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Background: The reduction of major depression incidence is a public health challenge., Aim: To develop an algorithm to estimate the risk of occurrence of major depression in patients attending primary health centers (PHC)., Material and Methods: Prospective cohort study of a random sample of 2832 patients attending PHC centers in Concepción, Chile, with evaluations at baseline, six and twelve months. Thirty nine known risk factors for depression were measured to build a model, using a logistic regression. The algorithm was developed in 2,133 patients not depressed at baseline and compared with risk algorithms developed in a sample of 5,216 European primary care attenders. The main outcome was the incidence of major depression in the follow-up period., Results: The cumulative incidence of depression during the 12 months follow up in Chile was 12%. Eight variables were identified. Four corresponded to the patient (gender, age, depression background and educational level) and four to patients' current situation (physical and mental health, satisfaction with their situation at home and satisfaction with the relationship with their partner). The C-Index, used to assess the discriminating power of the final model, was 0.746 (95% confidence intervals (CI = 0,707-0,785), slightly lower than the equation obtained in European (0.790 95% CI = 0.767-0.813) and Spanish attenders (0.82; 95% CI = 0.79-0.84)., Conclusions: Four of the factors identified in the risk algorithm are not modifiable. The other two factors are directly associated with the primary support network (family and partner). This risk algorithm for the incidence of major depression provides a tool that can guide efforts towards design, implementation and evaluation of effectiveness of interventions to prevent major depression.

Objective: To find out the influence of gender and age on various types of utilization of primary care services., Method: A random sample group containing 2662 patients over 14 years of age was observed over a continuous period of a year. Having already excluded the losses subjects, health service utilization was measured using patients whose clinical records had previously been validated., Results: A small number of patients (15%) use a disproportionate amount of the total number of visits. A numerical breakdown shows: 43% of global visits (GV), 45% of acute clinical visits (ACV), 68% administrative visits (AV) and 94% programmed visits (PV). The ACV, PV and GV were significantly higher in woman (p = 0.000), though in the AV was not the case. These remained a significant difference when age was controlling factor. The coefficients of correlation between age and the logarithm of the ACV, AV, PV and GV were respectively 0.27, 0.23, 0.40 and 0.41. Gender is not a consideration with regard to use of health services below 35 and above 75 years of age. In multiple lineal regression equations age stands out as the most predictive variable, followed by gender, excluding the AV where the doctor comes before gender., Conclusion: A small group of highusers use a desproportionate amount of the total number of visits, particularly the AV and PV. The positive correlation between age and utilization is more clear by the PV and GV. The female is more user than the male, specially among 35 and 75 years old; although the gender is not determinant by the AV. There is not much explained variability with the age and gender, but the age is more important than the gender on utilization.

Objective: To describe the different fractions of the time used in on-demand medical consultations and their possible association with certain indicators of attendance., Design: A descriptive, observational study., Setting: An urban health centre., Participants: Patients who attended with a prior appointment for on-demand consultations with one of the Health Centre's family doctors between 27th September and 29th November, 1993., Measurements and Main Results: An observer with a chronometer measured the different fractions of time in 263 interviews. The 50% of the interview time was taken up by bureaucratic and recording activities; and the other 50% by doctor-patient communication and investigation. Bureaucratic recording time (prescriptions, sick-notes...) makes up 72% of total recording time, while the remaining 28% is for the writing-up of the clinical notes. Times for initial listening (23%), questioning (23%), investigation (21%) and information-education (26%) correlate positively among themselves. The average time dedicated to writing the clinical notes was significantly greater when the total consulting time was 3 to 4 hours than when it was 2 to 3 hours (p = 0.04). The average time dedicated to writing prescriptions was greater when the total number of patients per day was over 20 (p = 0.005); while the average time spent listening to the patient was greater when 21 to 25 patients per day were seen than when the figure was 10 to 20 or 26 to 29 patients per day., Conclusions: There is a need for certain organisational changes in consultations or some kind of bureaucratic-administrative support, if the fraction of interview time dedicated to doctor-patient communication is to be increased.

Objective: We set out to analyse factors which might affect the completion of the "static" register in the Primary Care clinical notes., Design: Crossover and observation study with a control of the confusion in data analysis., Setting: Albaycín Health Centre (Granada)., Patients and Other Participants: A random sample of 428 sets of Primary Care clinical notes., Measurements and Main Results: The "static" register showed over 50% observance in the sections on case history, allergies, tobacco and alcohol; whereas in housing (42%) and diet and physical activity (25%), the observance diminished until reaching its lowest level in counter-indicated medicines, anti-tetanus vaccination, a vaccine biography and family notes (< 10%). Age and gender variables showed virtually no association with the completion of the register. The static register was significantly better for husbands/wives as against children, for patients included in health programmes, for those included in adult rather than other types of programme, for those with smaller-sized families, for patients who used the Centre more and also for three of the doctors as against a fourth. Finally we constructed an overall indicator of the static register (OISR) which was submitted to a process of internal validation and was object of a multiple linear regression model which explained 51.3% of the variability., Conclusions: We underline the need to go deeper into those factors affecting the register as a first step towards understanding its completion. In this way we will find criteria for improving it or modifying the organisation of its observance and/or format. We discussed a method of overall indicators for tackling such a problematic.

Of a total population of a pediatric office of the Zaidin South Health Care Center, all of the mothers that were frequent users (69) were chosen and compared with a random sample of normal users (82). Both groups carried out the anxiety scale STAI. Significant differences were found in that the high users have greater levels of anxiety about trait (p = 0.0003), as well as state (p = 0.000). The high levels of anxiety of trait are associated with being a house wife, having a child with a chronic illness, non maternal lactation, low levels of studies, health education and family income. Family income was the variable with the greatest association with the anxiety of trait (multiple regression). When we took into consideration the variables of predisposition, availability and ease of use, the maternal anxiety continued to have a significant influence. We point out the importance of maternal anxiety in the high frequency of pediatric health care use and we underline the modifiable characteristics of the anxiety factor, and therefore the possibility of reducing the high use of health care services addressed.

Objective: To find the nature of the relationship between the general level of mothers' health knowledge and the over-use of paediatric facilities at the Primary Care level., Design: A crossover study with a control group. SITE. Zaidin-Sur Health Centre (Granada)., Patients or Others Participants: We selected all the over-users (69) of a Paediatric office and compared them to a random sample, grouped by age, of normal users (82); n = 151., Main Measurements and Results: To control confusion, we measured a total of 31 variables, grouped as to need, predisposition and expediting factors. After validating the scales, the average scores for general health understanding and the score for clinical attitudes and knowledge were significantly lower in the over-user group (p = 0.017 and p = 0.000). The scale for attitudes to and knowledge of prevention did not attain any importance (p = 0.104). We worked out a model of multiple logistical regression which included in the equation the scale of clinical attitudes and knowledge (p less than 0.005)., Conclusions: We emphasised the importance of mothers' health knowledge to the question of over-use of paediatric facilities. It is desirable to attempt to intervene on this question in order to lessen excessive use of health facilities.

BackgroundThere 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.MethodFamily 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.ResultsThere 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.ConclusionsPredictA 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. [ABSTRACT FROM PUBLISHER]