Next Article in Journal
Vigilance in the Decision-Making Process Regarding Termination of Pregnancy Following Prenatal Diagnosis of Congenital Heart Disease—Application of the ‘Conflict Decision-Making Model’
Next Article in Special Issue
The North Italian Longitudinal Study Assessing the Mental Health Effects of SARS-CoV-2 Pandemic on Health Care Workers—Part I: Study Design and Psychometric Structural Validity of the HSE Indicator Tool and Work Satisfaction Scale
Previous Article in Journal
Protective Factors against Self-Harm and Suicidality among Australian Indigenous Adolescents: A Strengths-Based Analysis of the Longitudinal Study of Indigenous Children
Previous Article in Special Issue
Occupational Health and Safety Receptivity towards Clinical Innovations That Can Benefit Workplace Mental Health Programs: Anxiety and Hypnotherapy Trends
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Mental Illness and Work-Related Limitations in Healthcare Workers: A Preliminary Retrospective Study

1
Department of Psychology, University of Bologna, 40127 Bologna, Italy
2
Department of Psychiatry, Bologna University Hospital Authority St. Orsola-Malpighi Polyclinic IRCCS, 40138 Bologna, Italy
3
Department of Management, Technology and Economics, ETH Zürich, 8092 Zürich, Switzerland
4
Occupational Health Unit, Bologna University Hospital Authority St. Orsola-Malpighi Polyclinic IRCCS, 40138 Bologna, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2022, 19(15), 9098; https://doi.org/10.3390/ijerph19159098
Submission received: 9 July 2022 / Accepted: 23 July 2022 / Published: 26 July 2022
(This article belongs to the Special Issue Mental Health at the Workplace)

Abstract

:
This retrospective observational study investigated hospital staff requests for job fitness visits, addressed to occupational medicine. Specific objectives were to analyze: (1) health workers’ requests, sociodemographic characteristics, psychiatric diagnoses, assigned doctor’s fit notes, and (orthopedic, psychiatric) limitations; (2) associations between psychiatric diagnoses, sociodemographic (sex, age), and work-related (job, department) characteristics; (3) associations between the same psychiatric diagnoses/orthopedic limitations, fit notes, and/or psychiatric limitations. Data of St. Orsola-Malpighi Polyclinic health workers (N = 149; F = 73.8%; mean age = 48 ± 9.6 years), visited by both the occupational medicine physician and psychiatrist (January 2016–May 2019), were analyzed. 83.2% of the sample presented with at least one psychiatric diagnosis, including mood (47%), anxiety (13.4%), and anxious-depressive (10.7%) disorders. Significant differences between psychiatric diagnoses according to sex and fit notes (both p < 0.01) have been found, whereas no significant associations based on age and work-related characteristics have been observed. Analysis of frequencies of participants with the same psychiatric diagnosis (orthopedic limitation being equal), according to doctor’s fit notes and psychiatric work limitations, showed a high heterogeneity of assignments. The current occupational medicine procedure for fit notes/job limitations assignments does not allow taking into consideration clinical factors possibly associated with more specific assignments. To standardize the procedure and translate the psychiatrist’s clinical judgment into practice, further studies to test the usefulness of clinimetrics, which might represent a reliable approach in considering different fit notes and job limitations, are needed.

1. Introduction

Mental illness represents the second leading cause, after musculoskeletal disorders, of work-related problems, and it accounts for more than one-third of work-related illnesses [1]. Whatever the mental disorder, psychopathological conditions in work settings have deleterious effects on performance, absenteeism, and days of disability at work [2,3,4,5,6,7,8].
Hospital medical and technical staff may be exposed daily to health risks such as ergonomic hazards, shift work, work-related stress, and violence [9,10], which have been shown to cause mental disorders [11]. Among healthcare workers, both nurses [12,13,14,15] and physicians [16,17,18] may present high levels of stress and work-related mental illness [19,20]. Moreover, working in different departments, such as oncological and hematological, anesthesia and emergency areas, and intensive and critical care units, was associated with different levels of work-related stress and the presence of mental disorders [21,22,23,24,25,26,27].
In recent years, the mental health of healthcare workers has been gaining increasing attention worldwide as a major public health threatening issue, in terms of quality of care delivery [28]. There is strong evidence that healthcare workers are exposed to multiple stress factors within their work, which have the potential to negatively affect their physical and psychological well-being [29,30,31]. Even before the pandemic, indeed, in the United States, 44% of physicians reported at least one symptom of burnout in 2017 compared with about 54% in 2014 and about 45% in 2011 [32], whereas in Latin American countries, the mental health of healthcare workers was poorer than the mental health of the general population [33]. In Great Britain, the category of human health and social work activities had significantly higher rates of work-related stress, depression, or anxiety (2770 cases per 100,000 workers) than the average for all other industries [34]. According to the National Institute of Statistics, in Italy, 32% of healthcare workers reported exposure to at least one work-related psychosocial risk factor [35]. The World Health Organization estimates a projected shortfall of 18 million health workers by 2030, mostly in low- and lower-middle-income countries [36]. Given this international overview, the role of occupational medicine, its assessment of disability and psychological limitations at work, and, consequently, of psychic fitness for work, become crucial [37,38]. In Italy, the occupational physician’s assessment of fitness for work can be described by a categorization including standardized definitions, as follows: fit, fit with restrictions (in this case, the physician should indicate the type of limitation and whether it is temporary or permanent), temporarily unfit (in this case, the physician should specify a date for the follow-up), and permanently unfit [39]. The occupational physician evaluates whether cognitive, relational, behavioral, and creative skills have been compromised [40]. Based on this, he or she will formulate a fitness for work assessment explaining the state of health of the subject, considering the ability to carry out the work without worsening the worker’s own mental health and causing damage to third persons. Furthermore, the physician should be equipped with reliable instruments to evaluate cognitive and emotional abilities essential for the job [37]. For the collection of anamnestic data, it would be desirable to use structured and semi-structured interviews, which should also evaluate individual vulnerability with a certain sensitivity towards psychopathology [41]. The occupational physician should collaborate with other healthcare professionals (such as psychiatrists and psychologists) to manage possible mental problems [40] and he/she should assess whether the use of psychodiagnostic tests is necessary to formulate a complete worker’s clinical picture [42]. However, the overall Italian situation is far from optimal [40]. Moreover, in occupational medicine, little research was published on the assessment of fitness for work [43]. Porrone and Esposito [39] also pointed out, with reference to the Italian literature, that specific studies on fitness for work, including validated procedures and instruments for a standardized assessment of possible work-related pathological conditions, are insufficient. In the same vein, Serra and colleagues [44] showed that the assessment instruments in work contexts should be specific whereas there is very little scientific evidence, probably because standard or valid methodologies for all professions and circumstances are lacking, despite occupational specialists expressing this need.
The aims of the present preliminary retrospective observational study are as follows: (1) to assess healthcare workers’ requests, sociodemographic characteristics, psychiatric diagnoses according to current nosography, assigned doctor’s fit notes, and limitations (orthopedic and psychiatric) in an Italian hospital; (2) to identify statistical associations between psychiatric diagnoses, sociodemographic characteristics (e.g., sex, age), and work-related variables (e.g., job, department); (3) to evaluate descriptive associations between the same psychiatric diagnoses/orthopedic limitations, fit notes, and psychiatric limitations.

2. Materials and Methods

2.1. Sample

The sample included 149 healthcare workers at Sant’Orsola-Malpighi Polyclinic in Bologna. All the workers had been visited by an occupational physician, and then by a psychiatrist, for psychological and psychiatric issues from January 2016 to May 2019.

2.2. Assessment (Definition of Variables)

Data of the sample were retrospectively collected from July to September 2021 by means of the web platform Infoclin, a software used for the management of health clinical data at Sant’Orsola-Malpighi Polyclinic. Only visits for psychic fitness were considered.
Sociodemographic information about sex, age, type of job, and department where the individuals worked, were collected. Data about the number of visits with the occupational physician, year of the first visit, diagnoses of mental disorder according to the DSM-5 [45], psychotherapeutic and/or pharmacological treatment, fit notes, and limitations at work according to the occupational physician, were reported as well. All subjects received a fit note according to their health status, as follows: fit for work, unfit for work, and fit with limitations. Limitations were prescribed according to orthopedic and/or psychiatric diseases. Regarding limitations at work for orthopedic problems, the occupational medicine Department at Sant’Orsola-Malpighi Polyclinic relies on a categorization from type A to type D based on the “Dictionary of Occupational Title” [46], according to the level of physical demand that workers can tolerate. Indeed, type A means that workers are able to cope with very heavy work: occasionally workers have to move objects > 45 kg, frequently 23 kg, constantly 9 kg; type B means that workers are able to cope with medium work: occasionally workers have to move objects 9–23 kg, frequently 4.5–11.5 kg, constantly 4.5 kg; type C means that workers are able to cope with light work: occasionally workers have to move objects < 9 kg, frequently < 4.5 kg, constantly negligible; type D means that workers are able to cope with very light work: occasionally workers have to move objects < 4.5 kg, frequently negligible, constantly negligible. Limitations related to psychiatric disorders include direct care exemption, night shifts exemption, high-risk area exemption, unfit for a specific department, and exemption from emergency departments.
Data of the sample were gathered by fulfilling a data collection sheet, specifically prepared for the present investigation. Diagnoses, treatments, and limitations were established by a psychiatrist together with an occupational physician. Data were analyzed anonymously according to the Italian data protection regulation (Legislative Decree No. 196/2003). The study was conducted in accordance with the ethical principles of the Declaration of Helsinki [47].

2.3. Data Analysis

Since this study follows a case series design, the sample size was not preliminarily calculated [48]. Descriptive and explorative data analyses were performed. Continuous data were expressed as means (±standard deviation, SD) and categorical data were shown as frequencies and percentages. A general linear model (ANOVA) was run to ascertain statistical differences among participants with different DSM-5 psychiatric diagnoses (fixed factor), according to age (dependent variable). Thereafter, Fisher’s exact test applied to contingency tables was used to evaluate the presence of statistical associations between psychiatric diagnoses and kind of job (i.e., physician, other health professionals, healthcare assistant/technician/other), department (i.e., medical departments, administrative departments), and fit notes (i.e., fit without limitations, fit with limitations/other, unfit). Finally, a descriptive analysis was made in order to outline frequencies of participants with the same psychiatric diagnosis/same orthopedic limitation, according to fit notes and psychiatric work limitations.
All calculations were performed using IBM SPSS 26.0 and a p-value < 0.05 was considered to be significant.

3. Results

3.1. Healthcare Workers’ Requests, Sociodemographic Characteristics, Psychiatric Diagnoses, Assigned Doctor’s Fit Notes and Limitations

The sample included 149 healthcare workers (mean age = 48 ± 9.6 years; F = 73.8%), mainly at the department of oncology/hematology (N = 23; 15.4%) (Table 1). The most represented job category was health professionals, who included nurses (N = 79; 53%), physiotherapist (N = 1; 0.7%), dietician (N = 1; 0.7%) and midwife (N = 1; 0.7%), followed by healthcare assistants (N = 35; 23.5%), such as formal carers (Table 1). The total number of psychiatric consults from 2016 to 2019 was 337, with a mean of 2.3 visits (±1.9) per person, and the most frequent psychiatric diagnosis according to DSM-5 was depression (N = 66; 44.3%) (Table 1). According to the doctor’s fit note, 52 (34.9%) workers were judged fit for work without any limitation, whereas 20 (13.4%) received work limitations for orthopedic issues, 42 (28.2%) for psychiatric conditions, and 23 (15.4%) for both orthopedic and psychiatric problems (Table 1). Finally, 9 (6%) workers were judged unfit for the job (Table 1).

3.2. Associations between Psychiatric Diagnoses, Sociodemographic Characteristics and Work-Related Variables

ANOVA did not show any significant association between age and psychiatric diagnoses (F = 0.401; p > 0.05) (Table 2). Using Fisher’s exact test, significant differences in psychiatric diagnoses according to sex (χ2 = 16.739; p < 0.01) and fit notes (χ2 = 24.181; p < 0.01) have been found, whereas no significant association according to a different kind of job and department has been observed. For further details, see Table 2.

3.3. Analysis of Frequencies of Participants with Same Psychiatric Diagnosis/Same Orthopedic Limitation, According to Fit Notes and Psychiatric Work-Limitations

Frequencies of participants with the same psychiatric diagnosis/same orthopedic limitation, according to doctor’s fit notes, are reported in Table 3. As to depressive disorder, which represented the commonest psychiatric condition, according to the physician’s judgment, depressed healthcare workers with the same orthopedic limitations encountered very heterogeneous scenarios. Specifically, among 39 (26.2%) depressed participants with type A limitation, 16 (10.7%) were considered fit to work without any limitation, whereas 23 (15.4%) were judged fit to work with psychiatric limitations. Three (2%) depressed subjects with type B limitation were fit to work with both psychiatric and orthopedic limitations. Among 14 (9.4%) depressed workers with type C limitation, 8 (5.4%) were considered fit to work with only orthopedic limitations, whereas 6 (4%) with both psychiatric and orthopedic limitations. Among 5 (3.4%) depressed subjects with type D limitation, 2 (1.4%) were judged fit to work with only orthopedic limitations, and 3 (2%) with both psychiatric and orthopedic limitations. Healthcare workers diagnosed with other psychiatric conditions encountered similar heterogeneous scenarios (Table 3).
Frequencies of participants with the same psychiatric diagnosis/same orthopedic limitation, according to psychiatric limitations to own job, are reported in Table 4. As to depressive disorder, depressed healthcare workers were assigned with a variety of psychiatric limitations, orthopedic issues being equal. Specifically, among 39 (26.2%) depressed subjects with type A limitation, 16 (10.7%) did not have psychiatric limitations, 15 (10.1%) received night shift exemption, 1 (0.7%) both night shift and emergency area exemption, 2 (1.4%) night shift and department activity exemptions, 2 (1.4%) direct care exemption, 2 (1.4%) changed department, and 1 (0.7%) was readdressed to work in outpatient placement. Among 14 (9.4%) depressed healthcare workers with type C limitation, 8 (5.4%) did not have psychiatric limitations, 5 (3.4%) received night shift exemption, and 1 (0.7%) changed department. Among 5 (3.4%) depressed subjects with type D limitations, 2 (1.4%) did not have psychiatric limitations, 1 (0.7%) received night shift exemption, and 2 (1.4%) direct care exemption. Healthcare workers diagnosed with other psychiatric conditions encountered similar heterogeneous scenarios (Table 4).

4. Discussion

The aims of this study were to describe the psychiatric clinical picture, according to current nosography, of healthcare workers at Sant’Orsola-Malpighi Polyclinic in Bologna, who required one or more visits to the Occupational Medicine Department from 2016 to 2019, and to understand the clinical procedure used to prescribe fit notes and work limitations according to psychiatric diagnoses, orthopedic limitations being equal.
Firstly, descriptive analyses revealed requests from almost three-quarters of females and a prevalence of nurses unevenly distributed across different departments of the hospital. This is consistent with the literature showing that adult women report a higher prevalence of affective disorders and psychoses than men among healthcare workers and in the general population [49,50]. In line with what has been described in the literature [49], the present study revealed a significant association between sex and psychiatric diagnoses. Indeed, sex could be taken into account as a factor that may influence developing or exacerbating disorders such as depression in vulnerable people. In the present study, no significant association between age and presence or type of diagnosis was found.
In the present investigation, the most frequent diagnosis was depressive disorder. This result is in line with the categorization of mental disorders by Glozier [2], which places depressive disorders in the category of the most frequent psychiatric disorders at work. Although there are numerous studies in the literature that have reported a high level of stress and a higher incidence of mental disorders related to nursing work [12,13,14,15], the results of our study did not support this finding. Indeed, contrary to what was expected [12,13,14,15,16,17,18,20], no significant associations between type of diagnosis and type of job were found, as well as between diagnosis and type of department, despite the fact that in some departments workers are characterized by high work-related stress and consequent mental disorders [21,22,23,24,25,26,27,51].
Furthermore, a descriptive analysis of the frequencies highlighted a great heterogeneity in fit notes and work limitations assigned by the psychiatrist in cooperation with the occupational doctor to categories of workers with the same psychiatric diagnosis (orthopedic limitations being equal). In fact, although some health workers have the same diagnosis, their assigned fit notes and job limitations varied a lot, ranging from complete unrestricted fitness to unfit for the job, from a change in working hours to a direct care exemption, which entails a reorganization of the working environment. It is possible to hypothesize that several factors contributed to the formulation of the psychiatrist’s clinical judgment in order to assign different fit notes and work limitations. These factors might include the worker’s medical history, presence of other comorbidities, course of the disorder including the specific stage (i.e., a person may present a psychiatric diagnosis in its acute, residual, or chronic phase), type, severity and sequence of symptoms, other aspects of daily life and other clinical characteristics resulting in diverse clinical, prognostic, and therapeutic differences among individuals [52]. Indeed, it is not surprising that most of the time clinicians rely not only on explicit evidence from research but also on their own experience and that of their colleagues (tacit knowledge or “mind-lines”) [53]. The standard procedure applied in occupational medicine, as well as in psychiatric settings in general, is thus based most of the time on the psychiatrist’s own clinical judgments following internal clinical parameters, which should be considered as clinimetric parameters. Feinstein [54] proposed a clinimetric approach that is intended to translate this internal judgment into clinical parameters, which could be shared among different clinicians. The clinimetric approach is an integrative model to the psychometric one in the evaluation of psychopathology, with the aim of making the assessment according to a clinical (and not only to a statistical) consistency. It advocates for including within a frame of reference the patient him or herself as a whole, and not simply his/her disorder [54]. It follows that it would be important to conduct a clinimetric assessment that could integrate the problem not only from a categorical nosographic point of view but also from a dimensional perspective considering the various factors mentioned above [55].
The literature, in line with the present findings, highlights a lack of standardized guidelines for the assessment of psychic fitness for a specific job and for the assignment of limitations and the fact that effective assessment instruments are not used [40]. The clinimetric approach could fill this gap. Indeed, it emphasizes the importance of including both observer- and self-rated instruments in the clinical assessment process that could allow discriminating between groups of patients with the same clinical diagnosis, physical impairment being equal [56].
The present investigation has some limitations that should be discussed. The first is represented by the cross-sectional design and the preliminary nature of the findings, which were obtained retrospectively by consulting electronic medical records (i.e., the Infoclin platform). Secondly, a convenience sampling method was used, thus limiting the generalizability of study findings. Finally, the third limit of this study is monocentricity, since it included workers from only one hospital located in Northern Italy. Future research should consider larger samples from different hospitals located in different regions in Italy, as well as in different European countries.

5. Conclusions

The findings of the present study have shown that a categorical approach in identifying the nuances of the severity of mental illness does not match with the complexity of the human being, and does not match, accordingly, with fit notes and job limitation assignments during the assessment procedure of occupational health visits. This procedure does not allow taking into consideration specific clinical factors that might be associated with a more specific fit note and task limitation assignment. In order to standardize the procedure in occupational medicine settings and translate into practice the psychiatrist’s clinical judgment, further studies are needed to test the usefulness of a clinimetric approach, including not only categorical but also dimensional tools, to assess the course of mental illness, stage of the disorder, level of severity of patient’s clinical picture, and comorbidity. These factors may be discriminatory in both prognosis and treatment of patients and may therefore be more specific and reliable in considering different fit notes and job limitations.

Author Contributions

Conceptualization, S.G., C.P. (Carmine Petio) and C.R.; data curation, L.N. and C.M.; formal analysis, L.N. and C.P. (Chiara Patierno); investigation, L.N. and C.M.; methodology, S.G., C.P. (Carmine Petio) and C.R.; project administration, V.L., C.P. (Carmine Petio) and C.R.; resources, C.M., V.L. and C.P. (Carmine Petio); supervision, S.G., C.P. (Carmine Petio) and C.R.; validation, S.G., L.N., V.L., C.P. (Carmine Petio) and C.R.; visualization, S.G. and L.N.; writing—original draft, S.G., L.N. and C.R.; writing—review and editing, S.G., L.N., C.M., C.P. (Chiara Patierno), D.C., C.B., S.Z., V.L., C.P. (Carmine Petio) and C.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. Given the peculiar setting of the present research, which included non-invasive procedures and confidential evaluations only, and the Italian legislation regarding occupational medicine, an additional ethical approval was not necessary. Indeed, according to the Italian Legislative Decree No. 81/2008 on health surveillance, healthcare workers must undergo to periodic occupational medicine visits, which frequency is established by the competent physician according to a risk-based evaluation. Data registered in Infoclin during these visits can be analyzed for health risk evaluation and research purposes.

Informed Consent Statement

Informed oral consent was obtained from all subjects involved in the study.

Data Availability Statement

The original data analyzed are available from the corresponding author on reasonable request.

Acknowledgments

The authors would like to acknowledge Luana Fantini for her support in preliminary data analysis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Self-Reported Work-Related Health Problems and Risk Factors—Key Statistics. Available online: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Self-reported_work-related_health_problems_and_risk_factors_-_key_statistics (accessed on 27 February 2022).
  2. Glozier, N. Mental ill health and fitness for work. Occup. Environ. Med. 2002, 59, 714–720. [Google Scholar] [CrossRef] [Green Version]
  3. Stansfeld, S.; Feeney, A.; Head, J.; Canner, R.; North, F.; Marmot, M. Sickness absence for psychiatric illness: The Whitehall II Study. Soc. Sci. Med. 1995, 40, 189–197. [Google Scholar] [CrossRef]
  4. Martin, J.K.; Blum, T.C.; Beach, S.R.; Roman, P.M. Subclinical depression and performance at work. Soc. Psychiatry Psychiatr. Epidemiol. 1996, 31, 3–9. [Google Scholar] [CrossRef] [PubMed]
  5. Dewa, C.S.; Lin, E. Chronic physical illness, psychiatric disorder and disability in the workplace. Soc. Sci. Med. 2000, 51, 41–50. [Google Scholar] [CrossRef]
  6. Duchaine, C.S.; Aubé, K.; Gilbert-Ouimet, M.; Vézina, M.; Ndjaboué, R.; Massamba, V.; Talbot, D.; Lavigne-Robichaud, M.; Trudel, X.; Pena-Gralle, A.B.; et al. Psychosocial stressors at work and the risk of sickness absence due to a diagnosed mental disorder: A systematic review and meta-analysis. JAMA Psychiatry 2020, 77, 842–851. [Google Scholar] [CrossRef] [PubMed]
  7. Hennekam, S.; Richard, S.; Grima, F. Coping with mental health conditions at work and its impact on self-perceived job performance. Empl. Relat. 2020, 42, 626–645. [Google Scholar] [CrossRef]
  8. Rapisarda, F.; Vallarino, M.; Brousseau-Paradis, C.; Benedictis, L.D.; Corbière, M.; Villotti, P.; Cavallini, E.; Briand, C.; Cailhol, L.; Lesage, A. Workplace factors, burnout signs, and clinical mental health symptoms among mental health workers in Lombardy and Quebec during the first wave of COVID-19. Int. J. Environ. Res. Public Health 2022, 19, 3806. [Google Scholar] [CrossRef]
  9. Balducci, C.; Avanzi, L.; Fraccaroli, F. Emotional demands as a risk factor for mental distress among nurses. Med. Lav. 2014, 105, 100–108. [Google Scholar] [PubMed]
  10. Balducci, C.; Vignoli, M.; Dalla Rosa, G.; Consiglio, C. High strain and low social support at work as risk factors for being the target of third-party workplace violence among healthcare sector workers. Med. Lav. 2020, 111, 388–398. [Google Scholar]
  11. Gorman, T.; Dropkin, J.; Kamen, J.; Nimbalkar, S.; Zuckerman, N.; Lowe, T.; Szeinuk, J.; Milek, D.; Piligian, G.; Freund, A. Controlling health hazards to hospital workers. New Solut. 2013, 23, 1–167. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Lambert, V.A.; Lambert, C.E. Literature review of role stress/strain on nurses: An international perspective. Nurs. Health Sci. 2001, 3, 161–172. [Google Scholar] [CrossRef] [PubMed]
  13. Aiken, L.H.; Clarke, S.P.; Sloane, D.M.; Sochalski, J.; Silber, J.H. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA 2002, 288, 1987–1993. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. McVicar, A. Workplace stress in nursing: A literature review. J. Adv. Nurs. 2003, 44, 633–642. [Google Scholar] [CrossRef]
  15. Vahey, D.C.; Aiken, L.H.; Sloane, D.M.; Clarke, S.P.; Vargas, D. Nurse burnout and patient satisfaction. Med. Care 2004, 42, II57–II66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Dyrbye, L.N.; West, C.P.; Satele, D.; Boone, S.; Tan, L.; Sloan, J.; Shanafelt, T.D. Burnout among US medical students, residents, and early career physicians relative to the general US population. Acad. Med. 2014, 89, 443–451. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Tsiga, E.; Panagopoulou, E.; Montgomery, A. Examining the link between burnout and medical error: A checklist approach. Burn. Res. 2017, 6, 1–8. [Google Scholar] [CrossRef]
  18. Martin, M. Physician Well-Being: Physician Burnout. FP Essent. 2018, 471, 11–15. [Google Scholar] [PubMed]
  19. Maslach, C.; Schaufeli, W.B.; Leiter, M.P. Job burnout. Ann. Rev. Psychol. 2001, 52, 397–422. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Mohanty, A.; Kabi, A.; Mohanty, A.P. Health problems in healthcare workers: A review. J. Fam. Med. Prim. Care 2019, 8, 2568–2572. [Google Scholar] [CrossRef] [PubMed]
  21. Lyckholm, L. Dealing with stress, burnout, and grief in the practice of oncology. Lancet Oncol. 2001, 2, 750–755. [Google Scholar] [CrossRef]
  22. Lert, F.; Chastang, J.F.; Castano, I. Psychological stress among hospital doctors caring for HIV patients in the late nineties. AIDS Care 2001, 13, 763–778. [Google Scholar] [CrossRef] [PubMed]
  23. Barrett, L.; Yates, P. Oncology/haematology nurses: A study of job satisfaction, burnout, and intention to leave the specialty. Aust. Health Rev. 2002, 25, 109–121. [Google Scholar] [CrossRef] [Green Version]
  24. Nyssen, A.S.; Hansez, I.; Baele, P.; Lamy, M.; De Keyser, V. Occupational stress and burnout in anaesthesia. Br. J. Anaesth. 2003, 90, 333–337. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Weibel, L.; Gabrion, I.; Aussedat, M.; Kreutz, G. Work-related stress in an emergency medical dispatch center. Ann. Emerg. Med. 2003, 41, 500–506. [Google Scholar] [CrossRef] [PubMed]
  26. Mealer, M.L.; Shelton, A.; Berg, B.; Rothbaum, B.; Moss, M. Increased prevalence of post-traumatic stress disorder symptoms in critical care nurses. Am. J. Respir. Crit. Care Med. 2007, 175, 693–697. [Google Scholar] [CrossRef] [PubMed]
  27. Vasconcelos, E.M.; Martino, M.; França, S. Burnout and depressive symptoms in intensive care nurses: Relationship analysis. Rev. Bras. Enferm. 2018, 71, 135–141. [Google Scholar] [CrossRef] [Green Version]
  28. Søvold, L.E.; Naslund, J.A.; Kousoulis, A.A.; Saxena, S.; Qoronfleh, M.W.; Grobler, C.; Münter, L. Prioritizing the mental health and well-being of healthcare workers: An urgent global public health priority. Front. Public Health 2021, 9, 679397. [Google Scholar] [CrossRef] [PubMed]
  29. Hayashino, Y.; Utsugi-Ozaki, M.; Feldman, M.D.; Fukuhara, S. Hope modified the association between distress and incidence of self-perceived medical errors among practicing physicians: Prospective cohort study. PLoS ONE 2012, 7, e35585. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Khanal, P.; Devkota, N.; Dahal, M.; Paudel, K.; Joshi, D. Mental health impacts among health workers during COVID-19 in a low resource setting: A cross-sectional survey from Nepal. Glob. Health 2020, 16, 89. [Google Scholar] [CrossRef] [PubMed]
  31. Muller, A.E.; Hafstad, E.V.; Himmels, J.; Smedslund, G.; Flottorp, S.; Stensland, S.Ø.; Stroobants, S.; Van de Velde, S.; Vist, G.E. The mental health impact of the COVID-19 pandemic on healthcare workers, and interventions to help them: A rapid systematic review. Psychiatry Res. 2020, 293, 113441. [Google Scholar] [CrossRef] [PubMed]
  32. Shanafelt, T.D.; West, C.P.; Sinsky, C.; Trockel, M.; Tutty, M.; Satele, D.V.; Carlasare, L.E.; Dyrbye, L.N. Changes in burnout and satisfaction with work-life integration in physicians and the general US working population between 2011 and 2017. Mayo Clin. Proc. 2019, 94, 1681–1694. [Google Scholar] [CrossRef] [Green Version]
  33. Rosales-Vaca, K.M.; Cruz-Barrientos, O.I.; Girón-López, S.; Noriega, S.; More-Árias, A.; Guariente, S.M.M.; Zazula, R. Mental health of healthcare workers of Latin American countries: A review of studies published during the first year of COVID-19 pandemic. Psychiatry Res. 2022, 311, 114501. [Google Scholar] [CrossRef]
  34. Health and Safety Executive (HSE). Work-Related Stress, Anxiety or Depression Statistics in Great Britain. 2021. Available online: https://www.hse.gov.uk/statistics/causdis/stress.pdf (accessed on 10 February 2022).
  35. Istituto Nazionale di Statistica (ISTAT). Salute e Sicurezza sul Lavoro in Italia. Anno 2020. Available online: https://www.istat.it/it/files//2021/11/Salute_e_sicurezza_sul_lavoro_-2020_Istat_Eurostat.pdf (accessed on 10 February 2022).
  36. World Health Organization (WHO). Working for Health and Growth: Investing in the Health Workforce. Report of the High-Level Commission on Health Employment and Economic Growth. 2016. Available online: http://apps.who.int/iris/bitstream/10665/250047/1/9789241511308-eng (accessed on 10 February 2022).
  37. Ferrari, G. Pena conDivisa. Rischi Psicosociali e Valorizzazione della Professionalità Degli Operatori Dell’amministrazione Penitenziaria; Edizioni FerrariSinibaldi: Milano, Italy, 2016. [Google Scholar]
  38. Mental Health in the Workplace in Europe. Available online: https://ec.europa.eu/health/system/files/2017-07/compass_2017workplace_en_0.pdf (accessed on 23 February 2022).
  39. Porrone, A.; Esposito, M. La Sorveglianza Sanitaria e il Giudizio di Idoneità alla Mansione Specifica: Profili Dottrinari, Giuridici, e Criteri D’indagine. Available online: https://www.melchiorregioia.it/pdf-mg/tagete/1780.pdf (accessed on 30 March 2022).
  40. Ferrari, G.; De Cesare, D.P.; Ferrante, S. Medicina del Lavoro e Idoneità Psichica: La Valutazione Dell’idoneità Psichica e la Temporanea Limitazione al Lavoro; Edizioni FerrariSinibaldi: Milano, Italy, 2016. [Google Scholar]
  41. Buselli, R.; Cristaudo, A. Il medico competente e il rischio stress lavoro correlato: Dalla collaborazione alla valutazione del rischio alla sorveglianza sanitaria. G. Ital. Med. Lav. Erg. 2009, 31, 261–264. [Google Scholar]
  42. Bettini, T.; Camusso, N.; Finardi, M.R.; Lamanna, R.; Rossi, L. Psicologia della salute e sicurezza nelle attività di diagnostica di laboratorio: Valutazione e strumenti per la prevenzione, nella sorveglianza dello stress lavoro-correlato, dal prelievo al risultato. Ital. J. Lab. Med. 2017, 13, 72–79. [Google Scholar] [CrossRef]
  43. Dorrington, S.; Roberts, E.; Mykletun, A.; Hatch, S.; Madan, I.; Hotopf, M. Systematic review of fit note use for workers in the UK. Occup. Environ. Med. 2018, 75, 530–539. [Google Scholar] [CrossRef] [Green Version]
  44. Serra, C.; Rodriguez, M.C.; Delclos, G.L.; Plana, M.; López, L.I.G.; Benavides, F.G. Criteria and methods used for the assessment of fitness for work: A systematic review. Occup. Environ. Med. 2007, 64, 304–312. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed.; American Psychiatric Publishing: Washington, DC, USA, 2013. [Google Scholar]
  46. Physical Demands Strength Rating Defined in Dictionary of Occupational Title. Available online: https://occupationalinfo.org/appendxc_1.html#STRENGTH (accessed on 15 February 2022).
  47. World Medical Association. World medical association declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA 2013, 310, 2191–2194. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Checkoway, H.; Pearce, N.; Kriebel, D. Research Methods in Occupational Epidemiology; Oxford University Press: New York, NY, USA, 2004. [Google Scholar]
  49. Shi, L.; Wang, L.; Jia, X.; Li, Z.; Mu, H.; Liu, X.; Peng, B.; Li, A.; Fan, L. Prevalence and correlates of symptoms of post-traumatic stress disorder among Chinese healthcare workers exposed to physical violence: A cross-sectional study. BMJ Open 2017, 7, e016810. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Riecher-Rössler, A. Sex and gender differences in mental disorders. Lancet Psychiatry 2017, 4, 8–9. [Google Scholar] [CrossRef]
  51. O’Brien-Pallas, L.; Irvine, D.; Peereboom, E.; Murray, M. Measuring nursing workload: Understanding the variability. Nurs. Econ. 1997, 15, 171–182. [Google Scholar] [PubMed]
  52. Fava, G.A.; Rafanelli, C.; Tomba, E. The clinical process in psychiatry: A clinimetric approach. J. Clin. Psychiatry 2012, 73, 177–184. [Google Scholar] [CrossRef]
  53. Fava, G.A.; Guidi, J.; Rafanelli, C.; Sonino, N. The clinical inadequacy of evidence-based medicine and the need for a conceptual framework based on clinical judgment. Psychother. Psychosom. 2015, 84, 1–3. [Google Scholar] [CrossRef] [PubMed]
  54. Feinstein, A.R. An additional basic science for clinical medicine: IV. The development of clinimetrics. Ann. Intern. Med. 1983, 99, 843–848. [Google Scholar] [CrossRef] [PubMed]
  55. Gostoli, S.; Buzzichelli, S.; Guidi, J.; Sirri, L.; Marzola, E.; Roncuzzi, R.; Abbate-Daga, G.; Fava, G.A.; Rafanelli, C. An innovative approach to the assessment of mood disturbances in patients with acute coronary syndrome. CNS Spectr. 2021, 1–12. [Google Scholar] [CrossRef] [PubMed]
  56. Carrozzino, D.; Patierno, C.; Guidi, J.; Montiel, C.B.; Cao, J.; Charlson, M.E.; Sparle Christensen, K.; Concato, J.; De Las Cuevas, C.; de Leon, J.; et al. Clinimetric criteria for patient-reported outcome measures. Psychother. Psychosom. 2021, 90, 222–232. [Google Scholar] [CrossRef] [PubMed]
Table 1. Socio-demographic characteristics of the participants (N = 149).
Table 1. Socio-demographic characteristics of the participants (N = 149).
N (%)Mean (±DS)
Age (range 23–65 years old) 48.0 (±9.6)
Sex
 Male39 (26.2)
 Female110 (73.8)
Job
 Physicians11 (7.4)
 Other health professionals82 (55)
 Healthcare assistants35 (23.5)
 Technicians, other21 (14.1)
Department
Medical departments
 Oncology/hematology23 (15.4)
 Women and children18 (12.1)
 Gatroenterology/endocrinology18 (12.1)
 Nephrology17 (11.4)
 Cardiology14 (9.4)
 Radiology12 (8.1)
 Emergency9 (6)
 Head/neck9 (6)
 Outpatient clinic8 (5.4)
 Infectivology3 (2)
 Scheduled hospitalizations3 (2)
 Test laboratory1 (0.7)
Administrative departments
 Administrative management 12 (8.1)
 Public relations office2 (1.3)
Number of psychiatric evaluations (range 1–13 visits) 2.3 (±1.9)
Year of first psychiatric evaluation
 201643 (28.9)
 201739 (26.2)
 201841 (27.5)
 201926 (17.4)
Psychiatric diagnoses
 None25 (16.8)
 Depressive disorder66 (44.3)
 Anxious-depressive disorder16 (10.7)
 Panic disorder with agoraphobia13 (8.7)
 Anxiety disorder7 (4.7)
 Alcohol abuse with/without comorbidity5 (3.3)
 Bipolar disorder4 (2.7)
 Post-traumatic stress disorder3 (2)
 Adjustment disorder3 (2)
 Eating disorder2 (1.3)
 Personality disorder3 (2)
 Obsessive-compulsive disorder1 (0.7)
Fit notes and limitations
 None52 (34.9)
 Unfit9 (6)
 Fit with orthopedic limitations20 (13.4)
 Fit with psychiatric limitations42 (28.2)
 Fit with both psychiatric and orthopedic limitations23 (15.4)
 Not available3 (2)
Table 2. Associations between psychiatric diagnoses and age, sex, job, department, and limitations.
Table 2. Associations between psychiatric diagnoses and age, sex, job, department, and limitations.
None
(N = 25)
Mood Disorder
(N = 70)
Anxiety Disorder
(N = 20)
Anxious-Depressive Disorder
(N = 16)
Alcohol Abuse (N = 5)Stress-Related Disorders (N = 6)Other
(N = 7)
Mean ± SDMean ± SDMean ± SDMean ± SDMean ± SDMean ± SDMean ± SDFp
Age47.4 ± 10.848.9 ± 9.447.1 ± 9.648.3 ± 8.749.6 ± 13.845.3 ± 7.244.4 ± 10.90.4010.877
N (%)N (%)N (%)N (%)N (%)N (%)N (%)χ2 *p*
Sex
 Male10 (25.6)14 (35.9)6 (15.4)0 (0)2 (5.1)3 (7.7)4 (10.3)16.7390.006
 Female15 (13.6)56 (50.9)14 (12.7)16 (14.5)3 (2.7)3 (2.7)3 (2.7)
Job
 Physicians 2 (18.2)4 (36.4)1 (9.1)2 (18.2)1 (9.1)0 (0)1 (9.1)7.720NS
 Other health professionals 12 (14.6)40 (48.8)10 (12.2)10 (12.2)2 (2.4)5 (6.1)3 (3.7)
 Healthcare assistants, technicians, other 11 (19.6)26 (46.4)9 (16.1)4 (7.1)2 (3.6)1 (1.8)3 (5.4)
Department
 Medical Dept.23 (17)63 (46.7)17 (12.6)16 (11.9)5 (3.7)6 (4.4)5 (3.7)5.260NS
 Administrative Dept.2 (14.3)7 (50)3 (21.4)0 (0)0 (0)0 (0)2 (14.3)
   Women and children a3 (16.7)9 (50)2 (11.1)2 (11.1)2 (11.1)0 (0)0 (0)
   Cardiology a2 (14.3)8 (57.1)3 (21.4)0 (0)1 (7.1)0 (0)0 (0)
   Radiology a2 (16.7)8 (66.7)0 (0)1 (8.3)0 (0)1 (8.3)0 (0)
   Nephrology a4 (23.5)6 (35.3)3 (17.6)3 (17.6)0 (0)1 (5.9)0 (0)
   Oncology/hematology a2 (8.7)13 (56.5)1 (4.3)3 (13)1 (4.3)1 (4.3)2 (8.7)
   Head/Neck a3 (33.3)3 (33.3)1 (11.1)1 (11.1)0 (0)1 (11.1)0 (0)
   Emergency a0 (0)4 (44.4)3 (33.3)2 (22.2)0 (0)0 (0)0 (0)
   Infectivology a0 (0)1 (33.3)1 (33.3)0 (0)0 (0)0 (0)1 (33.3)
   Gastroenterology/Endocrinology a4 (22.2)7 (38.9)3 (16.7)2 (11.1)0 (0)1 (5.6)1 (5.6)
   Scheduled hospitalizations a1 (33.3)0 (0)0 (0)1 (33.3)0 (0)1 (33.3)0 (0)
   Outpatient clinic a2 (25)3 (37.5)0 (0)1 (12.5)1 (12.5)0 (0)1 (12.5)
   Test laboratory a0 (0)1 (100)0 (0)0 (0)0 (0)0 (0)0 (0.0)
   Administrative management b2 (16.7)5 (41.7)3 (25)0 (0)0 (0)0 (0)2 (16.7)
   Public relations office b0 (0)2 (100)0 (0)0 (0)0 (0)0 (0)0 (0)
Fit notes
 Fit without limitations13 (25)18 (34.6)6 (11.5)5 (9.6)3 (5.8)1 (1.9)6 (11.5)24.1810.006
 Fit with limitations/other10 (11.5)48 (55.2)12 (13.8)11 (12.6)1 (1.1)5 (5.7)0 (0)
 Unfit2 (20)4 (40)2 (20)0 (0)1 (20)0 (0)1 (10)
   Type B (+other) c0 (0)1 (25)1 (25)1 (25)0 (0)1 (25)0 (0)
  Type C (+other) c3 (12.5)13 (54.2)3 (12.5)2 (8.3)0 (0)3 (12.5)0 (0)
  Type D (+other) c1 (33.3)1 (33.3)0 (0)1 (33.3)0 (0)0 (0)0 (0)
  No night shift (+other) c5 (18.5)17 (63)3 (11.1)2 (7.4)0 (0)0 (0)0 (0)
  No direct care (+other) c1 (6.7)8 (53.3)1 (6.7)4 (26.7)1 (6.7)0 (0)0 (0)
  Change department c0 (0)1 (0.7)0 (0)1 (0.7)0 (0)1 (0.7)0 (0)
  Other c0 (0)1 (33.3)2 (66.7)0 (0)0 (0)0 (0)0 (0)
  Unspecified/sent to commission c0 (0)6 (75)2 (25)0 (0)0 (0)0 (0)0 (0)
* Fisher’s exact test; a frequencies of each medical department; b frequencies of each administrative department; c frequencies of each limitation assigned by the physician.
Table 3. Frequencies of participants with the same psychiatric diagnosis/same orthopedic limitation, according to fit notes.
Table 3. Frequencies of participants with the same psychiatric diagnosis/same orthopedic limitation, according to fit notes.
FitFit with Psychiatric LimitationsFit with Only Orthopedic LimitationsUnfit
N (%)N (%)N (%)N (%)
Depressive disorder + Type A16 (10.7)23 (15.4)-4 (2.7)
Depressive disorder + Type B-3 (2.0)0 (0.0)
Depressive disorder + Type C-6 (4.0)8 (5.4)
Depressive disorder + Type D-3 (2.0)2 (1.3)
Anxious-depressive disorder + Type A3 (2.0)3 (2.0)-1 (0.7)
Anxious-depressive disorder + Type B-2 (1.3)0 (0.0)
Anxious-depressive disorder + Type C-2 (1.3)1 (0.7)
Anxious-depressive disorder + Type D-1 (0.7)1 (0.7)
Alcohol abuse + Type A1 (0.7)1 (0.7)-0 (0.0)
Panic disorder with agoraphobia + Type A8 (5.4)2 (1.3)-1 (0.7)
Panic disorder with agoraphobia + Type B-2 (1.3)0 (0.0)
Panic disorder with agoraphobia + Type C-1 (0.7)0 (0.0)
Anxiety disorder + Type A1 (0.7)3 (2.0)-0 (0.0)
Anxiety disorder
handling only with help
-1 (0.7)0 (0.0)
Anxiety disorder + Type C-0 (0.0)2 (1.3)
Bipolar disorder + Type A1 (0.7)1 (0.7)-0 (0.0)
Bipolar disorder + Type B-0 (0.0)1 (0.7)
Bipolar disorder + Type C-0 (0.0)1 (0.7)
Work-related stress + Type A0 (0.0)1 (0.7)-1 (0.7)
Work-related stress + Type C-0 (0.0)1 (0.7)
Insomnia + Type A-1 (0.7)-0 (0.0)
Table 4. Frequencies of participants with same psychiatric diagnosis/same orthopedic limitation, according to psychiatric limitations to work.
Table 4. Frequencies of participants with same psychiatric diagnosis/same orthopedic limitation, according to psychiatric limitations to work.
No Psychiatric
Limitations
No Night ShiftNo Night Shift + Department ActivityNo Night Shift + No Direct CareNo Direct CareChange DepartmentOutpatient PlacementNo Night Shift + No Emergency AreaNo Emergency Area
N (%)N (%)N (%)N (%)N (%)N (%)N (%)N (%)N (%)
Depressive disorder + Type A16 (10.7)15 (10.1)2 (1.3)0 (0)2 (1.3)2 (1.3)1 (0.7)1 (0.7)0 (0)
Depressive disorder + Type B0 (0)3 (2)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Depressive disorder + Type C8 (5.4)5 (3.4)0 (0)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)
Depressive disorder + Type D2 (1.3)1 (0.7)0 (0)0 (0)2 (1.3)0 (0)0 (0)0 (0)0 (0)
Anxious-depressive disorder + Type A3 (2)1 (0.7)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)1 (0.7)
Anxious-depressive disorder + Type B0 (0)1 (0.7)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)
Anxious-depressive disorder + Type C1 (0.7)1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)1 (0.7)0 (0)
Anxious-depressive disorder + Type D1 (0.7)0 (0)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)
Alcohol abuse + Type A1 (0.7)0 (0)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)
Panic disorder with agoraphobia + Type A8 (5.4)0 (0)0 (0)1 (0.7)1 (0.7)0 (0)0 (0)0 (0)0 (0)
Panic disorder with agoraphobia + Type B0 (0)0 (0)0 (0)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)
Panic disorder with agoraphobia + Type C0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Anxiety disorder + Type A1 (0.7)1 (0.7)0 (0)0 (0)1 (0.7)0 (0)1 (0.7)0 (0)0 (0)
Anxiety disorder handling only with help0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Anxiety disorder + Type C2 (1.3)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Bipolar disorder + Type A1 (0.7)0 (0)0 (0)0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)
Bipolar disorder + Type B1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Bipolar disorder + Type C1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Work-related stress + Type A0 (0)1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Work-related stress + Type C1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Insomnia + Type A1 (0.7)1 (0.7)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)0 (0)
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Gostoli, S.; Nicolucci, L.; Malaguti, C.; Patierno, C.; Carrozzino, D.; Balducci, C.; Zaniboni, S.; Lodi, V.; Petio, C.; Rafanelli, C. Mental Illness and Work-Related Limitations in Healthcare Workers: A Preliminary Retrospective Study. Int. J. Environ. Res. Public Health 2022, 19, 9098. https://doi.org/10.3390/ijerph19159098

AMA Style

Gostoli S, Nicolucci L, Malaguti C, Patierno C, Carrozzino D, Balducci C, Zaniboni S, Lodi V, Petio C, Rafanelli C. Mental Illness and Work-Related Limitations in Healthcare Workers: A Preliminary Retrospective Study. International Journal of Environmental Research and Public Health. 2022; 19(15):9098. https://doi.org/10.3390/ijerph19159098

Chicago/Turabian Style

Gostoli, Sara, Laura Nicolucci, Carlotta Malaguti, Chiara Patierno, Danilo Carrozzino, Cristian Balducci, Sara Zaniboni, Vittorio Lodi, Carmine Petio, and Chiara Rafanelli. 2022. "Mental Illness and Work-Related Limitations in Healthcare Workers: A Preliminary Retrospective Study" International Journal of Environmental Research and Public Health 19, no. 15: 9098. https://doi.org/10.3390/ijerph19159098

APA Style

Gostoli, S., Nicolucci, L., Malaguti, C., Patierno, C., Carrozzino, D., Balducci, C., Zaniboni, S., Lodi, V., Petio, C., & Rafanelli, C. (2022). Mental Illness and Work-Related Limitations in Healthcare Workers: A Preliminary Retrospective Study. International Journal of Environmental Research and Public Health, 19(15), 9098. https://doi.org/10.3390/ijerph19159098

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop