Effects of Occupational Stress Management Intervention ... JOHP... · Effects of Occupational Stress Management Intervention Programs: A Meta-Analysis Katherine M. Richardson and

Effects of Occupational Stress Management Intervention Programs:A Meta-Analysis

Katherine M. Richardson and Hannah R. RothsteinBaruch College, City University of New York

A meta-analysis was conducted to determine the effectiveness of stress management interventionsin occupational settings. Thirty-six experimental studies were included, representing 55 interven-tions. Total sample size was 2,847. Of the participants, 59% were female, mean age was 35.4, andaverage length of intervention was 7.4 weeks. The overall weighted effect size (Cohen’s d) for allstudies was 0.526 (95% confidence interval � 0.364, 0.687), a significant medium to large effect.Interventions were coded as cognitive–behavioral, relaxation, organizational, multimodal, oralternative. Analyses based on these subgroups suggested that intervention type played a mod-erating role. Cognitive–behavioral programs consistently produced larger effects than other typesof interventions, but if additional treatment components were added the effect was reduced.Within the sample of studies, relaxation interventions were most frequently used, and organiza-tional interventions continued to be scarce. Effects were based mainly on psychological outcomevariables, as opposed to physiological or organizational measures. The examination of additionalmoderators such as treatment length, outcome variable, and occupation did not reveal significantvariations in effect size by intervention type.

Keywords: stress management, meta-analysis, employee intervention

Employee stress has increasingly become a con-cern for many organizations. To paraphrase the “fa-ther of stress,” Hans Selye, stress is an unavoidableconsequence of life, and therefore an unavoidableconsequence of organizations. Americans are work-ing longer and harder, and job stress continues toincrease. The average work year for prime-age work-ing couples in the United States increased by nearly700 hours in the past two decades (Murphy & Sauter,2003; U.S. Department of Labor, 1999). From 1997to 2001, the number of workers calling in sick be-cause of stress tripled. The American Institute ofStress reported that stress is a major factor in up to80% of all work-related injuries and 40% of work-place turnovers (Atkinson, 2004). This is not solelyan American phenomenon. The Confederation ofBritish Industry reported stress as the second highestcause of absenteeism among nonmanual workers inthe United Kingdom, and the European Foundationfor the Improvement of Living and Working Condi-tions reported that stress affects a third of the Euro-

pean working population (Giga, Cooper, & Faragher,2003). In Australia, most states report an increasingnumber of annual workers’ compensation claimsresulting from workplace stress (Caulfield, Chang,Dollard, & Elshaug, 2004). Organizations provide amajor portion of the total stress experienced by aperson as a result of the amount of time spent on thejob, the demands for performance, and the interactionwith others in the workplace (DeFrank & Cooper,1987).

Although it is not possible to eliminate stress en-tirely, people can learn to manage it. Many organi-zations have adopted stress management training pro-grams to try and reduce the stress levels of theirworkforce. A stress management intervention (SMI)is any activity or program initiated by an organizationthat focuses on reducing the presence of work-relatedstressors or on assisting individuals to minimize thenegative outcomes of exposure to these stressors(Ivancevich, Matteson, Freedman, & Phillips, 1990).Interest in strategies to reduce stress at work hasincreased steadily since the 1970s. According to theU.S. Department of Health and Human Services,national surveys conducted in 1985, 1992, and 1999found the prevalence of stress management and coun-seling programs among private-sector worksites inthose years was 27%, 37%, and 48%, respectively(Nigam, Murphy, & Swanson, 2003). The popularity

Katherine M. Richardson and Hannah R. Rothstein, De-partment of Management, Zicklin School of Business, Ba-ruch College, City University of New York.

Correspondence concerning this article should be addressedto Katherine M. Richardson, Baruch College, City Universityof New York, One Bernard Baruch Way, New York, NY10010. E-mail: [email protected]

Journal of Occupational Health Psychology2008, Vol. 13, No. 1, 69–93

Copyright 2008 by the American Psychological Association1076-8998/08/$12.00 DOI: 10.1037/1076-8998.13.1.69

69

of worksite stress management programs has grownsignificantly abroad as well as in the United States.

Job Stress and Interventions

Newman and Beehr (1979, p.1) defined job stressas “a situation wherein job-related factors interactwith the worker to change his or her psychologicaland/or physiological condition such that the person isforced to deviate from normal functioning.” Implicitin this definition is the belief that work-related factorsare a cause of stress and that the individual outcomesmay be psychological, physiological, or some com-bination of these. A SMI may attempt to change thesework-related factors, assist employees in minimizingthe negative effects of these stressors, or both.Ivancevich et al. (1990) developed a conceptualframework for the design, implementation, and eval-uation of SMIs. According to the model, interven-tions can target three different points in the stresscycle: (a) the intensity of stressors in the workplace,(b) the employee’s appraisal of stressful situations, or(c) the employee’s ability to cope with the outcomes.The components of actual SMIs vary widely, encom-passing a broad array of treatments that may focus onthe individual, the organization, or some combination(DeFrank & Cooper, 1987; Giga, Noblet, Faragher,& Cooper, 2003).

Interventions may be classified as primary, sec-ondary, or tertiary. Primary interventions attempt toalter the sources of stress at work (Murphy & Sauter,2003). Examples of primary prevention programsinclude redesigning jobs to modify workplace stres-sors (cf. Bond & Bunce, 2000), increasing workers’decision-making authority (cf. Jackson, 1983), orproviding coworker support groups (cf. Carson et al.,1999; Cecil & Forman, 1990; Kolbell, 1995). Incontrast, secondary interventions attempt to reducethe severity of stress symptoms before they lead toserious health problems (Murphy & Sauter, 2003).Tertiary interventions—such as employee assistanceprograms—are designed to treat the employee’shealth condition via free and confidential access toqualified mental health professionals (Arthur, 2000).The most common SMIs are secondary preventionprograms aimed at the individual and involve instruc-tion in techniques to manage and cope with stress(Giga, Cooper, & Faragher et al., 2003). Examplesare cognitive–behavioral skills training, meditation,relaxation, deep breathing, exercise, journaling, timemanagement, and goal setting.

Cognitive–behavioral interventions are designedto educate employees about the role of their thoughts

and emotions in managing stressful events and toprovide them with the skills to modify their thoughtsto facilitate adaptive coping (cf. Bond & Bunce,2000). These interventions are intended to changeindividuals’ appraisal of stressful situations and theirresponses to them. For example, employees aretaught to become aware of negative thoughts or irra-tional beliefs and to substitute positive or rationalideas (Bellarosa & Chen, 1997).

Meditation, relaxation, and deep-breathing inter-ventions are designed to enable employees to reduceadverse reactions to stresses by bringing about aphysical and/or mental state that is the physiologicalopposite of stress (cf. Benson, 1975). Typically, inmeditation interventions, the employee is taught tofocus on a single object or an idea and to keep allother thoughts from his or her mind, although someprograms teach employees to observe everything thatgoes through their mind without getting involvedwith or attached to them. Meditation interventionsoften also include relaxation therapy and deep breath-ing exercises. Relaxation therapy focuses on the con-scious and controlled release of muscle tension. Deepbreathing exercises focus on increasing the intake ofoxygen and the release of carbon dioxide, althoughmuscle and mental relaxation is often an additionalgoal of slowing and deepening the breath.

Exercise programs generally focus on providing aphysical release from the tension that builds up instressful situations, increasing endorphin production,or both, although some have the goal of focusing theemployee’s attention on physical activity (rather thanon the stressors) or providing an outlet for anger orhostility (cf. Bruning & Frew, 1987).

Journaling interventions require the employee tokeep a journal, log, or diary of the stressful events inhis or her life (cf. Alford, Malouff, & Osland, 2005).The journal is used as a means of assisting the em-ployee to monitor stress levels, to identify the recur-ring causes of stress, and to note his or her reactions.Journals are also used to formulate action plans formanaging stress.

Time management and goal-setting interventionsare designed to help people manage their time better,both on and off the job. Employees often operateunder time pressure and are required to work onmultiple tasks simultaneously. Working under suchconditions can be particularly stressful. Time man-agement interventions provide skills training in theareas of goal setting, scheduling and prioritizingtasks, self-monitoring, problem solving, delegating,negotiating, and conflict resolution (cf. Bruning &Frew, 1987; N. C. Higgins, 1986).

70 RICHARDSON AND ROTHSTEIN

Electromyogram (EMG) biofeedback training pro-vides participants with continuous feedback of mus-cle tension levels (cf. Murphy, 1984b). The objectiveis to consciously trigger the relaxation response andcontrol involuntary stress responses from the auto-nomic nervous system. Through the use of electronicfeedback measuring forehead muscle tension or handtemperature, patients receive feedback via audibletones or visual graphs on a computer screen. Duringthe process they learn to monitor their physiologicalarousal levels and physically relax their bodies, ac-tually changing their heart rate, brain waves, musclecontractions, and more.

SMIs may focus on any one particular strategyoutlined above, such as relaxation training (cf. Fiedler,Vivona-Vaughan, & Gochfeld, 1989; R. K. Peters,Benson, & Porter, 1977), or combine multiple com-ponents to create a comprehensive training regimenthat may include any of the following: cognitive–behavioral skills, meditation, assertiveness, socialsupport, and so forth (cf. Bruning & Frew, 1986,1987; de Jong & Emmelkamp, 2000; Zolnierczyk-Zreda, 2002). A trained instructor or counselor ineither small group or one-on-one sessions generallyteaches the methods, but techniques are sometimesself-taught with the aid of books and tapes (cf.Aderman & Tecklenberg, 1983; Murphy, 1984b;Vaughn, Cheatwood, Sirles, & Brown, 1989) andincreasingly via computers (cf. Hoke, 2003;Shimazu, Kawakami, Irimajiri, Sakamoto, & Amano,2005). Treatment programs are usually administeredover several weeks and may take place at the work-site or at an outside location. Depending on thetreatment method used, session length may vary from15-min breaks to all-day seminars.

Which Interventions Are Most Effective?

The effectiveness of SMIs is measured in a varietyof ways. Researchers may assess outcomes at theorganizational level (e.g., absenteeism or productiv-ity) or at the individual level, using psychological(e.g., stress, anxiety, or depression) or physiological(e.g., blood pressure or weight) measures. Given thewide array of stress management programs and out-come variables, there has been much debate in theliterature as to which interventions, if any, are mosteffective (Briner & Reynolds, 1999; Bunce &Stephenson, 2000; Caulfield et al., 2004; DeFrank &Cooper, 1987; Giga, Noblet, Faragher, & Cooper, 2003;Ivancevich et al., 1990; Mimura & Griffiths, 2002;Murphy, 1984a; Newman & Beehr, 1979; Nicholson,Duncan, Hawkins, Belcastro, & Gold, 1988; van der

Hek & Plomp, 1997). Some critics have claimed thatstudies in this area are inconclusive and based largelyon anecdotes, testimonials, and methodologically weakresearch (Briner & Reynolds, 1999; Ivancevich et al.,1990).

Newman and Beehr (1979) were among the firstresearchers to perform a comprehensive narrativereview of personal and organizational strategies forhandling job stress, examining both medical and psy-chological literature. They reported a significant lackof empirical research in the domain and challengedindustrial/organizational psychologists to bring theirexperience to the field of job stress–employee health(Newman & Beehr, 1979). During the 1980s, severalresearchers reviewed the SMI literature (DeFrank &Cooper, 1987; Murphy, 1984a; Nicholson et al.,1988). Murphy (1984a) performed a narrative reviewof 13 studies and concluded that they generally dem-onstrated acceptable positive effects, but noted thatthe “reports varied significantly in terms of the ade-quacy of the methodology used” (p. 2). DeFrank andCooper (1987) criticized the methodological qualityof the studies reviewed by Murphy. Three of the 13studies from that review did not use control groups,and the majority had small sample sizes with lowpower and short follow-up time frames, making itdifficult to assess the maintenance of gains.

Nicholson et al. (1988) expanded on Murphy’s(1984a) work and identified 62 published evaluationsof stress management programs from the medicine,public health, psychology, and education fields.These included case studies, preexperiments, quasi-experiments, and experimental studies (Nicholson etal., 1988). Of the 62 studies examined, only 18 pro-vided adequate data to quantitatively summarize theresults. Within these 18 studies, the average improve-ment in the treatment groups was equal to threequarters of one standard deviation in the controlgroup scores, yielding “mildly encouraging results”(Nicholson et al., 1988). This translates into a Cohen’sd of 0.75, which approaches a large effect (J. Cohen,1988). However, only a third of the studies in Nicholsonet al.’s review included participants from occupationalsettings. The remainder consisted of participants from avariety of groups, including schoolchildren, juveniledelinquents, college students, epilepsy patients, hyper-tension patients, and substance abusers.

Over the past two decades, intervention studies inoccupational settings have proliferated, and research-ers have conducted more focused reviews to examinetheir effectiveness (Briner & Reynolds, 1999; Bunce& Stephenson, 2000; Caulfield et al., 2004; Giga, No-blet, Faragher, & Cooper, 2003; Mimura & Griffiths,

71EFFECTS OF STRESS MANAGEMENT INTERVENTIONS

2002; van der Hek & Plomp, 1997). Results havecontinued to be mixed. Briner and Reynolds con-ducted a narrative review of organization-level inter-ventions (e.g., job redesign) and concluded that theyoften have little or no effect. Bunce andStephenson examined interventions that focused onindividual-level outcomes and reviewed 27 studies,assessing their levels of descriptive information andstatistical power. They reported that “at present thequality of reporting and research design is such that itis difficult to form an impression of what type of SMIis appropriate to whom, and in what circumstances”(p. 198).

More recent narrative reviews have focused onparticular job occupations, such as the nursing pro-fession (Mimura & Griffiths, 2002) or mental healthprofessionals (Edwards, Hannigan, Fothergill, &Burnard, 2002), or specific geographic regions,such as the United Kingdom (Giga, Noblet, Faragher,& Cooper, 2003) and Australia (Caulfield et al.,2004). A problem with such focused reviews, how-ever, is that they result in a small number of studies,and each study may compare multiple interventionmethods or outcomes. This makes it difficult to ob-tain precise estimates of the relative effectiveness ofdifferent interventions, or to assess generalizability ofresults.

The accumulation of stress management studiesacross a wide variety of occupational and geographicsettings, assessing a multitude of intervention tactics,calls for a systematic review. In behavioral and med-ical research, as well as in other fields, meta-analysishas become the widely accepted technique for assess-ing the effectiveness of interventions. It has replacedthe traditional narrative assessment of a body ofresearch as a better way to accumulate data andsynthesize them into generalizable knowledge (Eden,2002). The primary goals of meta-analysis are toderive the best estimate of the population effect sizeand to determine whether there are any sources ofvariance around this effect (Rothstein, McDaniel, &Borenstein, 2002).

A study by van der Klink, Blonk, Schene, and vanDijk (2001) used meta-analytic techniques to exam-ine the effectiveness of worksite stress interventions.The researchers meta-analyzed data from 48 inter-ventions published in 45 articles between 1977 and1996. A small but significant overall effect size wasfound (d � 0.34). When effects were broken down byintervention type, cognitive–behavioral interventionsachieved the largest effect size (d � 0.68), followedby multimodal (d � 0.51), relaxation (d � 0.35), andorganization-focused programs (d � 0.08). The

present study seeks to update the van der Klink et al.meta-analysis. We believe that a new meta-analysis isappropriate for three reasons. First, although thevan der Klink et al. review was published in 2001, itincludes studies published only through 1996, and aconsiderable number of new, methodologically rig-orous studies have been conducted since that time.There is a growing consensus that meta-analyses andsystematic reviews, particularly those with healthpolicy or practice implications, should be updatedwhenever a sizable number of new studies appear (cf.Chalmers & Haynes, 1994; Clark, Donovan, &Schoettker, 2006; J. P. T. Higgins & Green, 2005).This review expands the eligibility timeframethrough early 2006.

Second, van der Klink et al. (2001) included stud-ies of varying study designs and methodologicalquality. Nine of their included studies used quasi-experimental designs, and others did not include ano-treatment control or comparison group. In addi-tion, the van der Klink et al. meta-analysis includedseven randomized experiments that did not reportsufficient statistics to calculate an effect size or thatreported results of significant outcomes and not oth-ers. They did this by making assumptions about theprobability values in these studies. As one of theconsistent criticisms of studies of SMIs is that theyare methodologically weak, our goal was to focusonly on studies with methodologically strong de-signs. We therefore included only those interventionsthat were evaluated using a true experimental design,with random assignment of participants to treatmentand control groups. This reduces the threat of selec-tion bias and increases the internal validity of theincluded studies (Cook & Campbell, 1976) and,therefore, the validity of the meta-analytic results.

Finally, the van der Klink et al. (2001) review wasbased entirely on published journal articles and ex-cluded dissertations, conference proceedings, bookchapters, and the like. This exclusion of so-called“gray literature” has been shown to increase thethreat that publication bias (a tendency toward prep-aration, submission, and publication of research find-ings that is based on the nature and direction of theresearch results rather than on the quality of theresearch; Dickersin, 2005) will affect the meta-analytic results. Publication bias affects the degree towhich published literature is representative of all theavailable scientific evidence; when the research thatis readily available differs in its results from theresults of all the research that has been done in anarea, we are in danger of drawing the wrong conclu-sion about that body of research (Rothstein, Sutton,


& Borenstein, 2005). In order to minimize the threatof publication bias, the current meta-analysis in-cluded experimental studies from both published andunpublished sources.

Our meta-analysis had two main goals. First, it wasintended to bring together and synthesize experimen-tal studies of SMIs that have been conducted (andreported) in a variety of disciplines (e.g., education,health care, organizational studies, and psychology)to identify what works, how well it works, and whereor for whom it works. Second, we hoped to use ourmeta-analytic results to identify areas in the stressmanagement literature where additional primarystudies are needed.

To summarize, we intended our systematic reviewto improve on the van der Klink et al. (2001) meta-analysis by drawing from an additional decade ofstudies, by including only randomized experimentswith sufficient statistical data to compute effect sizeswithout making additional assumptions about proba-bility values, and by incorporating a more compre-hensive literature search strategy. Rather than ex-clude the seven randomized experiments from thevan der Klink et al. study for which they inferred pvalues, we performed a sensitivity analysis using theeffect sizes for these studies that were imputed byvan der Klink et al. to determine whether their inclu-sion changes our results. Our goals are to synthesizeresearch from a variety of disciplines to assess whathas been learned and also to identify areas in whichadditional primary studies are needed.

Method

Literature Search

Studies that assessed the effectiveness of a work-site SMI were collected from a variety of sources.Because our intent was to build on the van der Klinket al. (2001) meta-analysis, we began by obtaining all45 studies used in that review. Second, we conductedan electronic search of six databases: AcademicSearch Premier, British Library Direct, DissertationsAbstracts, ERIC, ProQuest ABI Inform Global, andPsycARTICLES. These databases were chosen toobtain studies from different countries in a broadrange of research fields, including social sciences,health care, and education. In addition, several ofthese databases include both published and unpub-lished studies. For the Academic Search Premier,British Library Direct, ERIC, and PsycARTICLESdatabases, we entered the following search terms onthree lines: employee or work or management, AND

stress or wellness, AND program* or intervention orprevention. This same procedure was followed forthe Dissertations Abstract database, but it yielded noresults. We therefore changed the search criteria totwo lines: worksite and stress and management, ANDprogram or intervention or prevention. For the Pro-Quest ABI Inform Global database, the same searchterms were used but were entered on one line withclassification codes, as follows: SU(employee orwork or management) AND ((stress or wellness) w/2(program* or intervention or prevention)) ANDCC(9130 or 5400). The classification codes 9130 and5400 indicate experimental and theoretical work,respectively. These electronic searches yielded942 documents (Academic Search Premier � 377,British Library Direct � 255, ERIC � 122,PsycARTICLES � 99, Dissertation Abstracts �31, and Proquest ABI Inform Global � 58).

Third, we performed a network search and e-mailed colleagues knowledgeable in the field to see ifthey recommended any studies. We also attended theAmerican Psychological Association/National Insti-tute for Occupational Safety and Health Work,Stress, and Health 2006 conference and reviewed theconference proceedings. Fourth, we performed asnowball search and reviewed the reference list ofeach article obtained to identify additional citationsbeyond the electronic search. Finally, we searchedprivate and government-sponsored Web sites devotedto stress research to locate additional unpublishedliterature, including those for the American Institutefor Stress (www.stress.org), the Canadian Instituteof Stress (www.stresscanada.org), and the NationalInstitute for Occupational Health and Safety(www.cdc.gov/niosh).

Criteria for Inclusion

A study had to meet the following criteria to beincluded in the meta-analysis: (a) be an experimentalevaluation of a primary or secondary SMI (i.e., em-ployee assistance programs were excluded); (b) in-clude participants from the working population (i.e.,studies involving students were excluded) who arenot already diagnosed as having a major psychiatricdisorder (e.g., depression or posttraumatic stress) orstress-related somatic disorder (e.g., hypertension);(c) use random assignment to treatment and controlconditions; (d) report sample sizes, means, and stan-dard deviations for both treatment and a no-treatmentor waiting-list control group; if means and standarddeviations were not reported, some other type ofstatistic that could be converted into a standardized


mean effect size (Cohen’s d) was necessary; and (e)be written in English after 1976. This date was cho-sen because it is the year the APA Task Force onHealth Research published a report that exhortedpsychologists, including industrial/organizationalpsychologists, to take a role in examining the healthproblems of Americans (Beehr & Newman, 1978).

Among the 45 articles used in the van der Klink etal. (2001) meta-analysis, 19 met the inclusion criteriaoutlined above and were included in our study. Theremaining 26 articles were excluded for the followingreasons: Nine used a quasi-experimental design with-out random assignment, 8 did not include a no-treatment comparison group, 7 did not report suffi-cient statistics to calculate an effect size, 1 used astudent sample, and 1 did not include outcome vari-ables related to stress or strain. We reviewed theabstracts of the 942 articles identified in the elec-tronic search online to determine whether to obtainthe studies for a full text review. Most studies wereexcluded on initial abstract review because theylacked a control group, did not include appropriateparticipants (e.g., used students or patients with clin-ically diagnosed disorders), assessed employee atti-tudes about interventions rather than the behavioraleffects of the interventions, or had already been iden-tified via the van der Klink et al. study. In total, 50experimental studies were obtained for a full textreview. Of these, 37 were excluded because theywere quasi-experimental (17), did not use a controlgroup (9), used a student or patient sample (7), or didnot include the appropriate statistics (4). Thirteenstudies met all the inclusion criteria and were in-cluded in the meta-analysis (9 peer-reviewed journalarticles and 4 unpublished dissertations). In addition,19 from the van der Klink et al. meta-analysis wereincluded. During this process, we identified 19 othernonempirical review articles and also obtained themto examine the reference lists for additional studies.

The network search resulted in four usable studies(one journal article, two book chapters, and one un-published dissertation). The snowball search resultedin 24 additional documents for review, and 2 of thesewere used in the study. The searches on the stresswebsites yielded no usable studies. In total, 38 arti-cles were included in the current meta-analysis, rep-resenting 36 separate studies and 55 interventions.

Coding Procedure

We coded the reports at five levels: study, treat-ment–control contrast, sample, outcome, and effectsize. Study-level coding recorded the article’s full

citation, publication type, number of treatment–control contrasts, and source of article (e.g., data-base). The treatment–control contrast level was cre-ated because several of the studies evaluated morethan one type of treatment. Although some of thesewere totally independent evaluations, some had mul-tiple treatment groups (each with nonoverlappingparticipants) that were compared with a single con-trol group. We considered each of these treatment–control contrasts as a separate comparison for codingpurposes. At this level of coding, we recorded infor-mation about the treatment and comparison groups,including program components (e.g., cognitive–behavioral skills training, meditation, exercise, etc.),where the treatment and comparison groups worked,where the program was delivered, who delivered thetreatment, and the duration of the program. We usedthis information to code the intervention type asprimary, secondary, or a combination. At the samplelevel, we coded the number of people in the sample(before attrition), the types of workers, and demo-graphic information including country of partici-pants. At the outcome level, we recorded each de-pendent variable and categorized them according topsychological measures (e.g., general mental health,anxiety, or depression), physiological measures (e.g.,diastolic and systolic blood pressure or pulse), andorganizational measures (e.g., productivity or absen-teeism). We also coded the type of measurementscale (e.g., continuous) and the source of the data(e.g., self-report). For each outcome variable, we thencoded the necessary information to calculate its effectsize, including treatment and comparison group sam-ple sizes, the statistical data, the direction of theeffect size, and whether this difference was reportedas statistically significant by the original investigator.We both coded the initial 10% of studies to assessintercoder reliability. Because there was close to100% agreement, Katherine M. Richardson coded theremaining studies, reviewing unclear data when nec-essary with Hannah R. Rothstein until a consensusdecision was reached.

Two of the studies that met our inclusion criteriaused groups as the unit of random assignment totreatment or control conditions, rather than assigningindividuals. This clustering of individuals withingroups reduces the effective sample size of thesestudies. As we have no basis for estimating thiseffect, or for adjusting the weights of these twostudies, we used the original sample sizes in ouranalyses. This should not have much of an impact onthe overall effect size estimates or on the moderatoranalyses, but it will inflate the statistical significance


levels of these two studies and underestimate theconfidence intervals (CIs) for them.

Statistical Procedures

Comprehensive Meta Analysis Version 2 software(Borenstein, Hedges, Higgins, & Rothstein, 2005)was used to conduct the statistical analyses. Thestandardized mean difference (J. Cohen, 1992;Lipsey & Wilson, 2001) was calculated to representthe intervention effects reported in the eligible stud-ies. This effect size statistic is defined as the differ-ence between the treatment and control group meanson an outcome variable divided by their pooled stan-dard deviations. For this meta-analysis, the randomeffects model was most appropriate as heterogeneitywas expected owing to the variety of interventiontypes and occupational settings. Our procedures wereanalogous to a Hunter–Schmidt (1990) bare-bonesmeta-analysis in that we made no corrections forstatistical artifacts other than sampling error. Ourdecision was based on the lack of sufficient infor-mation in the retrieved studies to appropriatelymake such corrections (e.g., scale reliabilities). Bynot adjusting for artifacts, it is expected that thecalculated mean effect sizes will underestimatetheir actual values (Hunter & Schmidt, 1990). Wecalculated effect sizes at the treatment– controlcontrast level. Our meta-analysis represents thecombined effect of 55 independent interventionswithin 36 studies. For studies that reported multi-ple outcome variables, all applicable effect sizesthat could be extracted were calculated and coded.However, we followed Lipsey and Wilson’s (2001)advice that including multiple effect sizes from thesame intervention violates the assumption of inde-pendent data points that is fundamental to mostcommon forms of statistical analysis and inflatesthe sample size (N of effect sizes rather than N ofinterventions). They recommended either using theaverage of the outcomes at the treatment– controlcontrast level to get a combined effect or selectingthe most representative outcome measure withineach module. Owing to the wide range of outcomevariables within our population of studies, we usedthe average of the outcomes at the interventionlevel for our overall analysis rather than introducesubjectivity into the analysis process by selectingwhat we felt would be most representative. Wealso looked at individual outcomes in a series ofsubgroup analyses. Each effect size was weightedby its precision, so that interventions with larger

samples contributed more to the estimate of thepopulation effect size.

Results

Demographics

Table 1 summarizes the studies selected for themeta-analysis. Thirty-eight articles were identifiedthat met the inclusion criteria, representing 36 sepa-rate studies and 55 interventions. Total sample sizewas 2,847 before attrition and 2,376 after attrition.Individual sample sizes after attrition ranged from 14to 219 participants, with a mean of 49 per interven-tion. The participants represented a wide range ofoccupations, including office workers, teachers,nurses and hospital staff, factory workers, mainte-nance personnel, and social services staff. Two thirdsof the studies were conducted in the United States,and the remainder represented a diverse range ofcountries, including Australia, Canada, China (Tai-wan and Hong Kong), Israel, Japan, the Netherlands,Poland, and the United Kingdom. Fifty-nine percentof the participants were female (based on 28 studies)and mean age was 35.4 (based on 18 studies). Aver-age intervention length was 7.4 weeks. The meannumber of treatment sessions was 7.5, each lasting anaverage of 1–2 hr.

Types of Interventions

The studies primarily assessed secondary interven-tion strategies to reduce the severity of an employee’sstress symptoms. Only 8 studies included compo-nents that were considered primary intervention strat-egies, such as increasing workers’ decision-makingauthority (e.g., participatory action research) or socialsupport within the organization. All the interventionstudies compared at least one treatment group to ano-treatment or waiting list control. Fourteen studiesevaluated two treatment groups versus the same com-parison group, and 2 studies evaluated three treat-ment groups versus the same control. Each treat-ment– control contrast was treated as a separateintervention for analysis purposes. The majority ofstudies (k � 24) evaluated interventions conducted ina group-training environment. Other modes of treat-ment included individual counseling sessions (k �3); self-taught techniques using the Internet, tapes, orbooks (k � 5); or a combination of varying methods(k � 4). Twenty-five studies (69%) included relax-ation and meditation techniques. Twenty studies(56%) included cognitive–behavioral skills training.


Tab

le1

Pri

mar

ySt

udie

sIn

clud

edin

the

Met

a-A

naly

sis

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Ade

rman

&T

eckl

enbe

rg(1

983)

AV

ario

usor

gani

zatio

ns(T

�21

,C�

15)

Gen

eral

stre

ssed

ucat

ion

sem

inar

,plu

sm

edita

tion

and

rela

xatio

ntra

inin

gvi

aau

diot

apes

Anx

iety

(Ben

dig,

1956

)12

wee

ksR

elax

atio

n

BV

ario

usor

gani

zatio

ns(T

�19

,C�

15)

Gen

eral

stre

ssed

ucat

ion

sem

inar

Alte

rnat

ive

Alf

ord,

Mal

ouff

,&O

slan

d(2

005)

AC

hild

prot

ectiv

ese

rvic

esof

ficer

s,A

ustr

alia

(T�

31,C

�30

)

Jour

nal

wri

ting

abou

tre

cent

stre

ssre

actio

nsan

dem

otio

ns

Gen

eral

men

tal

heal

th(G

HQ

-12)

,pos

itive

affe

ct,n

egat

ive

affe

ct,j

obsa

tisfa

ctio

n(J

IG)

3da

ysA

ltern

ativ

e

Ber

toch

,Nie

lson

,Cur

ley,

&B

org

(198

9)A

Tea

cher

s(T

�15

,C�

15)

Hol

istic

prog

ram

:de

epbr

eath

ing,

exer

cise

,re

laxa

tion,

soci

alsu

ppor

t,as

sert

iven

ess,

and

nutr

ition

Stre

ss(D

SP),

stre

ss(O

SI),

stre

ss(t

each

erst

ress

mea

sure

),st

ress

(str

uctu

red

clin

ical

inte

rvie

w)

12w

eeks

Mul

timod

al

Bon

d&

Bun

ce(2

000)

AO

ffice

wor

kers

(T�

24,

C�

20)

“Acc

epta

nce

com

mitm

ent

ther

apy”

:cog

nitiv

e-be

havi

oral

skill

sto

enha

nce

emot

iona

lcop

ing

Gen

eral

men

talh

ealth

(GH

Q-1

2),d

epre

ssio

n(B

eck)

,mot

ivat

ion,

job

satis

fact

ion,

prop

ensi

tyto

inno

vate

14w

eeks

Cog

nitiv

e-be

havi

oral

BO

ffice

wor

kers

(T�

21,

C�

20)

“Inn

ovat

ion

prom

otio

n”pr

ogra

m:

goal

setti

ng,

part

icip

ator

yac

tion,

and

plan

ning

toen

hanc

epr

oble

m-f

ocus

edco

ping

Org

aniz

atio

nal

Bru

ning

&Fr

ew(1

986,

1987

)A

Offi

cer

wor

kers

(T�

16,

C�

16)

Man

agem

ents

kills

base

don

cogn

itive

-beh

avio

ral

tech

niqu

es,g

oals

ettin

g,tim

em

anag

emen

t,co

mm

unic

atio

n,pl

anni

ng

Puls

e,sy

stol

ic&

dias

tolic

bloo

dpr

essu

re,g

alva

nics

kin

resp

onse

8w

eeks

Mul

timod

al

BO

ffice

wor

kers

(T�

15,

C�

16)

Rel

axat

ion

and

med

itatio

nte

chni

ques

Rel

axat

ion

CO

ffice

wor

kers

(T�

15,

C�

16)

Exe

rcis

epr

ogra

mA

ltern

ativ

e

(tab

leco

ntin

ues)


Tab

le1

(con

tinu

ed)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Car

son

etal

.(19

99)

AN

urse

s,U

nite

dK

ingd

om(T

�27

,C�

26)

Soci

alsu

ppor

tgr

oup

toen

hanc

eco

ping

abili

ties

Stre

ss(D

CL

),so

cial

supp

ort

(SO

S),s

elf-

este

em(R

SES)

,em

otio

nal

exha

ustio

n(M

BI)

,gen

eral

men

tal

heal

th(G

HQ

)

5w

eeks

Org

aniz

atio

nal

Cec

il&

Form

an(1

990)

AT

each

ers

(T�

16,C

�19

)St

ress

inoc

ulat

ion

trai

ning

(Mei

chen

baum

,197

7)Sc

hool

stre

ss,t

ask-

base

dst

ress

,job

satis

fact

ion,

role

over

load

,soc

ial

supp

ort

(all

SISS

),co

ping

skill

s

6w

eeks

Cog

nitiv

e-be

havi

oral

BT

each

ers

(T�

17,C

�19

)C

owor

ker

supp

ort

grou

pO

rgan

izat

iona

l

Che

n(2

006)

AO

ffice

wor

kers

,Isr

ael

(T�

24un

its,C

�13

units

,N�

219

part

icip

ants

)

Act

ive

lear

ning

expe

rien

cede

sign

edto

incr

ease

part

icip

ants

’pe

rson

alre

sour

ces

Soci

alsu

ppor

t(H

ouse

,19

81),

perc

eive

dco

ntro

l(K

aras

ek,

1979

)

1w

eek

Alte

rnat

ive

Col

lins

(200

4)A

Offi

cew

orke

rs(T

�9,

C�

9)C

ogni

tive-

beha

vior

alsk

ills,

com

mun

icat

ion,

rela

xatio

nte

chni

ques

,tim

em

anag

emen

t

Stre

ss(J

SI),

burn

out

(MB

I),g

ener

alph

ysic

alhe

alth

,an

xiet

y(S

TA

I)

5w

eeks

Mul

timod

al

BO

ffice

wor

kers

(T�

8,C

�9)

Cog

nitiv

e-be

havi

oral

skill

s,re

laxa

tion

tech

niqu

esM

ultim

odal

deJo

ng&

Em

mel

kam

p(2

000)

AV

ario

usor

gani

zatio

ns,

the

Net

herl

ands

(T�

45,C

�41

)

Mus

cle

rela

xatio

n,co

gniti

ve-

beha

vior

alsk

ills,

prob

lem

solv

ing,

asse

rtiv

enes

str

aini

ng(t

augh

tby

clin

ical

psyc

holo

gist

)

Anx

iety

(Dut

chST

AI)

,ge

nera

lm

enta

lhe

alth

(GH

Q),

gene

ral

phys

ical

heal

th,

soci

alsu

ppor

t(S

SI),

role

over

load

(OSQ

),jo

bdi

ssat

isfa

ctio

n(O

SQ)

8w

eeks

Mul

timod

al

BV

ario

usor

gani

zatio

ns,

the

Net

herl

ands

(T�

44,C

�41

)

Mus

cle

rela

xatio

n,co

gniti

ve-

beha

vior

alsk

ills,

prob

lem

solv

ing,

asse

rtiv

enes

str

aini

ng(t

augh

tby

trai

ned

para

prof

essi

onal

s)

Mul

timod

al

(tab

leco

ntin

ues)


Tab

le1

(con

tinu

ed)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Fava

etal

.(19

91)

AA

rmy

offic

ers

(T�

20,C

�17

)St

ress

Typ

e-A

beha

vior

redu

ctio

npr

ogra

m,

cogn

itive

-beh

avio

ral

skill

s,re

laxa

tion,

self

-es

teem

enha

ncem

ent

Stre

ss(g

loba

las

sess

men

tof

rece

ntst

ress

),st

ress

(PSS

),ge

nera

lm

enta

lhe

alth

(Kel

lner

’sSy

mpt

omQ

),ex

erci

seat

titud

e

28w

eeks

Mul

timod

al

Fied

ler,

Viv

ona-

Vau

ghan

,&G

ochf

eld

(198

9)

AH

azar

dous

was

tew

orke

rs(T

�31

,C�

30)

Prog

ress

ive

mus

cle

rela

xatio

n,de

epbr

eath

ing

Syst

olic

bloo

dpr

essu

re,

dias

tolic

bloo

dpr

essu

re,g

ener

alse

veri

tyin

dex

(SC

L-

90)

9w

eeks

Rel

axat

ion

Gan

ster

,May

es,S

ime,

&T

harp

(198

2)A

Offi

cew

orke

rs(T

�36

,C�

34)

Cog

nitiv

e-be

havi

oral

skill

s(M

eich

enba

um,

1975

),pr

ogre

ssiv

em

uscl

ere

laxa

tion

Anx

iety

,dep

ress

ion,

irri

tatio

n,ge

nera

lph

ysic

alhe

alth

,ep

inep

hrin

e,no

repi

neph

rine

8w

eeks

Mul

timod

al

Gild

ea(1

988)

AFo

ster

care

agen

cyw

orke

rs(T

�9,

C�

8)

Stre

ss/a

nger

man

agem

ent

trai

ning

:co

gniti

ve-b

ehav

iora

lsk

ills,

jour

nalin

g,re

laxa

tion,

educ

atio

n,an

ger

cont

rol

Syst

olic

bloo

dpr

essu

re,

dias

tolic

bloo

dpr

essu

re,d

epre

ssio

n,ge

nera

lph

ysic

alhe

alth

,hos

tility

,and

anxi

ety

(all

SCL

-90)

n/a

Mul

timod

al

BFo

ster

care

agen

cyw

orke

rs(T

�8,

C�

8)

Rel

axat

ion,

jour

nalin

gR

elax

atio

n

N.C

.Hig

gins

(198

6)A

Offi

cew

orke

rs(T

�17

,C�

18)

Rel

axat

ion,

syst

emat

icde

sens

itiza

tion

Em

otio

nal

exha

ustio

n(M

BI)

,str

ain

(PSQ

),ab

sent

eeis

m

6w

eeks

Rel

axat

ion

BO

ffice

wor

kers

,mix

ed(T

�18

,C�

18)

Rat

iona

lem

otiv

eth

erap

y,tim

em

anag

emen

t,go

alse

tting

,ass

ertiv

enes

stra

inin

g

Mul

timod

al

Hok

e(2

003)

AV

ario

usor

gani

zatio

ns(T

�46

,C�

53)

Tw

ice

wee

kly

e-m

ails

that

teac

hde

epbr

eath

ing,

exer

cise

,hy

pnos

is,j

ourn

alin

g,m

edita

tion

and

rela

xatio

n,im

ager

y

Stre

ss(P

SS),

depr

essi

on,a

nxie

ty,

ange

r,da

ilyha

ssle

s

12w

eeks

Mul

timod

al

(tab

leco

ntin

ues)


Tab

le1

(con

tinu

ed)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Jack

son

(198

3)A

Hos

pita

lw

orke

rs(N

�66

)In

trod

uctio

nof

staf

fm

eetin

gsto

incr

ease

staf

fpa

rtic

ipat

ion

Rol

eco

nflic

t,ro

leam

bigu

ity,s

ocia

lsu

ppor

t,ge

nera

lm

enta

lhe

alth

(GH

Q),

job

satis

fact

ion,

abse

ntee

ism

24w

eeks

Org

aniz

atio

nal

Kol

bell

(199

5)A

Chi

ldpr

otec

tive

serv

ices

wor

kers

(T�

13,C

�12

)

Med

itatio

nan

dre

laxa

tion

trai

ning

via

audi

otap

es

Em

otio

nal

exha

ustio

n(M

BI)

,gen

eral

phys

ical

heal

th(B

SI),

abse

ntee

ism

4w

eeks

Rel

axat

ion

BC

hild

prot

ectiv

ese

rvic

esw

orke

rs(T

�13

,C�

12)

Soci

alsu

ppor

tgr

oup

Org

aniz

atio

nal

Lee

&C

rock

ett

(199

4)A

Hos

pita

lnu

rses

,T

aiw

an,C

hina

(T�

29,C

�28

)

Ass

ertiv

enes

str

aini

ngba

sed

onra

tiona

l-em

otiv

eth

erap

y(E

llis,

1962

)

Ass

ertiv

enes

s(R

AS)

,st

ress

(PSS

)2

wee

ksC

ogni

tive-

beha

vior

al

Mad

di,K

ahn,

&M

addi

(199

8)A

Offi

cew

orke

rs,m

id-

leve

lm

anag

ers

(T�

18,C

�16

)

“Har

dine

sstr

aini

ng,”

base

don

cogn

itive

-be

havi

oral

tech

niqu

es

Har

dine

ss,j

obsa

tisfa

ctio

n,st

rain

,ge

nera

lph

ysic

alhe

alth

,soc

ial

supp

ort

10w

eeks

Cog

nitiv

e-be

havi

oral

BO

ffice

wor

kers

,mid

-le

vel

man

ager

s(T

�12

,C�

16)

Rel

axat

ion

and

med

itatio

nR

elax

atio

n

Mur

phy

(198

4b)

AH

ighw

aym

aint

enan

cew

orke

rs(T

�15

,C�

8)

Ele

ctro

myo

grap

hic

biof

eedb

ack

Gen

eral

phys

ical

heal

than

dan

xiet

y(B

SI);

trai

tan

xiet

y(S

TA

I);

job

diss

atis

fact

ion.

10da

ysA

ltern

ativ

e

BH

ighw

aym

aint

enan

cew

orke

rs(T

�11

,C�

8)

Mus

cle

rela

xatio

nvi

aca

sset

teta

pes

Rel

axat

ion

Pete

rs,B

enso

n,&

Port

er(1

977)

;Pe

ters

,B

enso

n,&

Pete

rs(1

977)

AO

ffice

wor

kers

,Uni

ted

Kin

gdom

(T�

54,

C�

36)

Dai

ly15

-min

brea

ks,

taug

htsp

ecifi

cre

laxa

tion

tech

niqu

ew

ithde

epbr

eath

ing

Gen

eral

phys

ical

heal

th(S

ympt

oms

Inde

x),

prod

uctiv

ity,s

ocia

lsu

ppor

t,ha

ppin

ess,

syst

olic

&di

asto

licbl

ood

pres

sure

8w

eeks

Rel

axat

ion

BO

ffice

wor

kers

,Uni

ted

Kin

gdom

(T�

36,

C�

36)

Dai

ly15

-min

brea

ks,n

ore

laxa

tion

tech

niqu

esta

ught

Rel

axat

ion

(tab

leco

ntin

ues)


Tab

le1

(con

tinu

ed)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Pete

rs&

Car

lson

(199

9)A

Uni

vers

itym

aint

enan

cew

orke

rs(T

�21

,C�

19)

Hea

lthed

ucat

ion,

cogn

itive

-beh

avio

ral

skill

s,go

alse

tting

,an

dre

laxa

tion

Anx

iety

,ang

er,a

ndde

pres

sion

(ST

PI),

heal

thse

lf-e

ffica

cy,

job

satis

fact

ion,

syst

olic

/dia

stol

icbl

ood

pres

sure

,ch

oles

tero

l

10w

eeks

Mul

timod

al

Prui

tt(1

992)

AA

rmy

pers

onne

l(T

�31

,C�

33)

Stre

ssaw

aren

ess

educ

atio

n,as

sert

iven

ess,

time

man

agem

ent,

rela

xatio

nvi

aau

diot

apes

Anx

iety

(ST

AI)

,an

xiet

y(S

CL

-90)

,sy

stol

ic&

dias

tolic

bloo

dpr

essu

re

n/a

Mul

timod

al

Shap

iro,

Ast

in,B

isho

p,&

Cor

dova

(200

5)A

Hea

lthca

repr

ofes

sion

als

(T�

18,C

�10

)

Min

dful

ness

-bas

edst

ress

redu

ctio

n(m

edita

tion,

deep

brea

thin

g,yo

ga)

Bur

nout

,gen

eral

men

tal

heal

th(G

SI),

perc

eive

dst

ress

8w

eeks

Rel

axat

ion

Shar

p&

Form

an(1

985)

AT

each

ers

(T�

30,C

�30

)St

ress

inoc

ulat

ion

train

ing

(Mei

chen

baum

,197

7)A

nxie

ty(T

Q4)

,anx

iety

(ST

AI,

stat

e),

anxi

ety

(ST

AI,

trai

t)

4w

eeks

Cog

nitiv

e-be

havi

oral

BT

each

ers

(T�

30,C

�30

)C

lass

room

man

agem

ent

skill

str

aini

ngA

ltern

ativ

e

Shim

azu,

Kaw

akam

i,Ir

imaj

iri,

Saka

mot

o,&

Am

ano

(200

5)

AO

ffice

wor

kers

ina

cons

truc

tion

mac

hine

ryco

mpa

ny,J

apan

(T�

100,

C�

104)

Self

-pac

edon

line

inte

rven

tion

teac

hing

cogn

itive

-beh

avio

ral

and

copi

ngte

chni

ques

Self

-effi

cacy

,str

ess

(BJS

Q),

gene

ral

phys

ical

heal

th,j

obsa

tisfa

ctio

n

11w

eeks

Cog

nitiv

e-be

havi

oral

Stan

ton

(199

1)A

Adm

inis

trat

ive

offic

ew

orke

rs,A

ustr

alia

(T�

15,C

�15

)

“Ego

-enh

ance

men

t”re

laxa

tion

tech

niqu

esSt

ress

(“st

ress

ther

mom

eter

”)n/

aR

elax

atio

n

Tho

mas

on&

Pond

(199

5)A

Cus

todi

alst

aff

(T�

14,C

�13

)C

ogni

tive-

beha

vior

alsk

ills,

rela

xatio

n,im

ager

y,an

dse

lf-

man

agem

ent

skill

s

Gen

eral

men

tal

heal

th(S

CL

-90)

,anx

iety

(ST

AI)

,job

satis

fact

ion

(JIG

),bl

ood

pres

sure

6w

eeks

Mul

timod

al

BC

usto

dial

staf

f(T

�13

,C�

13)

Cog

nitiv

e-be

havi

oral

skill

s,re

laxa

tion,

and

imag

ery

Mul

timod

al

CC

usto

dial

staf

f(T

�14

,C�

13)

Pers

onal

deve

lopm

ent

skill

sA

ltern

ativ

e

(tab

leco

ntin

ues)


Tab

le1

(con

tinu

ed)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Tsa

i&

Cro

cket

t(1

993)

AH

ospi

tal

nurs

es,

Tai

wan

,Chi

na(T

�68

,C�

69)

Rel

axat

ion

trai

ning

base

don

cogn

itive

-beh

avio

ral

mod

elof

rela

xatio

n(S

mith

,199

0)

Gen

eral

men

tal

heal

th(C

hine

seG

HQ

),st

ress

(Chi

nese

NSC

)

5w

eeks

Rel

axat

ion

Tun

necl

iffe

,Lea

ch,&

Tun

necl

iffe

(198

6)A

Tea

cher

s,A

ustr

alia

(T�

7,C

�7)

“Col

labo

rativ

ebe

havi

oral

cons

ulta

tion”

focu

sed

onpr

oble

m-s

olvi

ngap

proa

ch

Tea

cher

stre

ss(T

OSQ

)5

wee

ksC

ogni

tive-

beha

vior

al

BT

each

ers,

Aus

tral

ia(T

�7,

C�

7)R

elax

atio

ntr

aini

ngR

elax

atio

n

Vau

ghn,

Che

atw

ood,

Sirl

es,

&B

row

n(1

989)

AA

dmin

istr

ativ

ew

orke

rs(T

�8,

C�

10)

Prog

ress

ive

mus

cle

rela

xatio

nvi

aau

diot

apes

Stre

ss(S

RI)

4w

eeks

Rel

axat

ion

von

Bae

yer

&K

raus

e(1

983-

1984

)A

Nur

ses

ina

burn

trea

tmen

tun

it,C

anad

a(T

�7,

C�

7)

Cog

nitiv

e-be

havi

oral

skill

s,de

epbr

eath

ing,

rela

xatio

n,an

dro

lepl

ayin

g

Anx

iety

(ST

AI,

stai

t)an

xiet

y(S

TA

I,tr

ait)

1w

eek

Mul

timod

al

Wir

th(1

992)

AB

aker

yem

ploy

ees

(T�

28,C

�18

)L

eade

r-fa

cilit

ated

SMI:

cogn

itive

-beh

avio

ral

skill

s,em

otio

nal

stre

ssm

anag

emen

t,re

laxa

tion,

heal

thed

ucat

ion

Loc

usof

cont

rol,

gene

ral

phys

ical

heal

th(P

SC),

abse

ntee

ism

4w

eeks

Mul

timod

al

BB

aker

yem

ploy

ees

(T�

15,C

�18

)Se

lf-t

augh

tSM

I:co

gniti

ve-

beha

vior

alsk

ills,

rela

xatio

n,he

alth

educ

atio

n

Mul

timod

al

Yun

g,Fu

ng,C

han,

&L

au(2

004)

AA

dmin

istr

ativ

enu

rsin

gst

aff,

Hon

gK

ong,

Chi

na(T

�17

,C�

30)

Rel

axat

ion

usin

gst

retc

hing

and

rele

asin

gof

mus

cles

Anx

iety

(Chi

nese

STA

I,st

ate)

,anx

iety

(Chi

nese

STA

I,tr

ait)

,gen

eral

men

tal

heal

th(C

hine

seG

HQ

)

4w

eeks

Rel

axat

ion

BA

dmin

istr

ativ

enu

rsin

gst

aff,

Hon

gK

ong,

Chi

na(T

�18

,C�

30)

Rel

axat

ion

usin

gco

gniti

veim

ager

yR

elax

atio

n

(tab

leco

ntin

ues)


Many of the interventions had multiple components(such as cognitive– behavioral skills training andmeditation). Fourteen of the studies evaluated inter-ventions with four or more treatment components.Table 1 provides a summary of the included studies.

Outcome Variables

Each study contained multiple outcome mea-sures. We selected and coded all dependent vari-ables that related to stress, including psychologi-cal, physiological, and organizational outcomes.This resulted in more than 60 different outcomevariables, or an average of 3– 4 outcomes perstudy. We averaged these outcomes at the treat-ment– control contrast level to calculate a com-bined effect size for each intervention. Psycholog-ical measures were used in 35 out of 36 studies.The most common among these were stress (k �14), anxiety (k � 13), general mental health (k �11), and job/work satisfaction (k � 10). Unfortu-nately, there was no uniform scale used for anyconstruct. For example, stress was measured via 11different scales, including the Job Stress Index(Sandman, 1992), Occupational Stress Inventory(Osipow & Spokane, 1983), Perceived Stress Scale(Cohen, Kamarck, & Mermelstein, 1983), Personaland Organizational Quality Assessment (Barrios-Choplin & Atkinson, 2000), and Teacher StressMeasure (Pettegrew & Wolf, 1982).

Physiological measures were used in a quarter ofthe studies, and the most common of these was sys-tolic and diastolic blood pressure. Other physiologi-cal measures were epinephrine and norepinephrinelevels, galvanic skin response, and cholesterol. Onlysix studies measured organizational-specific out-comes. Four studies assessed absenteeism, and twoexamined productivity.

Effect Sizes

A combined analysis, using the inverse-varianceweighted average effect size from each individualintervention, yielded a significant effect size acrossall studies (d � 0.526, 95% CI � 0.364, 0.687). Thisis considered a medium to large effect size (J. Cohen,1988). By comparison, van der Klink et al.’s (2001)meta-analysis yielded a small combined effect size(d � 0.34, 95% CI � 0.27, 0.41). We checked forheterogeneity of effects in two ways. First, we usedthe traditional chi-square statistic to test the hypoth-esis that all of the observed heterogeneity was due tosampling error variance. The Q value was highlyT

able

1(c

onti

nued

)

Aut

hor(

s)an

dye

arT

reat

men

t-co

ntro

lco

ntra

stSa

mpl

esi

zea

and

desc

ript

ionb

Tre

atm

ent

com

pone

nts

Out

com

esm

easu

redc

Len

gth

Inte

rven

tion

type

Zol

nier

czyk

-Zre

da(2

002)

AFi

nanc

ial

sect

orof

fice

wor

kers

,Pol

and

(T�

40,C

�45

)

Cog

nitiv

e-be

havi

oral

skill

s,jo

bco

ntro

l,so

cial

supp

ort,

asse

rtiv

enes

s,an

ger

cont

rol

Prob

lem

-foc

used

copi

ng,

emot

iona

l-fo

cuse

dco

ping

,soc

ial

supp

ort

10w

eeks

Mul

timod

al

Not

e.T

�tr

eatm

ent;

C�

cont

rol;

GH

Q-1

2�

Gen

eral

Hea

lthQ

uest

ionn

aire

12;

JIG

�Jo

bin

Gen

eral

Scal

e;D

SP�

Der

ogat

isSt

ress

Profi

le;

OSI

�O

ccup

atio

nal

Stre

ssIn

vent

ory;

DC

L�

DeV

illie

rsC

arso

nL

eary

Scal

e;M

BI

�M

asla

chB

urno

utIn

vent

ory;

SISS

�St

ress

inth

eSc

hool

Setti

ng;

JSI

�Jo

bSt

ress

Inde

x;ST

AI

�St

ate

Tra

itA

nxie

tyIn

vent

ory;

SSI

�So

cial

Supp

ort

Indi

cato

r;O

SQ�

Occ

upat

iona

lSt

ress

Que

stio

nnai

re;

PSS

�Pe

rcei

ved

Stre

ssSc

ale;

SCL

-90

�Sy

mpt

omC

heck

list

90;

PSQ

�Pe

rson

alSt

rain

Que

stio

nnai

re;

RA

S�

Rat

hus

Ass

ertiv

enes

sSc

ale;

STPI

�St

ate-

Tra

itPe

rson

ality

Inve

ntor

y;T

Q4

�T

each

erQ

uest

ionn

aire

4;B

JSQ

�B

rief

Job

Stre

ssQ

uest

ionn

aire

;N

SC�

Nur

seSt

ress

Che

cklis

t;T

OSQ

�T

each

erO

ccup

atio

nal

Stre

ssQ

uest

ionn

aire

;SR

I�

Stre

ssR

espo

nse

Inde

x;SM

I�

stre

ssm

anag

emen

tin

terv

entio

n;SO

S�

Sign

ifica

ntO

ther

sSc

ale;

RSE

S�

Ros

enbe

rgSe

lf-E

stee

mSc

ale.

aB

ased

onpo

sttr

eatm

ent

mea

sure

s.b

U.S

.sa

mpl

e,un

less

othe

rwis

eno

ted.

cFr

eque

ntly

used

scal

esno

ted

inpa

rent

hese

s.


significant (Q � 202.6, p � .001), indicating thatthere was more heterogeneity of effects than could beaccounted for by sampling error. Second, we used theI2 statistic: I2 � [(Q – df)/Q] � 100%, where Q is thechi-square statistic and df is its degree of freedom(Higgins, Thompson, Deeks, & Altman, 2003). I2

represents the amount of variability across studiesthat is attributable to between-study differencesrather than to sampling error variability. In this case,the I2 statistic suggests that 73% of the total varianceis due to between-study variance, or heterogeneity,rather than to sampling error. Both statistics sug-gested the likely presence of moderators, so we pro-ceeded to conduct subgroup analyses.

Intervention-Level Moderators

To search for moderators, we classified the inter-ventions into more homogeneous subgroups and per-formed analyses on these groupings, again using theaverage outcome effect size for each intervention,when more than one outcome was assessed. First, wecoded our interventions into the same categories usedin the van der Klink et al. (2001) meta-analysis:cognitive–behavioral, relaxation, organizational, ormultimodal (multiple component). Seven interven-tions could not be classified into these groupings.These studies evaluated interventions composed ofexercise or EMG feedback, journaling, personalskills development, or classroom management train-ing (for teachers). We therefore created an “alterna-tive” intervention category, while recognizing thatthis grouping did not represent a specific type ofintervention. Table 2 shows the average effect sizefor interventions in each of these categories.

The results in Table 2 show that the average effectsizes of both the cognitive–behavioral and the relax-ation intervention categories were larger than theanalogous average effects from the van der Klink et

al. (2001) meta-analysis. Somewhat surprisingly,there was a great deal of heterogeneity of effects inthe cognitive–behavioral intervention category (I2 �89.5, Q � 57.0, p � .001). The alternative interven-tion category had the second largest average effectsize (d � 0.909, 95% CI � 0.318, 1.499), although italso had a wide confidence interval and, as would beexpected, substantial heterogeneity (I2 � 85.3, Q �40.8, p � .001). Organizational interventions yieldedvirtually no effect, also consistent with the priormeta-analysis. Multimodal interventions, however,yielded a significant but small effect size in thepresent study (d � .239, 95% CI � 0.092, 0.386),which is lower than the van der Klink et al. study.The present meta-analysis included 15 studies (19interventions) with multimodal programs, whereasthe van der Klink et al. study included only 8 studiesin this category. Within such multimodal programs,cognitive–behavioral, relaxation, and even organiza-tional techniques can all be included as treatmentcomponents. Among the 19 multimodal interventionsin our meta-analysis, 5 included cognitive–behav-ioral components, 3 included relaxation components,and 11 included both cognitive–behavioral and re-laxation components. This makes it difficult to assesswhether the specific components, the mixture of com-ponents, the number of components, or a combina-tion of these factors is causing the intervention effect.Another way to categorize our studies is to look at thenumber of components per intervention. Table 3shows the effect sizes based on these subgroups.

The results in Table 3 suggest that interventionsthat focus on a single component are more effectivethan those that focus on multiple components. Thegeneral trend is that as each component is added, theeffect is reduced. However, there was significantheterogeneity among the one-component studies(I2 � 81.6, Q � 103.0, p � .001), and the results inTable 3 are confounded by intervention type. For

Table 2Cohen’s d and Confidence Intervals on the Basis of Intervention Type

Intervention type k N d 95% CI y

Cognitive-behavioral 7 448 1.164** 0.456, 1.871 .68*

Relaxation 17 705 0.497*** 0.309, 0.685 .35*

Organizational 5 221 0.144 �0.123, 0.411 .08Multimodal 19 862 0.239** 0.092, 0.386 .51*

Alternative 7 455 0.909** 0.318, 1.499 N/A

Note. k � number of interventions; d � combined effect size; CI � confidence interval; y �Cohen’s d from van der Klink et al. (2001).* p � .05. ** p � .01. *** p � .001.


example, the one-component interventions with thelargest effects were cognitive–behavioral interven-tions (k � 2, d � 1.230, 95% CI � �0.968, 3.428).Four of the single-component interventions taughtsome form of personal development skills that spe-cifically related to increasing personal resources ormanagement skills that would assist employees intheir jobs (e.g., classroom management training).These yielded a significant large effect (d � 1.154,95% CI � 0.332, 1.975). Seven used relaxation as thetreatment and obtained a significant medium effect(d � 0.501, 95% CI � 0.161, 0.841).

Among the studies with two treatment compo-nents, relaxation techniques were most likely to bethe primary treatment component. This was the casewith 10 interventions, yielding a significant mediumeffect size (d � 0.502, 95% CI � 0.265, 0.739).Seven interventions used cognitive–behavioral tech-niques as the primary treatment component, and theseyielded a significant large effect size (d � 0.913,95% CI � 0.320, 1.505). Among the studies withfour or more treatment components, cognitive–behavioral skills training and relaxation were likelyto be incorporated. Nine interventions included bothcognitive– behavioral and relaxation components(d � 0.296, 95% CI � 0.086, 0.507), three includedcognitive–behavioral components (d � 0.201, 95%CI � �0.119, 0.522), and three included relaxationcomponents (d � 0.215, 95% CI � �0.069, 0.499).

We also examined whether treatment durationmade a difference among the interventions. The av-erage length was 7.4 weeks, but the range was 3 daysto 7 months. We therefore grouped studies accordingto the length of the intervention period (three studiesdid not provide this information). Because treatmentlength may be confounded with type of intervention,we further classified the studies based on interventiontype. Table 4 shows the effect sizes based on these

subgroups. The “All studies” column suggests thatshorter interventions are more effective than longerones. However, when one examines the data by in-tervention type, the pattern does not hold as firmly.The majority of interventions fall under the relax-ation and multimodal categories, but there are a lim-ited number of studies in each cell. Relaxation inter-ventions consistently produce medium-sized effects,regardless of length. Multimodal programs, in con-trast, appear to lose effect as treatment length in-creases.

Outcome-Level Moderators

Another way to classify the data into subgroups isto examine the outcome measures used in the studies.Outcome measures could be psychological, physio-logical, or organizational in nature, and we codedthem into 40 general categories. Some measures wereused more frequently than others. To assess whichmeasures produced larger effects and to examinewhether outcome variables differed between inter-vention types, we performed a subgroup analysis ofintervention type crossed with the outcomes we notedwere used most frequently. Table 5 shows the effectsizes based on these subgroups.

Disaggregating the data by outcome variable andtreatment type results in a small number of interven-tions in certain cells, but the analysis does illustrateseveral interesting findings. First, no studies thatevaluated single-mode cognitive–behavioral or orga-nizational interventions measured physiological out-comes. Thus, the large effect of the single-modecognitive–behavioral programs is based solely onpsychological and (less frequently) organizationalmeasures. Likewise, the large effects of alternativeinterventions are also based primarily on psycholog-ical variables. A pattern thus emerges in which out-

Table 3Cohen’s d and Confidence Intervals on the Basis of the Number ofTreatment Components

No. oftreatment

components k N d 95% CI

One 20 946 0.643*** 0.309, 0.977Two 18 970 0.607*** 0.346, 0.868Three 2 59 �0.104 �0.627, 0.418Four or more 15 716 0.271** 0.102, 0.440

Note. k � number of interventions; d � combined effect size; CI � confidence interval.** p � .01. *** p � .001.


come variables are likely to be chosen on the basis ofthe type of intervention. For example, interventionsthat focus on the individual (e.g., cognitive–behavioral, journaling, and stress education) use psy-chological measures, and those that focus on organi-zational changes generally include organizationalmeasures. The result is that we are left with gaps inthe body of research. We are unable to assess whetheralternative treatment programs (e.g., journaling, ex-ercise, and personal coping skills)—which have alarge effect on psychological and physiological out-comes—produce similar results using organizationalmeasures. Regarding specific organizational out-comes, measures of productivity appear to producelarger effects than absenteeism, but there is a generallack of studies that use such measures. In general,

there are no uniform outcome measures used to as-sess the effectiveness of stress management pro-grams. Only one third of the interventions reportedusing an actual measure of “stress,” and among thesethere was significant variation in the scales chosen.

To obtain a more pure assessment of whether typeof outcome measure played a moderating role, weselected only those studies for which psychologicaloutcomes were provided in combination with eitherphysiological or organizational measures. In otherwords, the same samples of participants were beingmeasured using both types of outcomes. All of thepsychological measures were based on self-report,continuous scales. This may affect the reliability ofthe outcomes. The physiological measures, in con-trast, were more likely to be administered by an

Table 4Cohen’s d on the Basis of Length of Treatment and Intervention Type

Length oftreatment All studies

Treatment type

CB Relax Org Multi Alternative

1–4 weeks 0.804*** (15) 1.477** (2) 0.560* (5) �0.097 (1) 0.274 (3) 1.217* (4)5–8 weeks 0.396*** (22) 1.576 (2) 0.500*** (7) �0.003 (2) 0.291* (9) 0.585* (2)9–12 weeks 0.346* (10) 1.230 (2) 0.315 (3) N/A 0.089 (4) 0.250 (1)�12 weeks 0.401** (4) 0.323 (1) N/A 0.328 (2) 0.718* (1) N/A

Note. Numbers in parentheses represent total number of interventions. CB � cognitive-behavioral; Relax � relaxation;Org � organizational; Multi � multimodal.* p � .05. ** p � .01. *** p � .001.

Table 5Cohen’s d on the Basis of Outcome Variables and Intervention Type

Outcome variable All studies

Treatment type


PsychologicalAll combined 0.535*** (52) 1.154** (7) 0.507*** (16) 0.134 (5) 0.258** (18) 0.905** (6)Stress 0.727*** (18) 1.007** (5) 0.834** (5) �0.314 (2) 0.595** (5) 1.367*** (1)Anxiety 0.678*** (22) 2.390*** (1) 0.611*** (5) N/A 0.418** (12) 0.841 (4)Mental health 0.441*** (16) 0.708* (1) 0.405* (5) 0.167 (3) 0.518 (5) 0.616* (2)Work-related outcomesa 0.183 (23) 0.682 (4) �0.381 (4) 0.243 (4) �0.115 (7) 0.794 (4)

PhysiologicalAll combined 0.292* (14) N/A 0.312 (5) N/A 0.166 (7) 0.714** (2)

OrganizationalAll combined 0.267 (11) 0.606 (1) 0.534*** (4) 0.247 (3) �0.122 (3) N/AProductivity 0.703*** (4) 0.606 (1) 0.661*** (2) 0.989** (1) N/A N/AAbsenteeism �0.059 (7) N/A 0.213 (2) �0.159 (2) �0.122 (3) N/A

Note. Numbers in parentheses represent total number of interventions. CB � cognitive-behavioral; Relax � relaxation;Org � organizational; Multi � multimodal.a Includes job/work satisfaction, motivation, social support, daily hassles, role ambiguity, role overload, and perceivedcontrol.* p � .05. ** p � .01. *** p � .001.


independent, trained examiner or via a medical de-vice (e.g., blood pressure monitor). The organiza-tional measures were based on company records(e.g., absenteeism) and self-report data (e.g., produc-tivity or propensity to innovate). Table 6 shows theeffect sizes based on these subgroups.

The data in Table 6 are based on a small number ofstudies and should therefore be interpreted cau-tiously. Even so, it appears that intervention typecontinues to confound outcome effects. The resultsfor all studies combined suggest that psychologicaland physiological outcome variables produce compa-rable effect sizes. However, this depends on type ofintervention. For example, for the alternative sub-group, the physiological measures produced largereffect sizes. When studies measured both psycholog-ical and organizational variables, psychological out-comes produced larger effects than organizationaloutcomes. But this may also depend on treatmenttype, as the relationship is reversed for the relaxationand organizational subgroups. Table 6 does alert us tothe overreliance on self-report measures in interven-tion studies. Among the 55 interventions, only 11measured both psychological and physiological out-comes, and 11 measured both psychological and or-ganizational outcomes.

Sample-Level Moderators

The final moderator analysis we performed wasbased on industry sector. Many early interventionstudies were performed in the health care or educa-tion fields. We classified studies into subgroups onthe basis of three industry sectors: office, health care,and education. We further grouped the results by

intervention type. Table 7 shows the effect sizesbased on these subgroups. Results depict effect sizesin the general direction of prior analyses, with cog-nitive– behavioral producing the largest effects.However, what may be more interesting is to exam-ine the distribution of intervention type by industry.For example, multimodal interventions appear morelikely to be used in office settings, perhaps becausethere has been no solid empirical evidence as to themost effective treatment in this particular setting, andtherefore a “potpourri” approach is used. In contrast,relaxation interventions appear more often withinhealth care settings, and cognitive–behavioral inter-ventions in education settings. However, disaggregat-ing the data produces small numbers of studies ineach cell, so these interpretations may be unstable.

Outlier Analysis

We performed outlier analyses by examining for-est plots of the effect sizes and confidence intervals,for all studies combined and at the subgroup levels.One alternative intervention was identified as a pos-sible outlier because of its very large effect size andthe fact that its confidence interval did not fall intothe range of similar interventions for that subgroup.We therefore excluded this study (which representedtwo alternative interventions: exercise only and lis-tening to music; Taylor, 1991) from the analysis.However, based on a sensitivity analysis, we notethat if we included this study in our calculations, thecombined overall effect size would increase slightly(d � 0.618, 95% CI � 0.432, 0.903).

Table 6Cohen’s d on the Basis of Outcome Variable and Intervention Type for Selected Studies

Outcome variable All studies

Treatment type


Psychological vs.physiological

Psychological 0.227* (11) N/A 0.303* (4) N/A 0.151 (6) 0.250 (1)Physiological 0.219 (11) N/A 0.282 (4) N/A 0.115 (6) 0.601 (1)Psychological vs.

organizationalPsychological 0.285** (11) 0.253 (1) 0.376* (4) 0.187 (3) 0.197 (3) N/AOrganizational 0.267 (11) 0.606 (1) 0.534*** (4) 0.247 (3) �0.122 (3) N/A



Sensitivity Analysis

We performed a sensitivity analysis to examinewhether including seven additional studies from thevan der Klink et al. (2001) meta-analysis wouldchange our overall results. These particular studiesdid not meet our inclusion criteria because, accordingto our review, they did not report sufficient statisticsto calculate an effect size.1 They were included in thevan der Klink et al. study on the basis of assumptionsmade by those authors. However, rather than excludethese interventions entirely, we used the reportedeffect sizes from the van der Klink et al. study andadded them to our meta-analysis. This slightly re-duced our combined overall effect size (d � 0.469,95% CI � 0.328, 0.609) but still yielded a mediumeffect.

Publication Bias

We performed an analysis to examine whether thecombined effect size from published studies differedfrom that of unpublished studies. The current meta-analysis included five unpublished dissertations, rep-resenting eight interventions. The combined effectsize from these eight interventions, using the averageeffect size across outcomes, yielded a significantmedium to large effect (d � 0.553, 95% CI ��0.126, 1.232, p � .110). In comparison, the com-bined effect from published studies was .509 (95%CI � 0.356, 0.661, p � .001). In this case, it appearsthat including unpublished studies slightly increasedthe size of our overall average effect, whereas thegeneral concern is that omission of unpublished workupwardly biases the effect size. We have no unam-biguous explanation for the direction of difference inour particular case. There were no apparent differ-ences in methodological quality between the twogroups of studies.

Another way to detect publication bias in a meta-analysis is the “trim-and-fill” technique, developedby Duval and Tweedie (2000). “Trim and fill” is anonparametric method designed to estimate and ad-just a funnel plot for the number and outcomes ofmissing studies (Duval, 2005). We used this methodon the overall effect size distributions and estimatedthe number of missing studies at six, all to the rightof the mean. This suggests that the combined effectof 0.526 is understated and that the potential impactof including the proposed “missing” studies wouldincrease the effect to 0.595. However, one limitationof the trim-and-fill method is that if the data areheterogeneous, the technique may impute studies thatare not really “missing.” Study-related factors maydistort the appearance of the funnel plot (Duval,2005). To adjust for heterogeneity, we performedadditional trim-and-fill analyses at the subgrouplevel, examining intervention type crossed with out-come. We were able to use the method only if therewas a minimum of three interventions in the sub-group. On the basis of the analyses, multimodal in-terventions was the only category that producedgreater than one “missing” study. On the basis of thepsychological outcome measures, it appeared thatthree studies were missing on the left side of themean, which would suggest an overstated effect andwould decrease the overall effect for multimodalinterventions (d � 0.190). We stress that the maingoal of the trim-and-fill method is as a sensitivity

1 For example, one study contained three distinct treat-ment modules but combined the participants of each intoone group and compared it with the control. Two studiesreported results of only the statistically significant findings,and several others failed to report all required statistics (e.g.,means with no standard deviations). In such cases, van derKlink et al. (2001) used p values, making assumptions whenno such value was reported (e.g., nonsignificant findings).

Table 7Cohen’s d Based on Industry Sector and Intervention Type

Industry All studies

Treatment type


Office 0.680*** (19) 0.872 (3) 0.619*** (7) 0.162 (1) 0.395* (6) 1.337** (2)Health care 0.492*** (8) 0.988*** (1) 0.462*** (4) 0.208 (2) 1.307* (1) N/AEducation 1.255** (7) 1.662* (3) 1.523* (1) 0.056 (1) 0.524 (1) 2.037*** (1)



analysis to assess the impact of missing studies on theoverall effect, rather than actually adjusting the endresults (Duval, 2005).

Discussion

In the present study, we used meta-analysis proce-dures to evaluate the effects of SMIs in workplacesettings. We updated a previous systematic reviewperformed by van der Klink et al. (2001). Thirty-eight articles met our inclusion criteria, representing36 studies and 55 interventions. A combined analy-sis, using the weighted average effect size from eachindividual intervention, yielded a significant effectsize (d � 0.526, 95% CI � 0.364, 0.687). However,this overall analysis may be misleading as there issignificant heterogeneity within the studies. Furtheranalysis was required to determine what moderatorswere present.

We classified interventions into more homoge-neous subgroups and performed analyses on thesegroupings to identify moderators. First, to be consis-tent with the van der Klink et al. (2001) study, wecoded interventions on the basis of their treatmentcomponents and categorized them into five sub-groups: cognitive–behavioral, relaxation, organiza-tional, multimodal, and alternative interventions. Al-though we found larger effects in each of the foursubgroups that we had in common with van der Klinket al., the relative effectiveness of the four groupswas the same in both meta-analyses, and van derKlink et al.’s average effect size value for each cat-egory was well within the 95% confidence intervalsaround our mean effects. Thus, our research bothsupports the results of the van der Klink et al. meta-analysis and extends it by ruling out the threat thatweak study design in some of the included studieswas responsible for the observed effects. In fact, weshow that higher average effects were obtained whenonly true experiments were included.

In the current meta-analysis, cognitive–behavioralinterventions (d � 1.164) and alternative interven-tions (d � 0.909) yielded the largest effect sizes. Onthe basis of the I2 statistic and Q values, however,there was substantial heterogeneity within each ofthese subgroups. We therefore performed additionalsubgroup analyses, and cognitive–behavioral inter-ventions consistently produced larger effects thanother types of interventions. Our findings are in ac-cord with other research that has shown cognitive–behavioral interventions to be among the more effec-tive methods for managing stress in other settings andwith other populations, including HIV-positive gay

men (Lutgendorf et al., 1998), women with earlystage breast cancer (Antoni et al., 1991), and students(Stein et al., 2003). Similarly, cognitive therapy hasproved to be an effective treatment for a variety ofpsychological, psychosomatic, and somatic disor-ders, including depression and anxiety (Lipsey &Wilson, 1993), chronic pain (Morley, Eccleston, &Williams, 1999), chronic fatigue syndrome (Whitinget al., 2001), and insomnia (Rybarczyk et al., 2005).

In an attempt to understand why cognitive–behavioral interventions might produce stronger ef-fects than other popular techniques such as relaxationor meditation, we compared the goals of the methods.Relaxation and meditation aim to refocus attentionaway from the source of stress, to increase the per-son’s awareness of the tension in his or her body andmind, and to reduce this tension by “letting go.”Although they may reduce or eliminate troublingthoughts or feelings, they do not direct the individualto confront dysfunctional ideas, emotions, or behav-iors. Thus, these are basically passive techniques.Cognitive– behavioral interventions, on the otherhand, are more active. These interventions encourageindividuals to take charge of their negative thoughts,feelings, and resulting behavior by changing theircognitions and emotions to more adaptive ones andby identifying and practicing more functional behav-ioral responses. In other words, cognitive–behavioralinterventions promote the development of proactiveas well as reactive responses to stress. This mayaccount for the relative magnitude of the two types oftreatments, but other differences, such as variationsin the length of the intervention and the mode ofinstruction, will need to be ruled out by future re-search.

Despite the stronger effects of cognitive–behav-ioral interventions, the most popular treatment com-ponents among the 55 interventions were relaxationand meditation techniques. They were used in 69% ofthe studies. On the basis of the subgroup analyses,these programs consistently produced medium ef-fects. A likely reason for the popularity of this treat-ment is its simplicity. A survey of subject matterexperts rated relaxation as the most practical inter-vention, because it is the least expensive and easiestto implement (Bellarosa & Chen, 1997). Often thesetechniques are self-taught via audiotapes. Cognitive–behavioral interventions, in contrast, are generallytaught by a trained professional in a group session,and therefore require a greater investment of organi-zational resources.

A somewhat surprising finding from the currentstudy is that the more components added to a cogni-


tive–behavioral intervention, the less effective it be-comes. Single-mode cognitive–behavioral interven-tions yielded a d of 1.230, but cognitive–behavioralinterventions with four or more components (e.g.,including relaxation, assertiveness, time manage-ment, etc.) yielded a d of 0.233. This finding contra-dicts Murphy’s (1996) narrative review, in which heconcluded that “the most positive results were ob-tained with a combination of two or more tech-niques” (p. 112). Multimodal interventions are quitecommon and are more likely to be of a longer dura-tion. However, longer treatment programs were gen-erally not associated with larger effect sizes. Organi-zational researchers may be tempted to institute acombination of treatments in hopes of producingmore effective stress management. We suggest thatwhen single components are resource intensive andrelatively multifaceted at the outset, as is the casewith cognitive–behavioral skills training, the organi-zation’s ability to implement additional componentseffectively may decrease and work to the detrimentof the more complex individual components. Simplerinterventions may not suffer from being bundled withother components. For example, the effect of relax-ation training varied less dramatically whether it wasdelivered on its own (d � 0.497) or as part of apackage four or more components (d � 0.246). Onthe basis of our meta-analysis, we suggest that cog-nitive–behavioral programs should not generally becombined with other treatments, but relaxation andmeditation can be used as part of a larger set oftreatment components. As one anonymous reviewernoted, however, shorter programs—which are likelyto be more cost-effective and practical to imple-ment—appear to be sufficient and perhaps even bet-ter than programs of longer duration.

The alternative interventions yielded a large aver-age effect, and several of these are worth noting.Three studies (Chen, 2006; Sharp & Forman, 1985;Thomason & Pond, 1995) incorporated an interven-tion designed to increase employees’ personal re-sources or management/job skills, and they produceda combined significant large effect (d � 1.414, CI �0.587, 2.241). We made the decision to code theseinterventions as alternative rather than organizationalbecause they were designed to provide employeeswith individual tools to assist them with the morestressful aspects of their work rather than to makestructural changes in their jobs. For example, Chen(2006) designed an intervention to increase partici-pants’ personal resources during the introduction of anew information technology system, and Sharp andForman (1985) provided classroom management

training to teachers. As these interventions may bethought to address organizational issues, we con-ducted a reanalysis by putting them in the organiza-tional subgroup. This increased the average effect oforganizational interventions from 0.144 (k � 5, CI ��0.123, 0.411) to 0.595 (k � 8, CI � �0.044,1.233). This sensitivity analysis both illustrates thatthe small number of studies in particular categoriesaffects the stability of the results for that subgroupand provides evidence that programs that increase theemployee’s job-related skills and abilities may be aneffective way to reduce employee stress. We suggestthat new primary studies are needed for this categoryof intervention.

Our examination of outcome measures by inter-vention type revealed several other gaps in the liter-ature. As noted in earlier reviews (Murphy & Sauter,2003; van der Klink et al., 2001), there remains a lackof studies that assess organizational-level outcomes.We suggest that future primary studies attend to thislevel of outcome. We further suggest that we willlearn more about the mechanisms by which interven-tions reduce stress and be able to more meaningfullycompare interventions by incorporating each of thethree types of outcome measures in each evaluation.Currently, researchers tend to choose outcome mea-sures that are highly aligned with the intervention.Thus, exercise interventions will almost always usephysiological measures, cognitive– behavioral andrelaxation programs will use psychological measures,and organizational interventions will include at leastone organizational outcome. Matching interventionto outcome type makes sense but also creates con-founds between intervention and type of outcome.For example, in our sample of studies, no single-mode cognitive–behavioral intervention used physi-ological outcome measures. These interventionsachieved some of the largest effects on the basis ofpsychological variables, but how would they havecompared with exercise interventions if they hadmeasured cardiovascular functioning? New primaryresearch comparing different interventions on similaroutcomes would contribute to both theoretical andapplied literatures on worksite stress management.

Limitations

A limitation of this meta-analysis is that there islimited information to assess the effects of organiza-tional-level interventions or organizational-level out-comes. The majority of studies reported only psycho-logical-level outcome measures, and there were veryfew studies with organizational-level outcomes (e.g.,


absenteeism and performance). Of the 36 studies,only 5 assessed the impact of an organizational in-tervention. One reason for this is because of the strictinclusion criteria we applied to our literature search.We limited the type of studies to only those experi-ments with random assignment to treatment and con-trol groups, and it is likely to be difficult to conducttrue experiments on organizational interventions. Onthe other hand, this may reflect the true state of theresearch literature, as reviews with less stringent in-clusion criteria also lament the lack of evaluationof organizational interventions (Giga, Noblet,Faragher, & Cooper, 2003; Murphy & Sauter, 2003).

Another limitation of this meta-analysis is that themoderators we examined are confounded by the type ofparticipants in each study, and with each other. Ouroverall effect size is an average of several heteroge-neous effects, which may have been produced by dif-ferences in the characteristics of the sample participantsas well as in the intervention type. The wide variety ofintervention types and outcome variables makes for amultitude of effect combinations. We have attempted toclassify the interventions into the most meaningful sub-groups while keeping in mind that subgrouping leads todecreased power and precision.

A final limitation is that we cannot account for thevarying organizational stress levels before the inter-vention and how they may have influenced the sizeand variability of treatment effects. Some studies inour sample did prescreen employees and selectedparticipants who, although not clinically diagnosedwith a stress-related illness, scored moderate to highon initial stress screenings. Other studies simply re-cruited employees through public notice. We cannotmake the assumption that pretreatment stress levelsamong our sample studies were uniformly high sim-ply because the organizations were willing to partic-ipate in an intervention. An anonymous reviewernoted that often the organizations with the moststressful environments are the ones whose manage-ment does not see the value in investing in training.

Future Research

The overall significant medium to large effect sizeindicates that there is value to SMI programs. Theseresults show that individual employees can be taughttechniques to reduce their stress levels and alleviatesymptoms of strain. In addition, nearly all of thesubcategories of interventions produced meaningfuleffects. Some of these, such as cognitive–behavioralinterventions and meditation, have been the focus ofa relatively large number of studies, but not all of the

potentially effective treatments have been studied veryoften. Specifically, single-mode treatment programsthat provide employees with personal job-related skillsand abilities (e.g., resource enhancement and goal set-ting) need more attention by researchers.

Our moderator analyses, even for popular interven-tions, are based on small numbers of studies. Further-more, it was not possible to remove potential con-founds such as the one between type of interventionand outcome type. Thus, future research that system-atically disentangles the confounding in the currentbody of literature would contribute to our knowledgeof the effectiveness of different types of programs.

Little is known about the long-term effects ofSMIs. In all of the studies in this meta-analysis, theposttreatment measures were taken either immedi-ately after training or within several weeks. Only aquarter of the interventions (k � 15) included fol-low-up measures subsequent to the posttreatmentevaluation. It would be useful to know how longthese effects last. Recent research on time away fromwork (i.e., respites) has found empirical evidence tosuggest a direct relationship between occupationalstress and strain. Studies have found that time awayfrom work will alleviate stress symptoms, but nomatter how long the respite—whether a weekend oryear-long sabbatical—employees ultimately return toprerespite stress levels (Eden, 2001). We need addi-tional primary studies to assess whether a similarpattern develops with SMIs.

Finally, the present meta-analysis illustrates thatafter 30 years of work, there are a large number ofmethodologically rigorous intervention studies in thestress management literature. We hope the resultsencourage future researchers to strive to design qual-ity experiments that incorporate random assignmentto treatment and control groups and report the resultsof all outcomes, not just the statistically significantones. In addition, we promote the continued use ofmeta-analytic procedures to synthesize the research.As more primary studies are conducted, it is impor-tant to update systematic reviews and continue toreassess the results.

References

*Aderman, M., & Tecklenberg, K. (1983). Effect of relax-ation training on personal adjustment and perceptions oforganizational climate. Journal of Psychology, 115, 185–191.

*Alford, W. K., Malouff, J. M., & Osland, K. S. (2005).Written emotional expression as a coping method in childprotective services officers. International Journal ofStress Management, 12, 177–187.


Antoni, M. H., Baggett, L., Ironson, G., LaPerriere, A.,August, S., Klimas, N., et al. (1991). Cognitive–behavioral stress management intervention buffers dis-tress responses and immunologic changes following no-tification of HIV-1 seropositivity. Journal of Consultingand Clinical Psychology, 59, 906–915.

Arthur, A. R. (2000). Employee assistance programmes:The emperor’s new clothes of stress management? Brit-ish Journal of Guidance and Counselling, 28, 549–559.

Atkinson, W. (2004). Stress: Risk management’s most se-rious challenge? Risk Management, 51(6), 20–24.

Barrios-Choplin, B., & Atkinson, M. (2000). Personal andorganizational quality assessment. Boulder Creek, CA:HeartMath Research Center, Institute of HeartMath.

Beehr, T. A., & Newman, J. E. (1978). Job stress, employeehealth, and organizational effectiveness: A facet analysis,model and literature review. Personnel Psychology, 31,665–699.

Bellarosa, C., & Chen, P. Y. (1997). The effectiveness andpracticality of occupational stress management interven-tions: A survey of subject matter expert opinions. Jour-nal of Occupational Health Psychology, 2, 247–262.

Bendig, A. W. (1956). The development of a short form ofthe Manifest Anxiety Test. Journal of Consulting Psy-chology, 20, 384.

Benson, H. (1975). The relaxation response. New York:Morrow.

*Bertoch, M. R., Nielson, E. C., Curley, J. R., & Borg,W. R. (1989). Reducing teacher stress. Journal of Exper-imental Education, 57(2), 117–128.

*Bond, F. W., & Bunce, D. (2000). Mediators of change inemotion-focused and problem-focused worksite stressmanagement interventions. Journal of OccupationalHealth Psychology, 5, 156–163.

Borenstein, M., Hedges, L., Higgins, J., Rothstein, H.(2005) Comprehensive meta-analysis (version 2) [Com-puter software]. Englewood, NJ: Biostat.

Briner, R. B., & Reynolds, S. (1999). The costs, benefits,and limitations of organizational level stress interven-tions. Journal of Organizational Behavior, 20, 647–664.

*Bruning, N. S., & Frew, D. R. (1986). Can stress interven-tion strategies improve self-esteem, manifest anxiety, andjob satisfaction? A longitudinal field experiment. Journalof Health and Human Resources Administration, 9, 110–124.

*Bruning, N. S., & Frew, D. R. (1987). Effects of exercise,relaxation, and management skills training on physiolog-ical stress indicators: A field experiment. Journal ofApplied Psychology, 72, 515–521.

Bunce, D., & Stephenson, K. (2000). Statistical consider-ations in the interpretation of research on occupationalstress management interventions. Work & Stress, 14,197–212.

*Carson, J., Cavagin, J., Bunclark, J., Maal, S., Gournay,K., Kuipers, E., et al. (1999). Effective communication inmental health nurses: Did social support save the psychi-atric nurse? NT Research, 4, 31–42.

Caulfield, N., Chang, D., Dollard, M. F., & Elshaug, C.(2004). A review of occupational stress interventions inAustralia. International Journal of Stress Management,11, 149–166.

*Cecil, M. A., & Forman, S. G. (1990). Effects of stressinoculation training and coworker support groups on

teachers’ stress. Journal of School Psychology, 28, 105–118.

Chalmers, I., & Haynes, B. (1994). Systematic reviews:Reporting, updating, and correcting systematic reviewsof the effects of health care. British Medical Journal,309, 862–865.

*Chen, S. (2006). Impact of enhanced resources on antici-patory stress and adjustment to new information technol-ogy: A field-experimental test of conservation of re-sources theory. Unpublished doctoral dissertation, TelAviv University, Tel Aviv, Israel.

Clark, C., Donovan, E. F., & Schoettker, P. (2006). Fromoutdated to updated, keeping clinical guidelines valid.International Journal for Quality in Health Care, 18,165–166.

Cohen, J. (1988). Statistical power analysis for the behav-ioral sciences. New York: Academic Press.

Cohen, J. (1992). A power primer. Psychological Bulletin,112, 155–159.

Cohen, S., Kamarck, T., & Mermelstein, R. (1983). Aglobal measure of perceived stress. Journal of Healthand Social Behavior, 24, 385–396.

*Collins, A. E. (2004). Promoting well-being in the work-place: A tailored approach to stress management. Bowl-ing Green, KY: Bowling Green State University.

Cook, T. D., & Campbell, D. T. (1976). The design andconduct of quasi-experiments and true experiments infield settings. In D. M. Dunnette (Ed.), Handbook ofindustrial and organizational psychology (pp. 223–326).Chicago: Rand McNally.

DeFrank, R. S., & Cooper, C. L. (1987). Worksite stressmanagement interventions: Their effectiveness and con-ceptualizations. Journal of Managerial Psychology, 2,4–10.

*de Jong, G. M., & Emmelkamp, P. M. G. (2000). Imple-menting a stress management training: Comparativetrainer effectiveness. Journal of Occupational HealthPsychology, 5, 309–320.

Dickersin, K. (2005). Publication bias: Recognizing theproblem, understanding its origin and scope, and prevent-ing harm. In H. R. Rothstein, A. J. Sutton, & M. Boren-stein (Eds.), Publication bias in meta-analysis: Preven-tion, assessment and adjustments (pp.11–33). Chichester,England: Wiley.

Duval, S. (2005). The trim and fill method. In H. R. Roth-stein, A. J. Sutton, & M. Borenstein (Eds.), Publicationbias in meta-analysis: Prevention, assessment and ad-justments (pp. 127–144). Chichester, England: Wiley.

Duval, S. J., & Tweedie, R. L. (2000). A non-parametric“trim and fill” method of accounting for publication biasin meta-analysis. Journal of the American StatisticalAssociation, 95, 89–98.

Eden, D. (2001). Job stress and respite relief: Overcominghigh-tech tethers. Exploring Theoretical Mechanismsand Perspectives, 1, 143–194.

Eden, D. (2002). Replication, meta-analysis, scientificprogress, and AMJ’s publication policy. Academy ofManagement Journal, 45, 841–846.

Edwards, D., Hannigan, B., Fothergill, A., & Burnard, P.(2002). Stress management for mental health profession-als: A review of effective techniques. Stress and Health,18, 203–215.

Ellis, A. (1962). Reason and emotion in psychotherapy.New York: Lyle Stuart.


*Fava, M., Littman, A., Halperin, P., Pratt, E., Drews, F. R.,Oleshansky, M., et al. (1991). Psychological and behav-ioral benefits of a stress/type A behavior reduction pro-gram for healthy middle-aged army officers. Psychoso-matics, 32, 337–342.

*Fiedler, N., Vivona-Vaughan, E., & Gochfeld, M. (1989).Evaluation of a work site relaxation training programusing ambulatory blood pressure monitoring. Journal ofOccupational Medicine, 31(7), 595–602.

*Ganster, D. C., Mayes, B. T., Sime, W. E., & Tharp, G. D.(1982). Managing organizational stress: A field experi-ment. Journal of Applied Psychology, 67, 533–542.

Giga, S. I., Cooper, C. L., & Faragher, B. (2003). Thedevelopment of a framework for a comprehensive ap-proach to stress management interventions at work. In-ternational Journal of Stress Management, 10, 280–296.

Giga, S. I., Noblet, A. J., Faragher, B., & Cooper, C. L.(2003). The UK perspective: A review of research onorganizational stress management interventions. Austra-lian Psychologist, 38, 158–164.

*Gildea, T. J. (1988). Anger management in the treatment ofmild hypertension. Unpublished doctoral dissertation, St.John’s University.

Higgins, J. P. T., & Green, S. (Eds.). Cochrane handbookfor systematic reviews of interventions 4.2.5 [updated inMay 2005]. In: The Cochrane Library, Issue 3, 2005.Chichester, UK: John Wiley & Sons, Ltd.

Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman,D. G. (2003). Measuring inconsistency in meta-analysis.British Medical Journal, 327, 557–560.

*Higgins, N. C. (1986). Occupational stress and workingwomen: The effectiveness of two stress reduction pro-grams. Journal of Vocational Behavior, 29, 66–78.

*Hoke, C. (2003). The effectiveness of an electronic-mailcampaign to modify stress levels, mood states, and cop-ing techniques among employed adults. Unpublisheddoctoral dissertation, University of North Texas.

House, J. S. (1981). Work stress and social support. Read-ing, MA: Addison-Wesley.

Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in research findings.Newbury Park, CA: Sage.

Ivancevich, J. M., Matteson, M. T., Freedman, S. M., &Phillips, J. S. (1990). Worksite stress management inter-ventions. American Psychologist, 45, 252–261.

*Jackson, S. E. (1983). Participation in decision making asa strategy for reducing job-related strain. Journal ofApplied Psychology, 68, 3–19.

Karasek, R. (1979). Job demands, job decision latitude, andmental strain: Implications for job redesign. Administra-tive Science Quarterly, 24, 285–306.

*Kolbell, R. M. (1995). When relaxation is not enough. InL. R. Murphy, J. J. Hurrell, S. L. Sauter, & G. P. Keita(Eds.), Job stress interventions (pp. 31–43). Washington,DC: American Psychological Association.

*Lee, S., & Crockett, M. S. (1994). Effect of assertivenesstraining on levels of stress and assertiveness experiencedby nurses in Taiwan, Republic of China. Issues in MentalHealth Nursing, 15, 419–432.

Lipsey, M. W., & Wilson, D. B. (1993). The efficacy ofpsychological, educational, and behavioral treatment:Confirmation from meta-analysis. American Psycholo-gist, 48, 1181–1209.

Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.

Lutgendorf, S. K., Antoni, M. H., Ironson, G., Starr, K.,Costello, N., Zuckerman, M., et al. (1998). Changes incognitive coping skills and social support during cogni-tive behavioral stress management intervention and dis-tress outcomes in symptomatic human immunodeficiencyvirus (HIV)-seropositive gay men. Psychosomatic Med-icine, 60, 204–214.

*Maddi, S. R., Kahn, S., & Maddi, K. L. (1998). Theeffectiveness of hardiness training. Consulting Psychol-ogy Journal: Practice and Research, 50, 78–86.

Meichenbaum, D. (1975). A self-instructional approach tostress management: A proposal for stress inoculationtraining. In C. D. Spielberger & J. G. Sarason (Eds.),Stress and anxiety (Vol. 1, pp. 237–263). New York:Halstead Press.

Meichenbaum, D. (1977). Cognitive behavior modification.New York: Plenum Press.

Mimura, C., & Griffiths, P. (2002). The effectiveness ofcurrent approaches to workplace stress management inthe nursing profession: An evidence based literature re-view. Occupational Environmental Medicine, 60, 10–15.

Morley, S., Eccleston, C., & Williams, A. (1999). System-atic review and meta-analysis of randomized controlledtrials of cognitive behaviour therapy and behaviour ther-apy for chronic pain in adults, excluding headache. Pain,80, 1–13.

Murphy, L. R. (1984a). Occupational stress management: Areview and appraisal. Journal of Occupational Psychol-ogy, 57, 1–15.

*Murphy, L. R. (1984b). Stress management in highwaymaintenance workers. Journal of Occupational Medi-cine, 26(6), 436–442.

Murphy, L. R. (1996). Stress management in work settings:A critical review of health effects. American Journal ofHealth Promotion, 11(2), 112–135.

Murphy, L. R., & Sauter, S. L. (2003). The USA perspec-tive: Current issues and trends in the management ofwork stress. Australian Psychologist, 38, 151–157.

Newman, J. E., & Beehr, T. A. (1979). Personal and orga-nizational strategies for handling job stress: A review ofresearch and opinion. Personnel Psychology, 32, 1–43.

Nicholson, T., Duncan, D. F., Hawkins, W., Belcastro,P. A., & Gold, R. (1988). Stress treatment: Two aspirins,fluids, and one more workshop. Professional Psychol-ogy: Research and Practice, 19, 637–641.

Nigam, J. A. S., Murphy, L. R., & Swanson, N. G. (2003).Are stress management programs indicators of goodplaces to work? Results of a national survey. Interna-tional Journal of Stress Management, 10, 345–360.

Osipow, S. H., & Spokane, A. R. (1983). Manual formeasures of occupational stress, strain and coping(Form E-2). Columbus, OH: Marathon Consulting &Press.

*Peters, K. K., & Carlson, J. G. (1999). Worksite stressmanagement with high-risk maintenance workers: A con-trolled study. International Journal of Stress Manage-ment, 6, 21–44.

*Peters, R. K., Benson, H., & Peters, J. M. (1977). Dailyrelaxation response breaks in a working population: II.Effects on blood pressure. American Journal of PublicHealth, 67, 954–959.

*Peters, R. K., Benson, H., & Porter, D. (1977). Daily


relaxation response breaks in a working population: I.Effects on self-reported measures of health, performance,and well-being. American Journal of Public Health, 67,946–953.

Pettegrew, L. S., & Wolf, G. E. (1982). Validating measuresof teacher stress. American Educational Research Jour-nal, 19(3), 373–396.

*Pruitt, R. H. (1992). Effectiveness and cost efficiency ofinterventions in health promotion. Journal of AdvancedNursing, 17, 926–932.

Rothstein, H. R., McDaniel, M. A., & Borenstein, M.(2001). Meta-analysis: A review of quantitative cumula-tion methods. In N. Schmidt & F. Drasgow (Eds.), Ad-vances in measurement and data analysis. San Francisco:Jossey-Bass.

Rothstein, H. R., Sutton, A. J., & Borenstein, M. (2005).Publication bias in meta-analysis. In H. Rothstein, A. J.Sutton, & M. Borenstein (Eds.), Publication bias inmeta-analysis: Prevention, assessment and adjustments(pp. 1–7). Chichester, England: Wiley.

Rybarczyk, B., Stepanski, E., Fogg, L., Lopez, M., Barry,P., & Davis, A. (2005). Placebo-controlled test of cog-nitive– behavioral therapy for comorbid insomnia inolder adults. Journal of Clinical and Consulting Psychol-ogy, 73, 1164–1174.

Sandman, B. A. (1992). The measurement of job stress:Development of the Job Stress Index. In C. J. Cranny,P. C. Smith, & E. F. Stone (Eds.), Job satisfaction: Howworkers feel about their jobs and how it affects theirperformance (pp. 241–254). New York: LexingtonBooks.

*Shapiro, S. L., Astin, J. A., Bishop, S. R., & Cordova, M.(2005). Mindfulness-based stress reduction for healthcare professionals: Results from a randomized trial. In-ternational Journal of Stress Management, 12, 164–176.

*Sharp, J. J., & Forman, S. G. (1985). A comparison of twoapproaches to anxiety management for teachers. Behav-ior Therapy, 16(4), 370–383.

*Shimazu, A., Kawakami, N., Irimajiri, H., Sakamoto, M.,& Amano, S. (2005). Effects of web-based psychoedu-cation on self-efficacy, problem solving behavior, stressresponses and job satisfaction among workers: A con-trolled clinical trial. Journal of Occupational Health, 47,405–413.

Smith, J. C. (1990). Cognitive-behavioral relaxation train-ing: A new system of strategies for treatment and assess-ment. New York: Springer.

Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970).STAI manual for the State-Trait Inventory. Palo Alto,CA: Consulting Psychologists Press.

*Stanton, H. E. (1991). The reduction in secretarial stress.Contemporary Hypnosis, 8, 45–50.

Stein, B. D., Jaycox, L. H., Katoaka, S. H., Wong, M., Tu,W., Elliott, M. N., et al. (2003, August 6). A mentalhealth intervention for schoolchildren exposed to vio-lence. JAMA, 290, 603–611.

Taylor, M. W. (1991). Effects of initial stress level, socialsupport, and participation in an exercise or music con-dition on the posttreatment stress, depression, and anx-

iety of nurses. Unpublished doctoral dissertation, St.John’s University

*Thomason, J. A., & Pond, S. B. (1995). Effects of instruc-tion on stress management skills and self-managementskills among blue-collar employees. In L. R. Murphy,J. J. Hurrell, S. L. Sauter, & G. P. Keita (Eds.), Job stressinterventions (pp. 7–20). Washington, DC: AmericanPsychological Association.

*Tsai, S., & Crockett, M. S. (1993). Effects of relaxationtraining, combining imagery, and meditation on the stresslevel of Chinese nurses working in modern hospitals inTaiwan. Issues in Mental Health Nursing, 14, 51–66.

*Tunnecliffe, M. R., Leach, D. J., & Tunnecliffe, L. P.(1986). Relative efficacy of using behavioral consultationas an approach to teacher stress management. Journal ofSchool Psychology, 24, 123–131.

U. S. Department of Labor. (1999). Report on the Americanworkforce. Washington, DC: Author.

van der Hek, H., & Plomp, H. N. (1997). Occupationalstress management programmes: A practical overview ofpublished effect studies. Occupational Medicine, 47(3),133–141.

van der Klink, J. J. L., Blonk, R. W. B., Schene, A. H., &van Dijk, F. J. H. (2001). The benefits of interventionsfor work-related stress. American Journal of PublicHealth, 91, 270–276.

*Vaughn, M., Cheatwood, S., Sirles, A. T., & Brown, K. C.(1989). The effect of progressive muscle relaxation onstress among clerical workers. American Association ofOccupational Health Nurses Journal, 37(8), 302–306.

*von Baeyer, C., & Krause, L. (1983–1984). Effectivenessof stress management training for nurses working in aburn treatment unit. International Journal of Psychiatryin Medicine, 13, 113–126.

Whiting, P., Bagnall, A. M., Sowden, A. J., Cornell, J. E.,Mulrow, C. D., & Ramirez, G. (2001, September 19).Interventions for the treatment and management ofchronic fatigue syndrome: A systematic review. JAMA,286, 1360–1368.

*Wirth, B. S. (1992). Effects of a leader-facilitated stressmanagement program and a self-taught stress manage-ment program on locus-of-control, absenteeism, andphysiological symptoms of bakery employees. Unpub-lished doctoral dissertation, Temple University.

*Yung, P. M. B., Fung, M. Y., Chan, T. M. F., & Lau,B. W. K. (2004). Relaxation training methods for nursemanagers in Hong Kong: A controlled study. Interna-tional Journal of Mental Health Nursing, 13, 255–261.

*Zolnierczyk-Zreda, D. (2002). The effects of worksitestress management intervention on changes in copingstyles. International Journal of Occupational Safety andErgonomics, 8(4), 465–482.

*Indicates study was used in the meta-analysis.

Received June 1, 2006Revision received February 17, 2007

Accepted March 18, 2007 y


Documents

Effects of Occupational Stress Management Intervention ... JOHP... · Effects of Occupational Stress Management Intervention Programs: A Meta-Analysis Katherine M. Richardson and