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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., (© British Journal of General Practice 2017.)

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.

Background: The List of Threatening Experiences (LTE) questionnaire is frequently used to assess stressful events; however, studies of its psychometric properties are scarce. We examined the LTE's reliability, factorial structure, construct validity and explored the association between LTE scores and psychosocial variables and mental disorders., Method: This study involved interviewing 5442 primary care attendees from Spain. Associations between four different methods of quantifying LTE scores, psychosocial factors, major depression (CIDI), anxiety disorders (PRIME-MD), alcohol misuse and dependence (AUDIT) were measured., Results: The LTE showed high test-retest reliability (Kappa range=0.61-0.87) and low internal consistency (α=0.44). Tetrachoric factorial analysis yielded four factors (spousal and relational problems; employment and financial problems; personal problems; illness and bereavement in close persons). Logistic multilevel regression found a strong association between greater social support and a lower occurrence of stressful events (OR range=0.36-0.79). The association between religious-spiritual beliefs and the LTE, was weaker. The association between mental disorders and LTE scores was greater for depression (OR range=1.64-2.57) than anxiety (OR range=1.35-1.97), though the highest ORs were obtained with alcohol dependence (OR range=2.86-4.80). The ordinal score (ordinal regression) was more sensitive to detect the strength of association with mental disorders., Limitations: We are unable to distinguish the direction of the association between stressful events, psychosocial factors and mental disorders, due to our cross-sectional design of the study., Conclusions: The LTE is a valid and reliable measure of stress in mental health, and the strength of association with mental disorders depends on the method of quantifying LTE scores., (© 2013 Elsevier B.V. All rights reserved.)

Background: The different incidence rates of, and risk factors for, depression in different countries argue for the need to have a specific risk algorithm for each country or a supranational risk algorithm. We aimed to develop and validate a predictD-Spain risk algorithm (PSRA) for the onset of major depression and to compare the performance of the PSRA with the predictD-Europe risk algorithm (PERA) in Spanish primary care., Method: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multi-level logistic regression and inverse probability weighting to build the PSRA. In Spain (4574), Chile (2133) and another five European countries (5184), 11 891 non-depressed adult primary care attendees formed our at-risk population. The main outcome was DSM-IV major depression (CIDI)., Results: Six variables were patient characteristics or past events (sex, age, sex×age interaction, education, physical child abuse, and lifetime depression) and six were current status [Short Form 12 (SF-12) physical score, SF-12 mental score, dissatisfaction with unpaid work, number of serious problems in very close persons, dissatisfaction with living together at home, and taking medication for stress, anxiety or depression]. The C-index of the PSRA was 0.82 [95% confidence interval (CI) 0.79-0.84]. The Integrated Discrimination Improvement (IDI) was 0.0558 [standard error (s.e.)=0.0071, Zexp=7.88, p<0.0001] mainly due to the increase in sensitivity. Both the IDI and calibration plots showed that the PSRA functioned better than the PERA in Spain., Conclusions: The PSRA included new variables and afforded an improved performance over the PERA for predicting the onset of major depression in Spain. However, the PERA is still the best option in other European countries.