A META-ANALYTICAL STUDY ON THE EFFECTS OF COGNITIVE BEHAVIORAL TECHNIQUES FOR REDUCING DISTRESS IN ORGANIZATIONS

All studies included a control group and were conducted on participants with no identified clinical symptoms, belonging to different types of organizational environments. In some studies, the participants were not part of a specific organization (e.g., unemployed at the time or students) but we included the results in our analysis because the intervention program was designed to reduce work-related distress. The selected studies described the intervention strategy as based on cognitive behavioral approaches. Using standardized methods, 23 mean effect sizes were calculated (see Table 1). Overall, effect sizes were based on the report of 1282 subjects. To avoid the possibility that studies with larger number of dependent variables would influence the final overall estimate of the impact of cognitive behavioral intervention, effect sizes were calculated as the mean effect for each paper. We calculated an overall effect size for the 23 studies included. A second set of analyses were conducted in order to calculate the effect size for REBT (we included in this category studies that described the intervention as being based on REBT or that specifically described the procedure according to REBT principles (Ellis, 1994)). In order to assess the effectiveness of the intervention programs in reducing the level of irrationality, we calculated the mean effect size from the studies that included evaluations of irrational beliefs.

The effectiveness of the interventions was assessed by different types of distress evaluations.  Since various outputs were reported, we coded them under the following categories: 1. direct evaluations of emotional distress; 2. consequences of emotional distress (e.g., self-esteem, indifference, absenteeism, and burnout).  Coding was done by two trained specialists in Psychology. An inter-rater agreement of k = 0.93 was obtained. Effect sizes were calculated according to published procedures (Hunter & Schmidt, 1990). Mean differences between the cognitive behavioral intervention groups and control groups were calculated for each study and then divided by the SD of the control group. The strength of the various effect sizes were interpreted using Cohen’s d criteria (i.e., 0.2-0.5 = small; 0.5.-08 = moderate; higher than 0.8 = large). To estimate the overall effect of cognitive behavioral interventions the 95% confidence interval (CI) was calculated.  If the 95% CI included zero, there would be no significant effect of the intervention. Next, effect sizes and 95 % CIs were calculated for each outcome category. CIs were assessed for the inclusion of zero to test the significance of the individual category effects, and a between group analyses of variance (ANOVA) was conducted to determine if the categories differed from each other. Taking into consideration that the decrease in emotional distress is a positive outcome, the “-“ sign in our analyses indicates an effect in favor of  the intervention (see Table 2).

 

Results

 

The meta- analysis revealed a significant benefit of cognitive behavioral interventions in reducing distress in organizational settings. Mean effect sizes averaged within studies, type of intervention, type of control condition, and 95% CIs are presented in Table 1.

The analysis of this data shows a large mean effect size due to cognitive behavioral interventions. A large average effect size of d = -0.92, 95% CI (-1.32 to -0.64) was obtained (see Table 2).

 

 

Table 1. Effect sizes and study characteristics

 

Crt. No	Study	Year	N (no. of subjects)	Type of intervention	Control	Mean effect size (d) / study	No. of effect sizes/ study
1	Forman, S.	1982	24	REBT	Wait list	-1.09	3
2	Thurman, C.	1985	21	CBT based	No intervention	-1.1	3
3	Sharp, J. & Forman, S	1985	60	REBT	control	-2.05	3
4	Tunnecliff, M. et al.	1986	7	CBT based	Control	-1.65	1
5	Cecil, M. & Forman, S.	1990	54	CBT based	control	-0.35	12
6	Hains, T.  et al.	1992	25	CBT based	Waiting list	-0.91	8
7	Kirkby, R.	1994	25	REBT based	Waiting list	-0.81	3
8	Lee, S. & Crocket, M.	1994	57	REBT based	control	-0.64	3
9	Kushnir, T.	1995	19	REBT based	Waiting list	-2.5	2
10	Malkinson, R. et al.	1997	27	REBT based	Waiting list	-0.83	4
11	Kushnir  et al.	1998	45	REBT based	Waiting list	-1.66	2
12	Maynard, W.I.	1998	41	CBT based	No intervention	-1.61	6
13	Bond, F. & Bunce, D.	2000	44	CBT based	No intervention	-0.12	2
14	Grime, P	2004	48	CBT based	No intervention	-0.63	2
15	Flaxman, P. & Bunce, F.	2004	87	CBT based	Control	-0.23	3
16	Gardner, B.  et al.	2005	92	CBT based	Waiting list	-0.61	2
17	Main, N. et al.	2005	45	CBT based	Wait list	-0.43	2
18	Shimazu, A. et al	2005	204	CBT based	No intervention	-0.21	4
19	Adomeh, O.C.I. et al.	2006	25	REBT based	No intervention	-0.52	2
20	Grant, M.A.	2006	20	CBT based	No intervention	-0.79	3
21	Granath, J. et al.	2006	19	CBT based	No intervention	-0.93	5
22	Ruwaard, J. et al	2007	239	CBT based	No intervention	-0.48	4
23	deVente, W.  et al.	2008	54	CBT based	No intervention	-0.92	6

Note: CBT based – programs based on Cognitive Behavioral Therapy; REBT based – programs based or including components of Rational Emotive Behavioral Therapy.

 

Table 2. Mean effect size for each  outcome category

 

Categories	d	No. of effect sizes/ category	95% CI
CBT – general	-0.92	80	(-1.32 to -0.64)
Irrationality	-1.74	6	(-2.68 to -0.79)
Direct evaluations of emotional distress	-0.72	38	(-1.2 to -0.52)
Consequences of emotional distress	-0.64	36	(-1.16 to -0.54)

Note: d- effect size on the specified category;

 

 

Because effect size calculations can be biased by variations in individual study sample sizes, we run another analysis, correcting for sample size, based on published procedures (Hunter & Schmidt, 1990). Specifically, both the mean difference and the variation of difference were adjusted for variation in the study sample size (D and VarD, respectively).  Results indicate a large weighted effect size (D = -0.81, VarD = 0.24) while the 95% CI shows that D differs significantly from zero (-1.72 to -0.45) (see table 3).

Table 2 illustrates the medium effect sizes and 95 % CI for each category. Analysis of these results shows that cognitive behavioral interventions are effective both for reducing the level of irrationality and the level of distress evaluated either directly or through its consequences. We run the analysis again for correction of d for each category. For irrationality, a corrected D = -1.6, Var D = 0.4 and 95% CI (-2.35 to -0.85) emerged (see Table 3).

 

Table 3. Corrected mean effect size for each outcome category

 

Categories	D	Var D	95% CI
CBT – general	-0.81	0.24	(-1.72 to -0.45)
Irrationality	-1.6	0.41	(-2.35; -0.85)
Direct evaluations of emotional distress	-0.73	0.04	(-1.23 to -0.55)
Consequences of emotional distress	-0.69	0.02	(-1.12 to -0.33)

Note: corrected effect size on the specified outcomes

 

 

This is a significant effect size, which confirms the effectiveness of cognitive behavioral interventions in reducing irrationality. For direct evaluations of distress we obtained a D = -0.73, VarD = 0.04, 95% CI (-1.23 to -0.55). For evaluations of emotional distress consequences we obtained D = -0.69, VarD = 0.02, 95% CI (-1.12 to -0.33) (see table 3). These values show the effectiveness of the cognitive behavioral interventions in reducing distress, with a larger effect size when the outcome was evaluated directly. An ANOVA approach failed to reveal any differences in effectiveness (F [1, 78] = 1.52, p > 0.05) based on outcome categories. Rather, the examination of the effect sizes and CIs for each category revealed that cognitive behavioral interventions had significant effects on all outcomes, in the expected direction. These results support the view that there is a broad beneficial impact of cognitive behavioral interventions in organizational settings across outcome categories. The same pattern of results was found for unadjusted effect sizes. In the next step, we run an analysis separating studies based (or including a core component) on the REBT theoretical framework from other CBT-based intervention programs. We found a total of 8 studies that circumvented our inclusion criteria, being included in the REBT-based category. Results are detailed in Table 4 and Table 5.

 

Table 4. Mean effect size for each CBT based and REBT based interventions

 

Categories	d	No. of effect sizes/ category	95% CI
CBT based	-0.73	15	(-1.41;-0.55)
REBT based	-1.16	8	(-1.65; -0.68)-

Note: CBT based – programs based on Cognitive Behavioral Therapy; REBT based – programs based or including components of Rational Emotive Behavioral Therapy.

 

 

Table 5. Corrected mean effect size for each CBT based and REBT based interventions

 

Categories	D	Var D	95% CI
CBT based	-0.52	0.11	(-0.68; -0.35)
REBT based	-1.14	0.4	(-1.59; -0.69)

Note: CBT based – programs based on Cognitive Behavioral Therapy; REBT based – programs based or including components of Rational Emotive Behavioral Therapy.

 

 

We calculated the effect size for each category (i.e., REBT-based and CBT-based) of intervention programs. For CBT-based programs (15 mean effect sizes) the mean effect size, calculated according to the described procedure, was d = -0.73, 95% CI (-1.41 to -0.55), while for the REBT category (8 mean effect sizes), it was d = -1.16, 95% CI (-1.65 to-0.68). The range of d values (based on Cohen ‘criteria) indicates a difference between the two categories. In the case of REBT-based intervention programs a strong effect size emerged, while in the case of CBT-based intervention programs, the effect size fell only into the moderate range. A further analyses using ANOVA was conducted yielding a significant difference between the two categories (F [1, 21)] = 4.57, p < 0.05). The difference between the two effect sizes is maintained even after correcting d for variation in study sample size. For CBT-based intervention programs we obtained a D = -0.52 (moderate effect size), Var D = 0.1, and 95% CI (-0.68 to -0.35), while for REBT-based intervention programs, we obtained a D = -1.14 (large effect size), Var D = 0.11, and 95% CI (-1.59 to -0.69) (see Table 4 and Table 5). Thus, the results show the efficiency of both types of intervention in reducing distress, with a stronger effect in favor of REBT-based intervention programs.

 

Discussion and conclusions

 

Distress responses and interventions on distress are hot topics in current research. However, approaches are heterogeneous and so are various distress response measures. On one hand, we have approaches coming from a clinical perspective, where participants are patients identified with different clinical symptoms. On the other hand, we have approaches from an organizational perspective, where we find differences regarding the specific nature of the organization and the personal characteristics of the participants included in the study.

Measures of distress response also differ between the two categories of approaches. While in the clinical environment distress is evaluated mainly directly, through modifications in anxiety levels, depression etc., in the organizational environment, distress can be evaluated both directly and indirectly, by assessing the effects of distress on behaviors such as absenteeism, indifference, fatigue, burnout etc.

Given this rich literature on the topic, as well as the heterogeneity of approaches and distress measures, we conducted a quantitative meta-analysis of studies discussing CBT-based interventions on distress in organizational settings. Results revealed that cognitive behavioral interventions have a significant effect in reducing distress. Indeed, the overall mean effect size (calculated for all the studies) indicates a strong effect of cognitive behavioral interventions on reducing distress (d = -0.92). This is in accord with previous results reported by Richardson and Rothstein (2008), (d = 1.16). For a more detailed analysis, we coded results into two categories, based on inter-rater agreement (k = 0.93): direct evaluation of emotional distress and evaluation of distress through its consequences. In both cases, the mean effect size was significant (d = -0.73, though in the case of evaluation through its consequences the effect size is slightly smaller, d = -0.69).

Given the numerous reports in the literature showing strong correlations between irrationality and various measures of distress in organizational settings (DiLorenzo et al., 2002; Grant, 2001; Sporrle, 2006), we ran a separate set of analyses including only the measures of irrationality. We found a strong mean effect size (d = – 1.6), showing the effectiveness of these interventions on reducing irrationality levels among people from different organizational settings. However, future studies, looking more thoroughly into the specific mechanisms that govern this relation are needed.

Another distinction in our study was made between studies based on the CBT theoretical framework and those based on the REBT framework. We have explained the reasons of this analysis in the introduction. On both categories (CBT and REBT), we obtained significant effect sizes. Even though the overall effect size for the general CBT category was in the “strong” category (d = -0.81), after separating the studies in REBT-based and other CBT-based, the strength of the effect sizes fell into the “moderate” category (d = -0.52) for CBT programs and remained in the “strong” category (d = -1.14) for REBT programs. The strong effect size for REBT supports the results reported in the literature regarding the high correlations between irrationality and distress. The mean effect size for the CBT category, situated in the moderate range, is consistent with the previous meta-analyses (van der Klink et al., 2001; Richardson & Rothstein, 2008). Richardson and Rothstein (2008) showed that single-mode cognitive–behavioral interventions have a stronger effect size than cognitive–behavioral interventions with more components (e.g., including relaxation, assertiveness training etc). This could explain the smaller (but  still significant) effect size for the CBT category in our analysis,  given the fact that most of the studies included in this category reported more than one component in the structure of the program. However, even the studies in the REBT category contained a core REBT component along with other techniques. Therefore, maybe this difference could be explained by Ellis’ argument that REBT targets more core beliefs (i.e., irrational beliefs) as compared to general CBT, and thus, it is faster and sometimes more efficacious; however, future studies should directly investigate this supposition, by directly comparing REBT and CBT in organizational settings, in the same experimental design.

As most meta-analytic research, the present study has several limitations. We excluded a number of studies where the intervention method was not clearly defined, retaining only those where the intervention was explicitly described as being based on cognitive behavioral principles. However, we have done this explicitly, arguing our decision (see also the file-drawer analysis below). Another limit of the present study is the wide range of settings from where data were collected.  Even though the overall effect size is in favor of CBT/REBT-based programs, the intervention procedure differed across studies according to their aims and the characteristics of the population included. This led to various measures of distress across the studies included in our meta-analysis. We tried to overcome this limitation by categorizing the results based on the method of assessing emotional distress. Nevertheless, there is a wide range of measures to evaluate distress in the literature, making it difficult to combine the studies. On the other side, this increases the generalizability of the results and their robustness across distress evaluations methods. The third limitation refers to follow-up measures. Because only one study reported follow-up data, we were not able to include this aspect our research. Consequently, our analysis is based only on post-intervention measures. Finally, because of the wide diversity in organizations and participants characteristics, we did not include socio-demographic analyses in our study.

As with any meta-analysis, there is what is referred to as the file-drawer problem. Investigators who obtained no significant results may have not published their findings, thus biasing the sample of studies in the expected direction. To overcome this limitation, we calculated, using published procedures (Hunter & Schmidt, 1990), the number of studies with effect sizes of zero that would be needed to annul our results. In this case, 1194 studies indicating no effect should be published to affect the results presented here.

In summary, CBT programs are efficient in approaching emotional distress in organizational settings. Out of these, REBT based intervention programs seems to be the most efficient, as supported by a mean effect size situated in the “strong” range according to Cohen’s criteria. However, even if the mean effect size for CBT-based intervention programs, after removing studies based on REBT, decreased into the “moderate” range, it still remained significant. Overall, CBT interventions are efficient in reducing distress and its job related consequences, with a higher effect when the program is based or includes a core component of REBT. These findings strongly support the development of future programs that emphasize the importance of REBT and irrational cognitions by including them as a core components of the intervention. Indeed, our findings suggest that effective interventions should focus on the modification of core irrational beliefs as precursors of dysfunctional emotions in order to modulate the response to stressors in organizational environment.

Considering these results and other findings reported in the literature regarding the relation between irrationality and distress, future studies should further explore the interactions between irrationality and distress in organizational setting. In addition, specific programs, based on the REBT theoretical framework can be designed for the modification of irrational beliefs and for the evaluation of the impact of irrationality on distress and other constructs such as performance, motivation, perceived quality of life, which we know to be highly correlated with distress. This can be the basis of a comprehensive intervention model in organizations with implications and benefits at both individual and organizational level.

 

Acknowledgements:

Investing in people!

Ph.D. scholarship, Project co-financed by the SECTORAL OPERATIONAL PROGRAM FOR HUMAN RESOURCES DEVELOPMENT 2007 – 2013

Priority Axis 1. “Education and training in support for growth and development of a knowledge based society”

Key area of intervention 1.5: Doctoral and post-doctoral programs in support of research.

Contract nr.: POSDRU 6/1.5/S/4 – “Doctoral studies, a major factor in the development of socio-economic and humanistic studies”

Babeş-Bolyai University, Cluj-Napoca, Romania

 

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