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The Influence of Work Control Trajectories on Men's Mental and Physical Health During the Middle Years: Mediational Role of Personal Control

¹ Department of Human Development and Family Studies, and Institute for Social and Behavioral Research, Iowa State University.
² Departments of Statistics and Psychology and Institute for Social and Behavioral Research, Iowa State University.
³ Carolina Population Center, University of North Carolina at Chapel Hill.

	Abstract

TOP Abstract Methods Results Discussion Appendix References

 
Objectives. This study investigated whether men's mental and physical health problems during the middle years may be attributed, in part, to the influence of varying levels of, and changes in, work control among members of a rural midwestern cohort. Specific study objectives were to examine (a) how trajectories of work control influence men's mental and physical health outcomes and (b) how this influence is mediated by the trajectories of personal control during the middle years.

Methods. The study used four waves of data on 318 employed men across 10 years of midlife. Variables included self-reported work control, personal control, and mental and physical health.

Results. The results supported the hypothesis that both the initial level and change in work control contribute to men's mental and physical health outcomes during the middle years. This influence was mediated by the initial level and change in personal control.

Discussion. Our results demonstrate the dynamic nature of work experiences, personal control beliefs, health, and long-term health consequences due to work conditions in a sample of middle-aged men. We discuss the theoretical implications of this.

Key Words: Midlife cohort • Work control • Personal control • Health

MOST men experience relatively stable work conditions during the middle years, defined approximately as the period between 40 and 60 years of age (Staudinger & Bluck, 2001). Still, a sizable fraction of men experience substantial changes in work conditions (Theorell et al., 1998). These changes often stem from individual socioeconomic and personal characteristics, but they may also be due to the historical context of the cohort to which one belongs. Indeed, the baby boom cohort emerges from a historical context in which its members experienced tough competition for high-quality jobs, the organizational restructuring of the workplace, and corporate downsizing (Elder & O'Rand, 1994; Moen & Wethington, 1999). In addition, the chronically low prices of agricultural products since the "farm crisis" of the 1980s continue to displace many from farms in rural areas. Without new work skills, men of this current middle-aged cohort may lose their jobs and control over work, along with their stability of occupation (Lorenz, Elder, Bao, Wickrama, & Conger, 2000).

Work organizational research suggests that adverse work conditions result in negative health outcomes (Karasek & Theorell, 1990). Previous studies have shown that low work control, or having little influence over decision latitude, is often associated with depression (Mausner-Dorsch & Eaton, 2000), anxiety (Griffin, Fuhrer, Stansfeld, & Marmot, 2002), and poor physical health (Wickrama, Lorenz, Fang, Abraham, & Elder, 2005). Several decades ago, work socialization research documented that work control contributes to increased psychological resources such as personal control (Kohn & Schooler, 1973). In health psychological research, an increasing number of studies have documented that personal control contributes to better mental and physical health (Haidt & Rodin, 1999; Marmot et al., 1998). To our knowledge, however, no study has empirically investigated the dynamic associations among work control, personal control, and health together as a continuous process in which personal control mediates the association between work control and health over time.

Instead, most previous research linking these concepts has been based on static, cross-sectional studies or inadequate analytic techniques. As a result, researchers know very little about how individual changes in personal control mediate the association between individual changes in work control, and mental and physical health outcomes. In the present article, we first provide the theoretical arguments for why personal control might mediate the association between changes in work control, and mental and physical health outcomes. Then, using four waves of prospective data collected from middle-aged men from the rural Midwest during a 10-year period, we extend previous research by examining the change in personal control as an important mechanism that links change in work control to health outcomes in the middle years of men's lives.

Work Control
Karasek and Theorell (1990) defined work control as having latitude over one's work decisions and the possibility for use and further development of one's skills (i.e., skill discretion). Thus, the combination of work authority and skill discretion indicators adequately captures work control (Griffin et al., 2002; Karasek & Theorell, 1990). Although early research on work and health has documented the adverse multiplicative effect of low work control and high psychological demand on health (Karasek & Theorell, 1990), an increasing number of studies have provided supporting evidence for additive effects of work control alone on mental and physical health outcomes (e.g., Mausner-Dorsch & Eaton, 2000; Wickrama et al., 2005).

Work Control and Personal Control
The work socialization perspective contends that work control is associated with positive work qualities such as occupational self-directiveness, substantive complexity, and non-routine work. These positive work characteristics contribute to intellectual and cognitive abilities and habits such as intellectual flexibility and a flexible orientation toward the self and society (Kohn & Slomczynski, 1990; Kramer, Bherer, Colombe, Dong, & Greenough, 2004). In turn, these individual characteristics shape one's general beliefs, attitudes, and values related to personal control (Kohn & Schooler, 1973; Kohn & Slomczynski, 1990). Personal control beliefs (referred to as personal control hereafter) concern the extent to which one feels able to control or influence outcomes or believes that one controls his or her life rather than being at the mercy of powerful others and outside forces (Lachman & Weaver, 1998; Lorenz, Conger, Montague, & Wickrama, 1993).

Work control may influence personal control beliefs through processes involving various intraindividual mechanisms. First, the accumulation of experiences in which one successfully controls his or her environment leads to perceptions of mastery (Pearlin, Lieberman, Menaghan, & Mullan, 1981). Second, consistent with the notion of role–person merger (Turner, 1978), skills, habits, beliefs, and values used in one setting tend to generalize or spill over to other situations. Individuals may learn and emulate skills, habits, and beliefs from work and bring them to other life situations in a manner that is consistent with social cognitive theory (Bandura, 2001). Third, according to the reflected appraisal notion (reflected appraisals are perceptual and inferred from others' behavior toward the individual), favorable reflected appraisal is predicted to have positive effects on psychological resources such as sense of control (Schwalbe & Staples, 1991). We posit that a high level of work control is suggestive of positive assessments of others, which in turn would contribute to favorable reflected appraisal.

We further posit that a high degree of work control can significantly and indirectly contribute to increased perceptions of personal control through various social and psychological pathways. Specifically, research has shown that sense of control at work influences social and family relationships through the following mechanisms. First, self-directive work experiences and intellectual flexibility associated with work control carry over into greater problem-solving efforts with peers, friends, and family. Better problem solving, consequently, facilitates greater quality and supportiveness in social, marital, and parent–child interactions (Menaghan & Parcel, 1990; Whitbeck et al., 1997). Conversely, anger and distress generated by a lack of power and control at work may carry over to social and family relationships through expression of negative affect to peers, friends, and family members (Menaghan, 1991; Whitbeck et al., 1997). Second, people with less control over work generally face more rigid time schedules and greater time pressures, which potentially limit their opportunities for leisure and pleasurable activities with peers, friends, and family members (Wickrama, Lorenz, Conger, Matthews, & Elder, 1997). Intimate marital interactions and high levels of social integration, in turn, promote a sense of meaning, purpose, and beliefs about personal control (Thoits, 1992; Wickrama et al., 1997).

Accordingly, positive changes in work conditions should directly and indirectly contribute to positive changes in general beliefs related to personal control, and negative changes in work conditions tend to erode those beliefs. Although some theorists view control as a relatively stable personality dimension (Kobosa, 1979), increasing evidence suggests that actual experience of life changes contributes to changes in general beliefs about personal control (Merluzzi & Nairn, 1999). Indeed, psychological research suggests that personal control consists of two distinct components, including an enduring stable component and a malleable component that varies with changes in context (Pierce, 2005).

Personal Control and Health
Previous research has documented that strong personal control is linked to better mental health (Haidt & Rodin, 1999) and physical health (Marmot et al., 1998). In fact, the relationship between personal control and health grows stronger with age (Rodin & Timko, 1992). Previous research suggests that personal control influences mental and physical health directly and indirectly through several pathways.

Numerous studies suggest that lack of personal control and low self-worth associated with persistent absence of work control may directly produce a sense of powerlessness. Mirowsky and Ross (2003) posited that lack of control or self-worth, however, does not exist in a vacuum; instead, one's sense of powerlessness and worthlessness is a form of subjective alienation that generates depressive symptoms and other forms of distress. Impaired mental health also contributes to the development and/or progression of a wide range of medical conditions such as joint pains, pruritus, psoriasis, and uticaria (Carney & Freedland, 2000).

People with a high level of personal control are more likely to initiate preventive behaviors such as getting regular check-ups; adhere to health behaviors such as maintaining balanced diets and exercising (Tedesco, Keffer, & Fleck-Kandath, 1991); and quit risky behaviors such as smoking, excessive drinking, and substance use (Seeman & Seeman, 1983). Consistent with a life-span perspective (Baltes & Baltes, 1990), these behavioral adaptations may be important for the selective optimization processes that compensate for diminishing biological robustness among men during the middle years.

Existing research also links personal control to positive outcome expectancies. Personal control correlates with other positive psychological constructs such as optimism or a generalized expectation that good things will happen in the future (Scheier, Carver, & Bridges, 1994). An increasing body of literature points to the beneficial influence of having a positive view on mental and physical health outcomes. For example, studies have demonstrated that optimistic individuals report fewer physical symptoms (Scheier & Carver, 1985) and recover faster following surgery (Scheier et al., 1989).

We also argue that personal control directly reduces the detrimental health influence of stressful life circumstances by decreasing the probability of illness and delaying the onset of health problems. That is, men with high personal control can reduce the health consequences of stressful circumstances through avoidance of and/or disengagement from subsequent stressful activities. Consistent with a life-span perspective, this process reflects a method of secondary control aimed at minimizing the negative effects of failures (Heckhausen, 1997). This may be especially applicable to men at midlife because they are especially likely to experience more stressful life events, losses, or failures in different non-work-life domains including self, marriage, children, and parents than men at younger and older ages.

We contend that men's personal control represents a proximal health resource that is enhanced and sustained by work control that serves as an important link between work control and health outcomes. As such, the direct influence of work control on men's health (Griffin et al., 2002; Mausner-Dorsch & Eaton, 2000; Wickrama et al., 2005) may partially operate through men's perceptions of personal control.

Figure 1 outlines a theoretical model beginning with work control trajectory characterized by level and change over time. Our essential thesis is that work control trajectories contribute to men's physical and mental health outcomes through the trajectories of personal control during the middle years.

View larger version (10K): [in this window] [in a new window]   Figure 1. Theoretical model

The development of health problems may not correspond simply to the chronic level of impaired personal control. Rather, one's development of health problems may also correspond to his or her rate of change (growth or decline) in personal control (Wickrama, Beiser, & Kaspar, 2002). Thus, as shown in the figures, we hypothesized the following:

1. Both the initial level and rate of change in work control influence mental and health outcomes during the middle years.
   
2. The initial level and rate of change in work control influence the initial level and rate of change in personal control during the middle years (parallel trajectories).
   
3. Thus, the initial level and rate of change of personal control mediate the influences of the initial level and rate of change in work control on mental and physical health outcomes during the middle years.
   

By controlling for initial levels of health status, we minimized the possibility of an alternative selection hypothesis that healthy men possess higher levels of work and personal control and select into higher quality jobs. Also, because several factors, including occupation, income, education, negative family events, work disruption, and/or changes in these factors, may be associated with work control and personal control trajectories and health outcomes, we included those factors as control variables in the analyses. The arrow from control variables in Figure 1 indicates that we controlled all of the endogenous constructs for those factors.

	METHODS

TOP Abstract Methods Results Discussion Appendix References

 
Sample and Procedures
Data for this study came from the Iowa Midlife Transition Project, a study of 390 men who originally participated in the Iowa Youth and Families Project between 1989 and 1994 and who continued to participate in the Iowa Midlife Transition Project in 2001 (N = 370). We determined the site for the research from our interest in rural economic stress and well-being. Because some of the variables were not available in the data set prior to 1991, the present study utilized four waves of data collected in 1991, 1992, 1994, and 2001. Many of the outcomes and processes considered in the overall study were about children's development, therefore families selected to participate had at least two children. We tested our theoretical model with a sample of 318 employed men (including self-employed men) who provided data for all assessments in 2001.

1n 1991, 93% of the men were employed. About 97% of the employed men were full-time workers in the following categories: professionals, managers, owners, and officials (23.6%); craftsmen, foremen, and farmers (24.8%); operatives, transportation, and kindred workers (15.4%); salesworkers, clerical, service workers, private household workers, and military service (15.1%); farm laborers and laborers (7.5%); and other (13.6%). The median yearly work-related income in 1991 was $26,847. The median ages for men in 1991 and in 2001 were 41 (range = 33–70) and 51 (range = 44–80), respectively. Because there are very few minorities in the rural population studied, all families in the combined sample were White.

Out of the 318 cases in 2001, some cases were unavailable for a specific wave of data collection (about 9%). This study used full information maximum likelihood to test the hypotheses using all available data in the analysis. Compared to other procedures such as listwise deletion, pairwise deletion, or imputation of means, a maximum likelihood algorithm for use with missing data such as full information maximum likelihood provides more efficient parameter estimates (Enders, 2001). We further tested the model with and without the inclusion of the 9% missing cases and found no differences in the results. Also, 27 men (out of 318) experienced some sort of unemployment between 1991 and 1994. Because job disruptions (sporadic employment) may be associated with work control, personal control, and health outcomes, we controlled the models for experiences in job disruption.

We performed an attrition analysis to examine possible differences between the analyzed sample (N = 318) and those who were not included in the analyses, either due to dropping out of the study or because of unavailability of 2001 health data (i.e., 390 – 318). The education level of those who were not in the analysis (M = 13.02) was slightly lower than that of those who remained in the study (M = 14.12). Those who were not in the analysis also reported slightly poorer health in 1991 (M = 2.56) than people who remained in the study (M = 2.31). Those who were in the analysis and those who were not in the analysis were not significantly different in 1991 in their work control, personal control, or depressive symptoms.

Measures
Work control
We measured work control of respondents in each of the three study years (i.e., 1991, 1992, and 1994) by using the mean of eight items as indicated in the Appendix. Each item was scored using a 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5) (Karasek & Theorell, 1990). We coded responses such that higher scores indicated higher levels of work control. The coefficient alphas for each measurement wave were.83,.84, and.81 for 1991, 1992, and 1994, respectively.

Personal control
We used seven items from Pearlin's mastery scale (Pearlin et al., 1981) to assess respondents' personal control. On a 5-point scale, the respondents rated how much they agreed or disagreed with each of the statements as reported in the Appendix. We coded responses so that higher scores indicated higher personal control. The coefficient alphas for 1991, 1992, and 1994 were.78,.81, and.81, respectively.

Poor physical health
Previous research has demonstrated that self-reports of health status correlate highly with physician assessments of morbidity (Ferraro & Farmer, 1999; Romelsjo, Kaplan, Cohen, Allebeck, & Andreasson, 1992). Self-assessments of poor global health were obtained in 1991 and 2001 using two global measures. The first global measure asked participants to indicate the following on a scale from 1 (excellent) to 5 (poor): "How would you rate your overall physical health?" The second global health measure asked participants to indicate the following on a scale from 1 (much better) to 5 (much worse): "Would you say your overall physical health is better or worse than other people your age?" We created a measure of self-assessed global physical health by taking the mean of these two items, with higher scores representing poorer physical health. The coefficient alphas for self-report of poor physical health in 1991 and 2001 were.78 and.72, respectively.

Depressive symptoms
Depressive symptoms were measured in 1991 and 2001 by calculating the mean of the 13-item depressive symptomology subscale of the Symptom Checklist-90 Revised (Derogatis, 1983). Respondents indicated on 5-point scale ranging from not at all (1) to extremely (5) how much in the past week they were bothered by symptoms of depressed mood, such as crying easily, feeling trapped or caught, blaming themselves for things, feeling lonely, feeling blue, feeling worthless, and feeling hopeless about the future. Physical symptoms of depression, such as "feeling low in energy or slowed down" and "feeling everything is an effort," were also included. Scores on the depressive symptoms subscale could potentially range from 1 to 5. Greater scores for this variable represented higher depressive symptoms. The coefficient alphas for depressive symptoms in 1991 and 2001 were.93 and.90, respectively.

Control variables
We included as control variables education, work-related income, level of occupation, negative family events, and work disruption. We measured education as the number of years of formal education for the respondent in 1991. We calculated work-related income in $10,000 by adding earned wages, self-employed income, and farm income in 1991. We computed the change in work-related income from 1991 to 1994 by subtracting work income in 1991 from work income in 1994. We measured the level of occupation in 1991 by using five broad ordinal-level categories based on occupational prestige (1 = manual worker; 2 = sales workers, service workers, and clerical workers; 3 = operatives and kindred workers; 4 = skilled workers, including craftsmen, foremen, and farmers; and 5 = professionals, managers, and officials). We constructed the negative family event measure by counting the occurrence of five major family events (divorce, marital problems, serious illness or injury, family member with a serious illness or injury, and death of a family member) in 1991. We computed change in negative family life events from 1991 to 1994 by subtracting negative family events in 1991 from negative family events in 1994. We measured work disruption using responses to two items: During the past 12 months, did you: (a) change jobs for a worse one? and (b) get laid off or fired? (1 = experienced at least one of two conditions during the period from 1991 to 1994, 0 = experienced none).

Analysis Plan
We used latent growth curve modeling to estimate individual trajectories and to investigate their correlates. Growth curve estimation begins by describing change over time for each individual in the study. Conceptually, this is done by fitting a regression line (an individual growth trajectory) linking a variable (y) to time (t) for each individual in the study (t = 0, 1, and 3 for three repeated measurements in 1991, 1992, and 1994). Individual regression coefficients for the intercept and slope correspond to individual growth parameters for the initial level and rate of change (slope), respectively. We investigated individual growth parameters (trajectories) of work control and personal control that includes information about both their average levels and their interindividual variability.

In the analysis, the growth parameters of work control were specified as predictors of health outcome (Y) in 2001 by the following equation (Hypothesis 1):

In the above equation, β₀ is the intercept of the prediction equation, and β₄ and β₅ are regression coefficients linking the growth parameters of personal control to a health outcome variable. In the examination of the association between work control and personal trajectories (Hypothesis 2), the level and slope of personal control (1991–1994) were predicted by the level and slope of work control (1991–1994), as shown in the following equations:

To test the mediational process (Hypothesis 3) according to Baron and Kenny (1986), after showing the direct effects of work control growth parameters on health outcomes, we specified both work and personal control growth parameters as predictors of health outcome. If growth parameters of personal control became significant predictors of health outcomes while the direct influences of growth parameters of work control diminished, the mediational hypothesis would be supported (Baron & Kenny, 1986).

	RESULTS

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Table 1 presents the zero-order correlations, means, and the standard deviations of the main study variables. Most of the work control variables and all of the personal control variables were negatively correlated with poor health outcomes. However, the association of personal control variables with poor health outcomes was stronger than the association of work control variables with physical/mental health outcomes. The mean values of poor global health (2.30 and 2.61), and depressive symptoms (1.29 and 1.38) increased slightly from 1991 to 2001, indicating that, on average, there was a slight decline in health during the 10-year study period.

Univariate Growth Curves
Before testing the theoretical model, we estimated univariate growth curves for all three waves of work control and personal control variables (1991, 1992, and 1994). Table 2 summarizes the results of the fitted growth curves of work control and personal control variables. The intercept of 3.573 (see Table 2) was an estimate of the average work control reported by all respondents in 1991. The nearly significant mean of the linear slope (0.020; t = 1.95) indicated that, on average, there was an increasing trend in work control between 1991 and 1994. Results from descriptive statistics (see Table 1) showed that, indeed, there were slight increases in work control from 1991 to 1994 (Ms = 3.60, 3.62, and 3.65 for 1991, 1992, and 1994, respectively). However, the significant variance of the slope of work control (0.025; t = 3.75) in Table 2 implied that there was significant interindividual variation in the linear change of work control across time: Some individuals experienced increases in work control, whereas others experienced declines, some more dramatic than others (Lorenz, Wickrama, Conger, & Elder, 2006). This model fit the data, ²(1, N = 318) =.09.

Latent Growth Curve Models
We fit three sets of latent growth curve models to the data (see the figures). All control variables in 1991 are included in each of the models in the figures. We also tested the models separately to predict poor physical health and depressive symptoms. The first model investigated the total influence of work control on health outcomes. Figure 2 presents a summary of the results. As shown in Figure 2, initial level of work control in 1991 significantly predicted poor physical health in 2001. The negative sign associated with the coefficient and significant t ratio (–.148; t = –2.87) means that those who had high work control in 1991 tended to report less poor health in 2001, and vice versa. In addition, those who experienced greater increase in work control between 1991 and 1994 tended to report less poor health in 2001 (–.146; t = –2.52). The root mean square error of approximation (RMSEA) of.05 indicated that this model had a good fit with the data (Byrne, 1998). The influence of the change in work control on depressive symptoms in 2001 was marginally significant (t = –1.75). The RMSEA of.08 for the model predicting depressive symptoms indicated that this model had a reasonable fit with the data. For comparison purposes with subsequent incremental models (see Figures 3 and 4), the level and slope of personal control were included in Figure 2, paths from work control constructs to personal control were freed, and paths to poor health (2001) were fixed (not shown in Figure 2).

View larger version (8K): [in this window] [in a new window]   Figure 2. Total influence of the trajectories of work control on health outcomes (standardized values with t ratios in parentheses). Values above the line represent results predicting poor physical health, and values below the line represent results predicting depressive symptoms. RMSEA = root mean square error of approximation. p <.10; *p <.05

View larger version (12K): [in this window] [in a new window]   Figure 3. Direct and indirect influence of the trajectories of work control on health outcomes (standardized values with t ratios in parentheses). Values above the line represent results predicting poor physical health, and values below the line represent results predicting depressive symptoms. RMSEA = root mean square error of approximation. p <.10; *p <.05

The models in Figure 4 omitted the direct influence of the level and change in work control to health in 2001. For both the models predicting poor health and depressive symptoms in 2001, the level of work control in 1991 significantly predicted the level of personal control in 1991 (t = 4.55 and 4.54 for models predicting poor health and depressive symptoms, respectively). That is, men who had high work control in 1991 tended to had a higher level of personal control in 1991. The significant paths from the change in work control to the change in personal control (t = 2.85 and 2.61 for models predicting poor health and depressive symptoms, respectively) indicated that those who experienced greater change in work control between 1991 and 1994 also tended to have greater change in personal control between 1991 and 1994. Higher level of personal control in 1991, in turn, predicted less poor physical health in 2001 (t = –3.31) and lower depressive symptoms in 2001 (t = –5.76). Both models in Figure 4 provided a good fit with the data (RMSEA <.05). Compared to those in Figure 3, the models in Figure 4 did not result in significant increases in chi-square: ²(2, N = 318) = 3.67, for the model predicting poor physical health; and ²(2, N = 318) = 3.34, for the model predicting depressive symptoms. This indicated that Figure 4 was the most parsimonious and the best fitting model for the data. Table 3 presents separate results of all of the 1991 control variables associated with Figure 4.

View larger version (11K): [in this window] [in a new window]   Figure 4. Indirect influence of the trajectories of work control on health outcomes (standardized values with t ratios in parentheses). Values above the line represent results predicting poor physical health, and values below the line represent results predicting depressive symptoms. RMSEA = root mean square error of approximation. p <.10; *p <.05

	DISCUSSION

TOP Abstract Methods Results Discussion Appendix References

 
The process whereby aspects of work context affect an individual's health indirectly through one's personal control appears to be continuous. Thus, an investigation of health outcomes in the middle years calls for a "long view" so that health consequences of adverse work conditions in early midlife can be documented later, as they emerge in later midlife. Using prospective data of a 10-year period, we found support for the hypothesized pathways whereby dimensions of work control proximally influence the mental and physical health of middle-aged men.

The present study makes several specific contributions to the exiting literature. Our initial contribution to the research literature is methodological. Most previous studies examining associations among work control, personal control, and health outcomes were based on static, cross-sectional studies. These studies provided important but limited information, because research that does not include examination of within-individual changes over time could yield incomplete conclusions concerning certain outcomes (Karney & Bradbury, 1995). The present study focused on within-individual changes, interindividual variability in those changes, and predictors and consequences of those changes. These methodological advances have two important aspects. First, the prospective correspondence at the individual level or interlocking trajectories between growth parameters of work control and personal control provides compelling evidence for the systematic association between changes in work and personal control within an individual (Duncan, Duncan, Strycker, Li, & Alpert, 1999). Second, findings that both the initial level and rate of change of personal control uniquely contribute to one's health outcomes provides compelling evidence for the important influence of change in personal control beliefs on health outcomes regardless of the level of personal control.

As previously discussed, pioneer research on work organization and health suggested that low levels of work control influence health in combination with high work demand, as a multiplicative effect (Karasek & Theorell, 1990). The findings of the present study add to the increasing evidence for the additive influence of work control, and the loss of work control in particular, on both individual mental and physical health. More important, these findings point to the vulnerability of the members of the current middle-aged cohort who have been subject to losing their control over work without new work skills in the present context of tough competition for high-quality jobs, organizational restructuring of the workplace, and corporate downsizing (Elder & O'Rand, 1994; Lorenz et al., 2000; Moen & Wethington, 1999).

Although some theorists view personal control as a relatively stable personality dimension (Kobosa, 1979), the present findings suggest that one's personal control is malleable, and work experiences and changes in work conditions contribute to changes in personal control (Merluzzi & Nairn, 1999; Pierce, 2005). Our findings show that the rate of change in personal control has significant interindividual variability. That is, whereas some men experienced only little decline or stagnation in personal control, others reported steeper declines, and still others reported increases. This suggests that personal control beliefs remain susceptible to change during this stage of the lifespan (Lachman & James, 1997). However, the present study focused only on psychological resources as a mediator to explain the health effect of work condition. Other susceptible individual attributes such as family and marital relations and health behaviors would aid in elucidating more mechanisms through which work experiences contribute to health outcomes over the life course.

Despite the important findings of the present study, there are several possible limitations. First, beliefs about lack of personal control may be generated through chronic physical illness or functional impairment. For example, chronic health problems may contribute to erosion of psychological resources such as personal control both directly and indirectly. Second, socioeconomic failures and lack of achievement due to impaired physical health may also generate beliefs about lack of personal control. Again, an example: Severely unhealthy individuals might internalize these weakened beliefs about their personal control. Thus, there may be reverse causation and/or reciprocal influences between personal control and physical and mental health. Although the present findings demonstrate a promising mediational process from work control to health outcomes through personal control, we cannot discount potential reverse causation and/or reciprocal influences. In addition, the analytic approach did not take into account variability in work control and personal control over time ("shocks") as contributing factors for change in health.

The observed associations between work control and health, as well as between work control and personal control, may be moderated by the salience of one's work role. Identity perspective suggests that the health effects of life experiences in different role domains are a function of its salience (Thoits, 1992). Thus, the observed associations between work control and personal control, as well as work control and health, may be stronger for individuals who possess high levels of salience of work role than for individuals who possess low levels of salience of work role (Wickrama, Conger, Lorenz, & Matthews, 1995).

Our sample included all Whites from rural midwestern counties. Thus, characteristics of the study sample limit the generalizability of the results. Replication with a broader cross-section of the population that includes members of ethnic groups and those living in both rural and urban areas would increase our confidence in the general applicability of the findings presented in this study. Future research should extend this line of research by investigating more diverse populations.

Although it was subject to potential biases, we used self-reported information regarding work, personal control, and negative health outcomes. Future research should extend this line of research by using objective measures of work conditions and clinical measures of health outcomes. This study focused on the long-term influence of work control (1991–1994) on later mental and physical health outcomes (2001). Within the limitation of these data, we included important life events that occurred during this time period as control variables.

Finally, we believe that the results would be basically the same if the analysis had included the men who were dropped from the study. Our attrition analysis showed that although these attriters were slightly lower in socioeconomic status (e.g., education) compared to participants, they were not significantly different from participants in terms of the 1991 study variables. Also, we dealt with the 9% missing data from the 318 participants by using the full information maximum likelihood procedure.

Despite these limitations, the results presented here make an important contribution by demonstrating the long-term indirect health consequences for middle-aged men due to work conditions. In addition, the present study points to important theoretical implications. First, the study provides evidence for the additive influence of work control on individual health regardless of other personal experiences. Thus, researchers should further develop social psychological theories to explain the possible mechanisms for this direct association. Second, results show that individual personal control beliefs are malleable to one's work experiences. Thus, future research should acknowledge the time-varying nature of personal control beliefs. Finally, the results show that associations among work experiences, personal control beliefs, and health are dynamic in nature. More research should focus on these dynamic processes over the life course.

	Appendix

TOP Abstract Methods Results Discussion Appendix References

 
Measures

1 = strongly disagree to 5 = strongly agree; R = reverse coded.

1. This job matches my education and experience.
   
2. My job allows me to use my skills and abilities.
   
3. My job matches what I like to do.
   
4. I have skills from training or experience that I would like to use, but can't in this job. (R)
   
5. I am over qualified for the work that I do in this job. (R)
   
6. I have a flexible work schedule in this job.
   
7. In this work, I am mostly my own boss.
   
8. This job gives me the amount of independence I like.
   

1 = strongly agree to 5 = strongly disagree; R = reverse coded.

1. There is really no way I can solve some of the problems I have.
   
2. Sometimes I feel that I'm being pushed around in life.
   
3. I have little control over the things that happen to me.
   
4. I can do just about anything I really set my mind to. (R)
   
5. I often feel helpless in dealing with the problems of life.
   
6. What happens to me in the future mostly depends on me. (R)
   
7. There is little I can do to change many of the important things in my life.
   

	Acknowledgments

 
K. A. S. Wickrama planned the study, supervised the data analysis, and wrote the paper. Florensia F. Surjadi performed all statistical analyses and contributed to writing the paper. Frederick O. Lorenz helped plan the study and revise the manuscript. Glen H. Elder, Jr., helped plan the study and revise the manuscript.

	Footnotes

 
Address correspondence to K. A. S. Wickrama, Institute for Social and Behavioral Research, Iowa State University, 2625 North Loop Dr., Ste. 500, Ames, IA 50010. E-mail: S2kas@iastate.edu

Decision Editor: Kenneth F. Ferraro, PhD

Received for publication July 23, 2007. Accepted for publication January 19, 2008.

	References

TOP Abstract Methods Results Discussion Appendix References

 

• Baltes, P. B., Baltes, M. M. (1990). Psychological perspectives on successful aging: The model of selective optimization with compensation. In P. B. Baltes & M. M. Baltes (Eds.), Successful aging: Perspectives from the behavioral sciences (pp. 1–34). New York: Cambridge University Press.
• Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52,1-26.[Medline]
• Baron, R. M., Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51,1173-1182.[Medline]
• Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum.
• Carney, R. M., Freedland, K. E. (2000). Depression and medical illness. In L. F. Berkman & I. Kawachi (Eds.), Social epidemiology (pp. 191–212.). New York: Oxford University Press.
• Derogatis, L. R. (1983). SCL-90: Administration, scoring, and procedures manual II (2nd ed.). Towson, MD: Clinical Psychometric Research.
• Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F., Alpert, A. A. (1999). An introduction to latent variable growth curve modeling: Concepts, issues, and applications. Mahwah, NJ: Erlbaum.
• Elder, G. H., Jr., O'Rand, A. M. (1994). Adult lives in a changing society. In K. S. Cook, G. A. Fine, & J. S. House (Eds.), Sociological perspectives on social psychology (pp. 452–475). Boston: Allyn & Bacon.
• Enders, C. K. (2001). A primer on maximum likelihood algorithms available for use with missing data. Structural Equation Modeling, 8,128-141.
• Ferraro, K. F., Farmer, M. M. (1999). Utility of health data from social surveys: Is there a gold standard for measuring morbidity? American Sociological Review, 64,303-315.
• Griffin, J. M., Fuhrer, R., Stansfeld, S. A., Marmot, M. (2002). The importance of low control at work and home on depression and anxiety: Do these effects vary by gender and social class? Social Science & Medicine, 54,783-798.[Medline]
• Haidt, J., Rodin, J. (1999). Control and efficacy as interdisciplinary bridges. Review of General Psychology, 3,317-337.
• Heckhausen, J. (1997). Developmental regulation across adulthood: Primary and secondary control of age-related challenges. Developmental Psychology, 33,176-187.[Medline]
• Karasek, R. A., Theorell, T. (1990). Healthy work. New York: Basic Books.
• Karney, B. R., Bradbury, T. N. (1995). Assessing longitudinal change in marriage: An introduction to the analysis of growth curves. Journal of Marriage and Family, 57,1091-1108.
• Kobosa, S. (1979). Stressful life events, personality, and health: An inquiry into hardiness. Journal of Personality and Social Psychology, 37,1-11.[Medline]
• Kohn, M. L., Schooler, C. (1973). Occupational experience and psychological functioning: An assessment of reciprocal effects. American Sociological Review, 38,97-118.
• Kohn, M. L., Slomczynski, K. M. (1990). Social structure and self-direction: A comparative analysis of the United States and Poland. Cambridge, England: Blackwell.
• Kramer, A. F., Bherer, L., Colombe, S. J., Dong, W., Greenough, W. T. (2004). Environmental influences on cognitive and brain plasticity during aging. Journal of Gerontology: Medical Sciences, 59A,940-957.
• Lachman, M. E., James, J. B., (Eds.). (1997). Multiple paths of midlife development. Chicago: University of Chicago Press.
• Lachman, M. E., Weaver, S. L. (1998). Sociodemographic variations in the sense of control by domain: Findings from the MacArthur studies of midlife. Psychology and Aging, 13,553-562.[Medline]
• Lorenz, F. O., Conger, R. D., Montague, R. B., Wickrama, K. A. S. (1993). Economic conditions, spouse support, and psychological distress of rural husbands and wives. Rural Sociology, 58,247-268.
• Lorenz, F. O., Elder, G. H., Jr., Bao, W. N., Wickrama, K. A. S., Conger, R. D. (2000). After farming: Emotional health trajectories of farm, nonfarm, and displaced farm couples. Rural Sociology, 65,50-71.
• Lorenz, F. O., Wickrama, K. A. S., Conger, R. D., Elder, G. H., Jr.. (2006). The short-term and decade-long effects of divorce on women's midlife health. Journal of Health and Social Behavior, 47,111-125.[Medline]
• Marmot, M. G., Fuhrer, R., Ettner, S. L., Marks, N. F., Bumpass, L. L., Ryff, C. D. (1998). Contribution of psychosocial factors to socioeconomic differences in health. Milbank Quarterly, 76,403-448.[Medline]
• Mausner-Dorsch, H., Eaton, W. W. (2000). Psychosocial work environment and depression: Epidemiologic assessment of the demand-control model. American Journal of Public Health, 90,1765-1770.[Abstract/Free Full Text]
• Menaghan, E. G. (1991). Work experiences and family interaction processes: The long reach of the job? Annual Review of Sociology, 17,419-444.
• Menaghan, E. G., Parcel, T. L. (1990). Parental employment and family life: Research in the 1980s. Journal of Marriage and Family, 52,1079-1098.
• Merluzzi, T. V., Nairn, R. C. (1999). Adulthood and aging: Transitions in health and health cognitions. In T. L. Whitman, T. V. Merluzzi, & R. D. White (Eds.), Life-span perspectives on health and illness (pp. 189–206). Mahwah, NJ: Erlbaum.
• Mirowsky, J., Ross, C. E. (2003). Education, social status and health. New York: Aldine de Gruyter.
• Moen, P., Wethington, E. (1999). Midlife development in a life course context. In S. L. Willis & J. D. Reid (Eds.), Life in the middle: Psychological and social development in middle age (pp. 3–23). San Diego, CA: Academic Press.
• Pearlin, L. I., Lieberman, M. A., Menaghan, E. G., Mullan, J. T. (1981). The stress process. Journal of Health and Social Behavior, 22,337-356.[Medline]
• Pierce, C. P. (2005). Sense of control and psychological well-being during the transition to parenthood. Unpublished doctoral dissertation, University of Massachusetts, Amherst.
• Rodin, J., Timko, C. (1992). Sense of control, aging, and health. In M. G. Ory, R. P. Abeles, & P. D. Lipman (Eds.), Aging, health, and behavior (pp. 174–206). Thousand Oaks, CA: Sage.
• Romelsjo, A., Kaplan, G. A., Cohen, R. D., Allebeck, P., Andreasson, S. (1992). Protective factors and social risk factors for hospitalization and mortality among young men. American Journal of Epidemiology, 135,649-668.[Abstract/Free Full Text]
• Scheier, M. F., Carver, C. S. (1985). Optimism, coping, and health: Assessment and implications of generalized outcome expectancies. Health Psychology, 4,219-247.[Medline]
• Scheier, M. F., Carver, C. S., Bridges, M. W. (1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the Life Orientation Test. Journal of Personality and Social Psychology, 67,1063-1078.[Medline]
• Scheier, M. F., Matthews, K. A., Owens, J. F., Magovern, G. J., Lefebvre, R. C., Abbott, R. A., et al. (1989). Dispositional optimism and recovery from coronary artery bypass surgery: The beneficial effects on physical and psychological well-being. Journal of Personality and Social Psychology, 57,1024-1040.[Medline]
• Schwalbe, M. L., Staples, C. L. (1991). Gender differences in sources of self-esteem. Social Psychology Quarterly, 54,158-168.
• Seeman, M., Seeman, T. E. (1983). Health behavior and personal autonomy: A longitudinal study of the sense of control in illness. Journal of Health and Social Behavior, 24,144-160.[Medline]
• Staudinger, U. M., Bluck, S. (2001). A view on midlife development from life-span theory. In M. E. Lachman (Ed.), Handbook of midlife development (pp. 3–39). New York: Wiley.
• Tedesco, L. A., Keffer, M. A., Fleck-Kandath, C. (1991). Self-efficacy, reasoned action, and oral health behavior reports: A social cognitive approach to compliance. Journal of Behavioral Medicine, 14,341-355.[Medline]
• Theorell, T., Tsutsumi, A., Hallquist, J., Reuterwall, C., Hogstedt, C., Fredlund, P., et al. (1998). Decision latitude, job strain, and myocardial infarction: A study of working men in Stockholm. American Journal of Public Health, 88,382-388.[Abstract/Free Full Text]
• Thoits, P. A. (1992). Identity structures and psychological well-being: Gender and marital status comparisons. Social Psychology Quarterly, 55,236-256.
• Turner, R. H. (1978). The role and the person. American Journal of Sociology, 84,1-23.
• Whitbeck, L. B., Simons, R. L., Conger, R. D., Wickrama, K. A. S., Ackley, K. A., Elder, G. H., Jr.. (1997). The effects of parents' working conditions and family economic hardship on parenting behaviors and children's self-efficacy. Social Psychology Quarterly, 60,291-303.
• Wickrama, K. A. S., Beiser, M., Kaspar, V. (2002). Assessing the longitudinal course of depression and economic integration of south-east Asian refugees: An application of latent growth curve analysis. International Journal of Methods in Psychiatric Research, 11,154-168.[Medline]
• Wickrama, K. A. S., Conger, R. D., Lorenz, F. O., Matthews, L. (1995). Role identity, role satisfaction, and perceived physical health. Social Psychology Quarterly, 58,270-283.
• Wickrama, K. A. S., Lorenz, F. O., Conger, R. D., Matthews, L., Elder, G. H., Jr.. (1997). Linking occupational conditions to physical health through marital, social, and intrapersonal processes. Journal of Health and Social Behavior, 38,363-375.[Medline]
• Wickrama, K. A. S., Lorenz, F. O., Fang, S. A., Abraham, W. T., Elder, G. H., Jr.. (2005). Gendered trajectories of work control and health outcomes in the middle years: A perspective from the rural Midwest. Journal of Aging and Health, 17,779-806.[Abstract/Free Full Text]

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