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Lorena Carrascal-Laso,1 Manuel Ángel Franco-Martín,1 Elena Marcos-Vadillo,2 Ignacio Ramos-Gallego,3 Belén García-Berrocal,2 Eduardo Mayor-Toranzo,1 Santiago Sánchez-Iglesias,4 Carolina Lorenzo,4 Alfonso Sevillano-Jiménez,1 Almudena Sánchez-Martín,5 María Jesús García-Salgado,2 María Isidoro-García2,6 1Servicio de Psiquiatría, Hospital Provincial de Zamora, IBSAL, Zamora, 49071, Spain; 2Farmacogenética y Medicina de Precisión, Servicio de Bioquímica, Hospital Universitario de Salamanca, IBSAL, Salamanca, 37007, Spain; 3Departamento de Fisiología y Farmacología, Universidad de Salamanca, Salamanca, 37007, Spain; 4Servicio de Psiquiatría, Hospital Universitario de Salamanca, IBSAL, Salamanca, 37007, Spain; 5Pharmacogenetics Unit, Pharmacy Department, University Hospital Virgen de las Nieves, UGC Provincial de Farmacia de Granada, Granada, 18014, Spain; 6Departamento de Medicina, Universidad de Salamanca, Salamanca, 37007, SpainCorrespondence: Manuel Ángel Franco-Martín Email mfrancom@saludcastillayleon.esBackground: Schizophrenia is a severe mental disorder that often manifests within the first three decades of life. Its prognosis is uncertain and may result in a prolonged treatment that could extend throughout the entire lifespan of the patient. Antipsychotic drugs are characterized by a high interindividual variability when considering therapeutic effect and emergence of adverse effects. Such interindividual variability is thought to be associated primarily with pharmacokinetic matters.Objective: The objective of this study was to evaluate the economic impact of the application of the 5-Step Precision Medicine model (5SPM), an approach based on the pharmacogenetic analysis of the primary genes involved in the metabolism of the therapy for each patient, restructuring treatment as necessary.Patients and Methods: One hundred eighty-eight psychiatry patients were analysed for single nucleotide polymorphisms on genes CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5 and ABCB1. Information on patients’ diagnosis, pharmacotherapy, and hospitalizations was collected.Results: We achieved a cost–benefit ratio of 3.31– 3.59 with a reduction of direct cost (hospitalizations plus pharmacotherapy) with a reduction of total cost in 67% of the patients who underwent the clinical intervention.Conclusion: A rational Precision Medicine-based approach to psychiatric patients could result in a reduction on number of drugs required to control exacerbations, and the underlying pathologies, reducing the risk of adverse effects and improving adherence to treatment, leading to a potential decrease in direct costs. This methodology has been shown to be cost-dominant and, being based on a pharmacogenetic analysis, it has a lifelong nature, as the data obtained can be applied to other medical disciplines.Keywords: pharmacogenetics, pharmacoeconomics, psychotic disorders, cytochrome P-450, antipsychotics

We report a case of schizophrenia disorganized in which there is a pronouncedcognitive impairment and particularly intellectually deterioration. The reflection of the background, as well as the monitoring of the quantitative results with the observation qualitative and daily, leading to deepen respect to the need of consider both neuropsychological elements and psychopathological in the interpretations of the results of psychological tests. Moreover in pathologies where the limits and the relationship between the psychopathology and neuropsychology not clear. That is why the emphasis is on the valuation of the individual as a whole and not its dismemberment in parts.

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Background: E-learning has shown to be an effective intervention in helping informal caregivers of people living with dementia. It has the potential to reach people living in remote areas, increasing service coverage. As a response to the demographic context in Spain associated with a higher percentage of ageing, depopulation, and the complexities of health service delivery in rural areas, this paper describes the cultural adaptation and co-design of the iSupport online training and support programme for Castilla y León, Spain, as a potential e-health intervention to mitigate these constraints., Methods: The translation and cultural adaptation were performed following the WHO guidelines, with some adaptation due to the cultural context of Spain. Three focus groups were conducted with informal caregivers, health professionals, and a group of experts on cognitive impairment and dementia. The co-design process was performed as a Patient and Public Involvement activity with three groups consisting of people living with dementia, informal caregivers, rural population and experts on technology and dementia., Results: A total of 435 suggestions were proposed for adaptation associated with erroneous terminology, rewording text/writing, grammatical or punctuation marks errors, and repeated information or need for additional content. Several recommendations were exposed during the co-design process: preference for interactive material such as videos or images, a forum to receive feedback from health care professionals and to leave satisfaction comments, availability in multiple platforms (e.g., tablet, laptop, mobile), slide format for information presentation, and availability to edit letter size and background colours., Conclusions: A culturally adapted version of the iSupport was developed for Castilla y León, Spain. The need for modification of words and expressions, information links to local resources websites, adjustments of characters' names and caregivers' scenarios, and additional content to some sections were recommended. Suggestions for the design should be taken into account for further adapted versions and platform developments.

As assessed by numerous neuropsychological tasks, individuals with autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SSDs) have similar impairments related to executive functions (EFs). The neuropsychological profile of these two conditions was examined using the three-component EFs' framework of Miyake and Friedman (Cogn Psychol 41(1):49-100, 2000). This approach assesses Inhibition (suppression of unwanted and irrelevant information/responses), Updating (use and control of contents of working memory), and Shifting (disengagement between activities or mental tasks) using nine different tasks. In line with previous research, we expected greater performance deficits in ASD in all three components compared to SSD, as well as faster responses for the SSD group. A self-paced task format allowed us to examine whether unlimited time given for a task would lead to better performance. The sample was constituted by the control group (N = 25), ASD group (N = 24), and SSD group (N = 12). Groups did not differ on Inhibition performance. In Updating, individuals with SSD performed poorer than the other groups. As for Shifting, both groups demonstrated poorer performance compared to controls, with the SSD group presenting the greatest difficulties. In terms of reaction time (RT), SSD participants' RT were the slowest on Inhibition and Shifting tasks. There was a positive correlation between performance and time spent on Inhibition and Shifting only for the SSD group, which demonstrates that their performance improves when there are no time constraints. Our work provides a better understanding of spared and impaired EFs, which could be useful for designing strategies aimed at improving specific EFs in each group., (© 2022. The Author(s).)

Objectives: Mental health professionals are becoming increasingly involved in the process of employment rehabilitation of persons with psychiatric disabilities. However, few studies address the attitudes of these professionals toward the employability of those with mental illness. The aim of this research was to identify differences in the attitudes of medical and non-medical mental health professionals, as well as to detect any association between attitude scores and the type of professional., Methods: A sample of 140 employees from public and third sector mental health organizations answered a questionnaire using a scale measuring their attitudes and views on the employability of people with psychiatric disabilities. The psychometric characteristics of the scale are provided together with the variations detected in the professionals' attitudes., Results: This research shows that significant differences in the attitudes between medical and non-medical mental health employees exist and that there is a need for the implementation of educational programs that may help to improve the attitudes of medical professionals toward the employability of people with mental illness., Conclusion: This research indicates the importance of improving the professionals' attitudes to support people attempting to return to work., (© 2022 The Authors. Brain and Behavior published by Wiley Periodicals LLC.)

Suicide was the main source of death from external causes in Spain in 2020, with 3,941 cases. The importance of identifying those mental disorders that influenced hospital readmissions will allow us to manage the health care of suicidal behavior. The feature selection of each hospital in this region was carried out by applying Machine learning (ML) and traditional statistical methods. The results of the characteristics that best explain the readmissions of each hospital after assessment by the psychiatry specialist are presented. Adjustment disorder, alcohol abuse, depressive syndrome, personality disorder, and dysthymic disorder were selected for this region. The most influential methods or characteristics associated with suicide were benzodiazepine poisoning, suicidal ideation, medication poisoning, antipsychotic poisoning, and suicide and/or self-harm by jumping. Suicidal behavior is a concern in our society, so the results are relevant for hospital management and decision-making for its prevention., Competing Interests: Conflict of InterestThe authors declare no competing interests., (© The Author(s) 2022.)

Mental disorders are a critical public health challenge since they profoundly affected people lifestyle. Mental healthcare treatments aim to promote a higher quality of life of the patients. These procedures include interventions for prolonged mental illness which can be supported by telemedicine technologies. This paper presents a comprehensive analysis of mobile applications selected to address the most critical needs of people with mental problems. Needs include areas of the patient's life, such as basic activities, behavioral changes, and daily life tasks. This work has two main objectives; (1) identify critical needs for patients with mental disorders and (2) identify and analyze apps that can meet the identified critical needs. A Delphi methodology survey was carried with a group of thirteen volunteers, including nurses, assistants, and psychiatrists who are working in Zamora and Valladolid, Spain. This survey has recommended different needs for patients with mental disorders and address objective 1. Google Play and Apple Store have been assessed to select the most relevant mobile applications that were recommended in the Delphi study to address the essential needs of these patients according to objective 2. The results of the Delphi survey show 24 different needs for patients with mental disorders. This study has analyzed 62 mobile applications which address the essential needs recommended in the Delphi study. The selected mobile applications represent 31 applications with feedback (50%); 15 informative applications (24%), and 16 independent applications (26%). On the one hand, applications with feedback request can address 13 recommended needs (54%). On the other hand, informative applications can address 7 needs (29%). Finally, the independent applications are only able to respond to 4 of the 24 recommend needs (17%). Mobile health applications present effective technologies to support the needs of patients with mental disorders. However, this study suggests a critical limitation of mobile applications for mental health since the majority of the applications require user activity. Therefore, future research initiatives on the design and development of mobile apps for people who have mental disorders should focus on independent applications.

New computational methods have emerged through science and technology to support the diagnosis of mental health disorders. Predictive models developed from machine learning algorithms can identify disorders such as schizophrenia and support clinical decision making. This research aims to compare the performance of machine learning algorithms: Decision Tree, AdaBoost, Random Forest, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor in the prediction of hospitalized patients with schizophrenia. The data set used in the study contains a total of 11,884 electronic admission records corresponding to 6933 patients with various mental health disorders; these records belong to the acute units of 11 public hospitals in a region of Spain. Of the total, 5968 records correspond to patients diagnosed with schizophrenia (3002 patients) and 5916 records correspond to patients with other mental health disorders (3931 patients). The results recommend Random Forest with the best accuracy of 72.7%. Furthermore, this algorithm presents 79.6%, 72.8%, 72.7%, and 72.7% for AUC, precision, F1-Score, and recall, respectively. The results obtained suggest that the use of machine learning algorithms can classify hospitalized patients with schizophrenia in this population and help in the hospital management of this type of disorder, to reduce the costs associated with hospitalization.

During the first confinement in Spain, between the months of March to June 2020, Information and Communication Technologies strategies were implemented in order to support health workers in the Wellbeing of Mental Health. Faced with so much uncertainty about the pandemic, an Online Mindfulness course. The objective of the course was to support healthcare professionals in Castilla y León in managing stress, anxiety and other emotional disturbances generated by coping with a situation as uncertain and unexpected as a pandemic, in order to manage emotions and thoughts that can lead to suicidal ideation. The motivations for the demand, reasons or motivations in which the health professionals of Castilla y León decided to participate in the mindfulness course in the first wave of Covid-19 in Spain are described. The descriptive and inferential statistical analysis of the customer satisfaction survey applied at the end of the mindfulness course, to the health professionals who participated in a satisfaction survey (CSQ-8: Client Satisfaction Questionnaire). Professional were asked to complete a survey based on (CSQ-8: Client Satisfaction Questionnaire) whose Cronbach's alpha = 0.917 is why the instrument used with N = 130 participants has high reliability. The 66% answered with a highly satisfied that they would return to the mindfulness online course. The 93% of the people who answered the satisfaction survey were women, of which they are professionals in the nursing area, with a participation of around 62%. In relation to the online system used in the Mindfulness intervention, 74% expressed that they fully agreed that it has been easy to use the online system for the mindfulness intervention. Health Professionals responded with 58% high satisfaction and 36% satisfaction, making a total of 94% on the help received in the online mindfulness courses to solve their problems. There is no difference between the age groups of the professionals who have preferred the Mindfulness online course (p = 0.672)., (© 2022. The Author(s).)

Background: In the era of big data, networks are becoming a popular factor in the field of data analysis. Networks are part of the main structure of BeGraph software, which is a 3D visualization application dedicated to the analysis of complex networks., Objective: The main objective of this research was to visually analyze tendencies of mental health diseases in a region of Spain, using the BeGraph software, in order to make the most appropriate health-related decisions in each case., Methods: For the study, a database was used with 13,531 records of patients with mental health disorders in three acute medical units from different health care complexes in a region of Spain. For the analysis, BeGraph software was applied. It is a web-based 3D visualization tool that allows the exploration and analysis of data through complex networks., Results: The results obtained with the BeGraph software allowed us to determine the main disease in each of the health care complexes evaluated. We noted 6.50% (463/7118) of admissions involving unspecified paranoid schizophrenia at the University Clinic of Valladolid, 9.62% (397/4128) of admissions involving chronic paranoid schizophrenia with acute exacerbation at the Zamora Hospital, and 8.84% (202/2285) of admissions involving dysthymic disorder at the Rio Hortega Hospital in Valladolid., Conclusions: The data analysis allowed us to focus on the main diseases detected in the health care complexes evaluated in order to analyze the behavior of disorders and help in diagnosis and treatment., (©Susel Góngora Alonso, Andrés de Bustos Molina, Beatriz Sainz-De-Abajo, Manuel Franco-Martín, Isabel De la Torre Díez. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 16.06.2021.)

The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satisfaction level of the participants involved, with a view to establishing strategies to improve future experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks, and transfer learning, so as to classify the inputs into the following three categories: negative, neutral, and positive. Due to the limited amount of data available-86 registers for the first and 68 for the second-transfer learning techniques were required. The length of the text had no limit from the user's standpoint, and our approach attained a maximum accuracy of 93.02% and 90.53%, respectively, based on ground truth labeled by three experts. Finally, we proposed a complementary analysis, using computer graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages.

Background: Patients suffering from addiction are a vulnerable group in the midst of COVID-19, so their healthcare is considered essential. In this paper, the measures and responses of the Drug Addiction Assistance Network of Castile and Leon (DAACYL) in Spain during the first 6 weeks of the COVID-19 pandemic are explained. The aim is that this experience could be useful in places where this problem will continue and could help future interventions. Methods: A telephone survey was carried out as the main methodology, to collect information for the subsequent organization and repercussion on professionals and patients. This was carried out by the heads of the 18 DAACYL units. Among the interventions applied, the following stand out: implantation of telemedicine techniques, restriction of daily methadone dispensing, suspension of urine controls and initiation of care programs for the homeless. Results: As a result of these interventions, the professionals observed that patients are less demanding and mostly stable, with a low percentage of relapses. An increase in the consumption of alcohol and benzodiazepines have been reported as more common among people who relapse. Furthermore, the prevalence of COVID-19 infection in the sample is minimal; therefore, different hypotheses should be considered as an explanation (infra-diagnosis, immune system used to aggression, possible anti-inflammatory effect of some psychotropic drugs and a greater perception of danger against infection than the general population). Conclusions: The rapid adaptation and successful implementation of DAACYL have had satisfactory results. On the other hand, the prevention of the possible increase in the development of behavioral addictions and the use of homemade drugs should be considered., (Copyright © 2020 Roncero, Vicente-Hernández, Casado-Espada, Aguilar, Gamonal-Limcaoco, Garzón, Martínez-González, Llanes-Álvarez, Martínez, Franco-Martín and Álvarez-Navares.)

According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have committed suicide. Moreover, suicide is the second cause of unnatural death in people between 15 and 29 years. This paper reviews state of the art on the literature concerning the use of machine learning methods for suicide detection on social networks. Consequently, the objectives, data collection techniques, development process and the validation metrics used for suicide detection on social networks are analyzed. The authors conducted a scoping review using the methodology proposed by Arksey and O'Malley et al. and the PRISMA protocol was adopted to select the relevant studies. This scoping review aims to identify the machine learning techniques used to predict suicide risk based on information posted on social networks. The databases used are PubMed, Science Direct, IEEE Xplore and Web of Science. In total, 50% of the included studies (8/16) report explicitly the use of data mining techniques for feature extraction, feature detection or entity identification. The most commonly reported method was the Linguistic Inquiry and Word Count (4/8, 50%), followed by Latent Dirichlet Analysis, Latent Semantic Analysis, and Word2vec (2/8, 25%). Non-negative Matrix Factorization and Principal Component Analysis were used only in one of the included studies (12.5%). In total, 3 out of 8 research papers (37.5%) combined more than one of those techniques. Supported Vector Machine was implemented in 10 out of the 16 included studies (62.5%). Finally, 75% of the analyzed studies implement machine learning-based models using Python.

Background: Provision of follow-up and care during treatment of people with suicidal intentions is a challenge for health professionals and experts in information and communications technology (ICT). Therefore, health professionals and ICT experts are making efforts to carry out these activities in collaboration by using mobile apps as a technological resource., Objective: This study aimed to descriptively analyze mobile apps aimed at suicide prevention and to determine relevant factors in their design and development. In addition, it sought to analyze their impact on the support of treatment for patients at risk for suicide., Methods: We considered 20 apps previously listed in the article "Mobile Apps for Suicide Prevention: Review of Virtual Stores and Literature" (de la Torre et al, JMIR mHealth uHealth 2017;5[10]:e130). To find the apps in this list, the most popular app stores (Android and iOS) were searched using the keyword "suicide prevention." The research focused on publicly available app information: language, platform, and user ratings. The results obtained were statistically evaluated using 16 parameters that establish various factors that may affect the choice of the user, and the consequent support that the app can offer to a person at risk for suicide., Results: Of the 20 mobile apps, 4 no longer appeared in the app stores and were therefore excluded. Analysis of the remaining 16 apps sampled showed the following: (1) a high percentage of the apps analyzed in the study (n=13, 82%) are provided in English language; (2) the sampled apps were last updated in 2017, when only 45% of them were updated, but the constant and progressive update of treatments should be reflected in the apps; and (3) the technical quality of these apps cannot be determined on the basis of the distribution of scores, because their popularity indices can be subjective (according to the users). User preference for a particular operating system would require further, more specific research, including study of the differences in the technical and usability aspects between both platforms and the design of medical apps., Conclusions: Although there are positive approaches to the use of apps for suicide prevention and follow-up, the technical and human aspects are yet to be explored and defined. For example, the design and development of apps that support suicide prevention should be strongly supported by health personnel to humanize these apps, so that the effectiveness of the treatments supported by them can be improved., (©Gema Castillo-Sánchez, Ismael Camargo-Henríquez, Juan Luis Muñoz-Sánchez, Manuel Franco-Martín, Isabel de la Torre-Díez. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.08.2019.)

Objectives: This study aimed to carry out a pilot validation of Affect-GRADIOR, a computer-based emotion recognition test, with older adults. The study evaluated its usability, reliability and validity for the screening of people with Alzheimer´s disease (AD) and amnestic mild cognitive impairment (aMCI)., Methods: The test was administered to 212 participants (76.37 ± 6.20 years) classified into three groups (healthy controls, n = 69; AD, n = 84; and aMCI, n = 59) on the basis of detailed neurological, neuropsychological, laboratory and neuro-imaging evidence. Data on usability were collected by means of a questionnaire and automated evaluation., Results: The validated test comprised 53 stimuli and 7 practice items (one per emotion). Participants reported that Affect-GRADIOR was accessible and user-friendly. It had high internal consistency (ordinal Cronbach's α = 0.96). Test-retest reliability correlations were significant and robust (r = 0.840, p < 0.001). Exploratory factor analysis supported a seven-factor model of the emotions assessed (neutral expression, happiness, surprise, disgust, sadness, anger and fear). Receiver operating characteristic curve analyses suggested that the test discriminated healthy older adults from AD and aMCI cases. Correct answer score improved MMSE predictive power from 0.547 to 0.560 (Cox & Snell R 2 , p = 0.012), and Affect-GRADIOR speed of processing score improved MMSE predictive power from 0.547 to 0.563 (Cox & Snell R 2 , p = 0.010)., Conclusions: Affect-GRADIOR is a valid instrument for the assessment of the facial recognition of emotions in older adults with and without cognitive impairment.

Background: Data from primary health care in Spain show a high prevalence of the major depressive disorder. Blended treatment (combination of face-to-face and online components) seems to be a very promising tool for the optimization and dissemination of psychological treatments in a cost-effective form. Although there is growing data that confirm the advantages of blended therapies, few studies have analyzed their application in regular clinical practice. The objective of the present paper is to describe the protocol for a clinical study aimed at exploring the clinical and cost-effectiveness of a blended cognitive behavioral therapy (b-CBT) for depression, compared to treatment as usual (TAU) in a primary health care setting., Methods: A two-arm randomised controlled non-inferiority trial will be carried out, with repeated measures (baseline, 3 months, 6 months, and 12 months) under two conditions: b-CBT and TAU. The b-CBT program will consist in three face-to-face sessions and eight online sessions. The TAU is defined as the routine care delivered by the general practitioner for the treatment of depression in primary care. The primary outcome is a symptomatic change of depressive symptoms on the patient-health questionnaire (PHQ-9). Other secondary outcomes will be considered (e.g., quality of life, treatment preference). All participants must be 18 years of age or older and meet the diagnostic criteria for major depressive disorder according to the Diagnostic and Statistical Manual of Mental disorders 4th edition. 156 participants will be recruited (78 per arm)., Discussion: It is expected that b-CBT is clinically non-inferior when compared to TAU. This is the first study in Spain to use a b-CBT format in primary and specialized care, and this format could be an efficacious and cost-effective therapeutic strategy for the treatment of depression., Trial Registration: ClinicalTrials.gov NCT02361684. Registered on 8 January 2015. Currently recruiting participants.

Background: This study provides an analysis on the use of emerging technologies for the prevention of suicide in 8 different European countries., Objective: The objective of this study was to analyze the potentiality of using emerging technologies in the area of suicide prevention based on the opinion of different professionals involved in suicide prevention., Methods: Opinions of 3 groups of stakeholders (ie, relevant professionals in suicide field) were gathered using a specifically designed questionnaire to explore dimensions underlying perceptions of facilitating factors and barriers in relation to the use of emerging technologies for suicide prevention., Results: Goal 1 involved facilitating factors for the use of emerging technologies in suicide prevention. Northern European countries, except for Belgium, attach greater relevance to those that optimize implementation and benefits. On the other hand, Southern European countries attach greater importance to professionally oriented and user-centered facilitating factors. According to different stakeholders, the analysis of these facilitating factors suggest that professionals in the field of social work attach greater relevance to those that optimize implementation and benefits. However, professionals involved in the area of mental health, policy makers, and political decision makers give greater importance to professionally oriented and user-centered facilitating factors. Goal 2 was related to barriers to the usability of emerging technologies for suicide prevention. Both countries and stakeholders attach greater importance to barriers associated with resource constraints than to those centered on personal limitations. There are no differences between countries or between stakeholders. Nevertheless, there is a certain stakeholders-countries interaction that indicates that the opinions on resource constraints expressed by different stakeholders do not follow a uniform pattern in different countries, but they differ depending on the country., Conclusions: Although all countries and stakeholders agree in identifying resource constraints as the main barrier to the use of emerging technologies, factors facilitating their use in suicide prevention differ among countries and among stakeholders., (©Juan-Luis Muñoz-Sánchez, Carmen Delgado, Esther Parra-Vidales, Manuel Franco-Martín. Originally published in JMIR Mental Health (http://mental.jmir.org), 24.01.2018.)

Usability is one of the most prominent criteria that must be fulfilled by a software product. This study aims to evaluate the usability of SocialNet, a private social network for monitoring the daily progress of patients by their relatives, using a mixed usability approach: heuristic evaluation conducted by experts and user testing. A double heuristic evaluation with one expert evaluator identified the issues related to consistency, design, and privacy. User testing was conducted on 20 users and one evaluator using observation techniques and questionnaires. The main usability problems were found to be related to the structure of SocialNet, and the users presented some difficulties in locating the buttons or links. The results show a high level of usability and satisfaction with the product. This evaluation provides data on the usability of SocialNet based on the difficulties experienced by the users and the expert. The results help in redesigning the tool to resolve the identified problems as part of an iterative process.

Objectives: To estimate the efficacy of computer-based cognitive interventions for improving cognition in people with dementia (PWD)., Method: Online literature databases were searched for relevant studies. Interventions were categorised as follows: cognitive recreation, cognitive rehabilitation, cognitive stimulation or cognitive training. A systematic review, quality assessment and meta-analyses were conducted., Results: Twelve studies were identified. Their methodological quality was acceptable according to Downs & Black criteria, the weakest methodological area being the external validity. The meta-analyses indicated cognitive interventions lead to beneficial effects on cognition in PWD (SMD 0.69; 95% CI = 1.02-0.37; P < 0.0001; I(2) = 29%), [corrected] depression (SMD 0.47; 95% CI = 0.16-0.78; P = 0.003; I(2) = 0%) and anxiety (SMD 0.55; 95% CI = 0.07-1.04; P < 0.03; I(2) = 42%). [corrected]. They benefited significantly more from the computer-based cognitive interventions than from the non-computer-based interventions in cognition (SMD 0.48; 95% CI = 0.09-0.87; [corrected] P = 0.02; I(2) = 2%)., Conclusion: Computer-based cognitive interventions have moderate effects in cognition and [corrected] anxiety and small effects in depression in PWD. No significant effects were found on activities of daily living. They led to superior results compared to non-computer-based interventions in cognition. Further research is needed on cognitive recreation and cognitive stimulation. There is also a need for longer term [corrected] follow-up to examine the potential retention of treatment effects, and for the design of specific outcome measures.

Objectives: Information and communication technologies (ICT) developers, together with dementia experts have created several technological solutions to improve and facilitate social health and social participation and quality of life of older adults living with dementia. However, there is a need to carry out a systematic literature review that focuses on the validity and efficacy of these new technologies assessing their utility to promote 'social health' and 'active ageing' in people with dementia., Method: Searches in electronic databases identified 3824 articles of which 6 met the inclusion criteria and were coded according to their methodological approach, sample sizes, type of outcomes and results., Results: Six papers were identified reporting the use of 10 different interventions with people with dementia. Qualitative studies (four) showed a benefit of the use of technologies to foster social participation in people with dementia. At the same time, barriers to a widespread use of these technologies in this population were identified. A quantitative study and a mixed-method study with quantitative outcomes showed that ICT-based interventions promote more social behaviours than non-technology-based interventions., Conclusions: In the last years, several technological devices for living independently and fostering social health and social participation in people with dementia have been developed. However, specific outcome measures to assess social health and social participation are needed. Even though the analysed studies provided some evidence-base for the use of technology in this field, there is an urge to develop high quality studies and specific outcome measures.

Objectives: The reduction in cognitive decline depends on timely diagnosis. The aim of this systematic review was to analyze the current available information and communication technologies-based instruments for cognitive decline early screening and detection in terms of usability, validity, and reliability., Methods: Electronic searches identified 1,785 articles of which thirty-four met the inclusion criteria and were grouped according to their main purpose into test batteries, measures of isolated tasks, behavioral measures, and diagnostic tools., Results: Thirty one instruments were analyzed. Fifty-two percent were personal computer based, 26 percent tablet, 13 percent laptop, and 1 was mobile phone based. The most common input method was touchscreen (48 percent). The instruments were validated with a total of 4,307 participants: 2,146 were healthy older adults (M = 73.59; SD = 5.12), 1,104 had dementia (M = 74.65; SD = 3.98) and 1,057 mild cognitive impairment (M = 74.84; SD = 4.46). Only 6 percent were administered at home, 19 percent reported outcomes about usability, and 22 percent about understandability. The methodological quality of the studies was good, the weakest methodological area being usability. Most of the instruments obtained acceptable values of specificity and sensitivity., Conclusions: It is necessary to create home delivered instruments and to include usability studies in their design. Involvement of people with cognitive decline in all phases of the development process is of great importance to obtain valuable and user-friendly products. It would be advisable for researchers to make an effort to provide cutoff points for their instruments.

Background: The ability to recognize emotional expression is essential for social interactions, adapting to the environment, and quality of life. Emotion recognition is impaired in people with Alzheimer's disease (AD), thus rehabilitation of these skills has the potential to elicit significant benefits., Objective: This study sought to establish whether emotion recognition capacity could be rehabilitated in people with AD., Methods: Thirty-six participants with AD were assigned to one of three conditions: an experimental group (EG) that received 20 sessions of rehabilitation of emotion recognition and 20 sessions of cognitive stimulation therapy (CST), a control group (CG) that received 40 sessions of CST, and a treatment as usual group (TAU)., Results: A positive treatment effect favoring the EG was found; participants were better able to correctly identify emotions (p = 0.021), made fewer errors of commission (p = 0.002), had greater precision of processing (p = 0.021), and faster processing speed (p = 0.001). Specifically, the EG were better able to identify sadness (p = 0.016), disgust (p = 0.005), and the neutral expression (p = 0.014), with quicker processing speed for disgust (p = 0.002). These gains were maintained at one month follow-up with the exception of processing speed for surprise, which improved., Conclusion: Capacity to recognize facial expressions of emotions can be improved through specific rehabilitation in people with AD, and gains are still present at a one month follow up. These findings have implications for the design of rehabilitation techniques for people with AD that may lead to improved quality of life and social interactions for this population.

Introduction: In Spain, the number of elderly people is increasing, reason why the improvement in the attention given to the older adults has become a significant objective and requirement of health care systems. The physical activity is being recognized as a highly protective factor of the cognitive functions in aging, becoming a promising psycho-social strategy for the protection of the cognition in elderly population., Patients and Methods: PubMed, PsycINFO, Psicodoc, Scopus y SciELO sources were searched. We analyze the influence of the physical exercise in the prevention of the cognitive functions in healthy elderly and in the improvement or maintenance of the cognitive decline in older adults with early cognitive impairment. Thirty-one studies were selected and analysed., Results: These studies indicated that a greater amount of physical activity is related with a decrease of cognitive decline in aging., Conclusions: The physical activity constitutes a promising psychosocial strategy for older adults with and without cognitive impairment. More experimental studies and homogeneity in the assessment instruments are needed. A deeper study of the convenience in the frequency and intensity of the interventions is also required.

In the introduction the authors highlight the clinical theoretical and practical importance of affection disorders, especially depressive ones, during childhood and adolescence, their relationships of continuity and the limitations of psychopharmacological studies with antidepressants and other medicines. The authors review the bibliography consulted about the use of antidepressants in depressive disorders during adolescence following this order: authors and years, medicine used, type of population, number of cases, proportion of males and females, age ranges, dose in mg/kg/day, ranges of plasmatic concentrations, most frequent secondary and unwanted side effects, time of duration of the study, comorbidity, existence of a previous washing stage, as well as placebo and global results. The studies with triciclical antidepressants (TAD) are classified into open ones and controlled ones. Among the open ones, they review the studies by Dugas et al (1980), Geller et al (1985), Ryan et al (1986), Strober et al (1990), and Ambrosini et al (1994). Among the controlled ones, they review the studies by Kramer and Feiguine (1981), Geller et al (1990), Boulos et al (1991), and Kutcher et al (1994). In the third part, the studies of enhancement of TAD with lithium by Ryan et al (1988 a and b) and Strober et al (1992) are analysed. In the fourth part, the studies of enhancement of TAD with the IMAO by Ryan et al (1988-1990) are evaluated. In the fifth part, the ten studies with ISRS (fluvoxamine, fluoxetine, paroxetine and sertraline) on the treatment of depression during adolescence are also discussed. In the final comments there is a summary of the clinical perspective of this kind of psychopharmacological therapy. Four tables and 73 bibliographical references are included.

In the introduction the authors study some technical, methodological, ethical, administrative and marketing problems about the evaluation and investigation in child and adolescence psychopharmacology. They make a revision and critical evaluation about. As a whole the clinic use of antidepressive drugs in childhood psychiatry. Then, some open and controlled trial about tricyclic antidepressives are evaluated. After this, the authors present the most important advances about the open and controlled clinic trials with several antidepressives: tricyclic, tetracyclic, ISSR and MAO-Inhibitors and other drugs (placebo response, psychotherapy, imipramine, nortryptiline, amitriptyline, fluoxetine, MAO-Inhibitors, lithium, mianserin, maprotyline, etc.). Beside, placebo effect, response prediction factors, biologic markers, diagnostic criteria, evaluation methods and technics, drugs associations, clinic types of child depression, etc, are studied. In the last, the authors present some clinical conclusions about this subject.

Rett Syndrome was first described in 1966 by Andreas Rett. The disorder is characterized by a progressive loss of cognitive and motor skills as well as development o stereotyped hand movements, occurring after an apparently normal development. Authors present three typical cases, and, another one atypical, being all of them female. This study takes into account ten different areas about chronology, age and reasons in the first consultation, some milestones of psychomotor development, the diagnostic criteria--according to Rett Syndrome Diagnostic Criteria Work Group (R.S.D.C.W.G.), they consists of necessary, supportive and exclusion criteria-, some signs and symptoms that authors consider frequently associated with Rett syndrome, some diagnostic tests with neurophysiologic technics--E.E.G.--, as well as neuroimagins technics--C.T. and M.R.I.--; routine laboratory studies, development scales and something else, the DAS-SV scale which is usually used to study different handicaps and therapeutic interventions such as: psychosocial, clinical, pharmacological (valproic acid, carbamacepine, clorpromacine, etc.) and institutional. Three tables and 72 bibliographic notes are included.