Family doctors' problems and motivating factors in management of depression

BACKGROUND: Depression is a frequent psychiatric disorder, and depressive patient may be more problematic for the family doctors (FD) than a patient suffering from a somatic disease. Treatment of patients with depressive disorders is a relatively new task for Estonian FDs. The aim of our study was to find out the family doctors' attitudes to depression related problems, their readiness, motivating factors and problems in the treatment of depressive patients as well as the existence of relevant knowledge. METHODS: In 2002, altogether 500 FDs in Estonia were invited to take part in a tailor-made questionnaire survey, of which 205 agreed to participate. RESULTS: Of the respondents 185(90%) considered management of depressive patients and their treatment to be the task of FDs. One hundred and eighty FDs (88%) were themselves ready to deal with depressed patients, and 200(98%) of them actually treated such patients. Commitment to the interests of the patients, better cooperation with successfully treated patients, the patients' higher confidence in FDs and disappearance of somatic complaints during the treatment of depression were the motivating factors for FDs. FDs listed several important problems interfering with their work with depressive patients: limited time for one patient, patients' attitudes towards the diagnosis of depression, doctors' difficulties to change the underlying causes of depression, discontinuation of the treatment due to high expenses and length. Although 115(56%) respondents maintained that they had sufficient knowledge for diagnostics and treatment of depression, 181(88%) were of the opinion that they needed additional training. CONCLUSION: FDs are ready to manage patients who might suffer from depression and are motivated by good doctor-patient relationship. However, majority of them feel that they need additional training

Prediction of depression in European general practice attendees: the PREDICT study

Background Prevention of depression must address multiple risk factors. Estimating overall risk across a range of putative risk factors is fundamental to prevention of depression. However, we lack reliable and valid methods of risk estimation. This protocol paper introduces PREDICT, an international research study to address this risk estimation. Methods/design This is a prospective study in which consecutive general practice attendees in six European countries are recruited and followed up after six and 12 months. Prevalence of depression is assessed at baseline and each follow-up point. Consecutive attendees between April 2003 and September 2004 who were aged 18 to 75 were asked to take part. The possibility of a depressive episode was assessed using the Depression Section of the Composite International Diagnostic Interview. A selection of presumed risk factors was based on our previous work and a systematic review of the literature. It was necessary to evaluate the test-retest reliability of a number of risk factor questions that were developed specifically, or adapted, for the PREDICT study. In a separate reliability study conducted between January and November 2003, consecutive general practice attendees in the six participating European countries completed the risk factor items on two occasions, two weeks apart. The overall response rate at entry to the study was 69%. We exceeded our expected recruitment rate, achieving a total of 10,048 people in all. Reliability coefficients were generally good to excellent. Discussion Response rate to follow-up in all countries was uniformly high, which suggests that prediction will be based on almost a full cohort. The results of our reliability analysis are encouraging and suggest that data collected during the course of PREDICT will have a satisfactory level of stability. The development of a multi-factor risk score for depression will lay the foundation for future research on risk reduction in primary care. Our data will also provide the necessary evidence base on which to develop and evaluate interventions to reduce the prevalence of depression

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees : the PredictAL study

Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse

Prevalence of Depression in a Large Urban South Indian Population — The Chennai Urban Rural Epidemiology Study (Cures – 70)

BACKGROUND: In India there are very few population based data on prevalence of depression. The aim of the study was to determine the prevalence of depression in an urban south Indian population. METHODS AND FINDINGS: Subjects were recruited from the Chennai Urban Rural Epidemiology Study (CURES), involving 26,001 subjects randomly recruited from 46 of the 155 corporation wards of Chennai (formerly Madras) city in South India. 25,455 subjects participated in this study (response rate 97.9%). Depression was assessed using a self-reported and previously validated instrument, the Patient Health Questionnaire (PHQ) - 12. Age adjustment was made according to the 2001 census of India. The overall prevalence of depression was 15.1% (age-adjusted, 15.9%) and was higher in females (females 16.3% vs. males 13.9%, p<0.0001). The odds ratio (OR) for depression in female subjects was 1.20 [Confidence Intervals (CI): 1.12-1.28, p<0.001] compared to male subjects. Depressed mood was the most common symptom (30.8%), followed by tiredness (30.0%) while more severe symptoms such as suicidal thoughts (12.4%) and speech and motor retardation (12.4%) were less common. There was an increasing trend in the prevalence of depression with age among both female (p<0.001) and male subjects (p<0.001). The prevalence of depression was higher in the low income group (19.3%) compared to the higher income group (5.9%, p<0.001). Prevalence of depression was also higher among divorced (26.5%) and widowed (20%) compared to currently married subjects (15.4%, p<0.001). CONCLUSIONS: This is the largest population-based study from India to report on prevalence of depression and shows that among urban south Indians, the prevalence of depression was 15.1%. Age, female gender and lower socio-economic status are some of the factors associated with depression in this population

An international risk prediction algorithm for the onset of generalized anxiety and panic syndromes in general practice attendees: predictA.

BACKGROUND: There are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes. METHOD: Family practice attendees were recruited between April 2003 and February 2005 and followed over 24 months in the UK, Spain, Portugal and Slovenia (Europe4 countries) and over 6 months in The Netherlands, Estonia and Chile. Our main outcome was generalized anxiety and panic syndromes as measured by the Patient Health Questionnaire. We entered 38 variables into a risk model using stepwise logistic regression in Europe4 data, corrected for over-fitting and tested it in The Netherlands, Estonia and Chile. RESULTS: There were 4905 attendees in Europe4, 1094 in Estonia, 1221 in The Netherlands and 2825 in Chile. In the algorithm four variables were fixed characteristics (sex, age, lifetime depression screen, family history of psychological difficulties); three current status (Short Form 12 physical health subscale and mental health subscale scores, and unsupported difficulties in paid and/or unpaid work); one concerned country; and one time of follow-up. The overall C-index in Europe4 was 0.752 [95% confidence interval (CI) 0.724-0.780]. The effect size for difference in predicted log odds between developing and not developing anxiety was 0.972 (95% CI 0.837-1.107). The validation of predictA resulted in C-indices of 0.731 (95% CI 0.654-0.809) in Estonia, 0.811 (95% CI 0.736-0.886) in The Netherlands and 0.707 (95% CI 0.671-0.742) in Chile. CONCLUSIONS: PredictA accurately predicts the risk of anxiety syndromes. The algorithm is strikingly similar to the predictD algorithm for major depression, suggesting considerable overlap in the concepts of anxiety and depression