The Interplay of Locus of Control and Role Stress-evidences from Healthcare Sector

Abstract

The ability to handle the stress is largely dependent on the various personality factors. One such factor is locus of control (LOC). Over the past years, it has been indicated that persons who have internal LOC are able to manage the stress more effectively than the one’s having external LOC. The findings of the present study proved otherwise. The results of this study showed that moderate levels of both internal and external control decrease the levels of role stress. The study was conducted in the healthcare sector. Doctors from government hospitals were approached and data collected from them was subjected to ‘hierarchical moderated regression analysis’. The findings of this study can assist administrators and policymakers in the healthcare sector to provide a stress-free working climate. This may help to decrease side effects and consequences of role stress and increase productivity of doctors. In light of the findings of the study, a few Stress management interventions have also been proposed, which may help doctors develop healthy ‘stress coping styles’.

Keywords

Doctor India Locus of Control Role Stress

Background of the Study

Stress at workplace is a cause of concern for organizations, so it needs to be tackled both by individuals as well as by organizations. However, the aim of the present study is largely to determine the intensity and perception of stress by individuals based on their personality attribute ‘locus of control’ (LOC). Numerous studies have shown that the individual’s ability to cope with stress depends on his/her way of looking at life events. The research variable LOC included in the present investigation is globally regarded as an effective measurement of general coping. However, to the best of researcher’s knowledge, there are relatively few LOC studies that have been conducted in work setting, particularly in the Indian context. Moreover, coping effectiveness is likely to be influenced by certain personality variables (Holahan & Gilbert, 1979). LOC, being an important personality variable has a direct bearing with the ‘stress coping strategies’. So, to add to the utility of the present study, coping strategies have also been focused upon.

The utilization of the study may be justified by the fact that use of potentiality of human resource can help organizations to obtain competitive advantage over other firms. Also, there is a dearth of research on role stress as well as LOC in healthcare professionals, specifically, in India. The present study may add to the existing body of literature of the variables under consideration.

Literature Review

Literature review indicates that LOC is an antecedent of role stress (Organ & Greene, 1974; Cohen & Edwards, 1989; Kliewer & Sandler, 1992; Seifer et al., 1991; Cumins, 1989; Weigel et al., 1989; Cooper et al., 1994; Rashid & Talib, 2013). Although Keenan and McBain (1979) argued that there is a lack of conceptual support for this relationship, later researchers have proposed several explanations. For instance, Singh and Rhoads (1991) found that those with an internal LOC (ILOC) experience less role ambiguity, since they tend to be better informed about their role and task environment. Similarly, Emster and Harrison (1998) argued that ‘internals’ have a greater sense of control over situations and as a result experience less role ambiguity. Kalbers and Fogarty (1995) found those with an ILOC are less likely to experience a high level of stress but those with an external LOC (ELOC) are more likely to be vulnerable to stress and are more likely to perceive certain events as stressful.

An investigation of the effects of LOC and task complexity on task characteristics (Perrewe and Mizerski, 1987) reported that higher job enrichment was perceived by ILOCs on complex tasks and by ELOCs on simple tasks. In their meta-analysis on LOC in the working environment, Ng et al. (2006) found that individuals with ILOC reported higher levels of job motivation and have more positive social experiences. Researchers have also noted that externals are more likely to resort to the use of coercive power while internals are more likely to use persuasive forms of power (e.g., Goodstadt & Hjelle, 1973; Mitchell et al., 1975). It has also been found that internals are more considerate supervisors and are more satisfied in a participative work environment (Hendricks, 1985; Licata et al., 1986; Mitchell et al., 1975; Smith et al., 1971; Runyon, 1973; Spector, 1988). Entrepreneurial behaviour has also been related with LOC in a number of studies (Begley & Boyd, 1987; Bowen & Hisrich, 1986; Brockhaus, 1976; Durand & Shea, 1974; Miller & Toulouse, 1986; Shapero, 1975; Taylor, 1985). The findings of these studies showed that internals are more actively oriented and are likely to possess entrepreneurial qualities (e.g., take risks). The beneficial effects of ILOC on well-being has been studied in the areas of both work and general life (e.g., Doef & Maes, 1999; Frese, 1989; Judge et al., 1998; Lefcourt et al., 1981; Ross & Mirowsky, 1989). Overall, internals were found to have more favourable attitude, less dysfunctional behaviours and higher levels of performance on the job (Blau, 1984; Fusilier et al., 1987; Mia, 1987; Storms & Spector, 1987). Conversely, externals have been shown to report more burnout (Glogow, 1986; McIntyre, 1984), job dissatisfaction (Spector, 1982), stress (Halpin & Harris, 1985; Lester, 1982), alienation (Korman et al., 1981), and lower self-esteem (Lester, 1986). In addition, these researchers concluded that ELOC has a significant negative influence on job stress and tends to reduce personal accomplishments and job performance. Other researchers (Parkes, 1994; Wheaton, 1983) have shown that LOC moderated the relationship between stress and mental health.

LOC has also been found as an important construct for stress coping as well. Research has shown that individuals who are inclined to view events as more internally controllable tend to exhibit higher levels of coping, self-efficacy, and increased use of problem-focused coping behaviour (Chwalisz et al., 1992; Rahim, 1996). Conversely, an ELOC has been found to be related to poor coping with stress, increased used of emotion-focused coping behaviour and self-defeating personality styles (Folkman, 1984; Schill & Beyler, 1992).

The sum of the findings of above-mentioned studies suggests that internality plays a significant role in human development and purposeful living. Nevertheless, negative consequences of being internal have also been noted. For example, those who perceive their own abilities and actions as exclusively responsible for their failures are likely to be more stressed and may become more self-punitive (Mitchell et al., 1979).

Research Methods

Primary quantitative data by questionnaire method were generated. Although previously used research instruments were employed for the study, but their validity and reliability aspect was checked in pilot testing.

Organizational role stress (ORS) is the dependent variable of the study. ORS occurs due to 10 variables, namely inter role distance, role stagnation, role expectation conflict, role erosion, role overload, role isolation, personal inadequacy, self-role distance, role ambiguity and resource inadequacy (Pareek, 1986).

Independent variable for the study is ‘coping styles’ (CS). Two types of coping styles, namely ‘approach or effective coping’ and ‘avoidance or ineffective coping’, were considered for the present study. They were further sub-divided into four categories.

‘Approach coping strategies’ include the following styles of coping: impersistive, intropersistive, extrapersistive and interpersistive.

‘Avoidance coping strategies’ include the following styles of coping: impunitive, intropunitive, extrapunitive and defensive.

An important variable in the present study is a moderating variable, ‘LOC’. LOC is divided into two dimensions, namely ILOC and ELOC. The review of literature suggests that LOC is an important construct in role stress studies. A large number of studies have been carried out on moderating effects of LOC on role stress and other organizational aspects. The present study is an attempt to explore the interactive effect of LOC and coping strategies on role stress.

Introduction of moderator variable (LOC) helped us to broaden the scope of our study and draw more comprehensive results for dependent variable, that is, role stress, by exploring the interaction of coping styles and LOC.

C S \times L O C \to O R S

It may be concluded from the above discussion that the relationship between coping styles and role stress change under different conditions. That condition in the present study is a moderator variable, LOC. Introduction of LOC categorized the doctors into two groups, namely doctors with ILOC, doctors with ELOC. LOC helped to have a greater insight into the study and drawing of in-depth results based on type of control a group of doctors’ manifest. Moreover, to have a deeper insight into the nature of LOC as a moderator variable, each category of LOC was further divided into three subgroups. The independent variables and subgroups of each LOC variable were regressed with ORS.

Objectives of the Study

The aim of the study is:

to explore the moderating effect of LOC on ‘coping styles’ and ‘role stress’ and to identify the sources of role stress, their severity and coping strategies among doctors and

to propose the remedial measures for the management of stress.

Proposed Model for the Study

One of the research objectives is to develop a conceptual model depicting the relationships between the research variables, that is, ‘coping strategies’, LOC and ‘role stress’. Figure 1 shows the conceptual model specifying the relationships among the research variables. The reason for carrying out the proposed model for the present study is to find out whether ILOC alleviate/mitigate the approach coping strategy and ELOC exacerbate it.

Measurement Tools

The ORS scale by Pareek (1986) is used in the present study to measure 10 role stressors. ORS is a 5-point scale (0 to 4) containing 5 items for each role stressor and a total of 50 statements. Loco inventory given by Levenson (1972) has been employed for collecting data for the present study. The Loco inventory is a 5-point scale. Role Pics instrument proposed by Pareek et al. (1968) is used for the present study. Role pics is a semi-projective (Pics) instrument for assessing a respondent’s style or strategy to cope with role stress. The reliability of the scales was found to fall in a range between 0.76 and 0.98.

Sampling and Data Collection

The sampling method for the present study includes ‘area cluster convenience sampling’. In this technique, the total population was divided into two geographical areas, namely Central Kashmir and Western UP. Further, the doctors from both areas were divided into six groups/clusters based on their specializations, namely physicians, surgeons, paediatricians, gynaecologists, anaesthetists and dentists. The profession of the doctor being one of the busy professions so these specialists were approached on the basis of the convenience.

The researcher visited the hospitals and handed over the questionnaire to the concerned doctors in person. At most of the occasions, questionnaires were filled in presence of the researcher. While filling up the questionnaires, many doctors shared their work experiences with the researcher. This helped the researcher to have a deeper insight into the problem/stress faced by government doctors and the mode of coping they adopt.

Questionnaire was administered on 500 male and female doctors, approached through area cluster convenience sampling at three main government hospitals in Central Kashmir and five in Western UP 381 filled questionnaires were received, out of which only 334 were found complete in all respects. These were found fit for analysis, making it a response rate of 66.8%. Such response rate is considered to be satisfactory for this type of sampling frame. The profile of respondents is presented in Table 1.

Table 1.

Sampling Profile of Doctors

Demographics		Overall		Total	Peaceful Ambience (Western UP)		Total	Disturbed Ambience (Central Kashmir)		Total
Demographics		No.	% age	Total	No.	% age	Total	No.	% age	Total
Gender	Male	182	54.5	334	86	54.4	158	96	54.5	176
	Female	152	45.5		72	45.6		80	45.5
Experience (in years)	Less than 5 years	104	31.1	334	53	33.5	158	51	29.0	176
	5–15	100	29.9		53	33.5		47	26.7
	16–25	68	20.4		28	17.7		40	22.7
	26 and above	62	18.6		24	15.2		38	21.6
Specialization	Physicians	72	21.6	334	31	19.6	158	41	23.3	176
	Surgeons	67	20.1		41	25.9		26	14.8
	Paediatricians	54	16.2		22	13.9		32	18.2
	Gynaecologists	49	14.7		20	12.7		29	16.5
	Anaesthetists	46	13.8		18	11.4		28	15.9
	Dentists	46	13.8		26	16.5		20	11.4

Source: The author.

Data Analysis

Hierarchical Moderated Regression Analysis

The main focus of the present study is to test the moderating effects of LOC on the dependent (ORS) and independent variable (coping strategies) relationship. The procedure suggested by Baron and Kenny (1986) was used. In terms of multiple regression, moderation is tested using equation of the following form:

Y = b_{0} + b_{1} X + b_{2} Z + b_{3} X Z + e

(1)

A moderated relationship is said to exist when the cross-product term explains a meaningful amount of variation in the outcome variable (Jex, 1998). This is the most common statistical procedure used to detect moderator effects (Kirkman et al., 2004; Lingard & Francis, 2006; Yip et al., 2008).

In the present study, the dependent variable is ‘ORS’. Two broad types of coping strategies, namely approach and avoidance coping strategies were taken as independent variables. A personality construct ‘LOC’ was taken as a moderator variable. There are two categories of LOC, namely ILOC, ELOC. However, to have a deeper insight into the nature of LOC as a moderator variable, each category of LOC was further divided into three subgroups. The independent variables and subgroups of each LOC variable were regressed with ORS.

Hierarchical Regression Analysis of ORS, ILOC and Coping Styles

To detect the multicollinearity problem, collinearity diagnostics (variance inflation factor [VIF]) and (tolerance value [TV]) were carried out for predictors describing the given model. The values of VIF for predictors range from 1.201 to 4.987. These values are far below the cut off values of 10. In addition, it could be seen that tolerance value for all the predictors is almost closer to 1, except the interaction terms, but their VIF values are satisfactory. Thus, this indicates that there is no evidence of multicollinearity. It may also be noted that the interaction terms are closer to the limit of multicollinearity values in comparison to non-interaction terms.

Note: Multicollinearity problem was detected in case of ‘approach coping strategy’. To remove multicollinearity from approach strategy, each dimension of approach strategy (namely impersistive, intropersistive, extrapersistive and intropersistive) was checked for multicollinearity. It was found that the problem lies with intropersistive strategy. Hence, it was removed from the regression analysis, in accordance with the remedial measure suggested by Field (2005). So, approach coping strategy consisted of only remaining three dimensions (impersistive, intropersistive and extrapersistive) in further analysis. The VIF and TV values for approach coping strategy in Table 2 are after the removal of multicollinearity problem.

After testing the data for multicollinearity, regression analysis was carried out. Table 3 shows the results of regression with subgroups of ILOC as moderator. Table 3 has been divided into three blocks, namely Blocks A, B and C. These show the results of regression with high-ILOC, medium-ILOC and low-ILOC as moderators respectively.

Table 3 shows the variability coefficients (R²), unstandardized regression coefficients (B) of the predictors, on the criterion (ORS).

It may be noted from Table 3 that Durbin–Watson test statistic for models under consideration fall within a desirable ranges, that is, ‘between’ 1.28 and 1.90, which is close to the acceptable statistic (i.e., 2). This indicates that the residuals are independent; hence, one of the assumptions of regression analysis is complied with.

Analysis of Block A (Table 3)—high-ILOC (H-ILOC) as moderator—using hierarchical regression analysis, the following variables were entered in the sequence described below:

Table 2.

Summary Table of Variables

Independent Variables	Moderator Variables	Dependent Variable
1. Approach coping strategies	1. High internal locus of control	Organizational role stress
2. Avoidance coping strategies	2. Medium internal locus of control
	3. Low internal locus of control
	4. High external locus of control
	5. Medium external locus of control
	6. Low external locus of control

Source: The author.

In Model 1, two coping strategies, namely approach (App) and avoidance (Avd) coping strategies were entered simultaneously. In Model 2, the variable high-ILOC is added to the model along with the two coping strategies. In Model 3, interaction terms of each of the coping strategies were (H-ILOC × Approach and H-ILOC × Avoidance) were entered simultaneously along with the predictors entered in Model 2. The interaction terms were constructed by multiplying high-ILOC by each of the coping strategy.

Table 3.

Hierarchical Regression Analysis of ORS with Coping Strategies and ILOC

Block A H-ILOC as Moderator				Durbin–Watson Test	Block B M-ILOC as Moderator				Durbin–Watson Test	Block C L-ILOC as Moderator				Durbin–Watson Test
Predictors	R²	B	T	Durbin–Watson Test	Predictors	R²	B	T	Durbin–Watson Test	Predictors	R²	B	t	Durbin–Watson Test
Model 1				1.283	Model 1				1.283	Model 1				1.283
App Avd	0.289	−0.58 0.495	1.231* 3.130		App Avd	0.289	−0.58 0.495	1.231* 3.130		App Avd	0.289	−0.58 0.495	1.231* 3.130
App Avd	0.289	−0.58 0.495	1.231* 3.130		App Avd	0.289	−0.58 0.495	1.231* 3.130		App Avd		−0.58 0.495	1.231* 3.130
Model 2				1.345	Model 2				1.379	Model 2				1.398
App Avd H-ILOC	0.299	−0.46 0.560	2.22 2.02*		App Avd M-ILOC	0.325	−0.59 0.498 −0.45	3.211 −4.719 2.267		App Avd L-ILOC	0.290	−0.32 0.387 0.704	−0.68 −1.05 1.28
App Avd H-ILOC	0.299	0.821	3.23*		App Avd M-ILOC	0.325	−0.59 0.498 −0.45	3.211 −4.719 2.267		App Avd L-ILOC	0.290	−0.32 0.387 0.704	−0.68 −1.05 1.28
Model 3				1.834	Model 3				1.869	Model 3				1.902
App Avd H-ILOC App × H-ILOC Avd × H-ILOC	0.321	0.49 0.521 0.735 0.652 0.828	2.33 2.01 2.70 1.19 4.32**		App Avd M-ILOC App × M-ILOC Avd × M-ILOC	0.423	−0.50 0.890 −0.78 −0.46 0.633	−1.163 2.562 −0.679 2.834** 2.031		App Avd L-ILOC App × L-ILOC Avd × L-ILOC	0.292	−0.49	0.34
												−0.42	−1.98
												0.820	2.01
												0.762	1.313
												0.925	−0.33

Source: The author.

Notes: H-ILOC, High-ILOC; M-ILOC, Medium-ILOC; L-ILOC, Low-ILOC; App, Approach; Avd, Avoidance.

*p ≤ 0.05 and **p ≤ 0.01.

The results of hierarchical regression analysis are explained below:

Models	R² Values	Implications
1	R² = 0.289	This implies that 28.90% of the variance in ORS* is accounted for by the coping strategies, namely approach and avoidance coping strategies
2	R² = 0.299	This implies that 29.90% of the variance in ORS is accounted for by the coping strategies along with the variable high-ILOC.
3	R² = 0.321	This implies that 32.10% of the variance in ORS is accounted for by the two interaction terms, namely App × High-ILOC and Avd × High-ILOC.

Source: The author.

Note: ORS* = Organizational role stress.

The results in Table 3 (Block A) shows that the approach coping strategy is statistically significant negative predictor of ORS; while avoidance coping strategy and H-ILOC are statistically a significant positive predictors of ORS. Also the test of significance of ‘interaction term’ (Avd × H-ILOC) in Model 3 shows a significant positive effect (p < .01); while ‘interaction term’ (App × H-ILOC) failed to show significant results. The two terms accounted for 32.10% of the variation in ORS.

In other words, it may be noted that high-ILOC moderates the relationship between avoidance coping strategies and ORS while no moderation effect of high-ILOC was seen between ORS and approach coping strategy. This means that ‘avoidance coping strategy adopted by doctors having high-ILOC exhibit higher levels of stress than the doctors who adopt approach mode of coping’.

Analysis of Block B (Table 3)—medium ILOC (M-ILOC) as moderator—the results of hierarchical regression analysis for Block B are explained below:

Models	R² Values	Implications
1	R² = 0.289	This implies that 28.90% of the variance in ORS is accounted for by the coping strategies, namely approach and avoidance coping strategies.
2	R² = 0.325	This implies that 32.50% of the variance in ORS is accounted for by the coping strategies along with the variable medium-ILOC.
3	R² = 0.423	This implies that 42.30% of the variance in organizational role stress is accounted for by the two interaction terms, namely App × Medium-ILOC and Avd × Medium-ILOC.

Source: The author.

The results in Table 3 (Block B) shows that the approach coping strategy and the variable M-ILOC are statistically significant negative predictors of ORS; while avoidance coping strategy is statistically a significant positive predictor of ORS. Also the test of significance of ‘interaction term’ (App × M-ILOC) in Model 3 shows a significant negative effect (p < .01); while ‘interaction term’ (Avd × M-ILOC) failed to show significant results. The two terms accounted for 42.30% of the variation in organizational ORS.

In other words, it may be noted that medium-ILOC moderates the relationship between approach coping strategies and ORS (in negative direction) while no moderation effect of ILOC was seen between ORS and avoidance coping strategy. This means that ‘approach coping strategy adopted by doctors having medium-ILOC exhibit lower levels of stress than the doctors who adopt avoidance mode of coping’.

Analysis of Block C (Table 3)—low ILOC (L-ILOC) as moderator—the results of hierarchical regression analysis for Block C are explained below:

Models	R² Values	Implications
1	R² = 0.289	This implies that 28.90% of the variance in ORS is accounted for by the coping strategies, namely approach and avoidance coping strategies.
2	R² = 0.290	This implies that 29.0% of the variance in ORS is accounted for by the coping strategies along with the variable low-ILOC.
3	R² = 0.292	This implies that 29.20% of the variance in ORS is accounted for by the two interaction terms, namely App × Low-ILOC and Avd × Low-ILOC.

Source: The author.

The results in Table 3 (Block C) show that the approach coping strategy is statistically significant negative predictor of ORS. However, no significant contribution of rest of predictors to model was found. In other words, it may be noted that ‘low-ILOC failed to moderate the relationship between approach/avoidance coping strategies and ORS’.

Hierarchical Regression Analysis of ORS, ELOC and Coping Styles

Table 4 shows the results of regression with subgroups of ELOC as moderator.

It may be noted from Table 4 that Durbin–Watson test statistic for models under consideration, fall within desirable ranges, that is, ‘between’ 1.28 and 1.98, which is close to the acceptable statistic (i.e., 2).

Analysis of Block A (Table 4)—H-ELOC as moderator—using hierarchical regression analysis, the following variables were entered in the sequence described below:

In Model 1, two coping strategies, namely approach (App) and avoidance (Avd) coping strategies, were entered simultaneously. In Model 2, the variable high-ELOC is added to the model along with the two coping strategies. In Model 3, interaction terms of each of the coping strategies (H-ELOC × Approach and H-ELOC × Avoidance) were entered simultaneously along with the predictors entered in Model 2. The interaction terms were constructed by multiplying high-ELOC by each of the coping strategies.

Table 4.

Hierarchical Regression Analysis of ORS with ELOC and Coping Styles

Block A H-ELOC as Moderator				D–W Test	Block B M-ELOC as Moderator				D–W Test	Block C L-ELOC as Moderator				D–W Test
Predictors	R²	B	T	D–W Test	Predictors	R²	B	T	D–W Test	Predictors	R²	B	t	D–W Test
Model 1				1.28	Model 1				1.28	Model 1				1.28
App Avd	0.289	−0.58 0.495	1.23* 3.13		App Avd	0.289	−0.58 0.495	1.23* 3.13		App Avd	0.289	−0.58	1.23*
App Avd	0.289	−0.58 0.495	1.23* 3.13		App Avd	0.289	−0.58 0.495	1.23* 3.13		App Avd		0.495	3.13
Model 2				1.98					1.92	Model 2				1.95
App Avd H-ELOC	0.322	−0.56 0.660 0.810	2.22 2.02* 3.23*		App Avd M-ELOC	0.315	−0.43 0.498 −0.45	2.81* −4.71 3.13**		App Avd L-ELOC	0.294	−0.52 0.477 0.447	−0.68 −1.05 1.28


Model 3				1.89					1.87	Model 3				1.92
App Avd H-ELOC App × H-ELOC Avd × H-ELOC	0.346	0.49 0.521 0.735 0.62 0.52	2.33 2.01 2.70 1.19 5.32**		App Avd M-ELOC App × M-ELOC Avd × M-ELOC	0.345	−0.50 0.890 −0.908 −0.64 0.633	−1.16 2.56 −0.67 2.83** 2.03*		App Avd L-ELOC App × L-ELOC Avd × L-ELOC	0.298	−0.49	1.44
												−0.42	−2.98
												0.822	3.22
												0.963	2.49
												0.822	−0.23

Source: The author.

Notes: H-ELOC, High-external LOC; M-ELOC, Medium-ELOC; LOW ELOC, Low-external LOC; Avd, Avoidance; App, Approach.

*p ≤ .05, **p ≤ .01.

The results of hierarchical regression analysis are explained below:

Models	R² Values	Implications
1	R² = 0.289	This implies that 28.90% of the variance in ORS is accounted for by the coping strategies, namely approach and avoidance coping strategies.
2	R² = 0.322	This implies that 32.20% of the variance in ORS is accounted for by the coping strategies along with the variable high-ELOC.
3	R² = 0.346	This implies that 34.60% of the variance in ORS is accounted for by the two interaction terms, namely App × High-ELOC (O) and Avd × High-ELOC.

Source: The author.

The results in Table 4 (Block A) show that the approach coping strategy is a statistically significant negative predictor of ORS. The variable H-ELOC revealed a significant positive effect and also the test of significance of ‘interaction term’ (Avd × H-ELOC) in Model 3 showed a significant positive effect (p < .01). The ‘interaction term’ (App × H-ELOC) failed to show significant results. The two terms accounted for 34.60% of the variation in ORS.

In other words, it may be noted that high-ELOC moderates the relationship between avoidance coping strategies and ORS (in positive direction) while no moderation effect of ELOC was seen between ORS and approach coping strategy. This means that ‘avoidance coping strategy adopted by doctors having high-ELOC exhibit higher levels of stress than the doctors who adopt approach mode of coping’.

Analysis of Block B (Table 4)—M-ELOC as moderator—the results of hierarchical regression analysis for Block B are explained below:

Models	R² Values	Implications
1	R² = 0.289	This implies that 28.90% of the variance in ORS is accounted for by the coping strategies, namely approach and avoidance coping strategies.
2	R² = 0.315	This implies that 31.50% of the variance in ORS is accounted for by the coping strategies along with the variable medium-ELOC.
3	R² = 0.345	This implies that 34.50% of the variance in ORS is accounted for by the two interaction terms, namely App × Medium-ELOC and Avd × Medium-ELOC.

Source: The author.

The results in Table 4 (Block B) show that the approach coping strategy and the variable M-ELOC are statistically significant negative predictors of ORS. The test of significance of ‘interaction term’ (Avd × M-ELOC) in Model 3 shows a significant positive effect (p < .05); while ‘interaction term’ (App × M-ELOC) in Model 3 shows a significant negative effect (p < .01). The two terms accounted for 34.50% of the variation in ORS.

In other words, it may be noted that medium-ELOC moderates the relationship between approach coping strategies and ORS (in negative direction) while significant moderation effect of ELOC in positive direction was seen between ORS and avoidance coping strategy. This means that ‘approach coping strategy adopted by doctors having medium-ELOC exhibit lower levels of stress than the doctors who adopt avoidance mode of coping’.

Analysis of Block C (Table 4)—L-ELOC as moderator—the results of hierarchical regression analysis for Block C are explained below:

Models	R² Values	Results
1	R² = 0.289	This implies that 28.90% of the variance in ORS is accounted for by the coping strategies, namely approach and avoidance coping strategies.
2	R² = 0.294	This implies that 29.40% of the variance ORS is accounted for by the coping strategies along with the variable low-ELOC.
3	R² = 0.298	This implies that 29.80% of the variance in ORS is accounted for by the two interaction terms, namely App × Low-ELOC and Avd × Low-ELOC.

Source: The author.

The result in Table 4 (Block C) shows that the approach coping strategy is statistically significant negative predictor of ORS. However, no significant contribution of rest of the predictors to model was found. In other words, it may be noted that ‘low-ELOC failed to moderate the relationship between approach/avoidance coping strategies and ORS’.

Summary of Moderation Effects of LOC Variables

The summary of moderation effects of LOC and its categories on ‘role stress’ and ‘coping styles’ may be noted in Table 5.

Managerial Implications

The findings of this study can assist administrators and policymakers in the healthcare sector to provide a stress-free working climate. This may help to decrease side effects and consequences of role stress and increase productivity of doctors. Furthermore, it may also help doctors to explore the sources of stress and choose the relevant coping style. In light of the findings of the study, a few stress management interventions which would help doctors develop healthy coping styles have been suggested.

Table 5.

Summary of Moderation Effects of LOC Variables

LOC Variables	Avoidance Coping Strategy (Moderation Effect)	Approach Coping Strategy (Moderation Effect)
High-ILOC	✓	✗
Medium-ILOC	✗	✓
Low-ILOC	✗	✗
High-ELOC	✓	✗
Medium-ELOC	✓	✓
Low-ELOC	✗	✗

Source: The author.

Note: √, Moderation effect identified; ×, No moderation effect.

Moreover, it is a well-researched fact that individuals differ in their response to stress situation. Many researchers (Robbins, 1999; Reddy & Ramamurti, 1991; Beehr & Newman, 1978) have attributed this difference to the personality-related factors of an individual. One important personality construct, that is, LOC has been reported as an antecedent of stress (Organ & Greene, 1974; Kliewer & Sandler, 1992). In the present study, an attempt has been made to explore this issue further. Findings of the present study consonant with the personality construct LOC may be implied for healthcare professionals. Previous studies (Singh & Rhoads, 1991; Kalbers & Fogarty, 2005) reported that people having ILOC experience less stress. The findings of the present study were somewhat different. In this study, respondents were classified into three categories—high, medium and low—on the basis of their scores on LOC, as proposed by Pareek (1998). These categories describe the desirable and undesirable range of all the three sub-types of LOC, that is, ILOC and ELOC. An important finding of the study was that H-ILOC and L-ILOC lead to higher stress levels. However, ‘moderate level of ILOC reduces the stress level among doctors’. Similarly, analysis of ELOC indicated that doctors with higher ELOC also experience appreciable amount of stress. However, medium and low scores on ELOC failed to show any significant relationship with role stress. It may be concluded from the aforementioned discussion that it is the moderate level of ILOC which actually has a bearing on reducing stress levels among the respondent group. Furthermore, extreme levels of any of the two loci, that is, ILOC and ELOC act as stress inducers.

The present study also attempted to investigate the moderating role of LOC on ‘coping styles’ and ‘role stress’. It was found that ‘approach coping styles’ adopted by the respondent group having M-ILOC exhibit lower levels of stress. This again substantiates the above finding that doctors having moderate level of ILOC tend to adopt ‘approach/functional coping styles’, resulting in reducing stress levels. This important finding may be of great help to the respondent group to understand the realities of stress vis-→-vis personality construct, that is, LOC. This shall help design suitable stress management interventions as well.

Coping with Stress Viz-→-viz Locus of Control

A person’s sense of control over the events of his life indicates where his ‘locus’ lies. Locus refers to where a person assigns responsibility. When stress enters the picture, a person’s LOC can determine how well he is able to cope with the stressful life events. Substantial research has been carried out on LOC in the workplace viz-a-viz stress and employee’s well-being (e.g., Organ & Greene, 1974; Spector, 1988; Cohen & Edwards, 1989; Spector & O’Connell, 1994). The findings of most of such studies pointed towards the fact that internals experienced less role ambiguity have greater control over situations and experience less stress (Emster & Harrison, 1998; Kalbers & Fogarty, 1995). Research has also shown that individuals who are inclined to view events as more internally controllable tend to exhibit higher levels of coping efficacy (Chwalisz et al., 1992; Rahim, 1996). Conversely, externals have been found to adapt to poor coping styles, and possess self-defeating personality (Folkman, 1984; Schill & Beyler, 1992).

The findings of the present study indicated that the respondents having either H-LOC or H-ELOC exhibit higher stress levels. It may be pointed out that doctors with a strong ILOC tend to be very achievement-oriented, and this can leave people around them feeling trampled. And with a very strong ILOC, there is also a tendency to want to control everything, and this can lead to difficulties in taking direction.

The study also observed that the doctors with ‘moderate level of control whether internal or external exhibit lower stress levels and are better able to cope with stressful life events’. Consonant with the findings of the study, it may be concluded that ‘moderation is the best path’. So, doctors need to work on maintaining this moderate level of control, namely ‘internal’ and ‘external’.

Following recommendations may help doctors to overcome stressful situations:

Improving problem-solving and decision-making skills. This may help people to gain the confidence and the belief on themselves.

Expanding the mind to new possibilities. Keeping the mind open to welcome the information without labelling it good or bad.

Developing self-confidence not over-confidence.

Maintaining humour and optimism during rough times.

Becoming both self-reliant and socially responsible.

Due recognition of other’s functions in a given role to meet its desired end but avoiding keeping fate in other’s hands.

These strategies are in the form of proposals only. The research is needed to understand its implications.

Conclusion

Overall, the present study highlights the importance of a personality construct, that is, LOC in managing the levels of stress among doctors in government hospitals. It was found that LOC is an important determinant in coping with stressful situations. Finding of high internality and high externality being associated with more stress levels is an important observation. Also the moderate levels of LOC, that is, internality and externality were actually shown to have an important role in reducing stress in the respondent group. Although our results hint that moderate levels of ILOC among doctors is a desirable control to reduce stress levels. However, it is likely that the ways in which people translate their control beliefs into action varies across nations.

In light of the findings of the study, it can be concluded that doctors in government hospitals in India are exhibiting higher level of ORS. Stress management interventions are needed to cope with the alarming levels of stress. It may also be concluded that personality construct, that is, LOC moderates the relationship between ‘coping styles’ and ‘role stress’. Moderate levels of both Internal and External Loci has been found as an acceptable control, which has a role to play in reducing the levels of stress, when interacts with the coping styles. Based on the findings, the study proposed a few stress management interventions based on individual and organizational level. Also, an attempt has been made to propose coping styles for managing stress levels vis-→-vis LOC. There is a need to emphasize management of stress among doctors on a wider scale. Government hospitals need to design counselling programmes to Heal the Healers. If healthcare professionals will be stress free, they would be able to address the problems of their patients more effectively.

Limitations of the Study

Participation and cooperation of respondents is a serious problem in survey-based research. The same was observed in this study. Some doctors appeared reluctant in filling up the questionnaire. This may be due to the busy nature of their job or their unwillingness to participate in the survey. This limitation caused a lower than the anticipated response rate from the targeted hospitals.

One of the important demographic variables in the study is based on specialization of doctors. Approaching doctors having specialization in any of the particular field (namely general, surgery, anaesthesia, etc.) was a major and time-consuming challenge. In some hospitals, only two or three doctors could be approached for a particular specialization. This resulted in less number of responses from specialists of certain fields.

There was a scarcity of theoretical and empirical studies among doctors in this field, specifically in the Indian context. This limitation also affected the research. Some previous studies could have made the foundation of this effort more robust.

Healthcare professionals include both Medical and Paramedical staff. However, the scope of the study is limited to medical staff, that is, Doctors only. The researcher did not approach the paramedical staff as the same was beyond the scope of the study.

The research instrument used in the study has a general orientation, that is, generalized for all occupation groups. Doctor specific questionnaire could have helped the researcher to draw more specific inferences. However, in that case, cross occupational comparison would not have been possible.

The study was restricted to only two states of India. This may reflect only partial reality of stress among doctors.

Future Research Directions

Future research may be carried out to assist the healthcare professionals in inculcating moderate levels of ILOC and ELOC that may help them to reduce ‘stress’ levels.

The study was limited to only two regions and only the doctors working in government hospitals. It may be extended to include doctors from more regions and from private sector as well.

The study may also be extended to several other specialized groups of doctors, for example, ENT specialists, Oncologists, Opticians, etc.

Questionnaires used in the present study have a general orientation. There are stressors which are specific to doctor’s job. Therefore, there is a need to develop a doctor-/health care-specific questionnaire. This will help to understand the reality of stress among doctors more specifically.

The review of the literature suggests that there is a dearth of the research in stress management aspect, that is, strategies for managing stress. So, there is a pressing need in carrying out the studies in stress management context.

The scope of the present study was limited to the doctors only. Future research may also include the study of stress among Paramedical staff.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author received no financial support for the research, authorship and/or publication of this article.

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