.87 143 0.93 0.93 0.09 0.10Model 1 Linear Homoscedastic 377.90 142 0.93 0.93 0.09 0.10Model 2 Linear Heteroscedastic 375.78 140 0.93 0.93 0.09 0.10Model 3 Optimal Homoscedastic 374.72 141 0.93 0.93 0.09 0.10Model 4 Optimal Heteroscedastic 374.54 139 0.93 0.93 0.09 0.10

SOF, second-order factor; LGM, latent growth modeling; NNFI, non-normed fit index; CFI, comparative fit index; SRMR, standardized root meansquare residual; RMSEA, root mean square error of approximation.aRetained (most parsimonious) model.


DOI: 10.1002/job


some newcomers perceived higher levels of overload and conflict than others at entry, and that overload and conflict

increased at faster rates for some newcomers than others over the period of the study.

With respect to affective commitment and job satisfaction, the change factor mean was negative and significant

(mCH¼�0.09, p< 0.001, and�0.17, p< 0.001, respectively), indicating a linear decline in these two variables over

time. These findings yield support for Hypotheses 2a and 2b. In addition, the variance of initial status (s2IS¼ 0.82,

p< 0.001, and 0.47, p< 0.001, respectively) of, and change (s2CH¼ 0.01, p< 0.10, and 0.08, p< 0.05, respectively)

in, affective commitment and satisfaction were significant, revealing interindividual variance on newcomers’ mean

levels at entry and rates of decrease on commitment and satisfaction.

Finally, in support for Hypothesis 2c, the change factor mean for turnover intention was positive and significant

(mCH¼ 0.36, p< 0.001), suggesting that turnover intention increased over the time period of the study. In addition,

results showed interindividual variations in both the initial status of, and change in, turnover intention (s2IS¼ 0.92,

p< 0.001, and s2CH¼ 0.15, p< 0.001), revealing that some newcomers displayed greater turnover intention at entry

than others, and that newcomers differed in their rate of increase in turnover intention over time.

Multivariate FOF LGM models

As a last step, we examined the associations among initial status and change factors among study variables. First, we

estimated a multivariate FOF LGM model (which incorporated the retained specifications of variables’ univariate

LGM models and allowed covariances among initial status and change factors to be freely estimated) that included

the three stressors, affective commitment, job satisfaction, turnover intention, and well-being. That model yielded a

good fit to the data, x2 (151)¼ 356.80, p< 0.01, CFI¼ 0.92, NNFI¼ 0.88, SRMR¼ 0.032, and RMSEA¼ 0.065.

Table 4 presents the latent covariances among growth parameters for this model. Hypothesis 4a, which predicted a

positive association between the rate of increase in role overload and the rate of decline in commitment (C¼�0.02,

p< 0.05) and Hypothesis 4c, which predicted a positive association between the rate of increase in role conflict and

the rate of decline in job satisfaction (C¼�0.03, p< 0.05) were supported. Hypothesis 4e, which predicted that the

initial status of commitment would be related to an increase of role overload, was also supported (C¼ 0.09,

p< 0.001). Hypothesis 4b, which predicted a positive association between the rate of increase in role overload and

the rate of decline in satisfaction, was not supported (C¼�0.02, ns). Hypotheses 4d, 5a, 5b, and 5c could not be

tested because role ambiguity and well-being did not change over time (cf. Table 3).

Other findings are worth noting. First, the initial statuses of overload, conflict, and ambiguity were negatively

related to the initial status of well-being (Cs¼�0.26, �0.22, and �0.17, respectively, all p< 0.001). Second, the

Table 3. Univariate SOF latent growth models: Growth parameters estimates

Variable

Initial status (IS) Change (CH)

CovarianceIS–CH (sIS–CH)

Mean(mIS)

Variance(s2IS)

Mean(mCH)

Variance(s2CH)

Role overload (linear and homoscedastic) 2.70�� 0.66�� 0.11�� 0.03y �0.03Role conflict (linear and homoscedastic) 2.16�� 0.39�� 0.14�� 0.03y �0.01Role ambiguity (no change) 3.33�� 0.47�� – – –Affective commitment (linear and homoscedastic) 3.45�� 0.82�� 0.09�� 0.01y 0.00Job satisfaction (linear and homoscedastic) 3.91�� 0.47�� 0.17�� 0.08� �0.04y

Turnover intention (linear and homoscedastic) 2.16�� 0.92�� 0.36�� 0.15�� 0.08y

Well-being (no change) 3.00�� 0.14�� – – –

Note. Standardizing the manifest variables impedes the ability to examine change because the standardization equates the means and variances(Tisak & Meredith, 1990); therefore, unstandardized estimates are reported. Note that given the relatively low sample size (N¼ 170) which mayreduce power in the estimation of parameters in latent growth modeling analyses, we used a more liberal p value of 0.10 (for a similar practice, seeJokisaari & Nurmi, 2009). SOF, second-order factor.yp< 0.10; �p< 0.05; ��p< 0.01; ��p< 0.001.


DOI: 10.1002/job


initial statuses of commitment, satisfaction, and well-being were positively associated with an increase in role

overload (C¼ 0.09, p< 0.001, C¼ 0.12, p< 0.001, and C¼ 0.04, p< 0.05, respectively). Third, the initial status of

turnover intention was associated with a reduced increase of role overload (C¼�0.11, p< 0.01). Finally, the

increase in role conflict was positively related to the increase in turnover intention (C¼ 0.03, p< 0.05). Second, we

estimated a multivariate FOF LGM model including job attitudes as antecedents of turnover intention and well-

being. This model fit the data quite well, x2 (49)¼ 105.13, p< 0.01, CFI¼ 0.96, NNFI¼ 0.93, SRMR¼ 0.023, and

RMSEA¼ 0.060. Table 5 presents the latent covariances among growth parameters for this model. Supporting

Hypotheses 6a and 6b, the declines in affective commitment and job satisfaction were significantly associated with

the increase in turnover intention (Cs¼�0.06 and�0.12, both p< 0.001). Finally, as well-being did not change over

time (cf. Table 3), Hypotheses 7a and 7b could not be tested.

Table 5 also reveals that the initial status of commitment and satisfaction was positively related with well-being’s

initial status (Cs¼ 0.11 and 0.22, both p< 0.001), and that job satisfaction’s initial status was related to an increase

in turnover intention (C¼ 0.07, p< 0.05).

Note that the inclusion of the 57 individuals who turned over in the course of the study to the sample used for

testing the twomultivariate FOF LGMmodels (resulting in aN of 376 instead of 319) did not change significantly the

results presented in Tables 4 and 5. Similarly, the inclusion of sex, age, and organizational tenure as controls did not

affect the results either.

Table 5. Latent covariances among growth parameters in a multivariate FOF LGM model: affective commitment, jobsatisfaction, turnover intention, and well-being

Affective commitment Job satisfaction

Initial status Change Initial status Change

Turnover intention Initial status �0.47�� 0.08�� 0.57�� 0.06Change 0.06 �0.06�� 0.07� �0.12��

Well-being Initial status 0.11�� 0.01 0.22�� 0.01

Note. FOF, first-order factor; LGM, latent growth modeling.�p< 0.05; ��p< 0.01; ��p< 0.001.

Table 4. Latent covariances among growth parameters in a multivariate FOF LGM model: Stressors, affective commitment, jobsatisfaction, turnover intention, and well-being

Role overload Role conflict Role ambiguity

Initial status Change Initial status Change Initial status

Affective commitment Initial status 0.07 0.09�� 0.15�� 0.00 �0.22��

Change 0.04� �0.02� 0.03 0.00 0.01Job satisfaction Initial status �0.10� 0.12�� 0.30�� 0.04 �0.26��

Change 0.04 �0.02 0.03 �0.03� �0.03Turnover intention Initial status 0.14�� 0.11�� 0.28�� 0.01 0.28��

Change �0.05 0.03 �0.02 0.03� 0.00Well-being Initial status �0.26�� 0.04� �0.22�� 0.01 �0.17��

Note. For interpreting the meaning of covariances among LGM parameters, one needs to account for the nature of the change as reported in Table3. For example, a negative covariance between a decreasing change (i.e., the change factor mean [mCH] in Table 3 has a negative sign) and anincreasing change (i.e., the change factor mean [mCH] in Table 3 has a positive sign) indicates a positive relationship between the two: The steeperthe decline in one variable, the steeper the increase in the other. FOF, first-order factor; LGM, latent growth modeling.�p< 0.05; ��p< 0.01; ��p< 0.001.


DOI: 10.1002/job


Discussion

This study aimed to examine change in role stressors, job attitudes, turnover intention, and well-being during

organizational socialization and the role of change in the relationships among these variables in a sample of neophyte

newcomers. Based on the idea that newcomers’ appraisal mechanisms evolve toward more realism in the assessment

of encounters and resources over time (Lazarus & Folkman, 1984), we expected variables to change over time.

Moreover, drawing fromAET (Weiss &Cropanzano, 1996), we contended that expected increases in stressors would

influence changes in socialization outcomes. We also argued that employees’ initial level of commitment would

influence the evolution of role overload over time, and that decreases in commitment and job satisfaction over time

would result in an increase in turnover intention and a decline in well-being.

Theoretical implications

Using LGM to operationalize change, we found that perceptions of role conflict and role overload increased over the

study period, while affective commitment and job satisfaction declined and turnover intention increased. These

findings are consistent with the idea that newcomers are initially bound by prior positive beliefs about the

organization, and initially overestimate their resources to face the demands of their job – this may have been

amplified in our study as our neophytes got little job exposure before entry – and with the notion that a more realistic

process comes into play as time passes.

Contrary to expectations, however, no changes occurred in respondents’ perceptions of role ambiguity or in their

level of well-being. The fact that role ambiguity did not change may be due to the fact that individuals are not equally

proactive in seeking the information which would result in a reduction of ambiguity (Kammeyer-Mueller &

Wanberg, 2003), and organizational environments may not be equally helpful in clarifying expectations.

Alternatively, newcomers’ efforts at gaining information and learning curve may have prevented ambiguity from

increasing over time, as did the two other stressors. As for psychological well-being, the fact that no change occurred

appears somewhat puzzling given that our measure of well-being was work-related and that a number of assumed

predictors of workplace well-being included in this study did evolve following a negative trend. A potential

explanation for this may be that the influence of dispositional factors, such as neuroticism, negative affectivity or

trait anxiety, on well-being is underestimated. The argument has been made that dispositions determine the level at

which well-being tends to return after a ‘‘strong’’ situation has exerted its influence (e.g., Boswell et al., 2005). Given

that such situation was likely present in our study (Louis, 1980), the fact that well-being did not change provides

arguments for the importance of dispositional factors in well-being (see below).

We also found a positive change in role overload to be associated with a decline in affective commitment, while a

positive change in role conflict was associated with a decline in job satisfaction. These results lend support to the idea

that stressors influence job attitudes, but more interestingly, the differentiated effects of the two stressors (either on

commitment or on satisfaction) suggest that employee responses depend on whether the organization is perceived as

being responsible for the stressor. Indeed, the organization is likely seen as controlling employees’ workloads, which is

consistent with the finding that ‘‘insufficient resources’’ is the main perceived cause of work overload (Gryna, 2004), but

not the role conflicts which may be created by its constituents. Ultimately, though, the organization is penalized, as

declining changes in commitment and satisfaction were related to increasing change in turnover intention.

Unexpectedly, the increasing change in role conflict was also associatedwith the increasing change in turnover intention.

In other words, employees see this source of stress, in itself, as a reason to think about leaving. In addition, the initial

levels of affective commitment, job satisfaction, turnover intention, andwell-being were all related to the increase in role

overload. While the latter findings were not expected, they all support the idea that prior attitudes, cognitions and

psychological states may influence the perception of stressors, either by making employees susceptible to adopt

behaviors which create stressors, or bymaking themmore sensitive to stressors. Lastly, we found that the initial status of


DOI: 10.1002/job


job satisfaction was positively related to the rate of increase in turnover intention. This indicates that initial levels of

satisfaction may put individuals at risk of subsequent disappointment, which may lead to disengagement. It is also

consistent with the notion that ‘‘the higher they are, the harder they fall’’ (Brockner, Tyler, & Cooper-Schneider, 1992).

Our results provide an interesting insight into the psychology of role overload. Indeed, role overload correlates

positively with affective commitment (cf. Table 1). However, when one adopts a dynamic perspective, a different

pattern emerges. The initial level of overload, for instance, was associated with the decline in affective commitment,

suggesting that those who experienced overload at entry also experienced a steeper decline in commitment over time.

Similarly, an increase in overload was associated with a steeper decrease in commitment (cf. Table 4). This may

indicate that it is the perception of an increase in role overload over time, rather than a feeling of being overloaded at

one point in time, which exerts truly detrimental effects. Further, the fact that the level of affective commitment at entry

was related to an increasing change in role overload suggests that those who start off with a strong affective

commitment are probably more likely to become overloaded due to their willingness to contribute. This relationship

may explain the positive relationship which can be observed, adopting a static perspective, between the two constructs.

An alternative explanation for the divergent effects of role overload may be that this stressor can be appraised

simultaneously as a challenge and a hindrance. Indeed, recent research suggests that these may be two dimensions

that can be used for describing stressors, rather than mutually exclusive categories (Gilboa, Shirom, Fried, & Cooper,

2008; Staufenbiel & Konig, 2010). In sum, our perspective and results as well as those of these recent studies suggest

that the challenge/hindrance distinction is not a hermetic one; future research will help to determine whether

stressors can go from challenging to hindering, or whether they can present challenging and hindering facets

simultaneously.

Practical implications

This study has implications for practice. The significant increase in perceived role conflict and role overload, decline

in job satisfaction and affective commitment, and increase in turnover cognitions provide evidence that newcomers

become more realistic in their appraisal of environmental demands and resources to face them, and may feel initial

expectations are not met. While expectations are determined in part by individual factors, organizations clearly play

a role in shaping them. This study’s results emphasize the importance of avoiding painting an overly positive picture

during the recruitment process, but rather strive to provide ‘‘realistic job previews’’ (Buckley, Fedor, Veres, Wiese, &

Carraher, 1998), that is, sufficient and accurate information regarding the job and thework environment. This study’s

results also emphasize the importance of reducing role stressors to which newcomers are exposed. Indeed, the faster

stressors are perceived to increase, the faster job attitudes fall. This will likely entail negative consequences for

organizations as, in addition to intended turnover, affective commitment, and job satisfaction are known predictors

of turnover and job performance. The solution may be to provide sufficient workload to employees, while making

sure that the employees’ increased efforts to meet this challenge are met with success. Organizational support, as a

valuable resource, may also contribute to keeping their workload manageable, hence turning it into a challenge

rather than a hindrance.

Limitations and future directions

This study has limitations. First, we did not examine the order of causality between variables. Along this line, it

would be worth examining whether job attitudes mediate the effect of stressors on turnover intention and strain.

Inclusion of these variables within a panel design would allow researchers to examine whether job attitudes act as

mediators within dynamic relationships. Another limitation stems from the use of self-report measures. Although

collecting data at several points in time reduces common method variance, studies using multiple sources of data are

warranted. Finally, we did not control for dispositions which could influence stressors and well-being, and/or exert


DOI: 10.1002/job


an effect on outcomes. The fact that trends were observed for the entire sample in the perception of stressors and in

job attitudes while no such trend occurred with regards to well-being suggests that dispositional factors may play a

greater role in influencing well-being than previously thought, but does not exclude the possibility that dispositions

also bias the perception of stressors (cf. Judge, Erez, & Thoresen, 2000). Individual differences may also moderate

the patterns of change in stressors, attitudes or well-being, as we suggested in the case of role ambiguity.

Overall, this study revealed that role overload and conflict increased over time among neophyte newcomers, but

that well-being was immune to short-term fluctuations in perceived stressors and job attitudes. Future research

examining the dynamics of stressors and attitudes during organizational entry will be critical to further advance our

understanding of the complex phenomenon of newcomer socialization.

Author biographies

Christian Vandenberghe is a professor of organizational behaviour at HEC Montreal. Since 2005, he has been the

holder of the Canada Research Chair in management of employee commitment and performance. His research

interests include organizational commitment, turnover and performance, organizational change, and employee well-

being. His work has been published in a variety of journals, including Journal of Applied Psychology, Journal of

Organizational Behavior, Journal of Vocational Behavior, Journal of Occupational and Organizational Psychology,

Group & Organization Management, and Human Resource Management.

Alexandra Panaccio has completed her Ph.D. in administration at HECMontreal in 2009 and is now a postdoctoral

fellow at the University of Illinois at Chicago. Her current research focuses on workplace commitments, leadership,

employee well-being, and retention. Her work has been published in peer-reviewed journals, including Journal of

Vocational Behavior and Journal of Occupational and Organizational Psychology.

Kathleen Bentein is a professor of organizational behaviour at Ecole des sciences de la gestion, Universite du

Quebec a Montreal. Her research interests include commitment toward multiple foci, turnover, attitude change

across time, and newcomer socialization. Her work has been published in a variety of journals, including Journal of

Applied Psychology, Journal of Vocational Behavior, and Journal of Occupational and Organizational Psychology.

She is currently co-Director of the Competency Management Chair at her university.

KarimMignonac is a professor of organizational behavior and human resource management at Universite Toulouse 1

Capitole. His current research interests include commitment and identification in organizations, interorganizational

relationships, and volunteering. His work has been published in a variety of journals, including Strategic Management

Journal, Journal of Organizational Behavior, Journal of Vocational Behavior, and Human Resource Management.

Patrice Roussel is a professor of organizational behaviour and human resource management at Universite Toulouse

1 Capitole. He is the director of the Center of Research in Management (CNRS). His research interests include work

motivation, job satisfaction, individual performance, organizational socialization, compensation policy and manage-

ment, and methodology. His work has been published in a variety of journals, including Journal of Organizational

Behavior, International Journal of Human Resource Management, and Revue de Gestion des Ressources Humaines.

He has published seven research books in France and Europe.

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Assessing longitudinal change of and dynamic relationships among role stressors, job attitudes, turnover intention, and well-being in neophyte newcomers