In E. Gullone and R. A. Cummins (Eds.), (2002). The Universality of Subjective Wellbeing Indicators (pp. 151-173). Dordrecht, The Netherlands: Kluwer Academic Publishers.
GEORGIA POMAKI AND STAN MAES
PREDICTING QUALITY OF WORK LIFE: FROM WORK CONDITIONS TO SELF-REGULATION
Abstract. Quality of work has been frequently defined in terms of work conditions. Work conditions, described in theoretical models (as the Job Demand-Control-Social support model, the Effort-Reward Imbalance model and the Vitamin model) are presented as important predictors of wellness/health outcomes. Although empirical findings have clearly illustrated the predictive power of these models, limitations and inconsistent results support the exploration of additional, complementary perspectives. We suggest a person-centered, self-regulatory approach to quality of work life. Personal goals are presented as the core predictor of wellness and health. Within Motivational Systems theory (MST), personal goals help employees direct and organize behavior. The strategies and processes involved in goal pursuit are predictive of goal attainment. The opportunity to attain goals or the frustration of one’s goals is the key to health and wellness. Although there are several theoretical models and theories describing the cognitive and emotional processes involved in the pursuit of personal goals, empirical research concentrating on such phenomena at the workplace has been scarce. An overview of studies investigating the relationship between personal goals and wellness/health outcomes among employees is presented and discussed. Although most of the studies stem from different theoretical models, we focus on goal processes that are common with MST processes in an attempt to provide constructive and systematic conclusions. Goal processes were significantly predictive of wellness indicators and workrelated outcomes in cross-sectional as well as longitudinal studies. More attention should however be paid on the assessment and operationalization of goals and the choice of the appropriate goal level. Personal goals and the processes involved in goal pursuit are certainly worthy of further investigation as part of sound, integrative models.
INDICATORS OF QUALITY OF WORK LIFE The majority of people spend between one third and one half of their active life at work. According to some authors, people’s quality of life is determined by their perceptions of their performance concerning four functional areas: physical and occupational functioning, psychological state, social interaction and somatic sensation (Schipper, Clinch, & Powell, 1990). Although not explicitly considered by these authors, the link between quality of life and quality of work life is obvious. From a conceptual perspective, Calman (1984) was the first to suggest that quality of life is determined by the gap between the person’s expectations and actual achievements. The potential gap between expectation and achievement can shape individuals’ perceptions of their performance on the aforementioned functional areas. The definition implies that quality of work life includes objective indicators of professional achievement (such as career and job performance) as well as indicators of the distance between the achievements and the person’s needs and expectations. In other words, quality of work life is a subjective concept. Over the past two decades, numerous investigations have been concerned with the prediction of quality of work life, both in and outside of the discipline of psychology. We first turn to several literature reviews, which summarize the effects of work conditions on work-related outcomes, psychological well-being, and
physical health. We then consider the models that give a more systematic insight into these data. This is followed by a person-centered approach related to the prediction of wellness and health at the workplace, namely motivational systems theory. Finally, we present and discuss empirical findings concerning the predictive value of personal goals, as the core component of this theory and give suggestions for future goal research on employee health. EFFECTS OF WORK CONDITIONS ON HEALTH AND WELLNESS Work-related outcomes, such as job satisfaction, intention to turnover, remaining in work, organizational commitment, job performance, absenteeism, and work-related accidents have been significantly predicted by work conditions (Lund & Borg, 1999; Roe, Zinovieva, Dienes, & Ten, 2000; Lu, Kao, Cooper, & Spector, 2000; Iverson & Maguire, 2000; Hui & Lee, 2000; Vahtera, Kivimaki, Uutela, & Pentti, 2000; Greiner, Krause, Ragland, & Fisher, 1998; Fried, BenDavid, Tiegs, Avital, & Yeverechyahu, 1998). In a review of absenteeism research, Harrison and Martocchio (1998) concluded that work characteristics play a significant role in the absenteeism process. Absenteeism was also found to be significantly related, in a time period of a few months to a year, to various withdrawal-indicative behaviors and low job performance. Studies investigating the relationship between work characteristics and psychological well-being have found strong associations with outcomes, including depression (Dwyer & Mitchell, 1999), self-esteem (Schonfeld, 2000), physical, psychological and social functioning (Stansfeld, Bosma, Hemingway, & Marmot, 1998; Sundquist & Johansson, 2000), emotional exhaustion (Feldt, Kinnunen, & Maunao, 2000), general stress levels (Rose, Jones, & Fletcher, 1998), mental health (Lu, Kao, Cooper, & Spector, 2000), psychiatric morbidity (Cropley, Steptoe, & Joekes, 1999), and accident proneness (Kirschenbaum, Oigenblick, & Goldberg, 2000). Finally, regarding physical health, one of the most frequently studied outcomes is cardiovascular disease together with cardiovascular disease symptoms, and coronary heart disease. Schnall, Landsbergis and Baker (1994), in their review of job strain and cardiovascular disease (CVD), concluded that there is considerable evidence to suggest a strong association between job characteristics and CVD outcomes, such as CVD morbidity and mortality, myocardial infarction, angina pectoris, coronary heart disease (CHD), and all-cause mortality. Tennant (2000) also concluded that job stress consistently predicts CHD events and CHD-adverse risk factors. A review by Kasl (1996) on the same topic suggested that there has been considerable empirical support for the association between work-related factors and coronary heart disease, mainly in studies conducted within sound theoretical frameworks. Several recent studies have also supported the association of job characteristics with coronary heart disease events (Wamala, Mittleman, Horsten, Schenck, & Orth, 2000), and mortality due to coronary heart disease (Alterman, Shekelle, Vernon, & Burau, 1994). Deleterious work environments have been shown to be predictive of increased use of non-medical drugs (Storr, Trinkoff, & Anthony, 1999), of increased blood pressure (Landsbergis et al., 1994; Steptoe, Cropley, & Joekes, 1999), and male
mortality (Hemstrom, 1999). Achat et al. (2000) in a study of the association between work stress and the incidence of invasive or in situ breast cancer among nurses found that less favorable work environments were associated with screening for breast cancer; no relation was observed with tumor diagnosis. Finally, literature reviews have showed that work conditions are somewhat related to lower back pain (Davis & Heaney, 2000) and to reduced reproductive health (Cox, Cox, & Pryce, 2000). In summary, in most of the cross-sectional, longitudinal and cross-cultural studies investigating the impact of adverse work conditions on employee wellness and health an association indeed has been confirmed. Models of work conditions attempt to identify specific work conditions that are of importance to wellness and health, describe pathways between work conditions and outcomes and explain how changes in the work environment, either positive or negative, can influence employee wellness and health. We turn to three such models in the following section. The first model is one of the most influential and most frequently tested models, while the last two models have been viewed as specification or relevant addition to the first model (Theorell & Karasek, 1996). MODELS OF QUALITY OF WORK LIFE The J-DCS Model The job demands-control-social support model (J-DCS), developed initially by Karasek (J-DC, Karasek, 1979; Karasek & Theorell, 1990) and later extended with the social support component by Johnson and Hall (J-DCS, 1988) is one of the most influential models on occupational stress. It has been tested in over 100 empirical studies (c.f. Barnett & Brennan, 1995). The initial J-DC model has two diagonals, the strain diagonal and the learning diagonal. On the strain diagonal the combination of demands and control results in four different classifications of jobs represented by the four quadrants of the model. These are labeled “high strain” jobs (high demands, low control), “low strain” jobs (low demands, high control), “active” jobs (high demands, high control) and “passive” jobs (low demands, low control) (Landsbergis, Schnall, Deitz, Friedman, & Pickering, 1992). On the learning diagonal, learning can inhibit strain in such a way that resource-taxing situations are converted into opportunities for growth and learning, by the exercising of control over one’s own work activities (Storr, Trinkoff, & Anthony, 1999). The basic premise of the J-DCS model is described in the strain and iso-strain hypotheses, which state that psychological strain and physical ill health can be predicted by the main effects of increased job demands, lack of control (strain) and lack of social support (iso-strain). Another way of looking at the model is to treat control and social support as buffer factors that reduce the detrimental effects of high demands on health outcomes (buffer-hypothesis). In this case, the interaction between demands, control and social support predicts the outcomes. To summarize, the J-DCS model has been described by means of three hypotheses:
(1)
The (iso-) strain hypothesis (demands, control, and social support predict strain).
(2)
The learning hypothesis (demands and control predict personal growth).
(3)
The buffer hypothesis (control and social support buffer the negative effects of demands on health).
In a review of 51 studies on the J-DC or the expanded J-DCS model and physical health outcomes, van der Doef and Maes (1998) explored the first and third hypotheses. The review revealed that the ‘strain’ hypothesis predominates in studies of all cause-related (i.e. mortality, cardiovascular disease related and other noncardiovascular disease) health outcomes, such as musculoskeletal symptoms and pregnancy outcomes. In contrast, the ‘buffer’ hypothesis proved to be most prevalent in research on self-reported psychosomatic complaints. In the case of both the strain hypothesis and the buffer hypothesis, the empirical findings are equivocal. Working in a high (iso-) strain job appears to be associated with elevated risk of cardiovascular disease and negative pregnancy outcomes, and a greater number of somatic and psychosomatic complaints. Conclusions concerning other physical outcomes seemed premature, considering the limited number of studies. The buffer hypothesis is supported in the few studies on cardiovascular disease outcomes and in some studies on somatic and psychosomatic complaints (Verhoeven, Maes, Kraay, & Joekes, in press). In a second review of 63 studies van der Doef and Maes (1999) explored the relationship between the J-DC(S) model and outcomes reflecting psychological well-being, such as depression, anxiety, job satisfaction, and burnout. The same two hypotheses were considered. While the literature provides considerable evidence supporting the strain and iso-strain hypotheses, support for the moderating influence of job control and social support is less consistent. The conceptualization of demands and control proved to be a key factor discriminating supportive from nonsupportive studies. This suggested that conceptualizations of job control should correspond with the specific demands of a given job. Detailed methodological questions have been successfully raised in several reviews concerning the J-DC(S) model (Carayon, 1993; van der Doef & Maes, 1998; Fletcher & Jones, 1993; Karasek, 1989; Landsbergis et al., 1992; Kristensen, 1995; Kristensen, 1996; Theorell & Karasek, 1996). One common critique is that the model explains a limited amount of variance in health outcomes or measures of psychological strain. It is also criticized as being too simple, due to its focus on just three work conditions. Inconsistency of evidence for the J-DCS model may also be attributed to a number of factors: inappropriate interaction terms used; inadequate operationalization of the concepts of job demands, control and social support; the use of occupational level analysis in some studies and the use of homogeneous samples in others; overlooking employment grade issues; gender differences; the possible moderating effects of personality variables that determine the vulnerability to stressors or the ability to benefit from the buffer factors. Finally, additional shortcomings have been suggested, including a conceptual overlap between the
stressor and the outcome variable, and possible common-method variance effects (van der Doef & Maes, 1999). Searle, Bright, and Bochner (1999) concluded that lack of support of the buffer hypothesis “may reflect problems with the theoretical model”. There are also a few conceptual considerations with regard to the J-DCS model. First, lack of consistent support for the J-DCS hypotheses could be attributed to individual differences that can underline vulnerabilities to job stressors. For example, within a given working population individuals may have varying degrees of need for demands, control and social support. Second, although there is a plethora of research investigating the relationship between the model’s three basic components with a variety of outcomes, it is unclear why high job demands, low job control and low social support constitute job stressors. The three model components could be related to basic human needs, the attainment of which is a prerequisite to effective human functioning. According to the self-determination theory (Deci, Connell, & Ryan, 1989), there are three basic needs that individuals strive to fulfill – competence, autonomy, and relatedness. Demands and competence, control and autonomy, and social support and relatedness could be related constructs. It is unknown how the work conditions and needs constructs relate to each other and whether the presence of unfavorable work conditions, as described by the J-DCS model, can thwart the fulfillment of these basic needs. These research questions may be worthy of further investigation. The Effort-Reward Imbalance Model The effort-reward imbalance model (ERI) that was developed by Siegrist (1996) is composed of environmental as well as personal components. The model encompasses broad psychosocial parameters and, according to Theorell and Karasek (1996), it could bring new insights to the J-DCS model. The aim of the ERI model is to identify work-related stressors as well as coping strategies that can predict strain and ill health. In the most recent version, the model specifies the environment and the person as the two sources of stress (Peter & Siegrist, 1999). Regarding the role of the work environment, the imbalance between high efforts spent at work and low rewards obtained predicts sustained stress experiences and consequently adverse health outcomes. Efforts are defined as the strivings of the individual to meet the demands and obligations of the job. Rewards can be obtained by means of three systems: money, esteem, and career opportunities, including job security. Regarding the role of the individual, the coping pattern of overcommitment is introduced as a possible source of strain, as it represents the tendency towards excessive striving, motivated by an overarching need for approval and esteem. It is assumed that the goal of the individual is to gain equilibrium and/or reduce stress, so effort-reward imbalance cannot be sustained in the long run. Peter and Siegrist (1999) emphasize that under certain conditions overcommitted individuals tend to persist investing in their jobs, independent of their high effort-low reward status, a condition that will eventually predict ill health. In a series of studies, Siegrist and his co-workers investigated the relationship between the model components and health outcomes. Using cardiovascular risk or disease as the health
outcome, five studies have fully or partially supported the model (Peter & Siegrist, 1999). The Vitamin Model The vitamin model, developed by Warr (1990) has been linked to the J-DCS model by introducing the concept of non-linearity. Just as vitamins can be beneficial for physical health up to, but not beyond a certain level, so too can work conditions. On the basis of this assumption, the observed associations between traditional work conditions, such as job demands, control and social support, and well-being are expected to be non-linear, with decrements in well-being being found at extremely low or high values of the work conditions. According to the vitamin model, work conditions are differentially related to employee health, and their effects can be dependant on employees’ individual characteristics, such as abilities, preferences and goals. Though this concept has not been a crucial part of the model, Warr has in a way introduced the idea of individual differences in the traditional work stress research. MODELS OF QUALITY OF WORK LIFE AND INDIVIDUAL DIFFERENCES Partial empirical support of the J-DCS model’s buffer hypothesis and an emphasis on non-linear relationships and the role of overcommitment – as noted by Warr (vitamin model) and Siegrist (ERI model) respectively – suggest that more attention could be paid to individual differences within the quality of work life models. In line with this suggestion is the view that a better match between the stressor (e.g., demands) and the buffering factor (e.g., control) might improve the predictive power of the buffer hypothesis. This match has been achieved by operationalizing both demands and control at a comparable level of specificity. In their review of the JDCS model, van der Doef and Maes (1999) concluded that support has been provided for the buffer hypothesis in studies where this comparable level of specificity was pursued. However, other empirical evidence has yielded inconsistent support of this match suggestion (Dormann & Zapf, 1999; Kivimaki & Lindstrom, 1995; Searle, Bright, & Bochner, 1999; van der Doef, Maes, & Diekstra, 2000). This may suggest that a more person-centered approach may have to be applied in order to achieve an even more specific match between the stressor and the buffering factor. In other words, it would be interesting to investigate how different individuals use different work conditions as buffer factors against the same stressors. For example, for one employee time pressure may be balanced by the opportunity to expand his/her knowledge and skills, whereas for another more tangible rewards are needed, such as a good salary and benefits. Individual differences, such as the work-related coping style of overcommitment, work-related self-efficacy and personal goal attainment possibilities could also act as buffer factors in contemporary workplaces (De Jonge, Bosma, Peter, & Siegrist, 2000; Gardner & Pierce, 1998; Roberson, Korsgaard, & Diddams, 1990). From this perspective it seems that the J-DCS model emphasizes only one of two possible sources of variance in emotional, behavioral and physiological arousal. The first source, considered above, refers to the impact of the work environment and work
conditions on employee wellness and health. The second source of variation in wellness and health is concerned with the individual, and his/her role at the workplace, and here motivational aspects of work and employee life, and the opportunity to set and attain personal goals may be important. Although the ERI model and the vitamin model partly include motivational factors, an integrative approach is necessary in order to more fully explore the individual’s role. The nature of the relationship between environmental pressures (i.e., work conditions) and individual-imposed pressures (i.e., personal goals) is of special interest. It is important to understand the exact way these two parameters interact in order to predict employee health and performance at work. Models such as the JDCS model and the ERI model could be linked to personal goal attainment. Along these lines, we would like to suggest that an adverse work environment characterized by work overload, lack of autonomy and social support may hinder the setting and pursuit of personal goals. Adverse work characteristics can therefore influence health directly and indirectly, by reducing opportunities for employees to attain their goals. Another example of an adverse work environment is one characterized by the imbalance between employees’ invested efforts and received rewards. In this case, employees may invest their energy and efforts in their attempts to fulfill the organization’s standards in order to acquire the desired rewards and consequently not attend to their own needs. If the organization also fails to supply the rewards necessary to fulfill the individuals’ goals, two consequences may result from such sustained behavior; first, ill health is predicted; second, the pursuit of personal goals is hindered. Again, the work environment can influence employee health directly and indirectly through personal goal frustration. The relationship between personal goal attainment and job stress models may be worthy of further investigation. SELF-REGULATION: AN INTEGRATIVE APPROACH TO QUALITY OF WORK LIFE Personal Goals as Motivational Sources While traditional occupational stress research has concentrated on the influence of the work environment’s pressures on the individual, little attention has been paid to the pressures that the individual sets on him/herself, and the processes that are involved in addressing these pressures. Both of these aspects are related to the concept of personal goals. Ford (1992) has defined goals as thoughts about desired consequences that the individual would like to achieve, or undesired consequences that the individual would like to avoid. Personal goals constitute strong motivational components that drive human behavior. Goal pursuit includes psychological processes that are responsible for the initiation, direction, and persistence of behavior and provides the foundation for learning, skill development, and behavior change (Ford, 1992). Personal goals can be seen as a set of intrinsic demands that are posed on the individual, or that the individual poses on him/herself. Research has shown that personal goals and the processes that are related to goal pursuit are significantly and
consistently predictive of people’s behavior and health (Brunstein, 1993; Emmons, 1992; Affleck et al., 1998). Motivational Systems Theory Motivational aspects of workplace phenomena cannot be thoroughly investigated in the absence of a relevant theory. Self-regulation theories could provide the framework for the investigation of motivation. Though a number of self-regulation theories exist, to our knowledge no model has been both specified and tested explicitly in a work-related context. According to Maes and Gebhardt (1999, p. 344), “self -regulation can be defined as a sequence of actions and/or steering processes intended to attain a personal goal”. Motivational systems theory (MST) is an integrative framework that describes, “how motivational processes interact with biological, environmental, and nonmotivational psychological and behavioral processes to produce effective and ineffective functioning in the person as a whole” (Ford, 1992, p.12). Its major advantage is that it integrates a number of concepts derived from theories of selfregulation into a comprehensive conceptualization of self-regulatory processes (Karoly, 1993). Personal goals as a strong motivational force are of great importance in this theory. A taxonomy of goals has been developed by Ford and Nichols (Ford & Ford, 1987). This is a standardized classification scheme that allows one to make comparisons across individuals and social groups. The taxonomy concentrates on goals as desired consequences of behavior and not as behaviors themselves. The taxonomy is divided into two types of abstract – long-term – goals: goals that represent desired consequences within individuals, namely affective, cognitive, and subjective organization goals, and goals that represent desired consequences with respect to the relationship between people and their environments, namely social relationship and task goals. Within the framework of MST, intentions and goals are formed and organized in two ways: as a nested hierarchical structure, where a goal can serve as a means to the attainment of other goals, and as a value hierarchy, where goals are ordered according to their importance and value to the person. Effective functioning requires a strategic approach to attainable short-term goals in combination with a continuous overview of the long-term goals that can give meaning to current behavior. Another interesting issue refers to goal alignment. When alignment among goals is reached, motivation is significantly enhanced, as the person has more than one reason to exert a specific behavior episode. On the other hand, goal conflict can have detrimental effects on the individual’s motivational status. Human functioning (see Figure 1) is regulated by four general functions: (a) biological functions; (b) governing (directive) functions, which include directive, regulatory, control cognitions; (c) arousal functions, which include emotional, attention, consciousness and activity arousal processes; and (d) transactional functions, or motor, communicative, ingestive, eliminative, and sensory perceptual actions, as well as environmental components. In general, the directive function determines the intentions and the goals to be set. The processes of goal choice and goal attainment often require evaluative
thoughts, such as self-evaluative thoughts, standards, rules, and values. The regulatory cognitions contribute to the selection among different options and the evaluation of information that can lead to goal attainment. The control cognitions connect current information with the person’s kno wledge, skills, and capabilities, by means of problem formulation, problem solving and plan execution processes. The arousal functions regulate the individual’s emotional and other resources. Finally, the transactional functions underline the relationship between the person and the environment, by including actions and communicative efforts (Ford, 1992). Ford and Nichols (1991) argued that there are three mechanisms for cognitive regulation: (1) feedback mechanisms that monitor and evaluate progress towards goal attainment, (2) feedforward mechanisms that regulate expectancies about one’s capabilities for effective functioning and about the responsiveness of the environment, and (3) activation of control processes that develop plans and problemsolving strategies. Human behavior, dynamic at its core, is subjected to change, self-developing, and self-maintaining processes. According to MST a number of processes illustrate these characteristics: (a) change and development processes, (b) stability maintaining processes, (c) incremental change processes and (d) transformational change processes. Ford and Nichols (1991) have outlined several dimensions along which people may vary in their general orientation to goal setting: (a) active-reactive, (b) approach-avoidance, and (c) maintenance-change. Empirical evidence regarding the approach-avoidance goal orientation, where a person may tend to conceptualize goals as positive consequences to be reached or negative consequences to be avoided has shown a significant relationship between these goal orientation and well-being outcomes (Elliot & Sheldon, 1997). At a situational level of analysis, effective functioning is represented by achievement. Achievement is defined as the attainment of a personally or socially valued goal in a particular context. At the personality level of analysis, effective functioning is represented by competence. Competence is defined as the perceived attainment of several relevant goals, using appropriate means and resulting in positive developmental outcomes. Achievements in a specific domain could lead to generalized competence only if they are pursued in a socially moral way and if they have positive long-term consequences. Achievement is the outcome of a goal-directed behavior that is combined with affective energizing, possession of relevant skill and capability beliefs, and a responsive environment. All of these aspects are necessary for achievement to occur. If one of them is missing, goal attainment becomes difficult. Effective functioning is central in MST and is anchored directly to motivational processes, such as feedback and feedforward mechanisms. To say that behavior is regulated by feedback mechanisms is to assume the existence of reference standards for behavior, which in most theories of self-regulation are identified with goals. Goals are therefore a fundamental component in most motivation theories (Carver & Scheier, 1982; Emmons, 1989; Cropanzano, James, & Citera, 1993; Klein, 1989; Edwards, 1992; Hyland, 1988). In the previous sections several theoretical points have been made. Work conditions have been consistently shown to predict well-being, health and work-
related outcomes. Although the job demands-control-social support model concentrates on the importance of work conditions, related models (effort-reward imbalance model, vitamin model) have successfully introduced the individual as another source of stress. Even within the J-DCS model research has shown that a more individual-focused approach can raise its predictive power. In other words, there is strong theoretical and empirical evidence suggesting that there may be two major predictors of employee health: the work environment as well as the person. In search of a theoretical model that can help organize research, a self-regulatory perspective has been presented. More specifically, motivational systems theory, a broad integrative framework, focuses on how individuals strive to pursue their personal goals within a specific context. Personal goals act as motivating forces, as internal demands. The content of goals, the processes involved in goal pursuit and finally goal attainment or frustration may be crucial for employee health. Personal goals research may provide a person-centered approach and improve the prediction of wellness/health outcomes. In the following section, we examine the empirical evidence regarding the link between goals and wellness/health within the work context and give suggestions for future research. PERSONAL GOALS AT THE WORKPLACE There has been considerable theoretical expectation, though less empirical evidence for the contribution of self-regulation in the explanation of health and wellness outcomes within the work context. Conceptual diversity and methodological shortcomings have inhibited a systematic investigation of goals and self-regulation. In the following section, we will discuss studies on personal goals that are workplace-related. The purpose of this overview is to examine the present empirical evidence concerning personal goals and personal goal processes with respect to health and wellness outcomes, and to provide insight and suggestions for future research. Research on personal goals is growing. An organized approach to the existing attempts at investigating goals may start a fruitful discussion on such topics as the accurate and meaningful assessment of goals, the selection of the appropriate goal level to be measured, the differences among populations, and the use of relevant self-regulation models. The studies were selected from different journal databases (PsychInfo, Current Contents), from the references included in relevant articles and from personal communication with researchers in the field. They covered a period of fifteen years (1986-2001). The criteria for this selection were the following: (a) goals were assessed among a working population, (b) these goals had to be personal goals of the employees and not imposed organizational goals, (c) the association between personal goals and some outcome variable was investigated (studies that examined only the content of goals across the life span or in relation to gender and age were not included), and (d) studies were non-experimental, i.e., not conducted in laboratory settings. In total, 12 studies fulfilled the criteria (Barrick, Mount, & Strauss, 1993; Brown, Cron, & Slocum, 1997; Christiansen, Backman, Little, & Nguyen, 1999; Karoly & Ruehlman, 1996; Leithwood, Menzies, Jantzi, & Leithwood, 1996; Noe, 1996; O'Neill & Mone, 1998; Phillips, Little, & Goodine,
1997; Probst, Baxley, Schell, Cleghorn, & Bogdewic, 1998; Roberson, 1989; Roberson, 1990; VandeWalle, Brown, Cron, & Slocum, 1999). A close look at these studies revealed that they focused on the predictive power of goal processes in relation to two distinctive sets of outcomes: (1) wellness and (2) work-related outcomes. All studies were cross-sectional with the exception of the studies conducted by Brown et al. (1997) and by VandeWalle et al. (1999), where a longitudinal design was applied with a time interval of three months between two measurement points. Two central issues will be discussed in relation to the studies: (a) the theoretical constructs that they investigated, and (b) the methodology that they followed in assessing personal goals. It is important that studies on personal goals result from theories and models. The studies that are reported here stem from a variety of theoretical backgrounds and research areas, such as work values, performance related goal-setting, leadership, career management, expectancy value theory, equity theory, and personal projects models. In order to assess the studies within a common framework, the constructs that have been investigated in these studies will be linked to the main components of the motivational systems theory. For this purpose we will first describe the studies and then link them to MST (see Table 1 for an overview of the studies). With regard to methodology, there seem to be three goal elicitation procedures (see below). We examined whether there is an association between the choice of method for goal assessment and the success in predicting the study outcomes. OVERVIEW OF THE STUDIES Goals and Work-Related Outcomes The majority of the studies (eight of twelve) investigated work-related outcomes (job performance, job satisfaction, organizational commitment, intention to turnover). The study by Barrick, Mount, and Strauss (1993) among 91 sales representatives found a mediating effect of autonomous goal-setting and goal commitment on the relationship between conscientiousness and performance on the job. Goal commitment was a weaker predictor than goal-setting. Noe (1996), in a study on the career goals of 72 employees and 40 managers of a state agency and the goals’ relationship with employee development and job performance, found that although career goal focus and career goal strategies were not related to job development-oriented behavior and job performance, after controlling for relevant study variables distance from career goal predicted positively job developmentoriented behavior. O’Neill and Mone (1998) in a study among 242 health care employees found that employees who set own deadlines for goal attainment and perceived their goals as specific and clear were more likely to be satisfied with their job, and less likely to intend to leave the organization. No association was observed with organizational commitment. Phillips, Little, and Goodine (1997), in a paper concerning gender issues in 112 managers working in public administration, discussed research findings from a study on the relationship between the managers’ personal goal processes and their job satisfaction. Perceived supportiveness of the organizational culture towards the
managers’ personal goals was strongly related to job satisfaction for women, although not for men. Perceived hindrance of personal goals provided by the organizational culture was associated with lower job satisfaction for male managers. No information on the statistical analyses is offered. Probst et al. (1998) found that after controlling for a number of organizational characteristics, participants (i.e., 65 residents and 50 staff members of a family medicine residency program) who reported that their organization gave them the opportunity to be autonomous and to achieve sufficient progress towards their goals had higher ratings on job performance (i.e., teaching quality assessed by self and others). Roberson (1989, 1990) conducted two studies among employees of various occupational groups and organizations, investigating work-related personal goals and their association with job satisfaction and goal-directed behavior, using the Work Concerns Inventory (WCI), a thorough goal elicitation and appraisal instrument. In a study of 172 employees (Roberson, 1989), goal commitment, approach goals and time availability for goal pursuit appeared as significant predictors of goal-related behavior. Interesting relationships were also observed among the goal processes, including the central role of goal commitment. In another study of 150 employees (Roberson, 1990) job satisfaction was significantly predicted by several goal processes such as perceived probability of success, lack of deadlines and proportionate amount of avoidance goals, after controlling for demographic variables (i.e., tenure, age, education and job level). Additional analysis was conducted for two different types of goals, job task versus non-job task goals. Non-job task goals referred to e.g., the future job situation, relationship with colleagues and supervisors, and work conditions. The results indicated the importance of including both job task and non-job task goals in goal studies. In addition, according to Roberson, a distinction should be made between approach and avoidance goals. The pursuit of a higher number of avoidance goals, in comparison to approach goals seemed to be predictive of decreased job satisfaction. In general, the best predictor of job satisfaction was perceived probability of success. VandeWalle, Brown, Cron, and Slocum (1999) investigated the association between goal orientation (learning versus performance) and goal processes (intended goal level, intended effort, intended planning) and actual goal-related behavior (sales performance, objectively measured) among 153 salespeople. All goal-related processes were predictive of actual sales reported. In addition, goal processes mediated the relationship between goal orientation and sales performance. Goals and Wellness Outcomes Four studies focused on general wellness indicators (anxiety, depression, well-being, burnout). Brown, Cron, and Slocum (1997) found a series of associations linking goal processes (anticipatory emotions, anticipated and actual strategic planning and effort, goal attainment) to positive and negative emotions of 141 salespeople. A limitation of this study is that personal goals were operationalized as personal stakes, i.e., the impact that the respondents expected their job performance (on a specified task) to have on professional and family aspects of their life. Christiansen, Backman, Little, and Nguyen (1999) investigated personal goal processes as predictors of subjective well-being, by using a goal elicitation procedure suggested
by Little called Personal Projects Analysis (PPA; 1989). The sample consisted of 120 adults of whom 40 were college students, 40 working individuals and 40 were retired. Perceived stressfulness of goal pursuit, positive impact (i.e., goal viewed as helping other goals), proximity of goal to personal identity and progress were the most significant predictors of subjective well-being in this study. Karoly and Ruehlman (1996) investigated the association between personal goal processes, differential pain experience, and well-being among 227 managers, by means of the Goals Systems Assessment Battery (GSAB), an instrument based on Ford’s motivational systems theory. Conflict between work and non-work goals explained the difference between the persistent pain group and the episodic or no-pain groups. Goal processes (self-criticism, goal conflict, negative and positive arousal) significantly explained considerable variance in anxiety, but less so in depression, in addition to the pain-related variables. Finally, Leithwood, Menzies, Jantzi, and Leithwood (1996) used another goal processes instrument based on motivational systems theory, measuring personal goals and four consequent processes (i.e., capability beliefs, context beliefs, emotional, and arousal processes) among 331 college teachers. According to the findings, perceptions of quality of leadership had both a direct and indirect association with burnout, through organizational support and personal goal processes. Teachers’ goal cognitions (context and capability beliefs) were significantly related to burnout. Personal goals showed a negative association with burnout. Emotional arousal processes were associated with capability beliefs, but were unassociated with burnout. One of the limitations of this study lies in the operationalization of the personal goals construct. Goals in this study seem to measure the degree of adherence to organizational goals, rather than the individuals’ personal goals. EMPIRICAL SUPPORT FOR THE THEORETICAL CONSTRUCTS Motivational systems theory focuses on goal content, goal hierarchies, goal-setting (e.g., short-term vs. long-term goals), change processes, goal evaluations (e.g., importance, attainability, emotional salience), mechanisms of cognitive regulation (e.g., feedback and feedforward) and standards for goal attainment. The cognitive (directive, regulatory and control cognitions), emotional (emotional, attention, consciousness and activity arousal processes), and transactional functions (motor, communicative, ingestive, eliminative, and sensory perceptual actions) determine the processes involved in human functioning. Capability beliefs and context beliefs are of central importance to goal pursuit and goal attainment. MST also identifies inherent and more stable patterns, such as goal orientations, personal agency belief patterns, emotional patterns, and non-emotional affective states. As can be seen in Table 1, the constructs that have been supported by the empirical findings reported here, in terms of their predictive power of the study outcomes refer to processes involved in directive, regulatory, and control cognitions, emotional arousal, goal orientations, and goal content. Other MST constructs – such as transactional functions, goal standards, goal hierarchies, goal-setting and change processes, and cognitive regulation mechanisms – have not yet been tested.
These goal processes were predictive of general wellness indicators (i.e., depression, anxiety, burnout), and most of work-related outcomes that were studied (job satisfaction, job performance, and intention to turnover). No significant associations were found between goal processes and organizational commitment. However, a more careful examination of the empirical findings showed a lack of consistency in the prediction of outcomes. In most studies only a small number of the hypothesized relationships between goal processes and outcomes were supported by the data. Reasons for the inconsistency of the results can be found in the assessment and operationalization of personal goals and the type and level of goal under investigation. There are also several interesting issues that emerge from single empirical studies. Firstly, the relationship between goal processes and outcomes may change with various types of goals. Roberson (1990) suggested that both job task and nonjob task related goals should be taken into account when investigating personal goals at the workplace; it is possible that different processes are involved in the pursuit of job task versus non-job task goals. Secondly, there may be a differential role of approach and avoidance goals. Approach goals represent striving towards a desired outcome (i.e., things an individual strives to achieve). Avoidance goals represent striving away from an undesired outcome independent of whether they are positively or negatively formulated (i.e., things an individual strives to abolish, avoid, or prevent from happening). According to Roberson (1990), employees with more avoidance goals reported decreased job satisfaction. It is noteworthy that some additional research, mainly among college students has shown that a higher percentage of avoidance goals is associated with lower well-being (Elliot, Sheldon, & Church, 1997). A higher number of approach goals has also been observed to be associated with lower scores on depression (Coats, Janoff-Bulman, & Alpert, 1996). Avoidance goals have also been associated with unfavorable goal processes: such goals have been rated higher on difficulty than approach goals, less important, and as having brought less happiness when accomplished (Coats et al., 1996). Thirdly, in the studies that have already been discussed and in many other goaloriented investigations that do not fall within the area of work-related goals, different goal terms and constructs have been assessed. One difference is how broadly they have been conceptualized. On the one hand, goal constructs such as life tasks (a problem you are working on at this moment of your life), and personal strivings (something you are trying to do) are more vaguely defined. Examples of such constructs are the general work goals (i.e., employees did not explicitly specify their goals, but were thought to have projects they were interested in pursuing at work) included in the studies by Leithwood et al. (1996), by Probst et al. (1998), and by O’Neil and Mone (1998) and the v ague career goals that were studied by Noe (1996). On the other hand, current concerns (when you have decided to do something but you are not sure whether you are going through with it) and personal projects (taking up actions that may lead you to attain your goal) refer to more specific events and action taken relevant to these events. The studies by Barrick et al. (1993), Brown et al. (1997), Christiansen et al (1999), Karoly and Ruehlman (1996), Phillips et al. (1997), Roberson (1989, 1990), and VandeWalle et al. (1999) are examples of investigations that examined more specifically identified goals.
Another difference lies in the time perspective. A part of goal constructs concerns goals that are meant to be attained within a limited period of time, while others are projects of a lifetime. Assessment instruments of goal processes and goal attainment should be designed with a clear view of the time frame within which goal pursuits take place. Another paragon that differentiates goal constructs from each other is the position they employ in the goal hierarchy. Life tasks, for example, refer to the core self, problems that individuals are working on during different developmental phases, and can be more relevant in critical life periods. On the other hand, current concerns are goals that demand a person’s energy and efforts on an everyday basis, and although important, they refer to goals that are lower in the goal hierarchy, closer to action units. GOAL ELICITATION Three goal elicitation procedures were used in the studies that were reviewed. One way includes a goal elicitation process, where respondents are asked to state and evaluate their personal goals on a number of goal processes. Another has been to directly ask respondents to evaluate their goals, without first requiring explicit goal formulation. The disadvantage of the latter method is that goals can often be organization-imposed, rather than self-defined. In this case, goal evaluations can be biased. The third method may be seen as a compromise between these two. It involves asking participants to select goals that are relevant to them from a specified list. Participants can also formulate goals that are not included in the list. Again, what usually follows is another group of questions investigating relevant goal processes. The goal elicitation procedure is important. All six studies, which used the goal elicitation process (Brown et al. 1997; Christiansen et al., 1999; Phillips et al., 1997; Roberson, 1989, 1990; VandeWalle et al., 1999), found consistent empirical support of the hypothesized associations between the goal-related processes and the study outcomes. Of the five studies that used only an evaluation procedure of the goalrelated processes (Barrick & Mount, 1993; Leithwood et al., 1996; Noe, 1996; O’Neill & Mone, 1998; Probst et al., 1998) – but no elicitation procedure – four found partial support for the contribution of goal processes to the studies’ outcomes. In the only study assessing goals using an already specified list (Karoly & Ruehlman, 1996), only a few associations were observed between goal processes and outcomes. In conclusion, it seems that the inclusion of a goal elicitation procedure in assessing personal goal processes can result in a more powerful and consistent prediction of outcomes. Assessment methods that do not include an elicitation procedure depend heavily on participants' memories of the goals they have set. Lastly, list-based procedures, although more helpful to the participants, can be indoctrinating, in the sense that participants tend to adopt the goals presented to them, which may not be their own goals. CONCLUSION
The above discussion of the studies on personal goals at the workplace allows several conclusions. First, in both cross-sectional and longitudinal studies, considerable empirical support has been found for several goal constructs and goal processes, in terms of their predictive power of wellness and work-related outcomes. Goal variables explained significant variance in the study outcomes, in some cases over and above demographic variables (Roberson, 1990), personality variables (Barrick et al., 1993; VandeWalle et al., 1999) and work characteristics (Leithwood et al., 1996; Probst et al., 1998). Inconsistency in the empirical support of these constructs may be due to goal elicitation methods, the use of various goal constructs, lack of attention to goal content, and a limited use of a sound theoretical framework as well as a theory-based goal measuring instrument. Second, there are theoretical constructs that have not attracted sufficient research attention. This may be due to the degree of difficulty in operationalizing and assessing them, as they frequently refer to dynamic processes (e.g., change processes and feedback mechanisms). Furthermore, goal content has received less research attention than processes involved in goal pursuit (Little, 1999). The effect that the content of goals can have on well-being is emphasized by Ryan, Sheldon, Kasser, and Deci (1996). Individuals who focus on extrinsic goals are more likely to suffer from poor well-being than are individuals who focus on goals that represent the needs for autonomy, competence, and relatedness (Ryan, Kuhl, & Deci, 1997). Another issue that has been neglected is the relationship between different levels of goals. Goal theories have emphasized the existence of a hierarchical structure among goals. The relationship between motives, or higher order goals and lower level personal goals is certainly worthy of further investigation. Concerning the findings of single empirical studies, several points can be made. First, approach goals seem to be positively related to well-being – the higher the percentage of approach goals, the higher the subjective well-being reported. Second, autonomous goals seem to be more positively correlated with goal attainment and effort invested than controlled goals. Third, goal attainment appears to be an obvious and probably powerful mediating variable in the relationship between personal goal processes and wellness outcomes. Behavioral outcomes may also provide further insight into the role that personal goals play in self-regulation. Fourth, for personal goals, gender differences should be taken into account. GENERAL CONCLUSION AND DISCUSSION There is ample evidence that work characteristics are linked to important wellness/health consequences, varying from job satisfaction, burnout, turnover, and absenteeism to physical ill-health. Unlike in other areas of quality of life research, several theoretical models concerning quality of work have been tested, including the job demands-control-social support model (Karasek, 1979), the effort-reward imbalance model (Siegrist, 1996) and the vitamin model (Warr, 1990). While these models have been successful in predicting wellness/health consequences, they mainly concentrate on the impact of the work environment on the individual and not on the way individuals define their work environments in terms of their personal goals and expectations.
Consequently, this chapter introduced self-regulation theory and specifically motivational systems theory (Ford, 1992) as a theoretical framework for research into these motivational aspects. While some research has been carried out from a personal goal perspective, it is difficult to get an integrated picture of the existing empirical literature, because of the lack of a common theoretical framework. In other words, theory-based research in the field of personal goals is crucial. Work characteristics have not been explicitly linked to employees’ ability to pursue and attain their personal goals. In addition, little information is provided in empirical studies on the pathways and the reasons underlying the observed relationships between goals and outcomes. There are several theoretical frameworks available and it is time that goal researchers start to constructively exchange opposing views and comments. Wyer, Carver and Scheier (1999) have begun this challenge successfully by discussing various approaches on self-regulation, parallel to their focus on control theory. Klein (1989) suggested an integrated control theory model of work motivation that explicitly incorporates feedback, goal setting, expectancy, and attribution theories, and can be extended to include several other theories (e.g., social learning theory). In addition, Hyland (1988) suggested a meta-theoretical framework based on control theory but enriched with concepts from a number of motivation and goal theories. Motivational systems theory (Ford, 1992) is another example of an integrative attempt, perhaps the most inclusive one to date. A number of theorists and researchers (Ford & Ford, 1987; Bandura, 1989; Carver & Scheier, 1982; Latham & Locke, 1991; Klein, 1991; Emmons, 1997; Austin & Vancouver, 1996; Powers, 1973; Robertson & Powers, 1990; Roberson, 1989; Affleck et al., 1998; Maes & Gebhardt, 1999) have presented arguments suggesting that the goal construct is fundamental to human functioning and consequently to wellness and health. We suggest that these integrative models be used to relate the findings of existing studies and to give an impetus for future research. Acknowledgments We would like to thank Arne Mooers for his valuable comments. Correspondence should be addressed to: Georgia Pomaki, Faculty of Social Sciences, Health Psychology Section, P.O.Box 9555, 2300 RB Leiden, The Netherlands. E-mail:
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Governing (COGNITIVE) FUNCTIONS Directive cognitions (personal goals)
Goal evaluation processes: Goal relevance Goal importance Goal attainability Emotional salience
Emotional arousal processes
Regulatory cognitions (evaluative thoughts)
Control cognitions (planning + problem solving thought)
Feedforward Feedback cognitions Information processing and memory functions
Attention and consciousness arousal processes
Activity arousal processes
AROUSAL FUNCTIONS
Motor communicative (natural environment)
Ingestive and eliminative actions (designed & human environment) Sensoryperceptual actions (socio-cultural environment ) Environmental Components Natural Designed Human Sociocultural
BIOLOGICAL FUNCTIONS
Figure 1. Motivational Systems theory (Ford, 1992): Functions
T R A N S A C T I O N A L F U N C T I O N S
Table 1. Overview of empirical studies Comparable variables MST supported by the empirical findings Directive cognitions
Empirical studies
Goal related variables
1. Barrick, Mount, & Strauss (1993)
Autonomously commitment
2. Brown, Cron, & Slocum (1997)
Positive & negative anticipatory emotions; Volitions; Goal-directed behavior; Goal attainment
Emotional arousal Behavioral output Transactional actions
Positive emotions Negative emotions
3. Christiansen, Backman, Little, Nguyen (1999)
Goal conflict; Meaning; Stress; Community; Structure; Efficacy; Personal identity; Positive impact; Negative impact; Progress Value; Self-efficacy; Social comparison; Self-monitoring; Planning; Self-reward; Self-criticism; Goal conflict; Positive arousal; Negative arousal
Emotional arousal Directive cognitions Regulatory cognitions
Subjective well-being
40 college students 40 employees 40 retired
Regulatory cognitions Directive cognitions Emotional arousal
Depression Anxiety Pain experience
227 managers at various organizations
5. Leithwood, Menzies, Jantzi, & Leithwood (1996)
Capability beliefs; Emotional arousal
beliefs;
Regulatory cognitions
Burnout
331 teachers
6. Noe (1996)
Career goal focus; Career goal strategies; Distance from career goal
Regulatory cognitions
Developmental behavior Job performance
7. O’Neill & Mone (1998)
Goal-related deadlines; Goal clarity
Directive cognitions
Job satisfaction
40 managers 72 subordinates at a state agency 242 health care employees
4. Karoly (1996)
&
Ruehlman
set
goals*;
Context
Goal
Outcomes
Sample 91 sales representatives
Job performance outcome
141 salespeople
outcome
college
8. Phillips, Little, & Goodine (1997)
Goal content; Goal challenge; Enjoyment; Control; Support by others; Support/Hindrance by the organization; Commitment; Stress; Others’ view of importance; Sense of competency
Regulatory cognitions
Intention to turnover Organizational commitment Job satisfaction
9. Probst, Baxley, Schell, Cleghorn, & Bogdewic (1998)
Opportunity for goal attainment
Regulatory cognitions
Teaching quality
10. Roberson (1989)
Probability of success; Sorrow; Joy; Instrumentality; Unhappiness; Response dependency; Time available; Goal nearness; Contingency; Goal commitment
Directive cognitions Emotional arousal
Goal-related behavior
11. Roberson (1990)
Goal content (approach vs. avoidance goals & job task vs. non-job task); Probability of success; Negative consequences of goal attainment; Goal commitment; Lack of deadlines; Time until goal attainment; Role dimensions (means); Instrumentality; Time available; Probability of success with out action
Goal content Directive cognitions
Job satisfaction
12. VandeWalle, Brown, Goal orientation; Goal level; Intended Goal orientation Cron, & Slocum (1999) effort; Intended planning Control cognitions * The variables in bold indicate statistically significant relationships.
Job performance
employees
65 residents 50 staff members at a family medicine residency program 172 employees from various organizations and occupational groups 150 employees from various organizations and occupational groups
112 managers at public administration
153 salespeople
