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ORIGINAL ARTICLE
Year : 2013  |  Volume : 22  |  Issue : 1  |  Page : 17-21  Table of Contents     

Socio demographic and clinical predictors of absenteeism A cross sectional study of urban industrial employees


Department of Psychiatry, Hindustan Aeronautics Limited Hospital, Bangalore, Karnataka, India

Date of Web Publication24-Dec-2013

Correspondence Address:
Suhash Chakraborty
Qtr No MD 13, 7th Main, Hal Old Township, Vimanapura PO, Bangalore - 560 017, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-6748.123589

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   Abstract 

Context: Public sector undertakings are facing a threat of privatization due to unsatisfactory performance putting pressure on management and in turn to employees. There is an increasing trend of absenteeism observed amongst employees citing job stress. Aim: To find an association between job stress and absenteeism in relation to socio-demographic and clinical profile. Materials and Methods: The study was conducted in an urban aeronautical industry with 68 employees who mentioned stress at workplace during evaluation. Job stress was assessed using Professional Life Stress Scale (David Fontana). Those who scored more than 30 (n = 43) were taken up for the study after an informed consent. A semi-structured questionnaire was administered to find socio-demographic and clinical profile. Employees who reported taking leave in last six months just to avoid work or workplace constitute the "absenteeism" group. The absenteeism group was compared to non-absenteeism group using Fisher exact/Chi-square test or independent t-test depending on type of variables. Results: Out of 43 subjects, 18 had absenteeism while 25 did not have absenteeism. Comparing the two groups, interstate migration, having more than one previous job, commuting time more than an hour, co-morbid anxiety/depression, and alcohol abuse were significantly associated with absenteeism (P < 0.05). Absentees complained more about fatigue and relationship problem with colleagues than non-absentees (P < 0.05). Factors like age, sex, marital status, education, gross pay, job tenure, past or family history of psychiatry illnesses had no significant association with absenteeism (P > 0.05). Conclusion: In absenteeism research, one of the widely accepted models is Steer and Rhode's "Process model of absenteeism." The model postulates job stress as one of the barriers for attendance. Thus, knowing the factors for absenteeism would help in preventing absenteeism.

Keywords: Absenteeism, clinical profile, job stress, socio-demographic


How to cite this article:
Chakraborty S, Subramanya AH. Socio demographic and clinical predictors of absenteeism A cross sectional study of urban industrial employees. Ind Psychiatry J 2013;22:17-21

How to cite this URL:
Chakraborty S, Subramanya AH. Socio demographic and clinical predictors of absenteeism A cross sectional study of urban industrial employees. Ind Psychiatry J [serial online] 2013 [cited 2019 Oct 16];22:17-21. Available from: http://www.industrialpsychiatry.org/text.asp?2013/22/1/17/123589

In the last two decades, professional stress has received a lot of interest among the researchers because of its detrimental effect on overall performance of the organization. Occupational stress was initially observed in private sectors then gradually to government-run public sector undertakings, mainly because of the threat of privatization or closure citing lack of performance. Job stress is an important cause of absenteeism in the public sectors. [1] Earlier Indian studies have shown that frequency of absenteeism in industrial sector due to stress is quite high. [2] However, not all workers suffering from job stress remain absentees. Our study is an attempt to analyze factors that lead to absenteeism amongst job-stressed employees.


   Materials and Methods Top


The study was conducted in the psychiatric department of an urban industrial hospital in Southern India. The psychiatry department of this hospital caters to approximately 30 to 35 patients per day in OPD. Subjects were enrolled between August, 2011 and March, 2012. A total of 68 employees (both officers and workmen) who came to see the psychiatrist either voluntarily or being referred by other professionals and who cited job stress as a cause of their ailment were enrolled as subjects. After taking informed consent, these subjects were assessed for professional stress using the Professional Stress Scale. The Professional Stress Scale is a reliable instrument for assessing job stress developed by David Fontana in the year 1989. [3] According to the scale, those who score between 31 and 45, stress is definitely a problem in their life, and a score of more than 45 is considered as major stress. By taking a cut-off score of 31, we found that 43 out of 68 subjects have definite professional stress. These 43 subjects constitute the study group. The study group was then administered two semi-structured questionnaires to find out their socio-demographic and clinical profile. The questionnaires for this purpose were designed by the investigator. [Table 1] is showing socio-demographic and [Table 2] is showing clinical profile. For diagnosing depression, anxiety, and alcohol abuse/dependence, we used ICD-10 criteria. [4]
Table 1: Comparison of socio-demographic characteristics

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The subjects were then divided into two groups - Absenteeism and Non-absenteeism. We took a qualitative definition of absenteeism for this purpose. Those subjects who reported that they took leave in last six months just to avoid work or workplace were defined as absentees and formed the absenteeism group. Six month was chosen because it balances the concern about short cycle susceptibility to bias [5] with problem associated with asking respondents to accurately recall their behavior over long period of time. [6] Those who did not avoid work or workplace in spite of the job stress constitute the non-absenteeism group. Finally, we compared the two groups based on the socio-demographic and clinical profile.

Descriptive statistics in terms of percentage were used for categorical variables; mean and SD were calculated for the continuous variables. Group comparisons were done using Fisher exact test/Chi-square test for categorical variables and independent t-test for continuous variables. A P < 0.05 was considered statistically significant.


   Results Top


Of the 43 subjects, 18 (42%) had absenteeism (95% CI = 28-57) while 25 did not have absenteeism (58%). Among males, majority (60%, n = 24) are non-absentees while two out of three females subjects were absentees (66.66%). Those under 30 years of age have equal number in both groups. Sixty percent of subjects between 30 and 45 years and 71% above 45 years were in non-absenteeism group. Similarly, majority from Hindu religion (60%), nuclear family (60%), urban background (55%), and married (58%) are non-absentees. Education-wise, majority in all three categories are in non-absenteeism group. Three-fourths (75%) of migrants are absentees, suggesting a strong association between migration and absenteeism. Interestingly, 62% (n = 18) and 71% (n = 5) above 25,000 and 50,000 rupees of gross pay, respectively, are non-absentees. Approximately 81% of subjects for whom present job is the first one are non-absentees while 78% who changed job more than once are absentees. For subjects who took up to 60 minutes to reach workplace, nine are absentees while 19 are non-absentees. However, when duration is more than 60 minutes, majority (60%) are absentees [Table 1].

[Table 2] shows clinical characteristics of job-stressed employees. Ten out of 13 subjects who complained fatigue are in absenteeism group (77%). However, majority who complained worries (63%), insomnia (70%), somatic complaints (75%), and irritability (100%) are in non-absenteeism group. While stating the main problem in workplace, poor inter-personal relationship was cited by 12 (85%) absentees compared to only two in the other group. Those who cited other reasons such as work overload (61%), spending more hours in factory (50%), wanting work in another field than the present one (100%), and lack of motivation (100%) belong to non-absenteeism category.
Table 2: Comparison of clinical characteristics

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Sixty percent of job-stressed employees who abuse or depend on alcohol are in absenteeism group. Two-thirds (66%) of those with a past or family history of psychiatric illness are non-absentees. Twenty-four employees attributed their physical illness to stress, of which only ten (41%) are absentees.

While comparing the two groups, it is seen that interstate migration, having more than one previous job, duration of journey of more than an hour to workplace, co-morbid anxiety/depression, and alcohol abuse are significantly associated with absenteeism (P < 0.05). Another significant finding is that absentees complained more about fatigue and relationship problem with colleagues than non-absentees (P < 0.05). On the contrary, factors like age, sex, marital status, family type, background, education, gross pay, job duration, complaints of worries, insomnia, somatic complaints, work overload, working overtime, past/family history of psychiatry illness, and physical co-morbidity have no significant association with absenteeism (P > 0.05), [Table 1] and [Table 2].


   Discussion Top


All 43 subjects in our study group had significant job stress measured on a standard scale. We found absenteeism in 42% employees. In an earlier study conducted at a public sector industry in Karnataka, sickness absenteeism was found to be as high as 67%. We cannot directly compare this with our finding because different studies have taken different parameter of absenteeism. For our study, we preferred a definition of absenteeism, which was just to avoid work or workplace. Our idea was to analyze job stress-induced absenteeism only.

Majority of the male subjects of all ages, Hindus, those who are married, belonging to nuclear family type, from urban or rural background with an educational qualification of graduate, under graduate or post-graduate belong to non-absenteeism group. Similarly, majority of employees who earn more than twenty five thousand rupees are non-absentees. On the contrary, being female, non-nuclear family type, and when gross income is less than twenty five thousand have higher representation in absenteeism group. These findings should be interpreted with the background that these are not statistically significant. This is in contrast to earlier studies where single men had the lowest absence rates while married women had the highest absence rates. This was attributed to higher sensitivity towards family responsibilities after marriage like taking care of children, spouse etc. [7]

However, there was a significant difference between the two groups on interstate migration (P = 0.001), commuting (P = 0.01), and number of previous jobs (P = 0.001). In a study done in Singapore, among 345 non-executive workers, it was found that compared to local counterpart, migrants had more sickness absence. Cultural and language differences, poor job adjustment, psycho-social stress were the factors attributed for this. [8] We also found that duration of journey to workplace of more than an hour have more absenteeism. This is in concurrence with an Italian study on 1167 industrial workers. Commuting is shown to interfere with patterns of everyday life by restricting free time and reducing sleeping time. Commuters who use public transport have problems due to more changes between modes, idle waiting times, and delays leading to late arrival at work. Further, overcrowding, noise, vibration etc., add to psychological stress in already stressed out employees. [9]

We have found that more employees in the absenteeism group changed job frequently in the past compared to non-absentees, for whom present job is their first one. The difference was statistically significant (P = 0.001). However, when we analyzed job tenure between the two groups, we found that mean duration of the present job for absenteeism and non-absenteeism group was 11.61 years and 12.22 years, respectively, and this is not significant statistically (P > 0.05). Ideally, we would have expected that employees in the absenteeism group would have much shorter job tenure. This finding is very interesting and somewhat contradictory. This shows that though majority of the absentees changed job frequently in the past, they seemed to have got settled in the present job. We found a support for our finding when we did a review of the literature. While some research has found that longer tenure is positively related to absenteeism, [7] others have found opposite result. [10] This stylized fact poses an interesting problem for contract theorists; is longer tenure correlated with greater job security? and does this lead to a higher propensity for absence? These contradictory effects could be the reason for the insignificant and inconclusive results found in our study.

Interestingly, absentees complained more about fatigue and poor inter-personal relationship with colleague than non-absentees. In a cohort study done by Janssen et al. on "fatigue at work," fatigue was associated with short-term but particularly with long-term sickness absence. [11] We found that many job-stressed employees were reluctant to go to workplace to avoid dealing with fear, anger, or other stresses associated with a co-worker. Stress occurred not only in horizontal relationships with colleagues but also in superior-subordinate relationships. Similar views were expressed in the literature. [12] Co-morbid anxiety/depression was found in two-third of the employees in the absenteeism group and one-third of non-absentees. This substantiates that job-stressed employees should always be assessed for major psychiatric illnesses so that proper remedial measures can be started early. The presence of anxiety/depression is a significant predictor of absenteeism (P = 0.02) in our study, which is in concurrence with other studies. [13] Finally, as expected, we found alcohol abuse or dependence as a strong predictor of absenteeism (P = 0.005). There are plenty of studies in the literature in support of our finding. In a study done in a tertiary care neuro-psychiatric hospital in the same city, 94.7% of the total 113 alcohol-dependents did not attend work 13.53 days a month, depicting a high rate of absenteeism in the alcoholics [Table 2]. [14]

The strength of our study is that it has taken only job-stressed employees diagnosed on a standard scale. To our knowledge, this is the first Indian study of its kind, which aimed at finding factors of absenteeism in diagnosed job-stressed employees. The study has certain limitations like small sample size, generalizing executive and non-executive stress, not relating severity of job stress with absenteeism, and accepting a qualitative self-measured definition of absenteeism. Subjects were chosen by purposive sampling, and response to questionnaires may be influenced by personal bias.

The findings of our study assume significance in view of the fact that we analyzed factors responsible for absenteeism in job-stressed employees only. In absenteeism research, one of the widely accepted models is Steer and Rhode's "Process model of absenteeism." [15] The model postulates job stress as one of the barriers for attendance. Thus, knowing the factors that make a stressed worker vulnerable for absenteeism would be helpful in prevention of absenteeism. However, the association of socio-demographic and clinical factors with absenteeism in our study is based on statistical significance and does not establish a causal model for absenteeism. Further in-depth research is necessary to establish a cause-effect relationship.

 
   References Top

1.Pfeifer C. Cyclical absenteeism among private sector, public sector and self-employed workers. Health Econ 2013;22:366-70.  Back to cited text no. 1
[PUBMED]    
2.Manjunatha R, Kiran D, Thankappan KR. Sickness absenteeism, morbidity and workplace injuries among iron and steel workers - A cross sectional study from Karnataka, Southern India. Australas Med J 2011;4:144-7.  Back to cited text no. 2
[PUBMED]    
3.David Fontana. Professional Life Stress Scale; Adapted from Managing Stress, The British Psychological Society and Routledge Ltd., 1989. Available from: http://www.ebookbrowse.com/professional-life-stress-scale-doc-d155261271. [Last accessed on 2011 Jul 31].  Back to cited text no. 3
    
4.World Health Organisation: International classification of diseases and related health problems: ICD-10. Geneva: WHO; 1994.  Back to cited text no. 4
    
5.Leonard C, Dolan SL, Arsenault A. Longitudinal examination of the stability and variability of two common measures of absence. Journal of Occupational Psychology 1990;63:309-16.  Back to cited text no. 5
    
6.Harrison D, Schaefer M. Comparative examinations of self reports and perceived absenteeism norms: Wading through Lake Wobegon. Journal of Applied Psychology 1994;79:240-51.  Back to cited text no. 6
    
7.Barmby TA, Ercolani MG, Treble JG. Sickness absence: An international comparison. The Economic Journal 2002;112:315-31.  Back to cited text no. 7
    
8.Chia KS. Sickness absence of migrants workers. Singapore Med J 1988;29:387-92.  Back to cited text no. 8
    
9.Costa G, Pickup L, Di Martino V. Commuting-a further stress factor for working people: Evidence from the European community. II. An empirical study. Int Arch Occup Environ Health 1988;60:377-85.  Back to cited text no. 9
    
10.Keller RT. Predicting absenteeism from prior absenteeism, attitudinal factors and non-attitudinal factors. Journal of Applied Psychology 1983;68:536-40.  Back to cited text no. 10
    
11.Janssen N, Kant IJ, Swaen GM, Janssen PP, Schröer CA. Fatigue as a predictor of sickness absence: Results from the Maastricht cohort study on fatigue at work. Occup Environ Med 2003; 60 Suppl 1:i71-6.  Back to cited text no. 11
    
12.Hanebuth D, Meinel M, Fischer JE. Health-related quality of life, psychosocial work conditions, and absenteeism in an industrial sample of blue- and white-collar employees: A comparison of potential predictors. J Occup Environ Med 2006;48:28-37.  Back to cited text no. 12
    
13.Hardy GE, Woods D, Wall TD. The impact of psychological distress on absence from work. J Appl Psychol 2003;88:306-14.  Back to cited text no. 13
    
14.Benegal V, Velayudhan A, Jain S. Social costs of alcoholism: A Karnataka perspective. NIMHANS Journal 2000;18 Suppl 1 and 2:67.  Back to cited text no. 14
    
15.Steers R, Susan R. Major influences on employee attendance: A process model. Journal of Applied Psychology 1978;63:391-407.  Back to cited text no. 15
    



 
 
    Tables

  [Table 1], [Table 2]

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