Mersey Primary Care R&D Consortium
Department of Primary Care, University of Liverpool
Laurel Bank Surgery, Malpas, Cheshire, UK
Correspondence: Mr C. Shiels, Department of Primary Care, Whelan Building, University of Liverpool,liverpool L69 3GB, UK. E-mail: cs50{at}liv.ac.uk
Declaration of interest C.H. is a principal in the general practice in which the study took place.
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ABSTRACT |
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Aims To identify symptomatic and socio-demographic correlates of depression in men attending a rural practice, and to compare and contrast general practitioners and patients assessments of depression.
Method All male patients of working age attending a rural general practice over a 12-month period were invited to participate.
Results Men reporting recent chest pain or feeling tired/little energy, expressing low job enjoyment or with a previous diagnosis of depression were more likely to be scored above threshold on the Hospital Anxiety and Depression Scale - Depression sub-scale. There was little agreement between the doctors and their male patients about the degree of perceived depression.
Conclusions Educational interventions aimed at addressing the diagnosis of depression in men should take greater account of factors within a particular social setting.
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INTRODUCTION |
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METHOD |
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Study design
Following approval of the study by Chester District Ethics Committee, all
male patients of working age attending a general practice appointment over a
12-month period (19971998) were approached to take part in the study.
Those agreeing to participate were given an information sheet and a consent
form, and issued with a baseline health and well-being questionnaire to
complete before seeing the doctor. Each general practitioner seeing a study
participant completed a separate assessment form following the index
consultation. In addition, relevant data items were collected from the
practice record.
Three forms were used to collect baseline data:
The Hospital Anxiety and Depression Scale was initially developed as a tool for identifying cases of anxiety and depression among patients in non-psychiatric clinics (Zigmond & Snaith, 1983). Each sub-scale one measuring anxiety (HADSA) and the other depression (HADSD) contains seven items and has a maximum computed score of 24. A review of studies testing the validity of the HADS (Bjellan et al, 2002) confirmed that the optimisation of sensitivity and specificity of both HADSA and HADSD for screening cases was achieved at a case cut-off score of 8 or more (as used in this study). The review concluded that the instrument performed well in screening for the separate dimensions of anxiety and depression in somatic, psychiatric and primary care patients, and in the general population (Bjellan et al, 2002).
We investigated associations between HADSD caseness and both patient-reported variables (physical symptoms and socio-demographic factors) and secondary clinical data collected from patient records. We also compared the extent of agreement between doctor and patient Likert scale depression ratings, and between doctors assessments and a caseness rating on the HADSD. The validity of the doctor and patient assessments of depression in predicting HADSD caseness was also tested.
Statistical analysis
For investigating differences between the groups of patients categorised as
cases and non-cases on the basis of the
HADSD cut-off score, we applied univariate statistical tests. For
continuous variables such as age, the independent samples t-test was
used to test for significant differences between the two patient groups. For
the dichotomous categorical variables (e.g. symptom reported or not), we used
the chi-squared test to detect any significant associations between the
variable and HADSD caseness. We constructed a logistic regression model
in order to test for independent effects of patient factors upon risk of
HADSD caseness. Only significant factors from the univariate analysis
stage were included as potential explanatory covariates in the regression
model.
In order to allow meaningful comparison of doctors and patients assessments, ratings on the Likert depression scales were collapsed into dichotomous measures. A score above 2 (the mid-point on the scale) was assumed to indicate a degree of perceived depression. The technical justification for doing so was to construct 2 x 2 tables enabling calculation of simple unweighted kappa coefficients to express agreement between patient and doctor on the rating of depression. Also, the construction of such tables was a prerequisite for testing the validity of the dichotomous assessment measures in predicting HADSD cases. For each measure, we report statistics relating to sensitivity, specificity, and positive and negative predictive tests.
Only patients consulting one of the three principal practice doctors or the assistant general practitioner were included in the analyses of agreement and validity. Patients seen by a locum doctor (n=179) were excluded from this part of the study. No statistically significant difference was found between locum patients and the other patients in relation to age or HADSD score.
Data were analysed using the Statistical Package for the Social Sciences, SPSS for Windows version 10.
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RESULTS |
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Patient factors and HADS depression cases
In this study, depression cases were defined by a score of 8 or more on the
HADSD self-assessment scale. The prevalence rate for depression
identified by this criterion among participants was 14% (126/901).
Table 1 summarises the relationship between a range of patient factors and depression. Significantly fewer men with depression were in paid work compared with the rest of the sample; if in work, they were less likely to enjoy their job. They were also significantly more likely to live in rented accommodation, to be receiving state benefits, to have a history of depression or to have been certified sick for more than 3 months in the year before the index consultation.
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Physical symptom reporting and HADS-D caseness
Differences in specified physical symptoms reported in the 4 weeks before
the index consultation in patients rated as depression cases and non-cases are
presented in Table 2. Men
categorised as depressed were significantly more likely to report physical
symptoms in all our defined categories except back pain. Associations between
reported symptoms and depression were not significantly affected by patient
age.
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Independent effects of patient factors and symptoms
We conducted a logistic regression to explore independent associations
between patient socio-demographic and clinical factors, reported physical
symptoms and risk of depression (Table
3). All variables significantly associated with depression at the
univariate level of analysis were initially included as covariates in the
regression model. However, the in paid work variable was
constant across all selected cases, and was thus excluded.
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After regression, only four covariates (two reported symptoms and two patient factors) retained a statistically significant association with depression. Men reporting chest pain in the previous 4 weeks were over twice as likely to be depressed as those not reporting this symptom. Men reporting being very tired or having no energy in the past month, men not enjoying their work and men with previous depression were also significantly more likely to be depressed.
Comparison of assessments of depression
Levels of agreement between doctor and patient assessments on the Likert
depression scale as well as with the HADSD-derived definition of
caseness are shown in Tables 4
and 5. Only the 722 (80.1%)
patients consulting one of the four general practitioners are included in the
analysis. Although 26.4% of patients rated their level of depression above the
mid-point on the Likert scale, only 5.3% of the doctors assessments did
so. This compares with a HADSD defined prevalence of 14.2%. Agreement
between the patients and doctors Likert depression ratings was
poor, with a mean coefficient of 0.15. However, the doctors
Likert depression assessments were more congruent with HADSD caseness
(mean
=0.30). Only one doctor failed to reach a fair to moderate level
of agreement with the HADS (
=0.08).
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Table 6 presents data on the validity of the doctors and patients assessments of depression, using HADSD caseness as the predicted gold standard. The doctors assessments (sensitivity 24.6%) were less accurate than patient ratings (sensitivity 75.5%) in identifying HADSD cases.
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DISCUSSION |
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Methodological limitations
Our sample was recruited over a complete year, and included over 90% of all
potential participants. The practice area meets recognised criteria for
rurality, although it cannot be assumed to be typical of all UK rural
populations. The Likert depression rating was developed for this study and had
not been previously validated. However, it is unlikely that the wide
differences between doctor and patient ratings could be explained by the
psychometric properties of the scale. We did not collect data on the
characteristics of the general practitioners (e.g. demographics and attitudes)
that might influence their rating of patient depression but there is no reason
to assume that they differ from those of other clinicians working in
comparable demographic settings. Although the men who declined to participate
in the study differed from the sample in some respects, the only variable that
might have biased our findings is the relatively lower proportion of
non-participants with a previous episode of depression recorded in their
notes. Men with depression may have a recall bias with regard to physical
symptoms, being more likely to notice them and amplify their duration and
severity (Katon, 2003), but
any such bias adds strength to the argument that the presentation of these
symptoms should be seen as a marker for possible depression.
Implications of our findings
Although the rate of rural male depression found in our study was higher
than that found in other studies, previous research has consistently found
lower rates of depression in rural areas compared with urban environments. The
European Outcome of Depression International Network (ODIN) study included
samples from five urban and four rural centres in five countries, including
the UK and Ireland, and collected data relating to prevalence of depressive
disorder and associated risk factors; in the UK, prevalence of depressive
disorder in the urban centre (17.1%) was substantially higher than that found
in the rural study population (6.1%)
(Ayuso-Mateos et al,
2001). The UK National Morbidity Survey reported significantly
higher rates of psychiatric morbidity and of alcohol and drug dependence in
urban compared with rural areas. After adjustment for a range of
socio-demographic factors the effect of urban residence upon risk of
psychiatric morbidity was considerably weakened, but was still statistically
significant: OR=1.33, P<0.05
(Paykel et al,
2000).
Our research suggests that the pattern of factors associated with depression among rural men may differ from those described for deprived urban populations. Employment status, housing tenure, type of work and family structure were not significant factors in predicting male depression in our study. However, for those in paid employment, lack of enjoyment in their work was a significant correlate of depression. Because our study was restricted to people of working age, no evidence is available concerning risk factors for depression in elderly men. Our finding of a significant link between low job enjoyment or satisfaction and depression is consistent with previous research exploring the attitudes of general practitioners to the interpretation and management of depression. A qualitative study of practice in different social settings in north-west England concluded that general practitioners in inner-city urban areas were more likely than their suburban and semi-rural counterparts to see depression as a product of social problems and to be largely intractable in nature. The semi-rural and suburban practitioners, treating less socially deprived patients in a more prosperous setting, were more prone to associate depression with purely work-related problems, and to consider it as largely treatable (Chew-Graham et al, 2002).
Perhaps our most striking findings relate to the differences between clinicians and patients in their immediate assessments of depression. Regardless of the analysis used (agreement or sensitivity) and the lack of previous validation of the rating scales, there was a clear disparity between the two agencies. We have postulated in previous research that precise agreement between the patient and general practitioner on the nature of symptoms is possibly less important than both parties identifying depression as the core problem (Gabbay et al, 2003). Furthermore, poor sensitivity in general practitioners detection of depression in cases defined by HADS score has been reported in other studies. Analysis of aggregated data from the Hampshire Depression Project found that nearly two-thirds of cases of depression (score >7 on HADSD) were missed by general practitioners using a four-point rating scale (Thompson et al, 2001). However, the study also reported that marked improvements in sensitivity were achieved by minor revisions in the HADSD case threshold (Thompson et al, 2001).
Previous research suggests that psychological symptom patterns may be categorised differently by health professionals and their patients (Leff, 1978). There is also evidence that patients tend to present physical symptoms before psychological ones (Burack & Carpenter, 1983) and that doctors tend to interrupt patients before they have completed their opening statements (Beckman & Frankel, 1984). These factors may explain the tendency to miss depression among patients using normalising symptom attributions (Kessler et al, 1999). The problems of underdetection of depression and suboptimal management of the condition when diagnosed, within general practice, have typically been addressed by educational interventions. This approach assumes that there are key skills that can be taught to primary care doctors in order to facilitate psychological symptom interpretation, more accurate diagnosis of depression and better management. However, results of intervention trials have been disappointing. A recent cluster randomised controlled trial of an educational intervention training general practitioners in managing depression found that patients treated by the intervention group had higher rates of satisfaction, but did not significantly differ from patients treated by the control group in terms of outcomes of depression (Gask et al, 2004). Educational initiatives have typically been based on methods of implementing clinical guidelines for the diagnosis and management of depression. One such randomised controlled trial, involving 60 primary care practices, developed a training intervention intended to support guideline adherence throughout the study year. However, despite considerable resource input, no significant difference was found between trial arms in relation to either the detection of true positives or the short-term and longer-term patient outcomes (Thompson et al, 2000).
Guideline-based education may in the future prove to be effective in increasing detection rates and improving outcomes for patients with depression. However, such an impact would require considerable expansion of the evidence base supporting the guideline recommendations and the subsequent educational interventions (Kendrick, 2000). In particular, more empirical evidence is required that would allow greater insight into why patients with various characteristics, and in a particular social setting, have specific risk factors associated with depression, and how the risk is mediated by the diagnostic skills of the general practitioner. This may include considering both pre-consultation factors, such as patient socio-demographic and occupational characteristics, and within-consultation factors, such as doctors different symptom attribution styles.
Improvements in identification and management of depression among men in rural communities will require more than general practitioner education alone. It is also important to ensure that relevant and effective resources to manage depression are available. Doctors are more likely to make a diagnosis of depression if they consider that they have sufficient skills and treatment options to manage it successfully (Dowrick et al, 2000). Since depression among rural men is relatively uncharted territory, it is possible that the doctors in this study were less likely to make a diagnosis because they were uncertain whether the limited range of treatment options available in primary care antidepressant medication or counselling would be acceptable to this group of patients.
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Clinical Implications and Limitations |
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Limitations
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Received for publication November 7, 2003. Revision received April 16, 2004. Accepted for publication April 22, 2004.
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