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BACKGROUND: This study aimed to determine conditional dependence relationships of variables that contribute to psychological vulnerability associated with suicide risk. A Bayesian network (BN) was developed and applied to establish conditional dependence relationships among variables for each individual subject studied. These conditional dependencies represented the different states that patients could experience in relation to suicidal behavior (SB). The clinical sample included 650 mental health patients with mood and anxiety symptomatology. RESULTS: Mainly indicated that variables within the Bayesian network are part of each patient's state of psychological vulnerability and have the potential to impact such states and that these variables coexist and are relatively stable over time. These results have enabled us to offer a tool to detect states of psychological vulnerability associated with suicide risk. CONCLUSION: If we accept that suicidal behaviors (vulnerability, ideation, and suicidal attempts) exist in constant change and are unstable, we can investigate what individuals experience at specific moments to become better able to intervene in a timely manner to prevent such behaviors. Future testing of the tool developed in this study is needed, not only in specialized mental health environments but also in other environments with high rates of mental illness, such as primary healthcare facilities and educational institutions.

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Objective: To identify clinical and sociodemographic factors that increase or decrease suicidal risk in a clinical sample of subjects seeking mental health care. Method: A cross-sectional study was performed at three health centers in Santiago, Chile. The Parental Bonding Instrument (PBI), Depressive Experience Questionnaire (DEQ), Outcome Questionnaire (OQ-45.2), Reasons for Living Inventory (RFL), and State Trait Anger Expression Inventory (STAXI-2), in addition to a sociodemographic survey, were applied to 544 participants (333 with suicidal behavior and 211 without current suicidal behavior). Through hierarchical clustering analysis, participants were grouped by similarity regarding suicidal risk. Then, a regression analysis was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) technique, and factors that decrease or increase suicide risk (SR) were identified for each cluster. Results: The resultant clusters were grouped mainly by the age of participants. The most important protective factor was having confidence in one's own coping skills in difficult situations. Relevant risk factors were major depressive disorder (MDD), poor anger management, and difficulties in interpersonal relationships. Conclusions: Suicidal risk manifests differently throughout the life cycle, and different types of bonds may protect from or increase risk of suicide.

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OBJECTIVE: To identify clinical and sociodemographic factors that increase or decrease suicidal risk in a clinical sample of subjects seeking mental health care. METHOD: A cross-sectional study was performed at three health centers in Santiago, Chile. The Parental Bonding Instrument (PBI), Depressive Experience Questionnaire (DEQ), Outcome Questionnaire (OQ-45.2), Reasons for Living Inventory (RFL), and State Trait Anger Expression Inventory (STAXI-2), in addition to a sociodemographic survey, were applied to 544 participants (333 with suicidal behavior and 211 without current suicidal behavior). Through hierarchical clustering analysis, participants were grouped by similarity regarding suicidal risk. Then, a regression analysis was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) technique, and factors that decrease or increase suicide risk (SR) were identified for each cluster. RESULTS: The resultant clusters were grouped mainly by the age of participants. The most important protective factor was having confidence in one's own coping skills in difficult situations. Relevant risk factors were major depressive disorder (MDD), poor anger management, and difficulties in interpersonal relationships. CONCLUSIONS: Suicidal risk manifests differently throughout the life cycle, and different types of bonds may protect from or increase risk of suicide.

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Objective: To analyze suicidal behavior and build a predictive model for suicide risk using data mining (DM) analysis. Methods: A study of 707 Chilean mental health patients (with and without suicide risk) was carried out across three healthcare centers in the Metropolitan Region of Santiago, Chile. Three hundred forty-three variables were studied using five questionnaires. DM and machine-learning tools were used via the support vector machine technique. Results: The model selected 22 variables that, depending on the circumstances in which they all occur, define whether a person belongs in a suicide risk zone (accuracy = 0.78, sensitivity = 0.77, and specificity = 0.79). Being in a suicide risk zone means patients are more vulnerable to suicide attempts or are thinking about suicide. The interrelationship between these variables is highly nonlinear, and it is interesting to note the particular ways in which they are configured for each case. The model shows that the variables of a suicide risk zone are related to individual unrest, personal satisfaction, and reasons for living, particularly those related to beliefs in one’s own capacities and coping abilities. Conclusion: These variables can be used to create an assessment tool and enables us to identify individual risk and protective factors. This may also contribute to therapeutic intervention by strengthening feelings of personal well-being and reasons for staying alive. Our results prompted the design of a new clinical tool, which is fast and easy to use and aids in evaluating the trajectory of suicide risk at a given moment.

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AIM: In efforts to develop reliable methods to detect the likelihood of impending suicidal behaviors, we have proposed the following. OBJECTIVE: To gain a deeper understanding of the state of suicide risk by determining the combination of variables that distinguishes between groups with and without suicide risk. METHOD: A study involving 707 patients consulting for mental health issues in three health centers in Greater Santiago, Chile. Using 345 variables, an analysis was carried out with artificial intelligence tools, Cross Industry Standard Process for Data Mining processes, and decision tree techniques. The basic algorithm was top-down, and the most suitable division produced by the tree was selected by using the lowest Gini index as a criterion and by looping it until the condition of belonging to the group with suicidal behavior was fulfilled. RESULTS: Four trees distinguishing the groups were obtained, of which the elements of one were analyzed in greater detail, since this tree included both clinical and personality variables. This specific tree consists of six nodes without suicide risk and eight nodes with suicide risk (tree decision 01, accuracy 0.674, precision 0.652, recall 0.678, specificity 0.670, F measure 0.665, receiver operating characteristic (ROC) area under the curve (AUC) 73.35%; tree decision 02, accuracy 0.669, precision 0.642, recall 0.694, specificity 0.647, F measure 0.667, ROC AUC 68.91%; tree decision 03, accuracy 0.681, precision 0.675, recall 0.638, specificity 0.721, F measure, 0.656, ROC AUC 65.86%; tree decision 04, accuracy 0.714, precision 0.734, recall 0.628, specificity 0.792, F measure 0.677, ROC AUC 58.85%). CONCLUSION: This study defines the interactions among a group of variables associated with suicidal ideation and behavior. By using these variables, it may be possible to create a quick and easy-to-use tool. As such, psychotherapeutic interventions could be designed to mitigate the impact of these variables on the emotional state of individuals, thereby reducing eventual risk of suicide. Such interventions may reinforce psychological well-being, feelings of self-worth, and reasons for living, for each individual in certain groups of patients.

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OBJECTIVE:: To analyze suicidal behavior and build a predictive model for suicide risk using data mining (DM) analysis. METHODS:: A study of 707 Chilean mental health patients (with and without suicide risk) was carried out across three healthcare centers in the Metropolitan Region of Santiago, Chile. Three hundred forty-three variables were studied using five questionnaires. DM and machine-learning tools were used via the support vector machine technique. RESULTS:: The model selected 22 variables that, depending on the circumstances in which they all occur, define whether a person belongs in a suicide risk zone (accuracy = 0.78, sensitivity = 0.77, and specificity = 0.79). Being in a suicide risk zone means patients are more vulnerable to suicide attempts or are thinking about suicide. The interrelationship between these variables is highly nonlinear, and it is interesting to note the particular ways in which they are configured for each case. The model shows that the variables of a suicide risk zone are related to individual unrest, personal satisfaction, and reasons for living, particularly those related to beliefs in one's own capacities and coping abilities. CONCLUSION:: These variables can be used to create an assessment tool and enables us to identify individual risk and protective factors. This may also contribute to therapeutic intervention by strengthening feelings of personal well-being and reasons for staying alive. Our results prompted the design of a new clinical tool, which is fast and easy to use and aids in evaluating the trajectory of suicide risk at a given moment.

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Clients', therapists', and observers' identification of change was studied in 27 therapeutic processes, and agreement on the amount, temporal location, and content of change was related to outcome. Results show that clients reported more changes in successful therapies. Client-therapist temporal match of change moments was low irrespective of outcome. Results from all three perspectives were consistent in that manifestation of new behaviors and emotions was the most representative content of change among all therapies. Meanwhile, client-therapist agreement on the frequency of grouped change indicators reported was associated with positive outcome, whereas client-observer agreement was related to negative outcome. Therapists and observers agreed in both successful and nonsuccessful therapies. The relationship between agreement and therapeutic outcome is discussed in relation to each dimension of analysis.

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Drawing on the speech acts theory, a linguistic pattern was identified that could be expected to be associated to therapeutic change, characterized by being uttered in the first person singular and present indicative, and by being self-referential in its propositional content. The frequency of the pattern was examined among verbalizations defined as change moments in three therapies with different theoretical orientation. Results show that the majority of change moments have the specified pattern, and that this pattern is significantly more frequent in change moments than in random non-change-related verbalizations, and so, it does not pertain to therapeutic conversation in general. Implications are discussed concerning the possibility of using the linguistic pattern as an additional and complementary criterion in the identification of moments of change in the therapeutic process.

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In-session change episodes were studied in four psychotherapeutic processes: a brief psychodynamic, a psychodynamic-cognitive, a family social-constructionist, and a group integrative therapy. A qualitative confirmatory methodology was applied to assess observed and video-recorded sessions. The analysis instrument was a hierarchical list of generic qualitative indicators, common to different psychotherapeutic modalities, whose presence and content was determined through an intersubjective consent of the research group, therapists of different orientations. Results show that it is possible to identify change moments by observation; the contents of change, evident through the indicators, are generic; and, the change indicators identify the moment of evolution of the therapeutic process and the antiquity of the consultants, having a predictive value that is also of practical relevance.

Se estudiaron episodios de cambio en cuatro procesos de psicoterapia: psicoanalítica breve, psicoanalítico-cognitiva, familiar construccionista-social e integrativa de grupo. Se aplicó metodología cualitativa, confirmatoria, a sesiones observadas y grabadas en audio y video. El instrumento de análisis fue una jerarquía de indicadores de cambio genéricos, comunes a diferentes modalidades psicoterapéuticas, cuya presencia y contenido se determinó a partir del consenso intersubjetivo del grupo de investigadores-psicoterapeutas de formaciones teóricas distintas. Los resultados muestran que es posible identificar los momentos de cambio; los contenidos del cambio son efectivamente genéricos; y, los indicadores de cambio identifican el momento de evolución de las terapias y la antigüedad de los consultantes, pudiendo tener un valor predictivo que es de relevancia no sólo teórica, sino también práctica.

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El presente artículo es parte de una investigación de proceso terapéutico, orientada al descubrimiento de las interacciones que favorecen el cambio experimentado durante la psicoterapia. Específicamente, persigue la fundamentación teórica y metodológica para un análisis de la conversación terapéutica -a través de la teoría de los actos de habla- en episodios de cambio identificados previamente por medio del estudio de momentos de cambio. Para los efectos de este trabajo, interesa como unidad de análisis el acto de habla ilocutivo, conceptualizado como aquel que se realiza al decir algo. Su estructura contiene un indicador de función, fuerza ilocutiva y un indicador de contenido proposicional, recogiendo la performatividad, al conectar acción y lenguaje. Se describen las condiciones de performatividad en los episodios de cambio intra-sesión que, en el proceso psicoterapéutico y al alero de una teoría del cambio subjetivo, implican por parte del paciente y terapeuta un acuerdo ilocutivo a nivel de indicador de función, fuerza ilocutiva, y contenido proposicional.

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Existe un creciente interés por investigar los aspectos psicológicos y biográficos involucrados en la etiología y mantención del trastorno de pánico. Actualmente se considera que tales aspectos interactúan con las alteraciones neurofisiológicas, históricamente más estudiadas y conocidas en este trastorno. El presente estudio aborda la compresión del trastorno de pánico desde una perspectiva psicodinámica. Más específicamente se evaluaron las relaciones objetales en un grupo de pacientes antes y después de recibir tratamiento farmacológico. La primera evaluación fue realizada en 20 pacientes y 14 de ellos pudieron ser reevaluados tres años después. En ambas ocasiones se administró el Test de Relaciones Objetales de H. Phillipson. El análisis y la interpretación de los resultados del test se focalizó en el tipo de ansiedades y mecanismos de defensa presominantes. En relación a estas características psicológicas, se observó un alto grado de homogeneidad entre los pacientes, tanto antes como después del tratamiento. Se manifestaron alteraciones en las relaciones objetales, caracterizadas globalmente pro un predominio de angustia persecutoria y mecanismos de defensa primarios, entorno a la incisión. Se observaron diferencias significativas en relación a una mayor eficacia de los mecanismos de defensa y una disminución de la intensidad de la angustia, en la evalución de seguimiento. Se realizó una comaparación entre los pacientes con una respuesta al tratamiento farmacológico favorable y desfavorable. También se discuten las posibles implicaciones de estos hallazgos en la etiología, tratamiento y pronóstico del trastorno de pánico

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