Psychosocial determinants of burnout in geriatric nursing

Pergamon

0020-7489(95)0000&2

hr. J. .V”ur.~ Sod, Vol 32, No. 5. pp. 4431156. IY95 CopyrIght c, 1995 Elsev~er Saence Ltd

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Psychosocial determinants of burnout in geriatric nursing

ANDR6 DUQUETTE, R.N., Ph.D. SUZANNE I&ROUAC, R.N., M.N., M.Sc. BALBIR K. SANDHU, R.N., M.Sc.N. FRANCINE DUCHARME, R.N., Ph.D. PIERRE SAULNIER, R.N., M.Sc.N. F'uxlrP dcs Scirnws Infirnli&w of/he UnirwsirP de Monirlal, QuSwc. Cmado

Abstract--The purpose of this study was to identify determinants of burnout using an adapted version of Kobasa’s theoretical framework, considering work stressors, work support, coping strategies and hardiness. Data were collected through a questionnaire mailed to 1990 randomly selected geriatric nurses. A participation rate of 77.6% was achieved. T-test, variance analysis and multiple regression analysis were conducted. Hierarchical multiple regression analysis indicated that 49% of the variance was explained by the study variables. Hardi- ness and work stressors were the most important predictors of burnout. The findings are discussed in relation to Kobasa’s framework, focusing on resources that reduce negative effects of geriatric work stressors. Implications for nursing practice, management, education and research are proposed.

Problem and literature review

Contemporary western society is experiencing an important increase in its aging population. It is generally recognized that aging often accompanies deterioration of functional capacities as well as severe health problems. Under these circumstances, institutionalization rates for the elderly have increased in the recent years, and it seems reasonable to believe that more nurses will be required in geriatric settings in the future.

Because the care of these elderly patients is demanding, it may be a stress-generating

443

444 A. DUQUETTE e/ al.

situation for the nursing staff. Investigations among geriatric caregivers showed that some situations related to patient care are perceived as stressful. Carter and Phillips (1987) identified stressors such as tiredness due to lifting of heavy and less mobile patients, as well as emotional stressors related to the care of an important group of patients suffering from debilitating diseases and encountering death and dying on a daily basis. Yu et al. (1991) found that urinary incontinence is stressful for both patients and caregivers; also, it presents an important work overload. Other factors contributing to geriatric work stress are cognitive deficits such as presented in Alzheimer’s disease or other dementia. These patients manifest behavioural disturbances and frequently have communication and speech defects making it difficult for the nursing staff to understand their needs and wishes (Astrom et al.. 1991). Studies in geriatric nursing underline the detrimental effects of such stressors on the mental well-being of caregivers and on the incidence of nursing burnout (Astrom, 1992; Astrom et al., 1987; Corbeil, 1991; Griffin, 1990; Saulnier, 1993).

Burnout has many implications for nursing care as well as for caregivers’ health and costs related to health services. Authors in the field of burnout agree that manifestation of burnout is related to important work stressors sustained over time; burnout appears, above all, to be an adverse work stress reaction with psychological, psychophysiological and behavioural components (Cherniss, 1980; Edelwich and Brosky, 1980; Freudenberger, 1980; Jones, 1982; Maslach, 1982; McConnell, 1982; Pines and Aronson, 1981). Jones (1980) defined professional burnout as a syndrome of physical and emotional depletion that is characterized by negative work attitudes, a poor self-concept and loss of concern for patients. It usually manifests as frequent irritation and anger with patients, withdrawal from work or absenteeism, staff turnover, low productivity, job dissatisfaction and a loss of creativity. In short, burnout appears to be a problem of adaptation with inhibition to work (Bibeau et al., 1988).

Duquette et al. (1994) conducted an analytical review of empirical knowledge of factors related to nursing burnout. This systematic analysis of the literature showed that the main correlates of burnout are: work stressors, work support, coping strategies and hardiness.

Work stressors are events related to nursing work that are perceived as menacing and stress generating; these situations could be physical such as workload, psychological such as death of patients and incertitude of treatment, and social such as interpersonal conflicts (Gray-Toft and Anderson, 198la). Many studies in the nursing literature show that work stressors may induce burnout (Beaver et al., 1986; Das, 198 1; Firth et al., 1987; Fong, 1984; Jenkins and Ostchega, 1986; Kaplan, 1987; Lai, 1988; Lewis et al., 1992; Pelletier, 1986; Richardsen et al., 1992; Stechmiller, 1990).

Work support refers to the positive social relationships involving free expression of ideas, friendship, encouragement, as well as the emotional and instrumental help persons give to each other in the work environment (Moos, 1986). Sixteen studies found a significant negative relationship between work support and nursing burnout (Constable and Russell, 1986; Cronin-Stubbs and Rooks, 198.5; Dick, 1986, Dick 1992; Duxbury et al., 1984; Eastburg, 1991; Fong, 1993; Haley, 1986; Hare et al., 1988; Mallett, 1988; Michaud, 1991; Mickschl, 1984; Oehler et al., 1991; Ogus, 1990; Paredes, 1982; Plante, 1993; Saulnier, 1993). These studies have been conducted in diverse settings, including geriatrics, across Canada and the U.S.A. Two sources of work support were mainly examined, support from superiors and support from colleagues.

In the perspective of Lazarus’s work (Lazarus and Folkman, 1984), the notion of coping refers to responses or adaptive strategies which an individual uses to confront stressors

BURNOUT IN GERIATRIC NURSING 445

and reduce stress-generating events on one’s functionning. Five studies investigated the relationship between nursing burnout and coping strategies. Ceslowitz (1989) surveyed 150 staff nurses from four hospitals and concluded that those who experienced increased levels of burnout used the coping strategies of escape and avoidance, self-controlling and confronting. Those who experienced decreased levels of burnout used the coping strategies of planful problem-solving, positive reappraisal, seeking social support and self-controlling. Chiriboga and Bailey (1986) interrogated 544 nurses employed on medical surgical units and coronary care units in six hospitals in California. Their findings showed that among nine coping strategies, only one significantly contributes to predict burnout. The anticipated coping strategy, characterized similarly as an action and vigilance strategy, correlated negatively with burnout. Kimmel (198 1) studied 135 nursing personnel: ward clerks, nurses aides, licensed practical and registered nurses in a large hospital. The findings showed two types of coping related to burnout. Self-blame coping was positively related and growth coping-a dynamic state of being creatively engaged and productive-was negatively related to burnout. Lauzon (199 1) conducted her study among 173 critical care nurses from three hospitals; she found that escape/avoidance and confrontational coping were predictive of burnout. Planful problem-solving and positive reappraisal were negatively related to burnout. Finally, Teague (1992) interrogated 163 nurses in one hospital and concluded that those who utilized more emotion-oriented coping styles reported the highest amount of burnout.

These inquiries suggest that action-oriented coping such as cognitive appreciation, information seeking, and problem-solving strategies may prevent experiencing burnout. Yet, avoidance strategies such as escape, inhibition and self-blaming may lead to professional burnout. However, it is difficult to draw conclusions from these studies. Only two investigators used the same instrument to measure coping, making comparisons difficult, and samples were limited to few hospitals, excluding geriatric care centers.

Kobasa (1979; Ouellette (same author), Ouellette, 1993) defined hardiness as a constellation of three personality traits, namely an openess to change (challenge), a capacity of commitment to whatever one undertakes (commitment), and a feeling of control in a situation (control). This constellation of components refers to beliefs, attitudes, cognitions and actions according to which stress generating events could be positively transformed. Many investigators have studied hardiness in relation to nursing burnout. The findings of the next seven studies showed that lack of hardiness has a significant positive relationship with burnout (Boyle et al., 1991; D’Ambrosia, 1987; Jama, 1987; Keane et al.. 1985; McCranie et al., 1987; Rich and Rich, 1987; Topf, 1989). These investigators used scales that measured negative indicators of hardiness (i.e. the higher the score, the individual expressed less commitment, control and challenge). Most of these investigators used con- venience samples of bedside nurses working in hospital units such as intensive care, anaes- thesia and oncology. More recently, other investigators used a positive indicator of hardiness (Hardiness Scale) and interrogated critical care nurses (Morissette, 1993) nursing faculty (Bausler, 1992; Buran, 1992) and undergraduate nursing students (Smochek, 1993). All of these findings revealed a significant negative correlation between hardiness and burnout.

Therefore, research findings suggested that hardiness appears to be an important factor related to nursing burnout. From their varied samples across the U.S.A. and Canada, excluding geriatric nurses, all investigators concluded that nursing personnel with hardy personality traits are less likely to burn out. Further, most of these investigators conclude

446 A. DUQUETTE et al.

that commitment, one of the three dimensions of hardiness, is the best predictor variable of burnout in nursing personnel. Commitment was described as a tendency to involve one’s self in all kinds of activities one does or encounters. Committed persons possess a system of beliefs and values that minimize perceiving a situation as menacing. A committed person does not avoid interacting with a situation. The person possesses a sense that permits one to identify events in the environment that are of significance. Commitment seems to provide protection against burnout.

Even though a large number of studies identified correlates of nursing burnout, it is still unknown which of these correlates are the main determinants of burnout. Most of the studies employed a bivariate design and none identified determinants of burnout using simultaneously work stressors, work support, coping strategies, and hardiness as determinants in a multivariate correlational design. A large number of these studies were conducted in critical, medical-surgical or psychiatric units and few of them were conducted in geriatric settings. Further, most studies do not use any conceptual underpinnings, except for Chiriboga and Bailey (1986), Ceslowitz (1989) and Smochek (1993) who used the Nursing Stress Model, the Stress and Coping Theory of Lazarus and the Hardiness Theory of Kobasa, respectively.

Purpose

The purpose of the present study was, therefore, to identify determinants of burnout in geriatric nurses using a theoretical framework considering work stressors, work support, coping strategies and hardiness.

Theoretical framework

A theoretical framework of factors affecting nursing burnout derived from Maddi and Kobasa’s (1984) model (Factors Affecting Health/Illness Status), was used in the present study. As illustrated in Fig. 1, these factors are sociodemographics, work stressors, hardiness, work support, coping and burnout.

Maddi and Kobasa (1984) propose that as stress-generating events mount up (work stressors), signs of strain increase. For an individual, a repetitive stress can represent a

1 Sociodeygraphics 1 1 Work Stfessors ]

,I Burnout 1

Fig. 1. Factors affecting nursing burnout.


menace or a tension, which may manifest physically (sweaty palms, tachicardia, chest pains, trembling) or psychologically (anxiety, irritability, loss of appetite). An individual who frequently finds himself in this situation may experience decreasing resistance to stress which may lead to physical or psychological strain (burnout). Maddi and Kobasa stipulate that to confront stressful events, hardy individuals examine the events in perspective and perceive them as meaningful (commitment) but changeable (control) and of potential value for personal growth (challenge). Hardiness not only influences effective coping but also the kind of social support someone would use in time of stress.

Method

Sarnplt7

With the collaboration of the Order of Nurses of Quebec, Canada, French-speaking nurses working in geriatrics (N=8066) were isolated from the register of all nurses (N=64,678) (OIIQ, 1993). From this population of geriatric nurses, a random sample of 1990 was drawn. A total of 1545 nurses (77.6% response rate) participated in the study.

Data were collected using a self-administrated questionnaire including measures of burnout, stressors, hardiness, work support, coping strategies and sociodemographic variables. The questionnaire was translated into French with a back-translation into English, and a few problematic items were re-phrased. The French version was pre-tested on a sample of 243 nurses who did not take part in the main study (Morissette, 1993).

Burnout was assessed by the Staff Burnout Scale for Health Professionals (SBSHP) (Jones, 1980). This instrument measures four dimensions: (1) cognitive dimension (“I often think about finding a new job”), (2) affective dimension (“After work I often feel like relaxing with a drink of alcohol”), (3) psycho-physiologic dimension (“I feel fatigued during the work day”), and (4) behavioural dimension (“I avoid patient interaction when I go to work”). The instrument contains 30 items; 20 items measure the four dimensions of burnout and 10 estimate social desirability. Jones (1980) obtained a Spearman-Brown split-half reliability coefficient of 0.93 for internal consistency. For the pre-test of the French translation, the Cronbach’s alpha was 0.78 (N=243) and it was 0.83 (N= 1545) for the present study. Alpha coefficients for the subscales were: 0.73 (cognitive), 0.59 (behavioural), 0.50 (affective) and 0.44 (psycho-physiologic).

Stressors were assessed by the Nursing Stress Scale (NSS) (Gray-Toft and Anderson, 198 I b). This instrument contains 34 items divided into three subscales: physical environment (workload), psychological environment (death and morbidity of patients, incertitude of treatment, insufficient preparation of nurses) and social environment (conflict with physicians and nurses). The internal consistency of the NSS estimated by Gray-Toft and Anderson (198 1 a, Gray-Toft and Anderson, 1985) with three different tests, resulted in a SpearmanBrown coefficient of 0.79, a Guttman Split-half coefficient of 0.79 and an Alpha coeflicient of 0.89; test-retest reliability has been estimated at 0.81. For the pre-test of the French translation, the Cronbach’s alpha coefficient was 0.87 (N=243) and for this study it was 0.85 (N= 1545). Alpha coefficients for the subscales were: 0.77 (psychological), 0.69 (physical) and 0.64 (social).

Hardiness was assessed by the third version of the Hardiness Scale (HS) (Kobasa, 1990).

448 A. DUQUETTE et al

The instrument contains 50 items organized into three subscales: challenge (“I like a lot of variety in my work”); commitment (“I really look forward to my work”); control (“Planning ahead can help avoid most future problems”). For internal consistency, Kobasa (1990) reported an alpha coefficient of 0.90, while commitment, control and challenge had an alpha of 0.70. For the pre-test of the French translation, the Cronbach’s alpha was 0.80 (N= 243) and it was 0.84 (N= 1545) for this study. Alpha coefficients for the subscales were 0.74 (commitment), 0.66 (challenge) and 0.62 (control).

Work support was assessed by the Work Relationship Index (WRI) (Moos, 1986) which consists of 27 items organized into three subscales containing 9 items each: support of superior, peer cohesion and group involvement. For the present study, two subscales were retained: support of superior (“The head nurse congratulates a nurse who is rather dynamic”) and peer cohesion (“Generally nurses help a new nurse to feel at ease”). For these subscales, Moos (1986) reported alpha coefficients of 0.77 (support of superior) and 0.69 (peer cohesion). For the pre-test of the French translation (n=243), the Cronbach’s alpha were: 0.69 (support of superior) and 0.48 (peer cohesion), and for the present study they were 0.82 (support of superior), 0.70 (peer cohesion) and 0.84 (global score).

Coping strategies were assessed by the Indices of Coping Responses (ICR) (Moos et al., 1986) which consists of 32 items organized into three methods of coping: active cognitive (“I considered several alternatives for handling the problem”), active behavioural (“I made a plan of action and followed it”), and avoidance (“I refused to believe that it happened”). Moos et al. (1986) reported alpha coefficients of 0.62 for active cognitive, 0.74 for active behavioural and 0.60 for avoidance strategies. For the pre-test of the French translation of the instrument, the Cronbach’s alphas (N=243) were: 0.59 (active cognitive), 0.73 (active behavioural), and 0.78 (avoidance), while for this study (N= 1,545) they were 0.72, 0.67, and 0.47, respectively.

Information on sociodemographic variables were also collected (age, sex, civil status, number of children, employment title and employment status, number of years of experience as a nurse, shift worked, and type of institution).

Procedure

The data collection model of Dilman (1978) was used as it tends to ensure a high response rate. The questionnaire was mailed to the homes of the 1990 randomly selected nurses with an accompanying letter and a stamped pre-addressed return envelope. The questionnaire was presented in the form of an attractive printed booklet. Two follow-up letters were mailed. An incentive, the possibility of receiving a personal profile after data analysis, was offered for participating. Everyone receiving the questionnaire was at liberty to refuse to participate in the project. A returned questionnaire was considered as giving consent for its use.

Data analysis

A hierarchical multiple regression analysis was conducted. Global scores, scores for the subscales of instruments and for sociodemographic variables were entered into the equation. Variables were chosen after close examination of the correlation matrix (Pearson’s coefficient). Only the variables with a significant correlation coefficient with burnout (p < 0.05) were retained. For sociodemographic variables, those with a significant difference with the global score or the subscale scores of the instruments were retained (T-test and


ANOVA). Using burnout (global score) as the dependent variable, each retained variable was entered into the hierarchical multiple regression using the direct method: “Enter” (Norusis, 1990). The sequence of sets was chosen according to the theoretical model used in the present study. Sets of data were entered as follow: step 1 (sociodemographic variables), step 2 (the three subscales of the NSS), step 3 (the three subscales of the HS), step 4 (the two subscales of the WRI), step 5 (the three subscales of the ICR).

Results

Sociodemographic characteristics of the study sample showed the majority of respondents to be women (92.7%), the average age being 41 years (S.D. =9.5). Most lived with a partner (73.1%) and 66.8% had one or more children under the age of 18 years living at home. The majority worked part-time (55.4%) and 72% had at least 10 years of experience as a nurse. The average number of years of experience on the present unit was 7.5 years (S.D. = 5.9). The majority worked day (46%) or evening (21%) shifts. Employment titles were: head nurses (8.7%) assistant head nurses (36.7%) team leaders (22.1%) bedside nurses (22.4%) and others (10.2%). The majority worked in hospitals (48.9%), but also a significant number worked in nursing homes (45.6%).

Relationship between demographics and other uariables

Table 1 presents the results of T-test and variance analysis between sociodemographic variables and other variables of the study (global or subscale score of instruments). Except for the variable number of children, all sociodemographics showed a significant difference with one or more variables: burnout, work stressors, hardiness, work support and coping methods. Data presenting significant difference with the global score are reported here. It appears that female nurses perceived more work stressors than male nurses (T= -2.03. df= 1546, p=O.O4). Those living with a partner used more active coping than others (T=2.71, df= 643, p=O.Ol). Bedside nurses were more burned out than other nurses (F= 4.54, df = 4, 1544, p = 0.00). Nurses occupying management positions (head nurses and assistant head nurses) perceived more work stressors (F= 2.89, df=4, 1542, p=O.O2) but also perceived more work support (F= 26.82, df = 4, 1541, p = 0.00) and demonstrated more hardiness (F= 11.46, df=4, 1544, p=O.OO). Full-time staff perceived more work stressors (T= 2.47, df= 1533, p=O.Ol) and were more burned out (I”= 1.97, df= 1536, p = 0.00) whereas part-time staff used more active coping (T= -2.90, df = 1508, p = 0.00). Nurses working on day shift perceived more work support (F= 4.55, df = 3, 1544, p = 0.00) and showed more hardiness (F=9.58, df= 3, 1541, p=O.OO). Finally, nurses working in nursing homes perceived more work stressors than those working in hospitals (F=3.03, df = 3. 1544, p =0.03).

Table 2 presents the results of hierarchial multiple regression analysis between the study variables and burnout. The overall regression equation explained 49.0% of the variance.

The hardiness set of variables explained a major part of the variance, more specifically 22.0%. Out of the three variables comprising this set, commitment (/I= -0.34) and control

450 A. DCJQUETTE et al.

Table 1, T-test and ANOVA between demographics and other variables (n = 1530)

Other variables

Sociodemographics

Age

Burnout

Sex ns ns

Civil status ns

Employment title

Employment status

Years of experience

Number of children

Shift worked

F=4.54 df=4, 1544

p =o.oo* T= 1.97

df= 1536 p=o.oo*

ns

ns

ns

Type of institution ns

Work stressors

S

T= -2.03 df= 1546 p=o.o4*

ns

F=2.89 df=4, 1542

p=o.o2* S

S

ns

S

F= 3.03 df=3, 1544

p=o.o3

Hardiness

s

S

ns

F= 11.46 df=4, 1544

p=o.oo* ns

ns

ns

F=4.55 df=3, 1544

p=o.oo* ns

Work support Coping

ns s

ns

F= 26.82 df=4, 1541

p=o.oo* T= 2.47

df= 1533 p=o.o1*

ns

ns

F= 9.58 df=3, 1541

p=o.oo* ns

S

ns

T=2.71 df = 643

p=o.o1* S

T= -2.90 df= 1508 p = o.oo*

S

ns

ns

ns

*Significant difference with global score, p < 0.05. s, significant difference with one or more subscales, p < 0.05. ns, no significant difference with global or subscale scores, p > 0.05.

(j3 = - 0.07) were significant determinants of burnout (p < O.Ol), whereas challenge did not contribute significantly in predicting burnout (j3 = > 0.05).

The work stressors set of variables also explained an important part of the variance (21%). All three dimensions of the work stressors contributed significantly @<O.OOl) to the prediction equation: social environment (/I = 0.14), physical environment (B = 0.12) and psychosocial environment @=0.06). These results suggested that the most important stressors inducing burnout are frequent conflicts with physicians and nurses as well as heavy workload.

The work support set of variables explained 2% of the variance. Both were significant determinants (p < 0.001) of burnout: support from superior (fi = - 0.10) and peer cohesion (/?= -0.10).

The last set of variables entered into the regression analysis was the coping methods which explained 2% of the variance in burnout. Out of the three coping methods, two were found to be significant determinants (p < 0.001) of burnout: avoidance (/3= 0.15) and active cognitive (p = - 0.08).

Finally, the sociodemographic set of variables also explained 2% of the variance. Only employment status contributed significantly (p < 0.05) to burnout (fl= 0.05). These findings suggested that the full-timers were more prone to burnout.

Discussion

The overall regression equation explained 49% of the variance which suggests a respect- able contribution of study variables in predicting nursing burnout. The main contribution

BURNOUT IN GERIATRIC NURSING

Table 2. Hierarchical regression of total burnout scores on sets of variables (n = 1505)

451

Variables Sets Beta (/I)

Step I Sociodemographics Employment status Employment title Shift worked Civil status

Age Sex Years of experience Type of institution

Step 2 Work stressors Social environment Physical environment Psychological environment

Step 3 Hardiness Commitment Control Challenge

Step 4 Work support Peer cohesion Support of superior

Step 5 Coping methods Avoidance Active cognitive Active behavioural

rz cum ? (r? square) (i square change)

0.02 0.02*** 0.05*

ns ns ns ns ns ns ns

0.14*** 0.12*x* 0.06***

-0.34*** -0.07***

ns

-0.10*** -0.10***

0.15*** -0.08***

ns

0.23 0.21***

0.45 0.22***

0.47 0.02***

0.49 0.02***

*p<o.o5; **p<o.o1; ***p<O.OOl; ns. nonsignificant.

of this study remains in the selection of known correlates of burnout integrated within a conceptual underpinning, namely Maddi and Kobasa’s hardiness theory applied to the concept of burnout. The regression of selected variables on burnout suggested that this conceptual model has validity as a predictive tool. Indeed, each variable set contributed significantly to the prediction of burnout.

As suggested by Maddi and Kobasa (1984), frequent and repetitive stress-generating events may lead to increased signs of strain. Geriatric work stressors appear to be important determinants of burnout, which is considered by Maslach (1982) as a work-related strain. These results are consistent with those reported in other studies of nurses working in other areas and in geriatric settings in particular (Astrom et al., 1991; Corbeil, 1991; Saulnier, 1993).

As proposed by Maddi and Kobasa (1984) findings of this study suggest that hardiness is the predominant predictor of burnout. Hardy nurses commit themselves to their lives and work; these nurses also have a feeling of control in a situation. However, a lack of challenge did not contribute in predicting burnout. These results are similar to those reported by earlier studies such as Boyle et al. (1991), D’Ambrosia (1987), Jama (1987) Keane et al. (1985) and Morissette (1993). It should be noted that none of the previous


research examined the relationship between burnout and hardiness among geriatric nurses. This particular group of geriatric nurses do not seem to differ from nurses working in other areas.

Results of this study suggest that geriatric nurses with hardy personality traits when faced with work stress-generating events are able to reduce strain and avoid burning out. These nurses are able to perceive stressors such as conflict with others and workload in an optimistic way, thus enhancing their possibility of decisive actions for altering them. There- fore, they do not avoid interacting with the situation. They believe that events could be influenced by what they think, choose, say or do. They possess a sense which allows them to identify and find events, objects and persons in the work environment that are of significance. They try to understand and adjust to the stressful events, thus diminishing their negative effect. They take action to proceed ahead; they do not stay passive and they do not avoid stressful situations.

Coping methods explained only 2% of the variance but avoidance and active cognitive methods of coping were found to be significant determinants of burnout. These findings suggest that nurses using avoidance strategies or responses such as escape, inhibition and blaming others are more inclined to burnout. Yet, those using active cognitive methods such as positive appraisal and objective analysis of stressful events are less prone to burnout. These results are similar to those found in previous studies among nurses working in other areas (Ceslowitz, 1989; Chiriboga and Bailey, 1986; Lauzon, 1991).

Findings of this study also show that work support explained 2% of the variance. Both support from superior and peer cohesion were equal determinants of burnout. It suggests that if geriatric nurses perceive social support in their work settings, either from their superior or their peers, they would be less likely to burn out. These results have been reported time and again in the 16 studies mentioned earlier.

The regression analysis suggested that sociodemographic variables explain a small part of the variance (2%). Compared with hardiness and work stressors, the sociodemographics seem to exert little influence on burnout. Even though T-test and variance analysis showed many significant differences between sociodemographics and other variables, it appears that demographics were not the main determinants of burnout when a multivariate correlational analysis is used. These results are consistent with those found in previous studies among nurses, social workers and teachers (Williams, 1989) and among hospitals nurses (Cash, 1988; Grutchfield, 1981; Teague, 1992). It is plausible to believe that demographics do not play a great role in producing burnout among nurses.

Maddi and Kobasa (1984) stipulate that hardy individuals have the capacity of seeking others’ assistance. To tackle stressful events, they seek help at the appropriate time from colleagues at work. Encouragement, goodwill and warm appreciation assist the individuals to cope transformationally. Hardy individuals have the ability to know when and where to seek support which encourages optimistic cognitive appraisal of stressors and decisive action to reduce their negative effect. The right kind of work support appears essential for effective coping in times of stressful events at work.

Therefore, it is suggested that hardiness could be a personal resource that a nurse may use to seek appropriate work support and to rely on active coping strategies for managing work stress events. Hardy nurses exposed to high stress in the work environment may avoid inhibition to work, psychological dysfunction and stay healthy.

This study highlights many factors which are important for nursing practice, management, education and research. At the threshold of the 21st century, where the values of


productivity, efficiency, effectiveness and rationalization of financial resources are important forces influencing health care services, it is highly probable that the nursing workload will not diminish. In this context, nurses will be constantly asked to do more with less. Nurses working in geriatric settings will be confronted daily with a multitude of difficulties: lack of personnel, heavy workloads and lack of time. These difficulties may accentuate the sources of stress. For this reason, nursing managers are invited to promote support from superiors as well as peers to attenuate the stress felt by the personnel. Adequate work planning may also help to reduce the frequency of the work stressors. Managers can help to develop and improve nurses’ hardiness at work. According to Dillard (1993) commitment to self and work can be enhanced when workers are encouraged to set specific, realistic and attainable goals for personal development and for work. Nurses need autonomy in their practice in order to improve their sense of control. Leaders are invited to help their nurses to recognize choices that are available in solving problems and resolving conflicts. Also, inservice educators may focus on knowledge of burnout and hardiness, as well as methods of conflict resolution in the workplace. Stress management methods could be included in curricula for geriatric nurses. Educators are invited to use innovative methods in teaching hardiness, support and coping in the workplace.

This study has shown cross-sectional relationships between the study variables and burnout. It is plausible to believe that an increasing burnout may reduce the capacity of a nurse to use hardiness to manage stressful events; the interactive nature of the relationships between these variables is not fully understood. Longitudinal research is required in order to better understand the relationships between work stressors, hardiness, coping methods, work support and burnout. As Maslach and Jackson (1981) pointed out, longitudinal research presents a large challenge, but it is of the utmost importance for our comprehension of burnout.

To enhance theoretical clarity, it is crucial that moderation and mediation relationships be clarified among the variables (Lindley and Walker, 1993). Testing a causal model of nursing burnout may be important in explaining when, how and why burnout phenomena occur. Using a statistical tool such as path analysis is recommended in order to test the Maddi and Kobasa model as applied to nursing burnout. Also, future research may focus in developing specific knowledge relative to nursing interventions which may contribute to the prevention of burnout and promotion of mental and physical health.

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(Received 24 FebrucrrJ 1993; accepted in reaised,form 13 December 1994)

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Psychosocial determinants of burnout in geriatric nursing