Original article

Identification of possible risk factors for alcohol use disorders among general practitioners in Rhineland-Palatinate, Germany

DOI: https://doi.org/10.4414/smw.2012.13664
Publication Date: 12.08.2012
Swiss Med Wkly. 2012;142:w13664

Michael Unrath, Hajo Zeeb, Stephan Letzel, Matthias Claus, Luis Carlos Escobar Pinzón

Please find the affiliations for this article in the PDF.


QUESTIONS UNDER STUDY: Research on alcohol use disorders among physicians has been scarce in Germany. The aim of our study was to identify possible risk factors for alcohol use disorders among general practitioners (GPs) working in the outpatient sector in the federal German state of Rhineland-Palatinate (RP).

METHODS: An anonymous survey was carried out between June and July 2009. 2,092 practice-based GPs in the federal German state of RP were asked to take part in the cross-sectional study via postal mail. The CAGE screening tool was used in its German version (CAGE-G) to screen for alcohol use disorders (AUD). Moreover, possible risk factors such as work stress (effort-reward imbalance), stress experienced in the leisure time and personality characteristics (Type D personality, resilience) were included in the questionnaire.

RESULTS: 808 GPs participated (response rate 38.6%), n = 790 were eligible for the analysis. The frequency of AUD according to the CAGE-G was 18.9% (n = 149). Moreover, nearly one in four general practitioners reported consuming alcohol on a daily basis (23.0%, n = 182). In the logistic regression analyses, stress experienced in the leisure time was positively related to the occurrence of AUD, whereas resilience was negatively associated.

CONCLUSIONS: AUD as screened for by the CAGE-G was frequent in our sample of German GPs. Approaches to reduce their occurrence could comprise actions helping physicians to relieve stress in their leisure time. Furthermore, measures to increase physicians’ resilience by improving coping strategies might prove useful.

Keywords: general practitioners, Germany, alcohol use disorders, psychosocial stress, resilience


AUD  Alcohol use disorders

aOR  Adjusted odds ratio

CAGE  Screening tool for alcohol use disorders such as dependence or abuse; CAGE Stands for “cut down”, “annoyed”, “guilty” und “eye opener”

CI  Confidence interval

DS14  Type D scale-14

ERI-Q  Effort-reward imbalance questionnaire

ERR   Effort-reward ratio

GP  General practitioner

RP  Rhineland-Palatinate

RS-13  Resilience scale (13 items version)

SBUS-B  Scales for the assessment of subjective occupational stress and dissatisfaction


There have been inconsistent findings with respect to the frequency of alcohol consumption and alcohol use disorders (AUD) among physicians. Some studies in the US and Europe have shown that physicians consume more alcohol and are at a greater risk of developing alcohol use disorders than the general population [1–3]. Other studies, however, suggest that there are no or only negligible differences between physicians and the general adult population or other professional groups [4–6]. Physicians’ reasons to engage in inadequate alcohol consumption are various. Some authors point to psychosocial work stress and job dissatisfaction as key factors that may lead to inadequate substance use among physicians [2, 7]. On the other hand, numerous studies of different occupational groups have failed to identify associations between factors such as work stress or job satisfaction and alcohol consumption [8–10]. A more consistently established risk factor for alcohol consumption among physicians is male gender [5, 11–14]. Further factors discussed in the literature are underlying psychiatric disorders such as depression or anxiety as well as characteristics inherent to the personality of the physicians [7, 15, 16]. Two personality traits that have frequently been investigated in terms of their effect on health are resilience and Type D personality. Whereas resilience is thought to be protective against health problems in the psychosomatic domain [17–19], Type D personality has been linked positively to a broad range of health impairments and unhealthy lifestyle habits [20–22]. Hence, these personality traits could also be relevant for AUD among physicians.

In Germany, research on substance use among physicians working in the outpatient sector has been scarce. Little is known about risk factors for AUD in this professional subgroup. To our knowledge, there is only one German study that aimed at estimating alcohol consumption among practice-based general practitioners (GPs) [23]. Hazardous or harmful drinking behaviour was reported by 27.5% of the male and 7.7% of the female GPs. As in most other studies, hazardous or harmful drinking was defined by the quantity and frequency of alcohol intake. This approach does not allow distinctions between problem drinking and more severe forms of AUD such as dependence. Furthermore, no analysis of risk factors except for age and gender was undertaken.

The aim of our study was to identify possible risk factors for AUD such as dependence or abuse within the target population of physicians working in the outpatient sector in Germany. We decided to investigate solely GPs as they hold a key position in the German health care system being the first contact for almost every patient.


In 2009, an anonymous survey was carried out among GPs working in the outpatient sector in the German federal state of Rhineland-Palatinate (RP). GPs with specialisation in general medicine and GPs without postgraduate specialty training were eligible. The cross-sectional study targeting n = 2,092 GPs was undertaken via postal mail. The distribution of the questionnaires was organised by the State Chamber of Physicians, which holds a database containing the addresses of all physicians working in the outpatient sector. The questionnaire covered a broad range of variables. Personality traits, perceived stress and health impairments were measured by means of standardised and psychometrically validated instruments. It took participants approximately 20–40 minutes to fill out the questionnaire (time estimation based on pilot interviews).

Alcohol use disorders

To estimate the prevalence of AUD in the sample, the CAGE questionnaire was used in its German version (CAGE-G) [24]. Consisting of four dichotomous items, this screening tool is characterized by a high degree of efficiency. The number of positively answered items (“yes”) is summed up in a score. We applied the recommended cut-off value ≥2 to screen for AUD. The CAGE has proven to be a valid screening instrument with good sensitivity and satisfying specificity in hospitalised (and therefore high-risk) populations, whereas its performance in non-hospitalised samples has been varied [25, 26].

Additionally the frequency of alcohol consumption was covered by the question ‘Do you drink alcohol?’ Participants could choose between four categories (“yes, every day”, “yes, occasionally”, “no, I stopped drinking alcohol”, “I never drank alcohol”). By choosing these rather rough categories we wanted to identify physicians who have made alcohol a part of their daily routine, because this subgroup could be at a greater risk to develop AUD.

Work stress

The short form of the Effort-Reward Imbalance Questionnaire (ERI-Q) [27] was administered. It consists of 16 items, with three of them pertaining to the subscale “effort”, seven items constituting the subscale “reward”, and six items being assigned to the subscale “overcommitment”. All three scales are assessed on a four point Likert scale ranging from “strongly agree” to “strongly disagree”. We calculated the so-called effort-reward ratio (ERR), which is an indicator of balance between the rewards received and the efforts invested at the workplace. The formula was adjusted to the short form by a correction factor. Furthermore, we calculated the sum score of the over commitment items. As suggested in the literature [28], both the ERR and the overcommitment sum score were divided into quartiles according to the empirical distribution in the sample.

Stress in the leisure time

Stress experienced in the leisure time was measured by the scale B4 (labelled “lack of relaxation and recreation”), which is part of the “Scales for the Assessment of Subjective Occupational Stress and Dissatisfaction” (SBUS-B) [29]. Scale B4 consists of nine dichotomous statements participants can either agree or disagree with. The scale is based on psychological stress theories such as the one framed by Lazarus [30], where the subjective experience of stress is the result of an evaluative process of the situation. Items pertaining to this scale refer, for example, to the experience of time constraints, the (in)ability to relax, the performance of pleasant activities, or the freedom to choose activities. We achieved a total stress score by summing up the single item scores and divided the total into quartiles according to the empirical distribution in the sample.

Job satisfaction

Job satisfaction was measured by the question “How satisfied are you altogether with your current job as a general practitioner?” Participants could answer on a six point Likert scale ranging from “not at all” to “absolutely”.

Personality factors

We included the Type D personality construct and resilience. Type D was measured by the German version of the scale DS14 [31], which is made up of the two dimensions “negative affectivity” and “social inhibition”. Negative affectivity relates to a dispositional readiness to easily experience negative emotional states, whereas social inhibition refers to the inclination to suppress the acting out of such negative emotions. Persons with Type D personality have both of these dispositions at the same time [31]. The applied version of the DS14 consists of 14 items to be answered on a five point Likert scale ranging from “completely disagree” to “completely agree”. We used the more conservative definition of Type D personality [31]. In this definition, it is required that a subject exceeds the upper limits of the 95% confidence intervals of both negative affectivity and social inhibition at the same time in order to be classified as having a Type D personality.

Resilience was measured by the German short form of the Resilience Scale RS-13 [32]. Resilience relates to the capacity to remain healthy in the face of strain and is therefore a sort of hardiness. The RS-13 is a one dimensional instrument and consists of 13 items assessed on a seven point Likert scale ranging from “completely disagree” to “completely agree”. We achieved a total resilience score by summing up the single item scores. This score was divided into quartiles so that non-linear trends could be identified and effect estimates were comparable to those of the stress measures.

Other covariates

Participants were asked for job-related variables such as average weekly working hours, duration of lunch breaks, and the presence of medical colleagues. Moreover, socio-demographic variables such gender, age (in five year categories), marital status, common household with a life partner, and number of children were covered.

Statistical analyses

Absolute and relative frequencies were calculated as well as the corresponding 95% confidence intervals, which were used to make comparisons between subgroups. Binary logistic regression analyses were applied to identify possible risk factors for AUD and predictors of daily alcohol consumption. Table 1 shows the explanatory variables considered in the binary logistic regression models. Both forward selection and backward elimination procedures were performed separately. A final set of predictors was then tested in an inclusion method. All analyses were carried out using SPSS version 18.0. The significance level for all statistical tests was defined by setting the error probability α = 0.05.

Missing values

Items 4 and 5 of the ERI-Q (subscale “reward”) had greater proportions of missing values (7.7%, n = 61 and 6.5%, n = 51) so that sum scores could not be calculated for a considerable proportion of the participants. To compensate the loss of power caused hereby we imputed missing values of items 4 and 5 for each subject by replacing them with the mean of the other five reward items [33]. Replacements were only carried out if all other five items of the “reward” scale were answered.

Table 1: Explanatory variables used in the binary logistic regression models.
Type of variableCovariate
Socio-demographic variablesAge
Life partner
Job-related variablesWeekly working hours
Duration of lunch break
Working with other GPs
Job satisfaction
Personality traitsResilience (RS-13)
Type D personality (DS14)
Psychosocial (work) stressSBUS-B B4
Overcommitment (ERI-Q)
Effort-reward ratio (ERI-Q)


Eight hundred and eight GPs participated (response rate 38.6%), 790 of these (37.8%) were eligible for the analysis. Eighteen questionnaires were discarded because the physicians did not work as GPs (n = 16) or because basic socio-demographic information was lacking (n = 2).

Socio-demographic and job-related measures

69.7% of the GPs (n = 551) were male, 30.3% (n = 239) female. Approximately two thirds of the participants (63.5%, n = 502) were between 46 and 60 years old. Relatively few participants were 45 years of age or younger (18.0%, n = 142). Only few GPs did not live together with a partner (9.5%, n = 75) or did not have children (11.6%, n = 92). The estimated weekly workload was 54.4 hours (SD = 12.7), about one quarter of which (13.4 hours) was dedicated to administrative work. Table 2 gives an overview of selected socio-demographic and job-related characteristics of the sample.

Table 2: Socio-demographic and work-related characteristics of the sample (n = 790, missings included).
 Male(n = 551)Female(n = 239)Total sample (n = 790)
Age categories31–45 years8114.76125.514218.0
46–60 years34863.215464.450263.5
>60 years12222,12410,014618,5
Marital statusMarried47385.818276.265582.9
Divorced / separated478.52912.1769.6
Living together with a partnerYes50190.919682.069788.2
Job satisfactionCompletely / very satisfied6311.43313.89612.1
Rather / to some extent satisfied33360.416870.350163.4
Little / no at all satisfied15327.83815.919124.2
Weekly workloadIn hours56.711.749.213.254.412.7
Administrative workIn hours13.58.513.09.513.48.8
Time for lunch breakIn minutes47.727.845.330.647.028.7
a Standard deviation.

Frequency of alcohol use disorders and daily alcohol consumption

Table 3 presents the prevalence of AUD and daily alcohol consumption in the sample. Furthermore, the 95% confidence intervals are given. The prevalence of AUD in the sample according to the CAGE-G was 18.9% (n = 149). Male GPs were affected somewhat more often (20.5%, n = 113) than female GPs (15.1%, n = 36).

Nearly one in four GPs reported consumption of alcohol on a daily basis (23.0%, n = 182). Two in five of these daily consumers (40.7%, n = 74) also exceeded the CAGE-G cut-off.

Daily consumption of alcohol was significantly more frequent in male (26.1%, n = 144) than in female participants (15.9%, n = 38). Occasional alcohol consumption was reported by about two thirds of the physicians (68.1%, n = 538). Only few GPs declared to never have consumed alcohol (4.9%, n = 39) or to have quit its consumption (3.7%, n = 29).

Table 3: Relative frequency of alcohol use disorders and daily alcohol consumption (in %, missings included).
  Alcohol use disorders
 (CAGE-G ≥2)
Daily alcohol consumption
  %95% CI an (age group)%95% CI an (age group)
Male31–45 years11.14.3–18.08112.35.2–19.581
46–60 years23.018.6–27.434824.720.2–29.2348
>60 years19.712.6–26.712239.330.7–48.0122
All ages20.517.1–23.955126.122.5–29.8551
Female31–45 years16.47.1–25.76111.53.5–19.561
46–60 years15.69.9–21.315415.69.9–21.3154
>60 years8.30.0–19.42429.211.0–47.424
All ages15.110.5–19.623915.911.3–20.5239
Total sample31–45 years13.47.8–19.014212.06.6–17.3142
46–60 years20.717.2–24.350221.918.3–25.5502
>60 years17.811.6–24.014637.729.8–45.5146
All ages18.916.1–21.679023.020.1–26.0790
a 95% confidence interval.

Regression analyses

The results of the automatic forward selection and the backward elimination differed only with respect to one predictor in the analysis of AUD. Overcommitment was included in the backward elimination, but not in the forward selection approach. Table 4 contains the adjusted odds ratios (aOR) resulting from the final regression model (inclusion method) alongside with the corresponding 95% confidence intervals (CI). Due to the explorative character of this study, we decided to include the more comprehensive set of predictors. Stress experienced in the leisure time (SBUS-B B4) was positively associated with AUD. The group with the highest stress level had a 2.5-fold higher chance to suffer from AUD than the group with the lowest stress level (95% CI = 1.28–4.67). With respect to the other stress measure overcommitment, none of the chosen contrasts yielded statistical significance (Wald tests). Yet there was a tendency that individuals with higher levels of overcommitment (3rd and 4th quartile) had a higher chance to be affected by AUD. Contrary to the stress measures, weekly working hours (aOR = 0.98; 95% CI = 0.96–1.00) and resilience (aOR for 4th quartile = 0.48; 95% CI = 0.27–0.86) were negatively associated with the outcome. Hence, those GPs with comparatively high levels of resilience had a lower chance of suffering from AUD.

Regarding the prediction of daily alcohol consumption, forward selection and backward elimination processes resulted in the same regression model. Table 4 displays the final set of predictors (inclusion method) and the corresponding aOR.

Female GPs had a 36% lower chance of consuming alcohol on a daily basis than their male colleagues (95% CI = 0.42–0.96). Older age was positively associated with daily alcohol consumption. The oldest age group (>60 years) had a more than fourfold chance of daily alcohol consumption when compared with the youngest age group (31–45 years; 95% CI = 2.33–8.12). Resilience was again negatively related to the outcome. Those GPs with the highest resilience level had a 46% lower probability of consuming alcohol daily when compared to their colleagues with the lowest resilience level (95% CI = 0.33–0.89). Contrary to resilience, Type D personality was not significantly associated with AUD or daily drinking behaviour in the multivariate analyses.

Table 4: Final set of predictors and adjusted odds ratios of the binary logistic regression models to predict alcohol use disorders and daily alcohol consumption (inclusion method).
PredictorQuartileAlcohol use disorders
(n = 746)
Daily alcohol consumption
(n = 781)
aORa95% CIbaORa95% CIb
Weekly workload (hours) 0.980.96–1.00e 
Over commitment1stref. c e 
2nd0.55n. s. d  
3rd1.14n. s. d  
4th1.35n. s. d  
SBUS-B B41stref. c e 
2nd1.27n. s. d  
3rd 2.031.16–3.55  
Resilience1st ref.c ref.c 
2nd 0.72n. s. d0.84n. s.d
3rd 0.570.38–0.960.450.27–0.74
4th 0.480.27–0.860.540.33–0.89
Age (in years)31–45e ref.c 
46–50  1.921.01–3.65
51–55  1.911.01–3.63
56–60  2.041.09–3.80
>60  4.352.33–8.12
GenderMalee ref.c 
Female  0.640.42–0.96
a Adjusted odds ratio; b 95% confidence interval; c reference category;  d contrast not significant (p <0.05); e variable not in the model (eliminated by stepwise procedure).


Principal findings and their implications

In our sample of GPs in the federal state of RP, Germany, the frequency of AUD according to the CAGE-G screening was 18.9%. The proportion was somewhat higher in male than in female GPs, and it was also slightly higher in the older age classes. Surveys among the German general population, which also used the CAGE-G, have found considerably lower proportions between 8% and 10% [34, 35]. The gender and age stratified descriptive comparisons in table 5 illustrate this discrepancy, which is even more marked for female GPs. Since other studies among physicians mostly used quantity/frequency approaches to define AUD, direct comparisons cannot be made. Nevertheless, the results reported here are well in line with a number of international studies reporting high proportions of risky alcohol consumption (between 14.5% and 30%) among (primary care) physicians [3, 13, 23, 36].

23% of the GPs reported drinking alcohol every day. Male GPs engaged in daily alcohol consumption more often than their female colleagues. In a study among the general population, only 6.4% of the non-abstaining women and 16.2% of the non-abstaining men in West Germany reported daily alcohol consumption as compared to 17.7% and 28.5% in our sample [37].

Since only the frequency of alcohol intake was covered in the questionnaire, conclusions as to the concept of hazardous or harmful drinking cannot be drawn. However, daily drinking has been linked to unhealthy lifestyle habits [38] and health impairments [39, 40] and could therefore be regarded as a risk factor in itself. The negative association we found between resilience and daily alcohol consumption may suggest that at least for a part of the physicians, daily alcohol consumption could act as a form of coping mechanism.

Altogether, especially female GPs in our sample seem to be affected more often by AUD and daily alcohol consumption than their counterparts in the general population in Germany. A possible explanation could be that female physicians might be exposed to a greater amount or a different kind of stress than women in the general population, whilst this difference could be less marked in men. One reason for this could be that – in comparison to the general female population in Germany – female physicians more often face the double burden of a challenging job and raising children. The lack of recreation caused hereby could make female GPs more susceptible to maladaptive coping strategies such as inadequate alcohol use.

In the regression analyses, stress experienced in the leisure time and work-related stress as captured by the overcommitment construct were positively related to the occurrence of AUD. Stress experienced in the leisure time seemed to be of even greater importance for the occurrence of AUD in our sample than work-related stress. Thus, it seems crucial for GPs to have leisure time which provides the possibility to relax and recreate. The results of another study of German physicians stress the importance of the life outside the job in a similar way [41]. Here, general satisfaction with life was markedly lower among physicians with a substance-related dependence than among physicians without dependence, whereas the two groups did not differ so much with respect to job satisfaction.

Resilience was negatively related to both the occurrence of AUD and daily alcohol consumption. This result is in line with a number of studies that consistently linked resilience to a relatively lower degree of psychosomatic health impairments [17–19]. The associations between resilience and the two alcohol-related outcomes were non-linear (table 4). From the third quartile onwards, the effect estimates remained fairly stable. This may suggest that a certain level of resilience has a protective effect, which does not alter so much if the degree of resilience increases further. It might therefore be worth considering measures that help to preserve or reach a certain level of resilience when planning interventions to prevent alcohol misuse among GPs.

Male gender and older age were identified as predictors of daily alcohol consumption, which is consistent with previous findings [5, 11–14]. We furthermore detected a negative association of the weekly workload and AUD. This seemed to be surprising at first glance. However, it is possible that the presence of AUD may lead to a lower overall functional status and thus to a reduction in the average weekly working hours. Due to the cross-sectional design, the direction of associations cannot be determined definitely.

Table 5: Descriptive comparison of the relative frequency of lifetime alcohol use disorders (CAGE-G ≥2) in the sample of GPs and the general German population [35], stratified by age group (missings excluded).
 General practitioners
(n = 780)
General German population
 (n = 7455) [35]
Age category%Age categoryn%
Male31–40 years6.930–39 years12.8
41–50 years24.140–49 years13.8
51–60 years20.250–59 years11.0
>60 years19.7>59 yearsa
Female31–40 years13.330–39 years3.4
41–50 years17.440–49 years4.0
51–60 years14.850–59 years2.8
>60 years8.3>59 yearsa
Total sample31–40 years9.130–39 years8.1
41–50 years21.640–49 years9.1
51–60 years18.650–59 years6.9
>60 years17.850–59 yearsa
a Participants of this survey were between 18 and 59 years.

Preventive measures to reduce alcohol use disorders among general practitioners

Our findings suggest that measures aiming at the prevention of AUD in GPs should consider physicians’ resilience and the relief of stress in the leisure time. Resilience and the relief of stress through recreation both refer to the way GPs cope with stressful life conditions. It seems essential that this coping process is successful. How can this be achieved? Surveys among GPs and other physicians suggest that resilience in terms of successful coping with stressful life events may be supported by the following strategies: positive attitudes towards the own role and personal limitations [42, 43] instead of self criticism [44], supportive personal relationships with family and friends [42, 43, 45, 46], enough leisure time spent outside medicine including hobbies and holidays [43, 46–48], emotional awareness [43, 46], help seeking behaviour [44] and a problem focused coping style [43, 49]. Some of these strategies may require the ability to set limits and grant priority to own needs [46]. There are also hints that strategies enhancing physicians’ resilience can be learned in specialised trainings focusing on stress management [49, 50]. Such training could already be implemented in medical school [44, 51] and could comprise relaxation techniques [50] and the beneficial use of leisure time. The available literature also points to the importance of regular exchanges with professional colleagues such as in Balint groups. Such groups might strengthen the resistance to work-related stress [52]. Our own data underline the importance of professional exchange among colleagues and relaxation techniques, which the majority of the users in our sample found helpful in reducing stress [53].

Strengths and limitations

To our knowledge, this is the very first time that the identification of risk factors for AUD was addressed in a state-wide German sample of GPs. Validated and standardized instruments were applied to measure subjective stress, personality factors and health measures. Another strong point is the considerable extent of this survey covering a broad range of variables. A limitation is that we only used a screening instrument to detect AUD, which means that a considerable proportion of false positive results is possible. Literature reviews reveal that the CAGE is a valid instrument to detect dependence [25, 26], but that there may be problems regarding less severe forms of AUD such as alcohol abuse or binge drinking. The CAGE screening instrument seems to capture the characteristics of dependence better than those of hazardous or harmful drinking behaviour. This may be attributable to the fact that it does not comprise questions related to the frequency or quantity of alcohol intake, which do play a role in the definition of hazardous / harmful drinking but not in the definition of dependence.

A further criticism refers to the fact that the CAGE performs best in hospitalised patients, whereas its performance in non-hospitalised and female populations has been varied [25, 54]. Current studies, however, add support to its validity in general populations [55, 56]. Thus, the application of the CAGE-G may have some drawbacks, but this holds true for any screening tool. Another possible source of bias is the delicate nature of the subject under study. AUD are a stigmatized topic, and one could assume that there was an underreporting of these problems. Especially among physicians, underreporting of alcohol use has been a frequently discussed topic [3; 57, 58].

Another limitation of this survey is the relatively low response rate of 38.6%. As a substantial proportion of the GPs did not respond, the possibility of selection bias in the sample has to be taken into account. Our sample does not show any bias with respect to the distribution of gender, but we cannot make any statements with respect to other relevant variables such as age because the database used to distribute the questionnaires does not provide the necessary information about the target group. Selection bias can lead to either an over or- an underestimation of point estimates and associations. It seems plausible that those GPs with the highest stress levels would rather not take part in a survey which consumes a considerable amount of time. Therefore, the subjects most inclined to inadequate alcohol consumption possibly did not participate. This might have resulted in an underestimation of AUD and the association between stress and these disorders. Compared to other surveys among physicians in Germany with response rates between 15 and 41% [23, 59–60] we still achieved a satisfactory response. This might be due to announcements made in the journal of the State Chamber of Physicians. On the other hand, mistrust in the institutions involved and the considerable extent of the survey may have prevented some physicians from participating.

Regarding the treatment of missing values, we calculated sensitivity analyses comparing results with and without imputation technique. In the regression models, slight differences occurred with respect to single predictors. All in all, there was a tendency that fewer predictors were included when analysing complete cases only. This finding is probably attributable to the loss of power brought about by excluding cases with a missing value.

There were hardly any differences between the results of the forward selection and the backward elimination procedures. Independently of the chosen selection procedure, fairly stable results were achieved. Due to the explorative nature of our study and the great number of potential influencing variables we decided to use this pragmatic approach.

The cross-sectional design of this study prevents us from drawing firm causal conclusions. However, some of the associations reported here apparently favour one direction of influence. For instance, personality traits can be regarded as fairly stable characteristics. Therefore, they should be more likely to have an influence on behaviour based variables such as alcohol consumption, than the other way around. The same holds true for variables such as gender or age. With respect to the experience of stress, of course, both directions of influence are possible.


GPs in our sample frequently screened positively for AUD. The results reported here indicate that a low resilience and a lack of stress relief in the leisure time may play an important role with respect to the occurrence of AUD. These findings suggest that actions to reduce stress and increase physicians’ resilience by improving coping strategies may prove useful to prevent AUD. Following the dissemination and discussion of our results, the development and implementation of such programmes, including appropriate evaluation activities, should be considered in Germany. Further research is warranted to determine if similar risk factors for AUD are relevant in other German and international samples of primary care physicians.

Ethical approvals:The ethics committee of the medical association of the German state of Rhineland-Palatinate and the data protection officer of Rhineland-Palatinate approved of this study.

Acknowledgements:We thank the federal physicians’ association of Rhineland-Palatinate for its kind support during the process of data collection. The authors would also like to thank the reviewers of Swiss Medical Weekly for their constructive and thoughtful comments.

Funding / potential competing interests: Funding for this study was provided through internal resources of the Institute of Occupational, Social and Environmental Medicine at the University Medical Centre of the Johannes Gutenberg University of Mainz, Germany. No other potential conflict of interest relevant to this article was reported.


Correspondence: Michael Unrath, MSc, Institute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, Gebäude D3, DE-48149 Münster, Germany, unrathm[at]uni-muenster.de


  1 Hughes PH, Brandenburg N, Baldwin DC, Jr., Storr CL, Williams KM, Anthony JC, et al. Prevalence of substance use among US physicians. JAMA. 1992;267:2333–9.

  2 Juntunen J, Asp S, Olkinuora M, Aarimaa M, Strid L, Kauttu K. Doctors’ drinking habits and consumption of alcohol. BMJ. 1988;297:951–4.

  3 Sebo P, Bouvier Gallacchi M, Goehring C, Kunzi B, Bovier PA. Use of tobacco and alcohol by Swiss primary care physicians: a cross-sectional survey. BMC Public Health. 2007;7:5. doi:1471-2458-7-5 [pii] 10.1186/1471-2458-7-5

  4 Kenna GA, Wood MD. Alcohol use by healthcare professionals. Drug Alcohol Depend. 2004;75:107–16. doi:10.1016/j.drugalcdep.2004.01.008S0376871604000328 [pii]

  5 McAuliffe WE, Rohman M, Breer P, Wyshak G, Santangelo S, Magnuson E. Alcohol use and abuse in random samples of physicians and medical students. Am J Public Health. 1991;81:177–82.

  6 Seppala MD, Berge KH. The addicted physician. A rational response to an irrational disease. Minn Med. 2010;93:46–9.

  7 Marshall EJ. Doctors’ health and fitness to practise: treating addicted doctors. Occup Med (Lond). 2008;58:334–40. doi:kqn081 [pii] 10.1093/occmed/kqn081

  8 Hodgins DC, Williams R, Munro G. Workplace responsibility, stress, alcohol availability and norms as predictors of alcohol consumption-related problems among employed workers. Subst Use Misuse. 2009;44:2062–9. doi:10.3109/10826080902855173

  9 Kouvonen A, Kivimaki M, Cox SJ, Poikolainen K, Cox T, Vahtera J. Job strain, effort-reward imbalance, and heavy drinking: a study in 40,851 employees. J Occup Environ Med. 2005;47:503–13. doi:00043764-200505000-00009 [pii]

10 Siegrist J, Rodel A. Work stress and health risk behaviour. Scand J Work Environ Health. 2006;32:473–81. doi:1052 [pii]

11 Rodríguez Fernández E, Espí Martínez F, Canteras Jordana M, Gómez Moraga A. Consumo de alcohol entre profesionales médicos de atención primaria. Aten Primaria. 2001;28:259–62.

12 Hull SK, DiLalla LF, Dorsey JK. Prevalence of health-related behaviours among physicians and medical trainees. Acad Psychiatry. 2008;32:31–8. doi:32/1/31 [pii] 10.1176/appi.ap.32.1.31

13 McNerney JP, Andes S, Blackwell DL. Self-reported health behaviours of osteopathic physicians. J Am Osteopath Assoc. 2007;107:537–46. doi:107/12/537 [pii]

14 Rosta J .Hazardous Alcohol use among hospital doctors in Germany. Alcohol & Alcoholism. 2008;43:198–203. doi: 10.1963/alcalc/agm180

15 Mühlau-Mahlke C. Suchterkrankungen bei Ärztinnen und Ärzten. Überblick über den derzeitigen Kenntnisstand mit erweiternden Aspekten aus der Integrativen Therapie. In: Petzold H, Schay P, Ebert W, editors. Integrative Suchttherapie. Theorie, Methoden, Praxis, Forschung. Wiesbaden: VS Verlag für Sozialwissenschaften; 2009.

16 Soukup J, Schmale M. Das Suchtrisiko bei Medizinern. Sind wir Anästhesisten besonders gefährdet? Anästh Intensivmed. 2009;50:286–95.

17 Friborg O, Hjemdal O, Rosenvinge JH, Martinussen M, Aslaksen PM, Flaten MA. Resilience as a moderator of pain and stress. J Psychosom Res. 2006;61:213–9. doi:S0022-3999(06)00006-7 [pii] 10.1016/j.jpsychores.2005.12.007

18 Leppert K, Gunzelmann T, Schumacher J, Strauss B, Brahler E. Resilience as a protective personality characteristic in the elderly. Psychother Psychosom Med Psychol. 2005;55:365–369. doi:10.1055/s-2005-866873

19 Tugade MM, Fredrickson BL, Barrett LF. Psychological resilience and positive emotional granularity: examining the benefits of positive emotions on coping and health. J Pers. 2004;72:1161–90. doi:JOPY294 [pii] 10.1111/j.1467-6494.2004.00294.x

20 Schiffer AA, Smith OR, Pedersen SS, Widdershoven JW, Denollet J. Type D personality and cardiac mortality in patients with chronic heart failure. Int J Cardiol. 2009;142:230–5.

21 Michal M, Wiltink J, Grande G, Beutel ME, Brähler E. Type D personality is independently associated with major psychosocial stressors and increased health care utilization in the general population. Journal of Affective Disorders 2011;134:396–403.

22 Mommersteeg PMC, Kupper N, Denollet J. Type D personality is associated with increased metabolic syndrome prevalence and an unhealthy lifestyle in a cross-sectional Dutch community sample. BMC Public Health 2010;10:714.

23 Voigt K, Twork S, Mittag D, Gobel A, Voigt R, Klewer J, Kugler J, Bornstein SR, Bergmann A. Consumption of alcohol, cigarettes and illegal substances among physicians and medical students in Brandenburg and Saxony (Germany). BMC Health Serv Res. 2009;9:219. doi:1472-6963-9-219 [pii] 10.1186/1472-6963-9-219

24 Rumpf H-J, Hapke U, John U. Deutsche Version des CAGE Fragebogens (CAGE-G). In: Glöckner-Rist A, Rist F, Küfner H, editors. Elektronisches Handbuch zu Erhebungsinstrumenten im Suchtbereich (EHES) Version 300. Mannheim: Zentrum für Umfragen, Methoden und Analysen; 2003.

25 Dhalla S, Kopec JA. The CAGE questionnaire for alcohol misuse: a review of reliability and validity studies. Clin Invest Med. 2007;30:33–41.

26 Fiellin DA, Reid MC, O’Connor PG. Screening for alcohol problems in primary care: a systematic review. Arch Intern Med. 2000;160:1977–89. doi:ioi90552 [pii]

27 Siegrist J, Wege N, Puhlhofer F, Wahrendorf M. A short generic measure of work stress in the era of globalization: effort-reward imbalance. Int Arch Occup Environ Health. 2009;82:1005–13. doi:10.1007/s00420-008-0384-3.

28 Siegrist J, Starke D, Chandola T, Godin I, Marmot M, Niedhammer I, Peter R. The measurement of effort-reward imbalance at work: European comparisons. Soc Sci Med. 2004;58:1483–99. doi:10.1016/S0277-9536(03)00351-4S0277953603003514 [pii].

29 Weyer G, Hodapp V, Neuhäuser S.Weiterentwicklung von Fragebogenskalen zur Erfassung der subjektiven Belastung und Unzufriedenheit im beruflichen Bereich (SBUS-B). Psychologische Beiträge. 1980;22:335–55.

30 Lazarus, RS. Psychological stress and the coping process. New York: McGraw-Hill; 1966.

31 Grande G, Jordan J, Kummel M, Struwe C, Schubmann R, Schulze F, et al. Evaluation of the German type D scale (DS14) and prevalence of the type D personality pattern in cardiological and psychosomatic patients and healthy subjects. Psychother Psychosom Med Psychol. 2004;54:413–22.

32 Leppert K, Koch B, Brähler E, Strauss B. Die Resilienzskala (RS) – Überprüfung der Langform RS-25 und einer Kurzform RS-13. Klinische Diagnostik und Evaluation. 2008;1:226–43.

33 Bono C, Ried D, Kimberlin C, Vogel B. Missing data on the Centre for Epidemiologic Studies Depression Scale: a comparison of 4 imputation techniques. Social and Administrative Pharmacy. 2007;3:1–27. doi:10.1016/j.sapharm.2006.04.001

34 Buhler A, Kraus L, Augustin R, Kramer S. Screening for alcohol-related problems in the general population using CAGE and DSM-IV: characteristics of congruently and incongruently identified participants. Addict Behav. 2004;29:867–78. doi:10.1016/j.addbeh.2004.02.057S0306460304000693 [pii]

35 Kraus L, Bloomfield K, Augustin R, Reese A. Prevalence of alcohol use and the association between onset of use and alcohol-related patterns in a general population sample in Germany. Addiction. 2000;95:1389–401.

36 Aalto M, Hyvönen S, Seppä K. Do primary care physicians’ own AUDIT scores predict their use of brief alcohol intervention? A cross-sectional survey. Drug and Alcohol Dependence. 2006;83:169–173.

37 Bloomfield K, Grittner U, Kramer S. Developments in alcohol consumption in reunited Germany. Addiction. 2005;100:1770–8. Doi: 10.1111/j.1360-0443.2005.01250.x

38 Kaneita Y, Uchida T, Ohida T. Epidemiological study of smoking among Japanese physicians. Prev Med. 2010;51:164–7. Epub 2010 May 8.

39 Marcus GM, Smith LM, Whiteman D, Tseng ZH, Badhwar N, Lee BK, et al. Alcohol intake is significantly associated with atrial flutter in patients under 60 years of age and a shorter right atrial effective refractory period. Pacing Clin Electrophysiol. 2008;31:266–72.

40 Kaneko K, Murakami Y, Katagiri A, Konishi K, Kubota Y, Muramoto T, et al. Does daily alcohol and/or cigarette consumption cause low-grade dysplasia, a precursor of oesophageal squamous cell carcinoma? J Clin Gastroenterol. 2010;44:173–9.

41 Jurkat HB, Reimer C. Arbeitsbelastung und Lebenszufriedenheit bei berufstätigen Medizinern in Abhängigkeit von der Fachrichtung. Schweizerische Ärztezeitung. 2001;82:1745–50.

42 Jensen PM, Trollope-Kumar K, Waters H, Everson J. Building physician resilience. Can Fam Physician. 2008;54:722–9.

43 Post, D. Value, stress, and coping among practicing family physicians. Arch Fam Med. 1997;6:252–5.

44 Firth-Cozens J. Interventions to improve physicians’ well-being and patient care. Soc Sci Med. 2001;52:215–22.

45 Lee FJ, Stewart M, Brown JB. Stress, burnout, and strategies for reducing them. What’s the situation among Canadian family physicians? Can Fam Physician. 2008;54:234-5.e5

46 Zwack J, Abel C, Schweitzer J. Resilienz im Arztberuf – salutogenetische Praktiken und Einstellungsmuster erfahrener Ärzte. Psychother Psych Med. 2011;61:495–502.

47 Lloyd S, Streiner D, Shannon S. Burnout, depression, life and job satisfaction among Canadian emergency physicians. J Emerg Med. 1994;12:559–65.

48 Rodrigues Torres A, Ruiz T, Swain Müller S, Pereira Lima MC. Quality of life, physical and mental health of physicians: a self-evaluation by graduates from the Botucatu Medical School – UNESP. Rev Bras Epidemiol. 2011;14:264–75.

49 Gardiner M, Lovell G, Williamson P. Physician you can heal yourself! Cognitive behavioural training reduces stress in GPs. Fam Pract. 2004;21:545–51.

50 Sood A, Prasad K, Schroeder D, Varkey P. Stress management and resilience among department of medicine faculty: a pilot randomized clinical trial. J Gen Intern Med. 2011;26:858–61.

51 Thomas SE, Haney MK, Pelic CM, Shaw D, Wong JG. Developing a program to promote stress resilience and self-care in first-year medical students. Can Med Educ J; 2011;2:e32-6.

52 Kjeldman D, Holmström I. Balint groups as a means to increase job satisfaction and prevent burnout among general practitioners. Ann Fam Med. 2008;6:138–45.

53 Unrath M, Zeeb H, Letzel S, Claus M, Escobar Pinzón LC. Arbeitssituation und Gesundheit von Hausärzten in Rheinland-Pfalz: Erste Ergebnisse einer landesweiten Befragung. Gesundheitswesen. 2012;74:389–96. Epub 2011 Jul 13.

54 Aertgeerts B, Buntinx F, Ansoms S, Fevery J. Screening properties of questionnaires and laboratory tests for the detection of alcohol abuse or dependence in a general practice population. Br J Gen Pract. 2001;51:206–17.

55 Skogen JC, Overland S, Knudsen AK, Mykletun A. Concurrent validity of the CAGE questionnaire. The Nord-Trøndelag Health Study. Addict Behav. 2011;36:302–7. Epub 2010 Nov 27.

56 Batty GD, Hunt K, Emslie C, Lewars H, Gale CR. Alcohol problems and all-cause mortality in men and women: predictive capacity of a clinical screening tool in a 21-year follow-up of a large, UK-wide, general population-based survey. J Psychosom Res. 2009;66:317–21. Epub 2009 Jan 8.

57 Berger K, Ajani U, Kase CS, Gaziano M, Buring J, Glynn R, et al. Light-to-moderate alcohol consumption and the risk of stroke among U.S. male physicians. N Engl J Med. 1999;341:1557–64.

58 Djoussé L, Gaziano M. Alcohol consumption and heart failure in hypertensive US male physicians. Am J Cardiol. 2008;102(5):593–7. Epub 2008 Jun 12.

59 Merz B, Oberlander W. Berufszufriedenheit: Ärztinnen und Ärzte beklagen die Einschränkung ihrer Autonomie. Dtsch Arztebl. 2008;105:A-322 / B-290 / C-28.

60 Gebuhr K. Die vertragsärztliche Tätigkeit im Lichte des Burnout-Syndroms. Ergebnisse schriftlicher Befragungen von 1996, 2002, 2004 und 2007. Berlin: Brendan-Schmittmann-Stiftung; 2008.

Verpassen Sie keinen Artikel!