Legal and Legislative Issues – CHAPTER 12

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Abstract

A variety of legal and legislative measures have been employed to reduce employee exposure to workplace risk factors for cardiovascular disease. These include legislation (and accompanying regulations) and collective bargaining by labor unions and employers, both of which are designed to reduce exposure to workplace chemical, physical, ergonomic and psychosocial hazards. The costs of workers’ compensation for work-related cardiovascular disease may also provide an incentive to reduce workplace exposure to cardiovascular risk factors. The state of legislation (and regulations) in Europe, the United States and Japan is briefly reviewed. In addition, the use of workers’ compensation and collective bargaining as prevention strategies in the United States is discussed. These measures not only have the potential to reduce exposure to workplace cardiovascular risk factors but also can promote the development of a “heart healthy” work environment.

Workplace Intervention Studies – CHAPTER 13

by Tage Kristensen

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The author reviews and discusses several intervention studies with implications for CVD or CV risk. The studies address chemical exposures, work schedules and working hours, and psychosocial factors at work. Effective strategies for prevention of CVD at the workplace are based on intervention research and integrate prevention at different levels.

The Workplace and Cardiovascular Health: Conclusions and Thoughts for a Future Agenda – CHAPTER 14

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We argued in the introduction that to adequately address the CVD epidemic, there is a need for a social epidemiologic approach that focuses on the workplace. Here, we briefly review the empirical, theoretical, and biological evidence presented earlier to demonstrate “convergent” validation that the relationship between workplace stressors and CVD risk is causal. The empirical findings are consistent with and predicted by the theoretical models, and the linkage between them is demonstrated to be plausible via biological mechanisms and experimental research. We then elaborate on new strategies, presented in the latter part of this book, for enhanced prevention and clinical management, workplace interventions, and social policy to reduce the impact of CVD.

EMPIRICAL EVIDENCE OF WORKPLACE EFFECTS ON CVD

In Chapter 2, we presented a substantial body of findings concerning the impact of workplace psychosocial, chemical, and physical conditions on CVD. The most consistent evidence is provided by research on sources of psychosocial stress at work, which are also the most prevalent risk factors. The most highly studied of these is work with high psychological demands coupled with low decision latitude, i.e., job strain. On the basis of empirical reviews focused on men and on women, as well as the recent review by the European Heart Network, (34) and notwithstanding some studies with null results, the conclusion of Schnall, Landsbergis, and Baker that “a body of literature has accumulated that strongly suggests a causal association between job strain and cardiovascular disease” has been corroborated and strengthened. The data relating job strain to AmBP and decision latitude to CVD outcomes are particularly compelling.

Besides consistency of association among studies, other evidence supporting causality has emerged. There are now data, albeit limited, suggesting a dose-response relationship between exposure to job strain or its major dimension(s) and both CVD and BP. New job strain cohort studies further confirm that exposure precedes outcome in time. Overall, of ten such studies in men, six show an increased CVD risk due to job strain or its components, and an additional two provide mixed results. Of five cohort studies among women, four demonstrate an elevated CVD risk related to job strain or its components.

Epidemiologic evidence of the plausibility of the relationship between job strain and CVD has expanded. Cross-sectional, as well as some longitudinal data, linking exposure to job strain with elevated AmBP in men and women suggests one major mediating mechanism for this process. There are now cohort data demonstrating that a change in job strain exposure is associated with a change in BP.(58) Furthermore, some data suggests an association between job strain and/or its major dimensions and other CVD risk factors, primarily smoking intensity in men, and possibly increased coagulation tendencies.

The magnitude of association between job strain and CVD typically range from risk ratios (RR) of about 1.2-2.0 for studies using imputed job characteristics (with resulting nondifferential misclassification bias towards the null), to 1.3-4.0 for studies using self-reported job characteristics. Associations are more consistent and stronger among blue-collar workers, with RR as high as 10. Systolic BP at work (as measured with an ambulatory monitor) among employees facing job strain is typically 4-8 mmHg higher than among those without job strain.

Reducing Occupational Stress An Introductory Guide for Managers, Supervisors and Union Members

Making Changes in Your Workplace to Reduce Stress

This handout assumes a working knowledge of the relationship between occupational stress and both psychological and physical strain, including cardiovascular disease. We will also assume that you have identified some of the organizational costs of high stress levels to your workplace and employees. Another key assumption, is that you are interested in a change strategy that includes structural, or organizational change. The approach discussed in this handout views individual approaches as augmenting, not replacing organizational change. Finally, we will assume that you have the opportunity to improve the quality of work in your organization.

If these assumptions are correct, congratulations. You have already taken the first steps toward improving the health and possibly the productivity of your employees. This handout will detail this process of healthy organizational change. Basically, this handout has two goals:

1. Identifying the major features of healthy organizational change.
2. Developing organizational and individual change strategies.

We will also provide you with some examples of successful organizational change efforts. One general note is in order. This handout will not review various theoretical models of change. It is intended to be a concrete and practical guide for healthy organizational change. For a review of theoretical models and references for additional examples, you can refer to the companion piece to this handout, Interventions to Reduce Job Strain (Landsbergis, Cahill & Schnall, 1995).

Social Science-Based Interventions

SOCIAL SCIENCE-BASED INTERVENTIONS

The most well-developed applied research tradition on bringing about planned change in organizations is the field of Organization Development (OD). OD has its roots in the “human relations” management and social theorists of the 1940s-’50s, who were reacting to the dehumanization, alienation, and bureaucracy characteristic of scientific management (Taylorism). (46, 47) OD practitioners conducted innovative work reform experiments during the 1950-’70s, including early joint labor-management Quality of Work Life (QWL) programs. These focused primarily on social relationships (for example, a sense of belonging, supportive supervision, participation in decision-making) rather than the technical features of production and work organization. In the 1980s, OD practitioners “discovered” the importance of technology, especially European Socio-Technical Systems (STS) theory, which promotes semiautonomous work teams. More importantly, by the 1980s, many OD professionals lost sight of their original stated mission to attempt to serve both employer interests and employee needs and applied their trade primarily on behalf of employers. (48, 49).

Scandinavian work reform experiments in the 1960s and 1970s, while influenced by the same human relations research (and also reacting against the dehumanizing effects of scientific management), placed a greater emphasis on technical aspects of production (for example, piece-rate, shiftwork, technology) as well as an understanding that physical illness and injury is an outcome of work organization (50); an outcome which has been largely ignored by OD. These different emphases, along with a progressive political climate and a highly unionized work force, led eventually to work environment legislation in the 1970s in Scandinavia and continuing job redesign and work reform efforts today. (5, 51) These experiments, and the emphasis on health as an outcome of work, also laid the foundations for Karasek’s model, and much stress research both in Scandinavia and the U.S.

Many OD and QWL efforts have failed, however, because of factors such as lack of support by top management or supervisors, failure to delegate authority, a bureaucratic, authoritarian climate, and rigid job descriptions and personnel practices. (52, 53) Some interventions have led to increased workload or “speedup” (54, 55), work force reductions (46), or were initiated as attempts to avoid unionization (56, 57) or weaken the existing union. (49, 58) However, positive experiences with cooperative programs have also been reported by some unions (59, 60), and the debate continues in the labor movement over the potential value of these programs in specific situations.

Recognizing these limitations, unions and occupational health professionals have much to gain by adopting the valuable set of techniques and processes (intervention research methods) developed by OD, and using them on behalf of workers. One of these methods is known as Action Research (AR). AR involves a partnership between outside experts (usually social scientists) and members of organizations in defining problems, developing intervention tactics, introducing changes that benefit organization members, and measuring outcomes. (38) Issues and changes that this approach typically involves include decisio-making structures and processes, task and role demands, information and communication practices, work schedules, and training policies. AR can be classified into “expert-dominated” approaches (also allied “weak” AR), in contrast to “strong” versions where there is relative equality among researchers and organization members in all aspects of the intervention and research process also termed Participatory Action Research (PAR). (61) While few studies have compared these approaches, one review suggests that PAR generates more positive outcomes. (62) Several key examples of “expert” AR and PAR interventions, which focused on improving workers’ physical or mental health, are briefly summarized below, followed by a discussion of policy and research issues.

Introduction to Prevention

“A wide variety of interventions and prevention programs have been developed and used in order to reduce job stressors and the health problems they cause. These interventions can be carried out at the level of the job, throughout the organization, at a more personal level, or at a state or national level through laws and regulations. It is important that the effects of interventions be carefully observed, measured, and documented [81].

Work organization and job stressors are also shaped by the competition employers face in the global economy. Thus, solutions to the problem will also need to be international in scope. The European-wide regulations and labor-management agreements that deal with job stress are one example of solutions achieved through national regulations while addressing organizational levels, and which are international in scope by encompassing all of the countries of the European Union. While more research on the effectiveness of different types of interventions would always be useful, the existing research allows us to draw various conclusions. For one, effective interventions tend to be those involving “systems approaches,” which focus on both primary prevention, that is, changing the causes of work stress, such as work schedules and workload, and include secondary and tertiary levels of prevention, with programs to help employees suffering symptoms of stress or who have become ill due to job stressors.

Additionally, the existing research allows us to conclude that effective interventions also involve meaningful participation of employees, increasing employees’ job control, and ensuring top management support. We should continue to be persistent and creative in developing, carrying out, and evaluating workplace changes designed to improve workers’ health. Listening to employees about their concerns, their pain, and the solutions they recommend is a key principle of this effort. The following chapters provide some excellent and more detailed examples of interventions carried out to reduce stress and create healthier work—and workers.”

81. Semmer, N., Commentary II. Health Related Interventions in Organizations: Stages, Levels, Criteria and Methodology, Soz-Praventivmed, 49:89-91, 2004.

Taken from: Schnall PL, Dobson M, Rosskam E, Editors Unhealthy Work: Causes, Consequences, Cures. Baywood Publishing, 2009.

Job Stress and Heart Disease: Evidence and Strategies for Prevention

We present here the full text of an article titled “Job Stress and Heart Disease: Evidence and Strategies for Prevention.” This article outlines an approach to the prevention of hypertension and heart disease, and appeared in the journal ‘New Solutions’ in 1993.

Excerpt:

SOCIAL SCIENCE-BASED INTERVENTIONS 

The most well-developed applied research tradition on bringing about planned change in organizations is the field of Organization Development (OD). OD has its roots in the “human relations” management and social theorists of the 1940s-’50s, who were reacting to the dehumanization, alienation, and bureaucracy characteristic of scientific management (Taylorism). (46, 47) OD practitioners conducted innovative work reform experiments during the 1950-’70s, including early joint labor-management Quality of Work Life (QWL) programs. These focused primarily on social relationships (for example, a sense of belonging, supportive supervision, participation in decision-making) rather than the technical features of production and work organization. In the 1980s, OD practitioners “discovered” the importance of technology, especially European Socio-Technical Systems (STS) theory, which promotes semiautonomous work teams. More importantly, by the 1980s, many OD professionals lost sight of their original stated mission to attempt to serve both employer interests and employee needs and applied their trade primarily on behalf of employers. (48, 49). 

Scandinavian work reform experiments in the 1960s and 1970s, while influenced by the same human relations research (and also reacting against the dehumanizing effects of scientific management), placed a greater emphasis on technical aspects of production (for example, piece-rate, shiftwork, technology) as well as an understanding that physical illness and injury is an outcome of work organization (50); an outcome which has been largely ignored by OD. These different emphases, along with a progressive political climate and a highly unionized work force, led eventually to work environment legislation in the 1970s in Scandinavia and continuing job redesign and work reform efforts today. (5, 51) These experiments, and the emphasis on health as an outcome of work, also laid the foundations for Karasek’s model, and much stress research both in Scandinavia and the U.S.

Many OD and QWL efforts have failed, however, because of factors such as lack of support by top management or supervisors, failure to delegate authority, a bureaucratic, authoritarian climate, and rigid job descriptions and personnel practices. (52, 53) Some interventions have led to increased workload or “speedup” (54, 55), work force reductions (46), or were initiated as attempts to avoid unionization (56, 57) or weaken the existing union. (49, 58) However, positive experiences with cooperative programs have also been reported by some unions (59, 60), and the debate continues in the labor movement over the potential value of these programs in specific situations.

Recognizing these limitations, unions and occupational health professionals have much to gain by adopting the valuable set of techniques and processes (intervention research methods) developed by OD, and using them on behalf of workers. One of these methods is known as Action Research (AR). AR involves a partnership between outside experts (usually social scientists) and members of organizations in defining problems, developing intervention tactics, introducing changes that benefit organization members, and measuring outcomes. (38) Issues and changes that this approach typically involves include decisio-making structures and processes, task and role demands, information and communication practices, work schedules, and training policies. AR can be classified into “expert-dominated” approaches (also allied “weak” AR), in contrast to “strong” versions where there is relative equality among researchers and organization members in all aspects of the intervention and research process also termed Participatory Action Research (PAR). (61) While few studies have compared these approaches, one review suggests that PAR generates more positive outcomes. (62) Several key examples of “expert” AR and PAR interventions, which focused on improving workers’ physical or mental health, are briefly summarized below, followed by a discussion of policy and research issues. 

Expert Dominated Action Research.

In a classic example, Jackson took advantage of a state legislative mandate for more frequent staff meetings in hospitals to measure the effects of participation in decision making on job stress, job satisfaction, absenteeism and turnover. (63) Units where the intervention was implemented held twice as many staff meetings as in non intervention units. Workers in participating units reported greater influence, less role conflict and ambiguity, less emotional strain, and greater job satisfaction at three month and six month follow­up. 

In another example, Golembiewski and colleagues worked with 31 “burned out” and overworked Human Resources (HR) staff of a corporation in the midst of rapid growth. (64) Four action planning groups developed recommendations, and the entire staff prioritized them and prepared implementation plans, which were presented to a corporate oversight committee. As a result, an HR career ladder was introduced as well as a change in reporting structure. Effects included a 50 percent reduction in reported ‘burnout’ that remained low four months after the last intervention, a turnover decline from 37 percent to 17 percent, and a significant increase in reports of “innovativeness.” 

Participatory Action Research (PAR).

An example of PAR was a six­year study by Israel, Schurman and colleagues in a components parts plant of a major unionized automobile company. (38, 65) With agreement from local union leadership and plant management, and working with union and management representatives, they set up a representative employee committee, primarily comprised of shop floor employees – the Stress and Wellness Committee (SWC) – to implement the project. Using the PAR process of iterative cycles of diagnosis, action-taking and evaluation, the committee identified four primary sources of stress and designed interventions (through subcommittees) for each: lack of participation and influence, hassles with supervisors, lack of information / communication, and “production vs. quality.” Interventions included establishment of a pilot cross-functional team in one department to address quality issues, convincing factory management to conduct state of-the-business meetings in each department, and creation of a weekly plant newsletter. Overall, SWC members report high levels of trust in and influence over the committee process. In addition, other employees who were more involved in and knowledgeable about the PAR project reported greater increases in participation, perceived participative climate and co-worker support than others with less exposure. (66)

Another example of PAR in a unionized setting began with a survey by Cahill of “burn out” and symptoms of stress among employees of the New Jersey child protection agency. (67) The survey, which found significantly higher levels of “burn out” than in national samples of social workers, was presented by the employees’ union in a legislative hearing. One result of the hearing was the formation of a labor management stress committee, which identified the agencies existing mainframe computer system as a major source of stress. The system included repetitive deskilled work for clericals, lack of control of data for administrators and social workers, hard to interpret monthly reports, and ergonomically poor work stations. The stress committee recruited a computer programmer to design software jointly with the local employees who would use a new PC based system. Once the new system was in operation, workers reported significantly higher levels of job satisfaction, decision latitude, skill discretion, control over equipment, a more streamlined information flow between local and central offices, and improved ergonomic conditions. 

A final example of PAR to reduce job stress was developed by Lerner and colleagues at the Institute for Labor and Mental Health, and was based outside the workplace. (68) Strategies for raising awareness of the social and workplace sources of stress included: meeting with unions; organizing a conference on job stress where workers told their story to government, public health officials and the media; a “family day” with workshops on stress of family and work life; and Occupational Stress Groups (OSGs). OSGs of 10 workers, led by shop stewards, met for eight to 12 weeks to discuss stress at work, develop social support, discuss the dangers of self-blame for feelings of powerlessness or stress, and to develop strategies for collective action. At follow-up, OSG participants showed significant improvements on virtually all measures of psychological well-being in comparison to controls. Behavioral changes and initiatives taken to improve the workplace were also reported in group interviews.

Other union sponsored and work site based initiatives, the OCAW Work and Family Program (69) and the District 65 UAW Stress Project (70), build on the OSG format. Both employ group meetings to raise awareness of stressful working conditions (and their impact on family life) and then develop collective bargaining proposals to improve working conditions.

Discussion.

PAR approaches with strong union involvement have significant advantages over weaker expert dominated or management dominated AR programs. Strong union involvement can ensure that the potential dangers of OD are minimized and that interventions genuinely improve the work environment. Unions played important roles in initiating and sustaining structural change in the auto parts factory and in the New Jersey state agency, as well as, of course, in developing the OSG, OCAW and District 65 programs. However, such programs are limited by the low unionization rate in the U.S. The community-based approach used by Lerner can be especially useful in non union settings (such as COSH group efforts to educate and help organize non union workers), or where unionized employers refuse to cooperate or commit required support and resources.

PAR is a flexible set of intervention processes and methods, not a pre packaged canned program. This allows it to be effective in different contexts, with different occupational groups, and with resulting different strategies and tactics. It is also an innovative social research method, which makes it valuable for occupational health research. PAR is an effective tool for the evaluation of change because both quantitative and qualitative data are included, and process, impact, and outcome are assessed (thus requiring multi disciplinary teams skilled in these techniques). For example, the intervention in the auto parts factory included three administrations of a plant-wide survey (including standardized survey scales), focus group interviews and five surveys of committee members, in depth interviews of all committee members and plant union and management leaders, and verbatim field notes from committee meetings. Other studies included standardized surveys and objective records such as frequency of staff meetings, absenteeism and turnover. Such multi method approaches permit “triangulation,” that is, cross validation of and increased confidence in the results. (38, p. 148) Process data enable participants and researchers to assess not just what happened but why it happened (including obstacles to change). Impact data can reveal which organizational or individual factors are affected by the intervention, and through which pathways. For example, in the auto parts factory, regression analysis of survey results indicated that the positive effects of participation were channeled through perceptions of influence. Outcome data can answer questions about health effects.

Another important research issue is the need for longitudinal designs, with adequate time for follow-up. For example, the amount of change reported by the intervention group in Jackson’s study increased significantly between the first and second post tests, suggesting that participation takes time to create effects. In the auto parts factory, 1.5 years was needed to conduct organizational diagnosis and needs assessment prior to engaging in major change strategies. 

Thus, PAR to reduce job stress appears to work in two main ways (corresponding to arrows A and B of Karasek’s model in figure 1), by: 1. modifying objective stressful conditions in the social and/or technical environment; and 2. the active (individual and collective) learning workers experience in successfully affecting positive change (for example, enhanced perceptions of control and influence, development of skills, positive self-appraisal, strengthened relationships with co-workers).

Genuine PAR allows workers not only to problem solve but also to, jointly, with researchers, define targets for research and intervention and evaluate change (to be involved in all aspects of the intervention). Workers bring a richness of experience that enhances problem definition and hypothesis development, as well as insights to creating change. (71, 72) For example, workers can specify the concrete manifestations of job demands or low job control in a particular workplace (not captured by standardized scales), necessary for targeting change efforts. Researchers bring a rich knowledge base, methods of questionnaire construction and research design, and other means of improving study validity. While some researchers argue that participant involvement in social research could bias results due to improper wording of questionnaires, or attempts to influence survey response, bias can also result from employees’ unwillingness to participate or candidly present their opinions “when involved with conventional research projects, because they associate researchers with management and the existing hierarchical structure.” In addition, PAR researchers’ use of multiple methods provides limit insights from the participants’ “inside” understanding of attitudes, needs, and the social environment. (38, p. 140)

Genuine PAR (as opposed to some QWL programs) increases the skills and activism of those participating in the intervention, although to date there is no evidence that it strengthens union solidarity. However, just as active and assertive union involvement in health and safety training programs strengthens the union’s position and credibility in the eyes of its members (73), benefits should be expected when the union is actively involved in improving other issues of concern to workers-job design and psychosocial work environment. (74, 75)

Personal stress management and health promotion was a component in many of these programs (including the District 65, UAW stress program). By discussing personal behavior change within the context of an overall program to improve the work environment, self blame for behaviors or feelings of stress is avoided, and the union shows it is concerned about the personal welfare of its members. It can also be an organizing tactic to help gain publicity and support for the overall program, as in the auto parts factory study. In general, multiple levels (individual, group, organization, society) need to be targeted for interventions to effectively reduce stress. (76)

Even in successful interventions, many obstacles to change remain, for example, management turnover, lack of management support, pending layoffs and general market conditions in the auto parts factory. In the New Jersey state agency, information and technology managers were initially resistant, perceiving the new technology and software as a threat to their power. Ensuring that they received some credit for the success of the project eventually led to their strong support for the intervention.

PAR can be a valuable technique in traditional occupational health programs. (71, 77) In addition, occupational health professionals and unionists can play a critical role in the next stage of stress research and stress prevention, by: 1. adding physical health as an outcome in PAR programs to improve the psychosocial work environment; 2. studying the effect of the physical work environment and fear of injury, on perceived stress and psychological well being; and 3. studying the possible interaction between physical and psychosocial hazards in the production of heart disease, hypertension, and psychological distress, and other outcomes potentially related to job stress, such as musculoskeletal disorders (78), adverse pregnancy outcomes (79), and “sick building syndrome.” (80)

COLLECTIVE BARGAINING APPROACHES 

In addition to more recent PAR programs, collective bargaining has been a traditional strategy to increase employee decision latitude (authority, influence, skill), and to regulate demands through contract language on issues such as job security, overtime, seniority, discrimination, technological change, skills training, career ladders, staffing, grievance procedures, and labor­management committees. (81, 82, 83) For example, the nurses’ shortage during the 198Os in the U.S. has been attributed to factors such as low salary and job stress. Nurses have expressed a strong desire to be treated as professionals, which can be denied through understaffing, lack of autonomy, or an authoritarian work climate. In response, unions have bargained for clinical career ladders for RNs in various specialties, joint physician nurse committees, greater “in service” education (84), and quality patient care and personnel committee. (82)

Many clerical workers have joined unions in the last decade, in part due to issues related to job stress: career mobility, pay equity, job security, child care, flextime, parental leave, sexual harassment, having a “voice” through union-management committees, and video display terminal (VDT) work. (85) VDT workers have bargained for better ergonomic conditions, but have also learned that adjustable equipment is not enough. For example, at a New York City newspaper, a union-management committee discovered that job design issues such as control over schedule, regular breaks, work variety, and training were as important as the purchase of new equipment. (86) The National Institute for Occupational Safety and Health (NIOSH) is conducting various studies of the role of psychosocial factors in the development of cumulative trauma disorders (CTDs) among VDT operators. (87) 

At least six million U.S. workers were electronically monitored in 1987, with the number expected to grow. (88) As part of a 1992 settlement of a Communications Workers of America (CWA) lawsuit, Northern Telecom agreed to prohibit secret voice, computer, and video monitoring of employees. (89) A CWA – U.S. West contract banned monitoring in 1989 with the help of early results from a study that showed that monitored workers had higher rates not just of psychological distress but also “stiff or sore wrists,” “loss of feeling in fingers or wrists” other symptoms of CTDs. (90) Similar studies by Bell Canada and the Communications Workers of Canada led to restrictions on monitoring in 1990. (89) Recently, AT&T agreed to ban secret monitoring of the job performance of workers. (91) A new study at U.S. West by NIOSH showed and stress due to monitoring, fear of job loss, increasing work pressure, and little job decision making opportunity contributes to injures even when proper equipment is used. (92)

The apparent interaction between psychosocial stress and physical stress and injury and illness needs to be better understood. Monitored workers have reported aspects of “job strain” (greater workload, less job control, unfair work standards, less skill use and variety), and poorer supervisor support. Do such factors lead to fewer breaks, longer work hours, or faster typing? Does increased muscle tension play a role? While some of the 10 fold increase in reported CTDs over the last decade (93) is undoubtedly due to better reporting, these studies suggest that some may be due to work speed-up, de-skilling of jobs into simpler, more repetitive tasks, lack of control, and fear of job loss.

Electronic monitoring is often used to punish, not reward (for example, by publicly displaying results), managers over rely on it, and an emphasis on quantity not quality is created. (94) However, unions have shown that there are productive alternatives to monitoring. For example, CWA members at an Arizona facility, together with AT&T management, “eliminated individual measurement and remote secret observation. AWT (average work time) was measured only for the whole group. Service observation was performed by small groups of peers by the old fashioned ‘jack in’ method, where the observer sits beside the person being monitored, listens to a few calls and then discusses the results with the employee.” As a result, AWT was better than under previous methods of supervision, them were fewer customer complaints, and both the grievance rate and absenteeism were lower. (94)

The loss of the 1981 PATCO strike and the firing of 11,000 unionized workers was a major setback in workers’ rights to organize and strike. Some argue that PATCO’s biggest failure was that it could not make an effective case for job stress a major strike issue. (95) The job of air traffic controller includes many aspects of “job strain:” 1. high demands (through understaffing, mandatory overtime, few vacations); 2. poor skill utilization (because of poor training methods, outmoded equipment, few opportunities for promotion); 3. little authority (due to an autocratic system and military style management, where grievants are labeled as troublemakers and not promoted). (95, 96) These conditions persist and, not surprisingly, new controllers have joined a new union and stress remains a major issue. 

However, medical proof of the job’s hazards has remained elusive. While the major 1975 through 1978 health study of controllers did report prevalence of hypertension 1.5 times that of national samples, and incidence of new cases of hypertension up to four times higher (97), much analysis focused on individual and psychological differences among men in the study. In addition, the Federal Aviation Administration (FAA) emphasized only the individual differences (not the high dissatisfaction with “management policies and practices” noted in the study, (97, p. 6281), and never published the non technical summary of the study. (2, pp. 1301 to 1303) For years, the FAA had ordered researchers conducting their stress studies “not to make recommendations” for corrective action. (2, p. 895) The FAA’s technical representative to the study later testified that if the findings of the study (and 28 other FAA studies) had been applied, ‘I am absolutely certain” that the 1981 strike “would have been averted.” (2, p. 874) Air traffic controllers’ experience of stress and desire for equity had been deflected into a debate about the quality of scientific evidence on stress and health. (98) 

In 1981, PATCO’s collective bargaining demands focused on ways of “escaping” rather than “confronting” job stress: reduced work hours, early retirement, and higher salary demands which did not win public sympathy. Alternative strategies such as improving organizational climate, supervision and communication (99) or more power over the work process, for example, flow control, curbing unregulated pleasure aircraft, disciplining of authoritarian supervisors, or more new hires, were not attempted. (95, p. 187) There were, of course, other reasons why the strike was lost, such as failure to effectively build alliances with other unions (95), poor public relations (100), and, most importantly, an intransigent administration in Washington, DC. However, former PATCO officer Bill Taylor emphasized that “knowing what I know now, I think we should have tried to double our effort to inform the public what the strike was all about, which was bargaining rights, not money.” (101 )

A more constructive resolution to a labor-management conflict over working conditions and health was arrived at by a union of toll collectors and a New York City agency. While a specific toxin had not been identified as the cause of illness among 34 bridge toll workers in New York City in 1990, union officials had ‘bridled” at the suggestion that the outbreak was due to “stress.” (102, 103). The union had attempted for years to improve safety and health conditions for the toll collectors, who have elevated heart disease mortality rates, due, at least in part, to documented excess exposure to carbon monoxide (CO) from automobile exhaust. After the outbreak, union officials demanded permanent air monitoring equipment and better ventilation. Some union officials acknowledged that while the first cases in the outbreak may have been due to inhalation of toxic vapors (arising from the burning of plastic­coated wire), later cases may have been due to “anxiety.” (102) The union and the agency recently bargained a substantial medical surveillance program, whose primary focus is on heart disease risk due to CO exposure. The program will also evaluate the possible role of “job strain” as an independent or interactive risk factor for heart disease.

STATEWIDE AND NATIONAL EFFORTS AND STRATEGIES TO REDUCE STRESS

Workers compensation. Spokespersons for the insurance industry argue that claims for “mental injury” rose sharply during the 1980s, and now account for about 15 percent of all occupational disease claims nationwide (104) – figures used to justify current efforts to limit claims. However, accurate data is difficult to obtain. In California, for example, one of only six states which considers mental injuries caused by gradual mental or emotional stress to be compensable, and a state with the most liberal law, the rate of mental stress (claims increased 540 percent between 1979-88, according to state data. (105) However, the 9,368 reported cases in 1988 represented only two percent of total disabling work injuries. According to an insurance industry institute in California, many claims are not reported to the state agency, and self-insured public employers have higher rates, suggesting that the number of stress claims is actually four fumes higher. (105) However, even the higher estimate does not support arguments that business “is under siege” (104), but is compatible with growing awareness of the job stress illness link

The California insurance institute study indicated that stress claimants are more likely to be female and older than other work disabled employees. Sales and clerical workers filed 40 percent of stress claims. Fewer than 10 percent of the claims followed a specific incident (for example, armed robbery), rather job pressures (69 percent) and harassment (35 percent) were the most common cited reasons for the claim. (105) While it is difficult to generalize from this data, since many factors influence workers’ ability or intention to file for compensation, it is compatible with the model of “job strain” as cumulative exposure to job pressures and low job control. The law still generally works against the worker since the burden of proof is upon the worker to define a condition and establish work relatedness. (106)

Recently, employers have pushed for tighter standards for stress claims. A 1990 amendment to the New York State law restricts “mental” claims when stress results from a normal personnel decision (work evaluation, job transfer, demotion) when taken in “good faith” by the employer. Similarly, since 1989, in California, the law requires that workers receive a psychiatric diagnosis of mental injury, and that “actual events” in the workplace were responsible for at least 10 percent of the causation of the injury not simply the worker’s perception of stress. (105) It remains to be seen to what extent the new scientific evidence on “job strain” will be used in compensation cases to explain causation for mental injury, hypertension, or heart disease.

Legislation and political action. In the U.S., job stressors are not covered by OSHA. There are no health standards for shift work, piecework, machine pacing, de skilling, job security, isolated work, or technological change (as in Scandinavia). (107) An innovative campaign, however, is being waged by the Service Employees international Union (SEIU) in Pennsylvania to reduce back injuries and stress caused by inadequate staffing in nursing homes. (OSHA has already cited several nursing homes under the General Duty Clause for insufficient staff to do person transfers.) The campaign is in support of a proposed state law that would compel nursing homes to reveal information about staffing, injuries and profits, and set minimum staffing levels. (108) A recent SEIU national survey of nurses re emphasized concerns about work load demands, understaffing and stress, and called for OSHA standards for nursing (including staffing), and providing health care workers with a voice in decisions. (109)

On the national level, support by the Clinton administration for the concepts of ”high skill, high wage strategies” and “worker participation” (110) to improve the competitiveness of U.S. businesses holds the promise for a new focus on developing healthier work environments and reducing “job strain.” However, in order to genuinely promote ”high skill,” active and lower “strain” jobs, job training and job design programs need to: 1. go beyond basic job skills, or narrow technical skills, and include “job ladders” or “career paths;” 2. promote computer software that encourages discretion and flexibility (“system knowledge”); 3. make skill training accessible to workers’ schedules; and 4. keep skilled jobs in the bargaining unit and therefore increase rather than decrease union strength. (111, 112)

In addition, a variety of current legislative proposals could help increase job control and support, for example, laws that limit electronic monitoring and regulate VDT work. Other proposals could reduce the more general burden of social stress on individuals, such as laws on parental and personal leave, day care and elder care, voluntary overtime and shift work, a limited work week to create jobs, job sharing and part time work (8, 9) Even the OSHA reform bill (through mandated joint committees, improved worker training and enforcement, protection against discrimination, and improved recordkeeping) could spur efforts to identify and reduce psychosocial risk factors, most likely through investigation of hypertension and musculoskeletal disorders. Psychosocial risk factors could be considered for inclusion in the forthcoming ergonomics standard.

The goal of all these interventions and strategies is to produce a healthy workplace – in which workers are respected, where they have the opportunity to develop their skills and abilities, and where authority is shared, in other words, workplace democracy. Therefore, it is also important to consider legislation that would strengthen workers’ collective voice (that is, unions) through banning of permanent replacements for strikers, and, in general, reforming labor law, as well as other means of increasing workers’ influence and economic security, such as full employment and opportunities for employee ownership. 

Low Social Support

Workplace social support has been added to the job strain model as a third major job characteristic in several studies of CVD (49, 50, Hall, Johnson and Tsou, 1993), all-cause mortality (8, 25), smoking and sedentary behavior (Johannson, Johnson and Hall, 1991), and ambulatory blood pressure (Landsbergis et al., 1994) as well as a number of studies of psychological strain outcomes (e.g., 60, 71).

The main effect of low social support on CVD was examined, with positive associations (25, 49), as well as the interaction between social support and job strain (8, 25, 49). Social support was as an effect modifier in the Swedish study of retired men (25) (increased job strain-mortality risk ratios for those with low social support), in the Swedish factory worker study (8) (reduced high latitude-mortality risk ratios for those with high workplace social support), and in a Swedish national study (49) (increased high demand-low latitude-CVD prevalence ratios with greater workplace social isolation).

One study of CVD risk factors (Johannson, Johnson and Hall, 1991) found an association between smoking and co-worker support, but only for women. While Landsbergis et al. (1994) found no association between social support and ambulatory blood pressure among 262 male employees in New York City, an earlier study found significant associations between a supportive foreman, supportive coworkers and lower casual diastolic blood pressure among 288 male factory workers (79).

Self-Efficacy and Heart Disease

Introduction: What is self-efficacy and how might it relate to cardiovascular health?

Self-efficacy refers to the confidence in one’s ability to behave in such a way as to produce a desirable outcome (Bandura, 1977). Self-efficacy makes a difference in how people feel, think, and act. In terms of feeling, a low sense of self-efficacy for a particular situation is positively related to depression and anxiety. High self-efficacy for a specific situation allows one to deal better with uncertainty, distress, and conflict. In terms of thinking, the strong sense of competence resulting from high self-efficacy facilitates enhanced cognitive processes and academic performance. Finally, in terms of action, self-related cognitions are a major ingredient of the motivation process. Self-efficacy levels can enhance or impede motivation. People with high self-efficacy in a particular domain of human functioning choose to perform more challenging tasks. They set higher goals and stick to them. Actions are preshaped in thought, and people anticipate either optimistic or pessimistic expected outcomes of a specific task in line with their level of self-efficacy. Once an action has been taken, high self-efficacious persons invest more effort and persist longer than those low in self-efficacy to accomplish a specific task. When setbacks occur, those with high self-efficacy recover more quickly and maintain commitment to their goals (Schwarzer, 1992). Self-efficacy levels for specific cardiovascular health-related behaviors may be an important determinant of future cardiovascular health. Dietary self-efficacy, physical activity self-efficacy, and cessation of smoking self-efficacy are among the examples that will be discussed where self-efficacy for specific health-related behaviors likely plays a large role in future cardiovascular risk factor profiles. The following sections will review the evidence supporting links between self-efficacy of specific cardiovascular health-related behaviors and specific well-established cardiovascular risk factors.

Assessing the multiple dimensions of self-efficacy

Bandura (1986) argued that self-efficacy expectations consist of three dimensions: magnitude, generality, and strength. Each of these dimensions implies different measurement procedures. Magnitude refers to the ordering of tasks by difficulty level. Generality concerns the extent to which efficacy expectations about a specific situation can be generalized to other situations. Finally, strength refers to a judgment of how certain one is of being able to succeed at a particular task (Mudde et al., 1995).

There is no standard measurement for self-efficacy. Self-efficacy, unlike dimensions of personality, must be considered in terms of a specific situation (Gerin et al., 1995). Therefore, different measures are used to assess self-efficacy for each particular health-related behavior studied. In addition, a different measure is often used to assess each of the three dimensions of self-efficacy for a particular health-related behavior.

Self-efficacy and Smoking Cessation

Cigarette smoking has been identified as a risk factor for cardiovascular disease. Furthermore, studies indicate that patients with coronary artery disease who stop smoking have a lower mortality from all causes of death and a less frequent occurrence of myocardial infarction in particular than those who continue to smoke (Vlieststra et al., 1986). Self-efficacy in the area of smoking cession has been thoroughly studied. Thus, this is an excellent first example of how self-efficacy has been shown to predict behavioral change for an important cardiovascular risk factor. i.e., smoking. “Several studies have emphasized the predictive value of self-efficacy for behavior change among smoking cessation treatment participants (for review see: Strecher et al., 1986; Crey et al., 1989). The consensus of these studies is as follows: pre-treatment self-efficacy was generally not predictive of smoking status after treatment. However, post-treatment self-efficacy of subjects who were abstinent after treatment was significantly higher than self-efficacy of those who were not successful. Post-treatment self-efficacy expectations were significant predictors for short-term maintenance of smoking cession (3-6 months after treatment) (Pederson et al., 1991; Haaga, 1989; Coelho, 1984; McIntyre et al., 1983). This relationship held true even when post-treatment smoking status was controlled for and only subjects, who were abstinent after the treatment were included (Haaga and Stewart, 1992; Bear and Lichtenstein, 1988; Diclemente, 1981). For self-quitters the predictive power of self-efficacy may be even stronger. Gritz et al., 1992 found that self-efficacy predicted long-term abstinence (12-18 months) from smoking as a result of self-initiated quit attempts in agroup of female smokers (Mudde et al., 1995).

A recent prospective study by Mudde et al., 1995 provides further insight by comparing different measures of self-efficacy for smoking cessation in regards to which is the strongest predictor for smoking cessation. Each measure represented different combinations of the three dimensions of self-efficacy. The perceived difficulty scale used (PDS- Strecher et al.,1985) represented magnitude and generality. The perceived ability scale (PAS- Coletti et al., 1985) and a 1-item perceived ability measure (PAM- Mudde et al., 1995) both incorporated generality and strength in different degrees. Their results confirmed that perceived self-efficacy for smoking cessation predicts short and long-term smoking cessation. Results also suggested that the PDS may predict short-term cessation, while the PAS may be a predictor of long-term abstinence. By means of factor analyses, various subscales were found in both of these scales. The negative/affective subscale of the PDS and the negative/moodstates subscale of the PAS appeared to be the most important elements of these two scales. However, it was the PAM measure that showed the greatest predictive power for post-follow-up abstinence from smoking. Since all three measures included the dimension generality, a conclusion might be that magnitude is the dimension of greatest importance for the prediction of short-term cessation success, while strength may be the dimension that best determines long-term abstinence. Please see Mudde et al., 1995 for further details or for a discussion of the external validity of the study.

“In summary, the predictive ability and consistency of self-efficacy evaluations for smoking behavior have been impressive. Few constructs in the social sciences can boast such a record. In almost every case, efficacy evaluations, particularly abstinence efficacy evaluations, have been the most significant, or among the only significant, predictors of smoking cessation treatment outcome that emerged from studies that included a wide range of other predictors (DiClemente, 1986; DiClemente et al., 1995).

Self-efficacy and Weight Loss

Being overweight is a significant risk factor for the development of hypertension and coronary heart disease (see the link for a review of obesity and cardiovascular health by clicking on “overweight” among the listed risk factors our web page: www.workhealth.org). Weight control self-efficacy to perform behaviors that lead to weight loss has been examined in a number of ways. In fact, the assessment of self-efficacy varies greatly from study to study and is more diverse than in smoking cessation self-efficacy research. Due to the great variety in assessment of the construct of weight control self-efficacy, it should be noted that it is difficult to summarize the findings and make generalizable conclusions. The closest thing to a standard assessment in the field of weight control self-efficacy is Glynn and Ruderman’s (1986) Eating Self-Efficacy scale (ESES) (DiClemente et al., 1995).

There is a large amount of evidence suggesting that weight control self-efficacy plays an important role in weight loss. Chambliss and Murray (1979) have found cross-sectional evidence that a self-efficacy enhancing treatment group had greater weight loss than a comparison group. However, this effect was only apparent for those with an internal locus of control. Much stronger evidence comes from numerous prospective studies investigating the predictive powers of weight control self-efficacy on weight control. “Efficacy to resist the urge to overeat increases during the course of treatment (Glynn & Ruderman, 1986; Forster & Jeffrey, 1986). Expectations that seem more like outcome expectancies than efficacy expectancies (i.e., subjects’ confidence in reaching their goal weight, confidence in losing a certain amount of weight, or confidence in their ability to lose weight and maintain that loss) have been able to predict dropout from a weight control program (Mitchell & Stuart, 1984), as well as weight loss (Weinberger et al., 1984), and the maintenance of that weight loss (Blair et al., 1989). Most studies that use efficacy to resist the urge to eat or refrain from overeating have found these efficacy evaluations to be predictive of weight loss during the active phase of treatment (Glynn & Ruderman, 1986; Forster & Jeffrey, 1986). In addition, posttreatment efficacy evaluations have been related positively to maintenance of weight loss (Patsis & Hart, 1991; Rodin et al., 1988; DiClemente et al., 1995).

“Despite all the difficulties and differences in the assessment of self-efficacy related to eating behavior in weight control, the role that self-efficacy appears to play is quite similar to that in smoking cessation, where the assessments have been a bit more uniform. Efficacy evaluations appear to be useful and unique predictors of weight loss. Few constructs predict weight loss and maintenance of that loss in as consistent a fashion as self-efficacy focused on overeating behaviors (DiClemente et al., 1995).

Self-Efficacy and Low-Fat Diet

“There is substantial evidence that reducing saturated fat in the diet decreases the risk of coronary heart disease (CHD) in populations (Kromhout and Lezenne-Coulander, 1984; Kushi et al., 1985; Keys et al., 1986). Efforts to alter dietary habits through various programs have met with limited effectiveness (Advisory Board – IHHC, 1992). One reason for the limited success is the failure to fully understand the cognitive mediators of dietary change (Plotnikoff and Higginbotham, 1995) .One recent study by Plotnikoff and Higginbotham (1995) found significant positive association between self-efficacy for following a low-fat diet (dietary self-efficacy) and outcome measures related to low-fat diet. Future research is needed focusing specifically on dietary self-efficacy to determine whether substantial saturated fat reductions can be obtained by treatment programs developed to increase dietary self-efficacy.

Self-efficacy and Recovery from Heart Attack

Ewart and colleagues have studied the relationship between physical activity self-efficacy and recovery from heart attack. According to Ewart, 1992, “large numbers of heart attack survivors experience unnecessary distress and put themselves at significant medical risk due to excessive fear of physical activity.” Self-efficacy theory has improved their ability to identify and alleviate these inappropriate fears. Research reviewed by Ewart(1992) suggests that self-efficacy appraisals influence patient involvement in exercise regimens and mediate beneficial effects of exercise participation.” Furthermore, evidence is reviewed that self-efficacy predicts physical over-exertion and has called for the development of scales of self-efficacy to identify individuals who may be at risk of dangerous overexertion due to unrealistically optimistic appraisals of their physical capabilities (Ewart, 1992).

Self-efficacy and Physical Activity

Of course, physical activity is not only important to recovery from heart attack. Physical activity appears to decrease the risk of coronary artery disease. The United States Center for Disease Control reviewed existing observational studies and found a significant and graded relationship between physical activity and the risk of coronary artery disease (Powell et al., 1987; Littman, 1993). Exercise is widely recommended for health promotion and primary-risk reduction in people who have not developed symptoms of cardiovascular illness, and who are not inhibited by the anxieties patients experience after a heart attack (Ewart, 1995). However, relatively few people engage in regular exercise for a period of time to secure the benefits of moderate exercise to physical health (Dubbert, 1992). “The attrition rate for both clinical and community-based exercise programs can be as high as 50% within the first 3 to 6 months of participation (Brawley & Rogers, 1993; Dishman, 1988). Social-cognitive variables, including self-efficacy, seem to play a major role in this attrition.” Research suggests that self-efficacy expectancy, outcome expectancy, and outcome value are important in the initiation and maintenance of a variety of exercise programs (Brawley & Rogers, 1993; Brawley & Horne, 1988; Desharnais et al., 1986; Dzewaltowski et al., 1990; Garcia & King, 1991; McAuley, 1991, 1994; McAuley & Courneya, 1993; McAuley & Jacobson, 1991; Poag-Ducharme & Brawley, 1991a, 1991b; Rogers & Brawley, 1991a, 1991b). The relative influence of self-efficacy and outcome expectancy on exercise behavior has been shown to differ at different stages of exercise experience (Marcus et al., 1992; McAuley, 1991; McAuley & Jacobson, 1991; McAuley & Rowney, 1990; Poag-DuCharme & Brawley, 1993). Although initial experience with exercise may base their decision to try it largely upon their beliefs of the value of the benefits of exercise, this initial experience with exercise strongly influences self-efficacy (Ewart et al., 1983) which become the primary determinant of persistence (Maddux et al., 1995). Recently, studies have attempted to learn more about what types of self-efficacy best predict exercise behavior over time. Self-efficacy for the exercise components, self-efficacy for scheduling, and self-efficacy for overcoming barriers have been studied by Poag-DuCharme and Brawley (1993). The types of self-efficacy that predicted exercise intentions varied at different points in their 12-week community-based exercise program. This study and others (Poag-Charme, 1993; McAuley, 1992, 1993) suggest the need for further study concerning changes in the relationship between self-efficacy and exercise over time (Maddux et al., 1995).

Self-efficacy as a Component of Active Coping to Stress, and Resulting Enhanced Cardiovascular Reactivity

Stress, specifically model of job stress called “job strain,” has been shown in over a dozen epidemiological studies over the last decade to be a significant risk factor for CHD (Schnall et al., 1994; See our review of job strain). The concept of active coping is one model in which we think about the stress-illness relationship (Gerin et al., 1996). Active coping to stress enhances cardiovascular reactivity, elevating blood pressure and heart rate (Gerin et al., 1996). However, it is unclear which aspect of the process actually produces the elevations. A recent study by Gerin et al., 1996 has “concluded that self-efficacy for a particular task may be an integral part of the active coping process, indirectly affecting the blood pressure response by acting on the effort involved in the coping response.” Subjects engaged in a video game shape-matching task, who were preevaluated to have a high self-efficacy for this task, had greater blood pressure cardiovascular reactivity than subjects engaged in the same task who were preevaluated to have a low efficacy for this task.

Social determinants of Self-efficacy

There has been remarkably little research on the determinants of self-efficacy, particularly social class and job stress. Such factors might shape personality development in childhood. For example, certain parental behavior patterns (i.e., overly strict, critical and demanding of conformity) are more common in low SES households, and may be viewed as a reflection of the parents’ occupational and other life experiences, which are characterized by low control and insecurity (see Sennett &Cobb, 1973, The Hidden Injuries of Class; Rubin, 1976, Worlds of Pain: Life in the Working Class Family). Similarly, an adult’s experience, which might include stressful, low control jobs, may shape their personality development (Kohn and Schooler, 1982). The active motivated persistent personality style described in the beginning of this review as resulting from “self-efficacy” is quite similar to the hypothesized effects of active (high demand-high latitude) jobs on personality and coping in Karasek’s model (Karasek, 1979; 1981; Landsbergis et al., 1992). In the Cornell worksite blood pressure study, a three year increase in job decision latitude among men was associated with quitting smoking (Landsbergis et al., 1998). It is not known whether increased self-efficacy was a mediator in this causal pathway. Thus, research on the social determinants of personality measures believed to be associated with illness outcomes needs to be a major priority in future research.

Conclusions

Smoking cessation, a CVD risk factor, has been the most common cardiovascular health-related behavior that self-efficacy has been linked to. “The predictive ability and consistency of self-efficacy evaluations for smoking behavior have been impressive. Few constructs in the social sciences can boast such a record. In almost every case, efficacy evaluations, particularly abstinence efficacy evaluations, have been the most significant, or among the only significant, predictors of smoking cessation treatment outcome that emerged from studies that included a wide range of other predictors.” (DiClemente, 1986; DiClemente et al., 1995).

Numerous studies have also investigated the relationship self-efficacy has on weight control, since obesity is a well-established CVD risk factor. Despite all the difficulties and differences in the assessment of self-efficacy related to eating behavior in weight control, the role that self-efficacy appears to play is quite similar to that in smoking cessation, where the assessments have been a bit more uniform. Efficacy evaluations appear to be useful and unique predictors of weight loss. Few constructs predict weight loss and maintenance of that loss in as consistent a fashion as self-efficacy focused on overeating behaviors.” (DiClemente et al., 1995).

Self-efficacy has been shown to play a role in influencing other CVD risk factors, such as high-fat diet, physical inactivity, and high blood pressure (via active coping to stress). In regards to high-fat diet, future research is needed focusing specifically on dietary self-efficacy to determine whether substantial saturated fat reductions can be obtained by treatment programs developed to increase dietary self-efficacy.

Concerning physical inactivity, research suggests that self-efficacy expectancy, outcome expectancy, and outcome value are important in the initiation and maintenance of a variety of exercise programs. Self-efficacy for physical activity may become particularly important for those recovering from a heart attack. However, the links between self-efficacy and these CVD health-related behaviors have not been as thoroughly studied as for smoking cessation and weight control. Finally, concerning high blood pressure, it appears that self-efficacy for confronting mentally and physically vigorous psychosocial environmental stressors may be a component of active coping. Active coping to stress enhances cardiovascular reactivity, elevating blood pressure and heart rate (Gerin et al., 1996). High blood pressure is of course a major CVD risk factor. As for high-fat diet and physical activity, the link between self-efficacy and high blood pressure through active coping to stress has not been studied thoroughly enough. More research is needed investigating the role that self-efficacy plays in active coping, work-stress models (i.e., job strain, effort-reward and John Henryism), and as a possible risk factor for hypertension.

Further research is definitely needed to better understand how much self-efficacy influences each of these CVD health-related behaviors, and the mechanism of that change by further narrowing in on what tasks self-efficacy is particularly important for in affecting behavioral change. Lastly, very little is known about the determinants of self-efficacy. Research on the social determinants of personality measures believed to be associated with illness outcomes needs to be a major priority in future research.

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Locus of Control and Cardiovascular Health

Introduction- What is Locus of Control?

Originally developed within the framework of Rotter’s (1954) social learning theory, the locus of control construct refers to the degree to which an individual believes the occurrence of reinforcements is contingent on his or her own behavior. The factors involved with reinforcement expectancy are labeled “external” and “internal” control. In short, internal locus of control refers to the perception of positive or negative events as being a consequence of one’s own actions and thereby under one’s own personal control. In contrast, external locus of control refers to the perception of positive or negative events as being unrelated to one’s own behavior in certain situations and thereby beyond personal control. As a general principle, the locus of control variable may be thought of as affecting behavior as a function of expectancy and reinforcement within a specific situation (Carlise-Frank, 1991).

The following sections will review the evidence supporting links between locus of control and specific cardiovascular health-related behaviors. In addition, methods of assessment of locus of control will be discussed, as well as the current limitations of studies investigating the relationship between locus of control and cardiovascular health-related behavior.

How is Locus of Control Assessed in Health-Related Research?

Rotter’s Locus of Control Scale (Rotter, 1966), a generalized measure of internal vs. external locus of control, continues to be widely used to assess perceived control in health-related research (see reviews by Strickland, 1978; Wallston and Wallston, 1978). However, many health researchers have chosen to use more situation-specific, health-related locus of control measures in their investigations. The most widely used instrument of this sort is the Multidimensional Health Locus of Control (MHLC) Scale (Wallston et al., 1978). The MHLC Scale consists of two alternative forms (A and B) each of which contains 18 items. Each form, in turn, contains three six-item Likert scales which, in “normal healthy” populations are uncorrelated, or only slightly correlated, with one another (Wallston and Wallston, 1981). The Internal Health Locus of Control (IHLC) dimension assesses the degree to which one believes one’s health status is influenced by one’s own behavior. People who score high on the IHLC are said to have a sense of responsibility for their own health (Wallston and Wallston, 1982). PHLC measures the belief that powerful other people (one’s family, friends or health-care providers) control one’s health. Lastly, CHLC assesses perceived non-control of health, or the belief that fate, luck, or chance determines one’s health status. (Wallston, 1989)

Another approach to measuring locus of control are “Sphere-specific measures of perceived control” developed by Delroy Paulhus (1983). Paulhus’ questionnaire has a total of 30 items, broken down into 3 subscales called “personal efficacy”, “interpersonal control”, and “socio-political control”. The internal consistency reliabilities for the scales are typically .75-.80, higher than those obtained for the Potter scale on the same samples. Pauljus argues convincingly that the construct of locus of control is multidimensional, and that therefore a scale (such as his) that measures perceived control in different domains of life is a better measure than Rotter’s single scale.

Locus of Control and Cardiovascular Health-Related Behaviors

The literature concerning research on the relationship between locus of control and health-facilitating behavior as a whole points toward internal locus of control as a mediating factor of actions taken to prevent health problems (See Lefcourt and Davidson-Katz, 1991; Carlise-Frank, 1991). Physical activity is one of these health-facilitating behaviors whose relationship to locus of control has been studied. Physical activity appears to decrease the risk of coronary artery disease. The United States Center for Disease Control reviewed existing observational studies and found a significant and graded relationship between physical activity and the risk of coronary artery disease

(Powell et al., 1987; Littman, 1993). Exercise is widely recommended for health promotion and primary-risk reduction in people who have not developed symptoms of cardiovascular illness (Ewart, 1995). However, relatively few people engage in regular exercise for a period of time to secure the benefits of moderate exercise to physical health (Duppert, 1992). The attrition rate for both clinical and community-based exercise programs can be as high as 50% within the first 3 to 6 months of participation (Brawley & Rogers, 1993; Dishman, 1988). Sonstroem and Walker (1973) studied locus of control and attitudes toward physical fitness and found that internals had more favorable attitudes towards physical activity, obtained significantly better fitness scores, and engaged in greater amounts of voluntary physical exercise than did externals (Carlise-Frank, 1991). It must be recognized, however, that these authors used a theoretical and methodological approach that supported a generalized expectancy for control beliefs. Validity of studies investigating the relationship between locus of control and health-related behaviors have been questioned due to the fact that an individual may have a tendency towards internality in many life areas, but have an external belief with regard to the particular health-related behavior in question. Please see the end of this section for further discussion of this methodological problem.

Like the research on health-facilitating behaviors, research on individuals who attempt to overcome health-damaging behaviors has also shown internals are often better off than externals (Coan, 1973; James et al., 1965; Mlott and Mlott, 1975; Naditch, 1975; Pryer and Distefano, 1977; Williams, 1967). Unlike research on health-facilitating behaviors, however, results of research on overcoming health-damaging behaviors has been far less consistent in favoring internality. In this area, results have shown that externals and internals are equally successful in overcoming their deleterious health behaviors when placed in treatment programs consistent with their personal control beliefs (Carlise-Frank, 1991).

Being overweight is a significant risk factor for the development of hypertension and coronary heart disease. In studies concerning weight reduction as a function of locus of control, Balch and Ross (1975) found internal beliefs to be predictive of success and completion of an overweight treatment program. (Carlise-Frank, 1991) (Wallston et al.1976), using the Health Locus of Control scale, found internals in weight reduction programs were more satisfied with the results of their treatment than externals, but these results failed to reach significance. “Some researchers have been unable to relate the internal/external (I-E) variable to weight reduction (Bellack et al., 1974; Manno and Marston, 1972; Tobias and MacDonalad, 1977).” (Carlise-Frank, 1991).

Cigarette smoking has also been identified as a risk factor for cardiovascular disease (Schnall et al., 1994). Furthermore, studies indicate that patients with coronary artery disease who stop smoking have a lower mortality from all causes of death and a less frequent occurrence of myocardial infarction in particular than those who continue to smoke (Vlieststra et al., 1986). Results from research on stopping smoking have shown that internals are far more likely than externals to be affected by the Surgeon General’s report and are more likely to stop smoking (James et al., 1965). In another study, internals were found to profit more from a stop smoking program using a saturation technique than externals (Best and Steffy, 1975). Though some researchers have reported that internals are more likely to reduce their smoking rate than externals (Best and Steffy, 1971; Steffy et al., 1970), others have failed to demonstrate a relationship between locus of control and control of smoking behavior. In these studies, I-E scores have failed to predict treatment success, suggesting that locus of control data have little predictive value in smoking cessation (Berstein, 1970; Best and Steffy, 1971; Danaher, 1977; Keutzer, 1968; Carlise-Frank, 1991).

Perhaps one of the most important reasons for the discrepancy of studies investigating the relationship between locus of control and cardiovascular health-related behaviors is the approach used in determining whether individuals should be placed in internal or external treatment groups (Carlise-Frank, 1991). “The most commonly used measure of subjects’ control beliefs has been a generalized unidimensional scale of overall expectancy. If an individual’s belief system pointed towards internality, then he or she would be placed in a treatment regime consistent with that belief. However, an individual may have a tendency towards internality in many life areas but have an external belief with regard to health or the particular health-related behavior in question. It is unlikely that a generalized unidimensional scale would be able to detect such distinctions. If such individuals were placed in treatment groups congruent with internal beliefs, success might be marginal at best. From this perspective, internally oriented individuals who have learned externality or passive acceptance towards their health-damaging behavior would not be expected to have a high success rate in such programs.”(Carlise-Frank, 1991). This would explain the failure by many researchers to demonstrate a relationship between locus of control as a predictor for overcoming the cardiovascular health-damaging behaviors previously discussed (Carlise-Frank, 1991).

Diagnosis of Myocardial Infarction, Recovery from Myocardial Infarction, and Locus of Control

Another area of investigation concerning locus of control and cardiovascular health involves how locus of control influences health-related behavior once myocardial infarction has already begun. Early detection of acute myocardial infarction(AMI) reduces myocardial infarction morbidity (Genton and Sobel, 1987), yet up to one third of AMIs are not recognized (Roseman, 1954; Lindberg et al., 1960; Roseman et al., 1967; Kannel and Abbott, 1984; Kannel et al., 1990). Unrecognized AMI includes completely asymptomatic events and those with a typical symptoms, so that neither the patient nor physician entertains the diagnosis of AMI (Bertolet and Hill, 1989). In a recent study by Theisen et al.(1995), patients with unrecognized AMI scored higher on the CHLC (“chance” locus of control) than patients with diagnosed AMI. Unrecognized AMI is known to result from a lack of symptom experience and/or avoidance of medical care when symptoms are experienced. In analysis of their results, Theisen et al.(1995) hypothesize that “chance” locus of control, the belief in chance or fate as determining health, may inhibit treatment-seeking for AMI. More research is needed to rigorously test this hypothesis (Theisen et al., 1995).

The role of locus of control in recovery from AMI has also been explored in a study by Cromwell et al. (1977). “Patients who were classified as internal from Rotter’s Internal-External Locus of Control Scale (Rotter, 1966) were rated by the professional staff as being more cooperative and less depressed than were externals throughout their stay in the intensive care unit. On three highly intercorrelated physiological measures (sedimentation rates, serum glutamic oxaloacetic transaminase levels, and lactate dehydrogenase levels), externals were found to have worse prognoses than internals. Additionally, externals had higher peak temperatures during intensive care and remained longer in the unit, and in the hospital, than did internals. One tempting hypothesis is that internals simply behave in a manner that does not aggravate their fragile conditions. Rather than becoming distressed, with all of the personal and physiological consequences of distress, internals showed greater cooperation and less depression, possibly reflecting their more active participation and greater hope in the struggle for survival. It is plausible that responses to life-endangering threats such as myocardial infarction may be at least partially determined by personality characteristics such as locus of control.”(Lefcourt and Davidson-Katz, 1991) However when a measure of control beliefs made up of items relating specifically to perceived control over recovery from heart disease was used, no support was found that perceived control is important for psychological adjustment among cardiac patients (Flowers, 1994). Further research is needed before an important evaluation of the hypothesis that an internal locus of control leads to increased likelihood of behavior favoring recovery from AMI.

Locus of Control and Job Strain

Karasek (1979) has defined “job strain” as work in jobs with high psychological demands and low control. In more than a dozen epidemiological studies over the last decade, occupational stress researchers have implicated job strain as a risk factor for heart disease (Schnall et al., 1994). Although the mechanism by which the stress of job strain influences development of CHD is unknown, previous findings suggest that job strain may be related to elevations of blood pressure at work (Schnall et al., 1990, Van Egeren, 1992). High blood pressure has long been known to be a marker for individuals at high risk for developing CHD, and therefore is one possible mechanism by which job strain might exert its deterious influences on the heart.

One basic question yet to be answered by the job strain model “relates to the issue of objective versus subjective control. Clearly, the job strain model considers control as an objective characteristic of the work situation. However, cognitive and affective responses of the workers to these characteristics vary considerably according to their individual patterns of appraisal and coping (Lazarus and Folkman, 1984). Generalized control beliefs have been found to moderate the effects of objective job conditions on well-being (Spector, 1987). Furthermore, through regression analysis, Hendrix (1989) found locus of control to be a statistically significant predictor of job stress (Beta=.39; p<.001). These findings (as well as findings where individual coping characteristics such as Type A behavior, hostility, or lack of hardiness were associated with increased ischemic heart disease) call for a conceptual clarification of the relationship between control-limiting job conditions and those personal characteristics (particularly locus of control) which influence the perception of control (Siegrist et al., 1990). One possible relationship is interaction between job conditions and personality characteristics. For example, Parkes (1991) found a significant three-way interaction between job demands, job decision latitude, and Paulhus’ locus of control scale, in predicting affective distress and anxiety. For externals, demands and latitude combined intractively to predict outcome (consistent with Karasek’s model), whereas for internals, additive findings (main effects for demands and latitude) were obtained.

Social determinants of Locus of Control

There has been remarkably little research on the determinants of locus of control, particularly social class and job control. Such factors might shape personality development in childhood. For example, certain parental behavior patterns (i.e., overly strict, critical and demanding of conformity) are more common in low SES households, and may be viewed as a reflection of the parents’ occupational and other life experiences, which are characterized by low control and insecurity (Sennett and Cobb, 1973; Rubin, 1976). Similarly, an adult’s experience, which might include stressful, low control jobs, may shape their personality development (Kohn and Schooler, 1982). For example, Lefcourt (1982, p. 31) pointed out that locus of control is “positively associated with access to opportunity”

In a study of 2174 Dutch men and women aged 25-74 (Bosma et al., 1998), subjects with higher chidlhood socioeconomic status (SES) had much higher levels of “perceived control” (locus of control) in adulthood. In addition, “perceived control” appeared to be an important mediatorof the association of SES with later mortality. The association between SES and mortality (RR=2.6) was reduced substantially (RR=1.8_ agter controlling for levels of “perceived control”. Thus, research on the social determinants of personality measures believed to be associated with illness outcomes needs to be a major priority in future research.

Conclusions

Validity of studies investigating the relationship between locus of control and health-related behaviors have been questioned due to the fact that an individual may have a tendency to be internal in many life areas, but have an external belief with regard to the particular health-related behavior in question. Valid locus of control measures more specific to the particular behavior being studied need to be developed. However, results using Rotter’s Locus of Control Scale and the more health behavior-related MHLC, have in general found that internals tend to behave in a more healthy way in regardseveral important cardiovascular health-related behaviors. Specifically,one study has shown internals to have better attitudes toward physical fitness, better physical fitness scores, and engaged in greater amounts of voluntary physical exercise (Sonstroem and Walker, 1973). Furthermore, there have also been findings suggesting that an internal locus of control may be beneficial in weight loss among the overweight, and successful smoking cessation. It should be noted however that there have been contradictory findings regarding the link between locus of control and these cardiovascular health-damaging behaviors. Another area of investigation concerning locus of control and cardiovascular health involves how locus of control influences health-related behavior once myocardial infarction has already begun. Patients with unrecognized AMI in one study were shown to score higher on the CHLC than patients with diagnosed AMI (Thiesen et al., 1995). This had led to the hypothesis that “chance” locus of control may inhibit treatment-seeking for AMI. Secondly, work by Cromwell et al. (1977) led to their hypothesis that an internal locus of control may lead to increased likelihood of behavior favoring recovery from AMI. There has been little further work investigating either of the aforementioned hypotheses. More research is definitely needed in these areas.

Locus of control may also be important in studies of job strain, implicated as a risk factor for heart disease by over a dozen epidemiological studies over the last decade. The current job strain model considers control as an objective characteristic of the work situation. Locus of control and other measures of generalized control beliefs have been shown to moderate the effects of objective job conditions on well being and as predictors of job stress. These findings call for future studies investigating the relationship between control-limiting job conditions and personal characteristics, such as locus of control, which influence the perception of control. Such work may lead to a better understanding of how the perception of control relates to job stress-related cardiovascular disease via the cardiovascular risk factor of job strain.

Lastly, there has been very little research on the determinants of locus of control. Research on the social determinants of personality measures believed to be associated with illness outcomes needs to be a major priority in future research.

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