Open Journal of Medical Psychology
Vol.07 No.03(2018), Article ID:85883,13 pages

Study of Resistance to Stress and Burnout among Public Health Professionals: The Case of Nurses and Physicians at Ibn Sina Hospital in Rabat Morocco

Hassan Chtibi1, Ahmed Ahami1, Fatima Zahra Azzaoui1, Abderezzak Khadmaoui2, Khaoula Mammad1, Charles Mottier3, Philippe Wallon4

1Unit of Clinical and Cognitive Neuroscience and Nutritional Health, Department of Biology, Faculty of Science, University Ibn Tofail, Kenitra, Morocco

2Genetics and Biometrics Laboratory, Faculty of Sciences, University Ibn Tofail, Kenitra, Morocco

3SARL Selection and Advice, Nyon, Switzerland

4INSERM Saint Rémy lès Chevreuse, Paris, France

Copyright © 2018 by authors and Scientific Research Publishing Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

Received: April 17, 2018; Accepted: July 7, 2018; Published: July 10, 2018


Occupational stress presents a major public health problem. It is the subject of many works in Morocco and in the world. Our work focuses on the study of stress resistance among nurses and physicians working in services at Ibn Sina Hospital in Rabat, Morocco. The aim of this study is to analyze the relationship between resistance status, burnout and level of psychological distress. A self-questionnaire is provided to all respondents. It includes questions about socio-demographic and professional, clinical, also neuropsychological tests such as the stress resistance test (CTRS), the burnout scale (MBI) and the general health questionnaire (GHQ12). This study shows that 42% of nurses and physicians have a high level of emotional exhaustion, high level of depersonalization affects 49% of nurses and physicians and subjects with low professional achievement account for 67% and 54% of nurses and physicians suffer from psychological distress. The stress test reveals that 88% of subjects have a low or moderate level of stress resistance and only 12% have good resistance. Thus, our study sheds new light on the understanding of stress at work by using new measurement and evaluation methods such as TRS, with the aim of reducing or eliminating the impact of occupational stress in hospitals.


Work Stress, Resistance, Burnout, Psychological Distress, Nurses, Physicians, Risk

1. Introduction

Stress is an adaptive response to the requirements and constraints. It is essential for the proper functioning of the body [1] [2]. Many research studies have shown the link between medical and paramedical activity and professional stress [3] [4] [5]. Stress is defined as a transaction between a person and their professional environment [6]. Thus, the nurses and physicians develop a coping strategy to increase its resistance to the adverse effects of stress [7]. However, some people develop a stress face resistance and others are unable to resist, giving rise to a job stress which can lead to long term, burnout and physical health disorders [8] [9] [10].

Nevertheless, burnout is one of the most serious complications of occupational stress [11]. It is characterized by a varied symptomatology around three major components: emotional exhaustion, depersonalization and self-accomplishment. In fact, more the relationship between the individual and the professional environment is disturbed over the risk of burnout is important [12] [13]. Furthermore, professional stress can be the main cause of psychosomatic and cardiovascular disease [14] [15] [16] [17]. Work stress can be caused by organizational, occupational and/or personal factors [18] [19].

In addition, the complexity of the professional tasks, the quality of care requirement, the emotional overload, the role conflicts and the noise make the nurses’ and physicians’ activity more difficult and increase sensitivity to stress [20] ; some studies have shown that the noise nuisance can generate a state of stress [21]. Additionally, according to a study conducted by Israel et al. (2014) on noise pollution, noise in workplaces can worsen the state of stress, disrupting the quality of work and impairing cognitive activity of nurses and physicians [22] [23] [24]. Noise can also disrupt neuroendocrine functions by increasing the secretion of certain neurotransmitters such as noradrenergic and ACTH (Adreno Cortico Trophin) [25].

In Morocco, studies of the effect of noise on neurocognitive status of nurses and physicians remain very limited. For this purpose, our work consists

o To study stress resistance among medical and paramedical personnel practicing in hospital services, by assessing risk factors.

o To study the impact of stress resistance on burnout and psychological distress.

2. Materials and Methods

1) Population and study area

The target population for this study is nurses and physicians with a total of 100 persons. In fact, the study was carried out among people aged between 24 and 45, working in the intensive care, medical imaging, laboratory, emergency and operating theater departments of Ibn Sina Hospital in Rabat city, Morocco.

2) Procedures and scales

In order to collect the data, the participants in the survey are asked to complete a questionnaire containing information on socio-demographic characteristics, health history and perceived stress effects. Each subject had to pass the computerized stress test (CTRS), the general health questionnaire (GHQ12) and the emotional exhaustion (MBI) scale.

2.1. Computerized Test of Stress Resistance (CTSR)

This test initiated by André Rey, under the name of “Test points to organize”. In 2011, an automated version was developed in collaboration with Seldage. The results obtained made it possible to produce, in collaboration with Philippe Wallon, a computer-generated version generating emotional stress [26] [27]. The computerized test consists of 15 lines, 6 boxes per line and 11 points dispersed differently per box. The principle of the test is that the candidate must organize the points, discover the hidden forms and trace the geometric shapes (two squares and a triangle), listening, with the help of headphones a sound sample per line, in a 40 seconds interval per line.

2.2. Maslach Burnout Inventory (MBI)

The Maslach Burnout Inventory (MBI) is used to assess burnout among nurses and physicians [28] , it is composed of 22 items divided into three dimensions: Emotional Exhaustion (EE) evaluated using nine items, the dehumanization of the relationship (DR) or “Depersonalization” (DP) (five items) and Personal Accomplishment (PA) (eight items). Each item is rated from 0 to 6. A high level of burnout manifested through high scores for the EE and DP sub-scales, combined with a low score on the PA sub-scale, with a reversal for a low burn-out level [29] [30].

2.3. General Health Questionnaire (GHQ12)

GHQ12 is a self-questionnaire quantifying the degree of subjective psychological suffering. In our work, we chose the short version in 12 items (each item is rated from 0 to 3), where the response choices to statements are: “No more than usual”, “Not at all”, “Rather more than usual” and “Much more than usual” [4] [31] [32] [33]. For reading test results, we used dichotomous scoring (0-0-1-1).

3. Results and Discussion

3.1. Socio-Demographic Characteristics of Nurses and Physicians

Table 1 presents the results of the socio-demographic and socio-economic distribution of 100 nurses and physicians practicing at Ibn Sina Hospital in Rabat, 50% of whom are female and 50% male.

The average age of the respondents is 30.14 ± 0.48 years, with a minimum age of 23 years and a maximum age of 44 years. This age distribution was Gaussian with an asymmetry coefficient of 1.18 and a flattening coefficient of 1.17, While 62% of these respondents are single and 35% are married, their level of education is almost high for most. In addition, 71% work day and night against 25%

Table 1. Socio-demographic characteristics of the cases studied.

exercise only during the day. However, 84% of the respondents are between 25 and 35 years old and 43% have a seniority of less than 4 years and 39% between 4 years to 8 years. This makes it possible to draw the idea that most of the respondents are new recruits (Table 1).

3.2. Characteristics of Antecedents Related to Health Status of Nurses and Physicians

The distribution of health care providers according to their state of health shows that 77% answered that they didn’t suffer from any disease against 10% who declared to suffer from a chronic disease (asthma 5.75%, hypertension 2.29%, hyperthyroidism in one case 1%, and two cases 2% of chronic sinusitis). However, 13% of these respondents did not report anything.

The distribution of respondents according to certain reactions and attitudes adopted in the face of stressors shows that 32% take coffee and 27% drink tea. To overcome the state of stress, 19% of respondents said they had used tobacco and 12% prefer to consume tonics. To compensate for the direct and/or indirect effects of stress, 22% of the respondents practice physical activities (sports). However, some consult their doctor (9%), others benefit from sick leave 7%, and 8% are absent from work and 7% take sleeping pills. On the other hand, the respondents told to have a change in their eating behavior during the stress period. However, 51% said their appetite is down, while 33% say the opposite. For the question “your body weight changes or not, during the stress period”, 47% of people reported feeling a weight increase compared to 36% who saw it decrease.

3.3. Result of the Stress Test

3.3.1. Validation of the Resistance Test

To evaluate the psychometric properties of the items, we performed an analysis of the accuracy and reliability of the answers provided by the respondents. The results of the analysis indicate that the test has internal consistency (α = 0.54). The validation results of the various items show that in general the scores obtained for the “sounds” proposed by the test are moderately accepted with a minimum score of 0 and a maximum score of 3.

Nevertheless, the internal consistency of all items verified by principal component analysis. Three large groups of sound extracts have been released, the first group contains all the troublesome sounds, a second group gathers the soft sounds and a third groups the sounds without effects (Figure 1).

The two axes 1 and 2 alone absorb 75% of the total variation, which makes it possible to distinguish three large groups of correlated items. The first group (annoying sounds) located on the positive side of the axis 1, which is composed of the determining sounds that of the Rhythms musical S2; Insect S6; Storm S7; Accident S9; Ambulance S10; Childbirth S12 and Panic S15. The second group (soft sounds) located on the negative side of axis 1, where brings together the sounds of Musical mode S4; Wolves S8; Newborn S1. Finally third group taking an intermediate position and collecting the sounds (music OM S1, wagner S3, percussion S5, heart beat S11, choking S14). It is qualified, therefore, a group of sound extract without any effect (neutral).

3.3.2. Study of the Distribution of Respondents According to Their State of Resistance

In this part, we applied the paired comparison method, while distinguishing between different groups of sounds. So the assessment made on the difference between the score of the first group, the second group and the third group. The determination of resistance states based on percentiles. The results shown in Table 2. The descriptive analysis show that the average stress resistance score is 4.60 ± 6.77, with a minimum score of −110 points and a maximum score of 240 Successful boxes. The distribution of scores follows a normal distribution with an asymmetry coefficient of 0.90 and a flattening of 1.63 (4). Indeed, the prevalence of people with a low resistance state is 14% against 12% with a very high level of resistance. However, 74% of the respondents showed a moderate level of resistance, so, they qualified at risk, it is necessary to monitor them afterwards.

Table 2 summarizes the overall results of the link between the level of stress and certain socio-economic and demographic parameters. The results of this

Figure 1. Diagram of principal component analysis after rotation.

Table 2. Distribution of respondents according to their state of resistance to stress.

*: significant difference at 5%; ns: no significant.

distribution show that 14% of the studied cases have a problem of resistance to proposed sounds of which half is female and more than three quarter with an age between 20 to 30 years. The results of the chi-square test show that age is significantly related to the state of resistance to stress (p < 0.05). Indeed, the 14 cases declared very sensitive are almost all new recruits (less than 10 years old) and 10 of them are single. The chi-square test showed a significant correlation between the social level and the stress resistance test (chi-square = 6.43, p < 0.02). Indeed, the 11 cases that are very sensitive to stress among the 14 identified belong to an average social level and three cases among them have a good social level. Our results are consistent with those confirmed by studies that show that noise decreases human performance As well, younger people are more vulnerable to stress than older [22] [23] [24] [34].

3.4. Maslach Burnout Inventory (MBI)

Calculation of Cronbach’s alpha for this test is largely sufficient, 0.81. The results of the descriptive analysis of our sample show that the degree of burnout is very high compared to the standards established by Maslach and Jackson [30]. Table 3 shows the distribution of each component of the MBI in the population as a whole, with reference to the evaluation criteria of Maslach (1986). However, 42% of nurses and physicians have a high level of emotional exhaustion, high level of depersonalization affects 49% of nurses and physicians and the percentage of staff with a low level of achievement is 67%.

Table 4 illustrates the results of the chi-square test of independence between the different levels of MBI and certain socio-demographic factors. The results of this analysis show that sex, age, civil status, seniority and working hours are not significantly associated with MBI. A 63 are nurses (78.75% of all nurses), and 17 physians (85% of all doctors). We remark that the physians therefore more exposed to the risk of burnout compared to nurses. Indeed, the association between occupational status and the occurrence of emotional exhaustion is statistically significant (p < 0.05).

3.5. Psychological Distress

The person considered in a state of distress if the score obtained by the test is lower than the threshold set in the literature (threshold less than 4) [5] [32]. The percentage of staff suffering from psychological suffering is 54%. The analysis of the results at the GHQ 12 show that the professionals obtain an average score of 3.49 ± 0.283 with a minimum score of 0 and a maximum score of 10. The distribution of the scores follows a normal distribution with a coefficient of asymmetry of 0.58 and a flattening of 0.71.

The Chi 2 independence study between GHQ12 categories and socio-economic factors (gender, age, family status, work profile, and job seniority) shows no significant relationship. On the other hand, the number of hours worked per week is significantly related to mental suffering among the staff (p < 0.009), which leads to the conclusion that the psychic state of the carers is very sensitive to the number of hours worked.

3.6. Overall Analysis of the Three Tests

Table 5 presents the results of the descriptive analysis of the three selected tests (MBI, TRS, GHQ12): The average score of the exhaustion dimension is

Table 3. Distribution of scores for each component of the Maslach Burnout (MBI) scale.

Table 4. Results of the chi-square test between MBI and selected socio-economic factors.

Table 5. Descriptive study of the three selected tests (MBI, CTRS, GHQ12).

Min: minimum; Max: maximum.

28.07 ± 1.08, with a minimum score of 5 points and a score of up to 50. The distribution of the scores follows a normal distribution with an asymmetry coefficient of 0.128 and a flattening of −0.73. The average score of depersonalization is 29.91 ± 0.73, with a minimum score of 6 points and a maximum score of 51, the distribution of scores follows a normal distribution with an asymmetry coefficient of 0.03 and a flattening of 0.97. Then the average score of the self-completion dimension is 11.47 ± 0.62, with a minimum score of 1 point and a maximum score of 29. The distribution of scores follows a normal distribution with an asymmetry coefficient of 0, 38 and a flattening of 0.17.

Table 6 shows the multiple correlation results between the five demerits of the three tests (GHQ12, MBI and CTRS). It appears from this table that all dimensions are significantly correlated with each other with differences in the degree of significance and sign of correlation. However, the stress test correlated positively with professional achievement (r = 0.95) and negatively with the other dimensions. On the other hand, the GHQ12 has been positively correlated with all dimensions except the resistance where the correlation is negative. However achievement is negatively correlated with exhaustion and dehumanization and positively correlated with GHQ12 and stress resistance.

Table 6. Multiple correlation of the dimensions of the three tests, two by two.

*. Correlation is significant at 0.05 (bilateral). **. Correlation is significant at 0.01 (bilateral). ***. Correlation is significant at 0.001 (bilateral).

In light of these results, the group of resistant nurses and physicians in our sample can be described as having a low degree of exhaustion and depersonalization, a high degree of achievement, and low psychological suffering.

4. Discussion

The objective of this study is to evaluate the resistance to stress and to identify the most frequent dysfunctions among health professionals in order to prevent the consequences of professional stress. Our data reveal a relatively low rate of stress resistance among health workers practicing in Ibn Sina Hospital in Rabat/Morocco. Indeed, 14% of the staff do not have any stress resistance, 74% have a “moderate resistance” and only 12% have a “good resistance” to stress, if one refers to the results of the stress resistance test of Mottier (2013) [26]. With regard to the study population, and despite the fact that the medical and paramedical profession is considered to be one of the professions most affected by occupational stress [3] [4] [5] , and according to the literature, our study, is one of the first Moroccan studies that deals with the effects of noise pollution as a factor generating stress in hospitals. We have applied this test to hospital-based physicians and nurses to provide health professionals with a cost-effective and reliable tool for assessing their state of resistance. A first paper-and-pencil version with auditory stimuli was conducted on a large population of candidates in vocational and paramedical schools, showing its relevance [26]. The analysis of the results of our study allows us to group the items into three large groups. A first group of annoying sounds that can disrupt perception and diminish the performance of nurses and physicians [22] [26] [27]. In addition, studies have identified the negative impact of noise pollution on the cognitive activities of nurses and physicians [29] [35] [36]. The second group of items brings together extracts of soft sounds, which can trigger pleasant feelings opposing the harmful effects of stressful emotions. Returning to literature, there are few studies on the positive effect of soft sounds on health. Soft music activates brain areas in a way similar to other emotional stimuli [37] and involves the limbic system while listening to music [38]. The treatment of musical sound uses common areas with the treatment of emotions [39]. The main beneficial effects of relaxing music in men are the help for relaxation, concentration, better self-control in the face of stressful events and better performance on cognitive tasks [40].

Our study indicates a statistically significant relationship between the state of resistance to stress and the socio-economic difficulties of nurses and physicians. These same results are found by some studies [34] [41] [42].

Like the low level of resistance to stress and psychological suffering, burnout remains very high in our population. Our results reveal that 42% of nurses and physicians are emotionally exhausted and 49% of them have high scores of depersonalization as well as a reduction of accomplishment in 67%. However, these figures are consistent with most studies published around the world [34] [43] [44].

However, returning to the analysis of the factors associated with depersonalization in this population, unlike other studies [45] [46] , we do not observe significant links between burnout, age, sex, marital status, length of service, number of hours worked and socio-economic level. On the other hand, professional status is very significantly related to burnout. These show that medical personnel are less resistant to stress than nurses. These data are opposed, then, to the results found by some studies; nurses are more susceptible to stress than physicians [47] [48]. With respect to the mental health of nurses and physicians, the analysis of the GHQ12 results indicates that 54% of nurses and physicians, suffer from psychological distress and the number of hours worked per week are significantly related to this suffering.

Our data also show a correlation between the stress test scores and the total GHQ12 score as well as the burnout score.

Our results also show that there is a better understanding of the relationship between stress resistance, mental health and burnout when considering individual differences, especially risk factors. Returning to studies done in Morocco and around the world, occupational stress mainly affects the care environment because of the specific nature of the profession, the increase in the workload, poor working conditions in hospitals, dissatisfaction at work and socio-economic difficulties of health personnel, particularly nurses [41] [47] [48].

This allows us to assume in this study that stress resistance depends on personal, occupational and environmental factors that may expose nurses and physicians to multiple and repeated occupational stress situations. [3]. In addition, during the clinical interviews, we talked about major dysfunctions related to the stress situation in hospitals. 8% of nurses and physicians miss work under stress, 7% take sleeping pills to sleep, 19% use tobacco, 12% prefer tonics to complete their work, 9% consult their doctor, 7% benefit from sick leave, 51% of respondents say they decrease their appetite under the effect of stress, and 10% suffer from chronic pathologies.

5. Conclusion

The results found in this context remain very encouraging despite the difficulties encountered during the sampling; the choice of subjects and the methods of analysis have posed a great obstacle for us to deepen the statistical analyzes. To identify these difficulties, sampling should extend to other professional sectors.

Cite this paper

Chtibi, H., Ahami, A., Azzaoui, F.Z., Khadmaoui, A., Mammad, K., Mottier, C. and Wallon, P. (2018) Study of Resistance to Stress and Burnout among Public Health Professionals: The Case of Nurses and Physicians at Ibn Sina Hospital in Rabat Morocco. Open Journal of Medical Psychology, 7, 34-46.


  1. 1. Lôo, P., Lôo, H. and Galinowski, A. (1999) Le stress permanent. Masson, Paris.

  2. 2. André, C., Lelord, F. and Légeron, P. (1998) Le stress. éditions Privat, Toulouse.

  3. 3. Girault-Lidvan, N. (1998) Burn-out: éMergence et stratégie d’adaptations, le cas de la médecine d’urgence. Thèse de psychologie, dir Pr Levy-Leboyer, Université René Descartes, Paris.

  4. 4. Goldberg, D.P. and Williams, P. (1998) A User’s Guide to the General Health Questionnaire. NFER-NELSON, Windsor.

  5. 5. Jehel, L. (2002) Victimes et soignants face au traumatisme psychique, études de facteurs prédictifs péritraumatiques et validations d’instruments de mesures. Thèse pour l’obtention du diplôme de Docteur, Université Paris-VI.

  6. 6. Rascle, N. (2001) Facteurs psychosociaux du stress professionnel et de l’épuisement professionnel. In: Bruchon-Schweitzer, M. and Quintard, B., Eds., Personnalités et maladies: Stress, coping et ajustement, Dunod, Paris, 221-238.

  7. 7. Nivet, P., Alby, J.M. and Crocq, L. (1989) Les réactions émotionnelles chez les décideurs, les sauveteurs et les soignants. Soins Psychiatriques, 106/107, 18-22.

  8. 8. McConnell, E.A. (1982) Burn Out in the Nursing Profession: Coping Strategies, Causes, and Cost. Mosby, Toronto.

  9. 9. European Agency for Safety and Health at Work (2002) Stress at Work. Rapport 2002. Office for Official Publication of the European Community, Luxembourg.

  10. 10. European Agency for Safety and Health at Work (2007) Expert Forecast on Emerging Psychosocial Risks Related to Occupational Safety and Health. Office for Official Publications of the European Communities, Luxembourg.

  11. 11. Cooper, L. (2005) Handbook of Stress Medicine and Health. CRC Press, Boca Raton.

  12. 12. Canoui, P. and Mauranges, A. (2004) Le burn-out. Masson, Paris.

  13. 13. Légeron, P. and Guéritault, V. (2006) L’épuisement professionnel. In: Guedj, M.-J. and Pascal, J.-C., Eds., La Psychiatrie en urgence, éditions de l’Interligne, Paris.

  14. 14. Després, J.P. (2004) Inter Heart: A Study of Risk Factors for First Myocardial Infarction in 52 Countries and over 27000 Subjects. Communication non publiée, European Society of Cardiology, Munich.

  15. 15. Kivimäki, M. (2002) Work Stress and Risk of Cardiovascular Mortality: Prospective Cohort Study of Industrial Employees. British Medical Journal, 325, 857-862.

  16. 16. Yusuf, S., Hawken, S., Ounpou, S., et al. (2004) Effect of Potentially Modifiable Risk Factors Associated with Myocardial Infarction in 52 Countries. (The Interheart Study). A Case-Control Study. The Lancet, 364, 937-952.

  17. 17. Bernard, B.P. (1997) Musculoskeleted Disorders and Workplace Factors. A Critical Review of Epidemiologic Evidence for Work-Related Musculoskeleted Disorders of the Neck, Upper Extremity and Low Back. U.S. Department of Health and Human Services, Public Health Service, CDC and NIOSH, Washington DC.

  18. 18. Schweitzer, M. (2005) La prédiction de la santé: Les modèlesexplicatifs. Psychologie de la santé. Modèles, concepts etméthodes. Dunod, Paris, 84-93.

  19. 19. Légeron, P. (2004) Le stress au travail: De la performance à la souffrance. Droit Social, No. 12.

  20. 20. Gray-Toft, P. and Anderson, J.-G. (1981) The Nursing Stress Scale: Development of an Instrument. Journal of Behavior Assessment, 3, Il-23.

  21. 21. Vallet, M., Gagneux, J.M., Clairet, J.M., et al. (1983) Heart Rate Reactivity to Aircraft Noise after a Long Term Exposure. In: Rossi, G., Ed., Noise as a Public Health Problem, Centro Ricerche e Studi Amplifon, Milano, 965-971.

  22. 22. Kenda, I.M., Agoub, M. and Ahami, A.O.T. (2014) Les effets du bruit sur la santé mentale: Recension des écrits. Santé mentale au Québec, 39, 169-181.

  23. 23. Ryherd, E.E., Waye, K.P. and Ljungkvist, L. (2008) Characterizing Noise and Perceived Work Environment in a Neurological Intensive Care Unit. The Journal of the Acoustical Society of America, 123, 747-756.

  24. 24. Gurses, A.P. and Carayon, P. (2009) Exploring Performance Obstacles of Intensive Care Nurses. Applied Ergonomics, 40, 509-518.

  25. 25. Soulairac, A. (1992) Le bruit: Aspects neuro-endocriniens. Bulletin de L’Académie Nationale de Médecine, 176, 401-405.

  26. 26. Mottier, C. (2013) Psychologue, Sélection & Conseils, Nyon, Suisse 9.

  27. 27. Wallon, P. and Mesmin, C. (2009) Test de la figure complexe de Rey. ECPA, Paris.

  28. 28. Dion, G. and Tessier, R. (1994) Validation de la traduction de l’inventaire d’e’puisement professionnel de Maslach et Jackson. Revue canadienne des sciences du comportement, 26, 210-227.

  29. 29. Canouï, P. and Mauranges, A. (1998) Le syndrome d’épuisement professionnel des soignants. Masson, Paris.

  30. 30. Maslach, C. and Jackson, S.E. (1986) The Maslach Burnout Inventory. Second Edition, Consulting Psychologist Press, Palo Alto.

  31. 31. Lépine, J.P. (1996) Le questionnaire de santé. In: Guelfi, J.D., Ed., L’évaluation clinique standardisée en psychiatrie, éditionsmédicales Pierre Fabre (JD).

  32. 32. Weinberg, A. and Creed, F. (2000) Stress and Psychiatric Disorder in Healthcare Professionals and Hospital Staff. The Lancet, 355, 533-536.

  33. 33. Whitley, T.W., Allison, E.J., Gallery, M.E., Cockington, R.A., Gaudry, P., Heyworth, J., et al. (1994) Work-Related Stress and Depression among Practicing Emergency Physicians. An International Study. Annals of Emergency Medicine, 23, 1068-1071.

  34. 34. Canoui, P. and Mauranges, A. (2008) Le burn out à l’hôpital. Le syndrome professionnel des soignants. 4th Edition, Elsevier-Masson, Paris, 240 p.

  35. 35. Cohen, S., Kamarck, T. and Mermelstein, R. (1983) A Global Measure of Perceived Stress. Journal of Health and Social Behavior, 24, 385-396.

  36. 36. Moghaddam, B. and Jackson, M. (2004) Effect of Stress on Prefrontal Cortex Function. Neurotoxicity Research, 6, 73-78.

  37. 37. Trainor, L.J. and Schmidt, L.A. (2003) Processing Emotions Induced by Music. In: Peretz, I. and Zatorre, R.J., Eds., The Cognitive Neuroscience of Music, Oxford University Press, Oxford, 310-324.

  38. 38. Blood Anne, J., Zatorre, P.B. and Evans, A.C. (1999) Emotional Reponses to Pleasant and Unpleasant Music.

  39. 39. Juslin, P.N. and Sloboda, J.A. (2013) Music and Emotion. The Psychology of Music, 3, 583-645.

  40. 40. Rickard, N.S., Toukhsati, S.R. and Field, S.E. (2005) The Effect of Music on Cognitive Performance: Insight from Neurobiological and Animal Studies. Behaviour Cognitive Neuroscience Review, 4, 235-261.

  41. 41. Laraqui, O., Laraqui, S., Laraqui, C.H., et al. (2008) Evaluation des contraintes psychosociales et organisationnelles chez le personnel de soins au Maroc: A propos d’une étude multicentrique. Archives des Maladies Professionnelles et de l’Environnement, 69, 672-682.

  42. 42. Gueroui, S., Vaxevanoglou, X., Nezzal, A.Z., et al. (2004) Les déterminants organisationnels et psychosociaux du stress et l’activité hospitalière au CHU de Annaba. Archives Des Maladies Professionnelles De Medecine Du Travail Et De Securite Sociale, 65, 138.

  43. 43. Delbrouck, M. (2008) Le burn out du soignant. Le sydrome d’epuisement professionnel. De boeck, Bruxelle, 280 p.

  44. 44. Shehabi, Y., Dobb, G., Jenkins, I., Pascoe, R., Edwards, N. and Butt, W. (2008) Burnout Syndrome among Australian Intensivists: A Survey. Critical Care and Resuscitation, 19, 312-315.

  45. 45. Hyman, S.A., Michaels, D.R., Berry, J.M., Schildcrout, J.S., Mercaldo, N.D. and Weinger, M.B. (2011) Risk of Burnout Perioperative Clinicians: A Survey Study and Literature Review. Aneshtesiology, 114, 194-204.

  46. 46. Embriaco, N., Azoulay, E., Barrau, K., Kentish, N., Pochard, F., Loundou, A., et al. (2007) High Level of Burnout in Intensivists: Prevalerice and Associated Factors. American Journal of Respiratory and Critical Care Medicine, 175, 686-692.

  47. 47. Blegen, M.A. (1993) Nurses Job Satisfaction: Meta-Analysis of Related Variables. Nursing Research, 42, 36-41.

  48. 48. Fanello, S., Morlier-Tournelle, C., Ripault, B., et al. (2003) Souffrance psychique des cadres infirmiers: Etude portant sur 97 cadres d’un centre hospitalier universitaire français. Archives Des Maladies Professionnelles De Medecine Du Travail Et De Securite Sociale, 64, 375-382.