Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm.

BACKGROUND: Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. AIM: To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. DESIGN AND SETTING: Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. METHOD: Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. RESULTS: From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. CONCLUSION: The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking.

Predicting the onset of anxiety syndromes at 12 months in primary care attendees. The predictA-Spain study.

BACKGROUND: There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. METHODS: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. RESULTS: The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval=0.78-0.83) and the Hedges' g=1.17 (95% confidence interval=1.04-1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. CONCLUSIONS: The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.

Psychosocial and sociodemographic predictors of attrition in a longitudinal study of major depression in primary care: the predictD-Spain study.

BACKGROUND: Few data exist on the psychosocial factors associated with attrition in longitudinal surveys. This study was undertaken to determine psychosocial and sociodemographic predictors of attrition from a longitudinal study of the onset and persistence of episodes of major depression in primary care. METHODS: A systematic random sample of general practice attendees was recruited in seven Spanish provinces between October 2005 and February 2006. Major depression was diagnosed using the Composite International Diagnostic Interview and a set of 39 individual and environmental risk factors for depression were assessed at baseline and after 6 and 12 months of follow-up. Data were analysed using multilevel logistic regression. RESULTS: 7777 primary care attendees aged 18-75 years were selected, of whom 1251 (16.1%) were excluded. Of the remaining 6526, 1084 (16.6%) refused to participate. Thus, 5442 patients (attending 231 family physicians in 41 health centres) were interviewed at baseline, of whom 3804 (70%) and 3567 (66%) remained at 6 and 12 months of follow-up, respectively. The province and sociodemographic factors were stronger predictors of attrition than psychosocial factors. Depression and anxiety had no effect but other psychosocial factors affected attrition. There were different profiles for the patients lost at 12 months when predictors measured at baseline versus 6 months were included. CONCLUSIONS: These findings suggest that several psychosocial factors might be considered factors of attrition in primary care cohorts and confirm that baseline characteristics are insufficient for analysing non-response in longitudinal studies, indicating that different retention strategies should be applied for patients interviewed at 6 and 12 months.

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: methodology.

BACKGROUND: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. METHODS: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. RESULTS: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. CONCLUSION: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care.