SESSAMO, follow-up of secondary students to assess mental health and obesity: a cohort study

During last decades, a departure from health-related lifestyles has been observed among adolescents. Evidence reports that healthy lifestyles could be predictors of better mental health status. The aims of the SESSAMO Project are: 1) to assess the association between lifestyles and physical and mental health; 2) to assess how self-concept and stressful life events can modulate these associations; and 3) to establish the role of social determinants in the lifestyle and in adolescents' health. The SESSAMO Project is a prospective cohort carried out in Spain. Students aged 14-16 years (2nd-4th ESO) and their parents are invited to participate. Baseline data are collected through on-line, validated, self-administered questionnaires through a digital platform. Information on lifestyles, stressful life events and self-concept are collected. Screening of depression, anxiety, eating disorders, suicide risk, psychotic experiences and COVID impact is assessed. Every three years, up to age of 25, participants will be contacted again to update relevant information.

[Evaluation of BIZI, a new Spanish-language online program for community-based suicide preventionAvaliação do BIZI, um novo programa on-line em espanhol para prevenção de suicídio com base na comunidade]

Objective

To evaluate the BIZI program, a Spanish-language gatekeeper training program with a novel online self-learning format that is brief and open-access. It was developed as part of the suicide prevention strategy in Euskadi (Spain) to improve community-based suicide prevention.

Methods

A group of experts from different fields created the program and tested its usability in a preliminary phase. A single-group design was used for the evaluation, with repeated measurements (before, immediately after, and after three months). Online questionnaires were used to evaluate the program's impact on core competencies for gatekeepers, as well as adherence to content and user satisfaction. Community agents (educators and social workers, among others) who responded to an invitation sent by regional public health coordinators were included in the study.

Results

In total, 728 people accessed the training, and 86% completed it; 569 people completed the assessment (81.2% women, mean age 41.4 years). The core gatekeeper competencies of attitude, self-efficacy, and knowledge improved significantly, and improvement was sustained ≥3 months in a subsample (P = 0.0001).

Conclusions

The results are promising and suggest that BIZI is useful in improving the capacity and willingness of community agents to identify people at risk and refer them to specialized resources. Its novel format gives it important advantages over other more common gatekeeper training programs, facilitating its dissemination in low-resource environments. It is the first program of its kind whose effectiveness has been demonstrated and also the first available in Spanish.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data

INTRODUCTION

Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

METHODS

Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia.

RESULTS

Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms.

CONCLUSIONS

The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data

INTRODUCTION

Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS.

METHODS

Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia.

RESULTS

Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms.

CONCLUSIONS

The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Validity of a computerised population registry of dementia based on clinical databases

INTRODUCTION

The handling of information through digital media allows innovative approaches for identifying cases of dementia through computerised searches within the clinical databases that include systems for coding diagnoses. The aim of this study was to analyse the validity of a dementia registry in Gipuzkoa based on the administrative and clinical databases existing in the Basque Health Service.

METHODS

This is a descriptive study based on the evaluation of available data sources. First, through review of medical records, the diagnostic validity was evaluated in two samples of cases identified and not identified as dementia. The sensitivity, specificity and positive and negative predictive value of the diagnosis of dementia were measured. Subsequently, the cases of living dementia in December 31, 2016 were searched in the entire Gipuzkoa population to collect sociodemographic and clinical variables.

RESULTS

The validation samples included 986 cases and 327 no cases. The calculated sensitivity was 80.2% and the specificity was 99.9%. The negative predictive value was 99.4% and positive value was 95.1%. The cases in Gipuzkoa were 10 551, representing 65% of the cases predicted according to the literature. Antipsychotic medication were taken by a 40% and a 25% of the cases were institutionalised.

CONCLUSIONS

A registry of dementias based on clinical and administrative databases is valid and feasible. Its main contribution is to show the dimension of dementia in the health system.

Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data

BACKGROUND

Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated.

OBJECTIVE

The objective of the study was to validate predictive models to separately identify psychotic and depressive symptoms in patients diagnosed with dementia using clinical databases representing the whole population to inform decision-makers.

METHODS

First, we searched the electronic health records of 4,003 patients with dementia to identify NPS. Second, machine learning (random forest) algorithms were applied to build separate predictive models for psychotic and depressive symptom clusters in the training set (N = 3,003). Third, calibration and discrimination were assessed in the test set (N = 1,000) to assess the performance of the models.

RESULTS

Neuropsychiatric symptoms were noted in the electronic health record of 58% of patients. The area under the receiver operating curve reached 0.80 for the psychotic cluster model and 0.74 for the depressive cluster model. The Kappa index and accuracy also showed better discrimination in the psychotic model. Calibration plots indicated that both types of model had less predictive accuracy when the probability of neuropsychiatric symptoms was <25%. The most important variables in the psychotic cluster model were use of risperidone, level of sedation, use of quetiapine and haloperidol and the number of antipsychotics prescribed. In the depressive cluster model, the most important variables were number of antidepressants prescribed, escitalopram use, level of sedation, and age.

CONCLUSION

Given their relatively good performance, the predictive models can be used to estimate prevalence of NPS in population databases.

Improving clinical symptoms, functioning, and quality of life in chronic schizophrenia with an integrated psychological therapy (IPT) plus emotional management training (EMT): A controlled clinical trial

Objective: This paper describes the results of testing a multi-component psychological therapy that includes integrated psychological therapy (IPT), together with an adaptation of emotional management therapy (EMT), versus treatment as usual (TAU), delivered in a community mental health setting for individual with chronic schizophrenia. We investigated the effectiveness of a psychological intervention on clinical symptoms, cognitive and social functioning, as well as the feasibility of treatment and its acceptance. Method: 77 outpatients were recruited, 42 in the experimental group, who were treated with IPT + EMT, and 35 participants in control condition (TAU), both during 8 months. The subjects of both groups were assessed pre and postreatment. Results: Treatment attendance was 98% in experimental group and none of patients required hospital admission during therapy, meanwhile 11 patients from the TAU group withdrew and 3 were hospitalized during therapy. After therapy, patients in the experimental group compared to TAU, reduced clinical symptoms and improved cognitive functioning and quality of life. Conclusion: Psychological therapy seems to be a feasible intervention even in the chronic stages of the disease.

Dementia-related neuropsychiatric symptoms: inequalities in pharmacological treatment and institutionalization

BACKGROUND

Dementia-related neuropsychiatric symptoms (NPS) are the main determinant of family stress and institutionalization of patients. This study aimed to identify inequalities by gender and socioeconomic status in the management of NPS in patients diagnosed with dementia.

METHODS

An observational study was carried out to study all the cases of dementia in the corporate database of the Basque Health Service (29,864 patients). The prescription of antipsychotics and antidepressants and admission to a nursing home were used to establish the presence of NPS. The socioeconomic status of individuals was classified by a deprivation index. Logistic regressions were used to identify drivers for drug prescriptions and institutionalization.

RESULTS

NPS are poorly recorded in the clinical databases (12%). Neuropsychiatric symptoms were severe enough in two thirds of patients with dementia to be treated with psychoactive medication. Institutionalization showed an increase from those who did not receive medication to those who had been prescribed antidepressants (OR: 1.546), antipsychotics (OR: 2.075) or both (OR: 2.741). The resulting inequalities were the increased prescription of antidepressant drugs in women and more nursing-home admissions for women who were the least socioeconomically deprived and men who were the most deprived.

CONCLUSIONS

In large clinical databases, psychoactive drugs prescriptions can be useful to underscore the considerable burden of dementia-related NPS. Specific tools are needed to monitor social and health care programs targeted to dementia-related NPS from a population perspective. Programs aimed at reducing the family burden of care of dementia patients at home become the key elements in reducing inequalities in these patients' care. Socioeconomic status is the most important driver of inequality, and gender inequality may simply be hidden within the social environment. Integrated programs boosting the continuity of care are an objective for which compliance could be measured according to the NPS coding in the electronic health record.

Validity of a computerized population registry of dementia based on clinical databases

INTRODUCTION

The handling of information through digital media allows innovative approaches for identifying cases of dementia through computerized searches within the clinical databases that include systems for coding diagnoses. The aim of this study was to analyze the validity of a dementia registry in Gipuzkoa based on the administrative and clinical databases existing in the Basque Health Service.

METHODS

This is a descriptive study based on the evaluation of available data sources. First, through review of medical records, the diagnostic validity was evaluated in 2 samples of cases identified and not identified as dementia. The sensitivity, specificity and positive and negative predictive value of the diagnosis of dementia were measured. Subsequently, the cases of living dementia in December 31, 2016 were searched in the entire Gipuzkoa population to collect sociodemographic and clinical variables.

RESULTS

The validation samples included 986 cases and 327 no cases. The calculated sensitivity was 80.2% and the specificity was 99.9%. The negative predictive value was 99.4% and positive value was 95.1%. The cases in Gipuzkoa were 10,551, representing 65% of the cases predicted according to the literature. Antipsychotic medication were taken by a 40% and a 25% of the cases were institutionalized.

CONCLUSIONS

A registry of dementias based on clinical and administrative databases is valid and feasible. Its main contribution is to show the dimension of dementia in the health system.

[Primary care and mental health care collaboration in patients with depression: Evaluation of a pilot experience]

Objetivo

Implementar y evaluar una experiencia colaborativa entre Atención Primaria (AP) y Salud Mental (SM) para mejorar la asistencia a los pacientes con depresión.

Diseño

Proyecto colaborativo piloto con enfoque de investigación acción participativa (IAP) durante 2013.

Emplazamiento

: País Vasco. Osakidetza (Servicio Vasco de Salud). Bizkaia y Gipuzkoa.

Participantes

Doscientos siete profesionales de medicina de familia, enfermería, psiquiatría, enfermería psiquiátrica, psicología y trabajo social de 9 centros de salud y 6 centros de salud mental de Osakidetza.

Intervenciones

Diseño y desarrollo compartido de 4 ejes de intervención: 1) comunicación y conocimiento entre profesionales de AP y SM; 2) mejora en la codificación diagnóstica y derivación de pacientes; 3) formación compartida mediante sesiones y guías de práctica clínica comunes, y 4) evaluación.

Mediciones principales

Encuestas a profesionales de centros de intervención y control sobre conocimiento y satisfacción en la relación AP-SM, actividades formativas conjuntas y valoración de la experiencia. Registros de Osakidetza sobre prevalencias, derivaciones y tratamientos. Reuniones de seguimiento.

Resultados

Mejoría en los centros de intervención respecto a los de control en los 4 ejes de intervención. Identificación de factores a considerar en el desarrollo y la sostenibilidad de la colaboración AP-SM.

Conclusiones

La experiencia piloto confirma que los proyectos colaborativos promovidos por AP y SM pueden mejorar la asistencia y satisfacción de los profesionales. Son proyectos complejos que requieren intervenciones simultáneas adecuadas a las singularidades de los servicios de salud. La participación pluridisciplinaria y continuada, y el apoyo de la gestión y los sistemas de información, son condiciones necesarias para su implementación.