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(M)eine kreative Kurzzeittherapie : Ein Selbsthilfe-, Entdeckungs- und Erfahrungsbuch / / Katrin Thomas
| (M)eine kreative Kurzzeittherapie : Ein Selbsthilfe-, Entdeckungs- und Erfahrungsbuch / / Katrin Thomas |
| Autore | Thomas Katrin |
| Pubbl/distr/stampa | Stuttgart, Germany : , : Ibidem Verlag, , [2021] |
| Descrizione fisica | 1 online resource (149 pages) |
| Disciplina | 016.36229 |
| Soggetto topico | Psychotherapy |
| ISBN | 3-8382-7491-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Nota di contenuto | Intro -- Einführung -- Meine Erfahrungen als Therapeutin und Klientin -- Krise als Chance -- Systemische Therapie: Eine Einführung -- Glaubenssätze, Affirmationen undsich selbsterfüllende Prophezeiungen -- Hausaufgaben -- Kreatives Zeichnen - Malen -- Fantasie, Intuition und Empathie nutzen -- Stammbaumarbeit -- Qigong und Psychotherapie - ein neuer Weg -- Und was nun? Ausklang -- Weiterführende Literatur. |
| Record Nr. | UNINA-9910794203003321 |
Thomas Katrin
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| Stuttgart, Germany : , : Ibidem Verlag, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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(M)eine kreative Kurzzeittherapie : Ein Selbsthilfe-, Entdeckungs- und Erfahrungsbuch / / Katrin Thomas
| (M)eine kreative Kurzzeittherapie : Ein Selbsthilfe-, Entdeckungs- und Erfahrungsbuch / / Katrin Thomas |
| Autore | Thomas Katrin |
| Pubbl/distr/stampa | Stuttgart, Germany : , : Ibidem Verlag, , [2021] |
| Descrizione fisica | 1 online resource (149 pages) |
| Disciplina | 016.36229 |
| Soggetto topico | Psychotherapy |
| ISBN | 3-8382-7491-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Nota di contenuto | Intro -- Einführung -- Meine Erfahrungen als Therapeutin und Klientin -- Krise als Chance -- Systemische Therapie: Eine Einführung -- Glaubenssätze, Affirmationen undsich selbsterfüllende Prophezeiungen -- Hausaufgaben -- Kreatives Zeichnen - Malen -- Fantasie, Intuition und Empathie nutzen -- Stammbaumarbeit -- Qigong und Psychotherapie - ein neuer Weg -- Und was nun? Ausklang -- Weiterführende Literatur. |
| Record Nr. | UNINA-9910811216803321 |
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Thomas Katrin
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| Stuttgart, Germany : , : Ibidem Verlag, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Implicaciones y Oportunidades de la Emergencia Sanitaria Por Covid-19 / / Maribel Espinosa-Castillo
| Implicaciones y Oportunidades de la Emergencia Sanitaria Por Covid-19 / / Maribel Espinosa-Castillo |
| Autore | Espinosa Castillo Maribel |
| Pubbl/distr/stampa | Madrid, Spain : , : Ediciones Díaz de Santos, , [2021] |
| Descrizione fisica | 1 online resource (135 pages) |
| Disciplina | 016.36229 |
| Soggetto topico | Epidemiology |
| ISBN | 84-9052-330-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | spa |
| Record Nr. | UNINA-9910795030803321 |
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Espinosa Castillo Maribel
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| Madrid, Spain : , : Ediciones Díaz de Santos, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Implicaciones y Oportunidades de la Emergencia Sanitaria Por Covid-19 / / Maribel Espinosa-Castillo
| Implicaciones y Oportunidades de la Emergencia Sanitaria Por Covid-19 / / Maribel Espinosa-Castillo |
| Autore | Espinosa Castillo Maribel |
| Pubbl/distr/stampa | Madrid, Spain : , : Ediciones Díaz de Santos, , [2021] |
| Descrizione fisica | 1 online resource (135 pages) |
| Disciplina | 016.36229 |
| Soggetto topico | Epidemiology |
| ISBN | 84-9052-330-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | spa |
| Record Nr. | UNINA-9910814642203321 |
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Espinosa Castillo Maribel
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| Madrid, Spain : , : Ediciones Díaz de Santos, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain
| Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain |
| Pubbl/distr/stampa | Cham, Switzerland : , : Birkhäuser, , [2022] |
| Descrizione fisica | 1 online resource (314 pages) |
| Disciplina | 016.36229 |
| Collana | Modeling and Simulation in Science, Engineering and Technology |
| Soggetto topico |
Epidemiology - Mathematical models
Epidèmies COVID-19 Models matemàtics |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-96562-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Modelling, Simulations, and Social Impact of Evolutionary Virus Pandemics -- 1 Aims and Plan of the Chapter -- 2 On the Contents of the Edited Book -- 3 Reasonings on Research Perspectives -- References -- Understanding COVID-19 Epidemics: A Multi-Scale ModelingApproach -- 1 Introduction -- 2 Mathematical Modeling Applied to Infectious Diseases: COVID-19 as a Case Study -- 2.1 The SIR and SHAR Models -- 2.2 The SHARUCD Modeling Framework -- 2.3 Modeling the Implementation of Control Measures -- 2.4 The Refined SHARUCD Model -- 2.4.1 Further Refinements: Detection Rate and Import -- 3 KTAP Modeling Framework -- 3.1 Modeling Contagion, Progression, and Recovery -- 3.2 Application of the KTAP Model to Selected Case Studies -- 3.2.1 Effect of Lockdown Measures and Restrictions Lifting -- 3.2.2 Effect of Heterogeneity -- 4 Discussion -- References -- Kinetic Modelling of Epidemic Dynamics: Social Contacts, Control with Uncertain Data, and Multiscale Spatial Dynamics -- 1 Introduction -- 2 Kinetic Modelling of Social Heterogeneity in Epidemic Dynamics -- 2.1 Modelling Contact Heterogeneity -- 2.1.1 Kinetic Model for Contact Formation -- 2.1.2 Quasi-Invariant Scaling and Steady States -- 2.1.3 The Macroscopic Social-SIR Dynamics -- 2.1.4 A Social-SIR Model with Saturated Incidence Rate -- 2.1.5 Extrapolation of the Shape of the Incidence Rate from Data -- 2.2 The Interplay Between Economy and the Pandemic -- 2.2.1 Wealth Exchanges in Epidemic Modelling -- 2.2.2 Fokker-Planck Scaling and Steady States -- 2.2.3 The Formation of Bimodal Wealth Distributions -- 2.2.4 The Increase of Wealth Inequalities -- 3 Social Control and Data Uncertainty -- 3.1 Control of Socially Structured Models -- 3.1.1 Optimal Control Formulation -- 3.1.2 Feedback Controlled Compartmental Models.
3.1.3 Containment in Homogeneous Social Mixing Dynamics -- 3.2 Dealing with Data Uncertainty -- 3.2.1 Feedback Controlled and Socially Structured Models with Uncertain Inputs -- 3.2.2 Application to the COVID-19 Outbreak -- 4 Multiscale Transport Models -- 4.1 Spatial Dynamics on Networks -- 4.1.1 1D Hyperbolic Compartmental Model -- 4.1.2 Macroscopic Formulation and Diffusion Limit -- 4.1.3 Extension to Multi-Compartmental Modelling -- 4.1.4 Network Modelling -- 4.1.5 Effect of Spatially Heterogeneous Environments in Hyperbolic and Parabolic Configuration -- 4.1.6 Application to the Emergence of COVID-19 in Italy -- 4.2 Realistic Geographical Settings -- 4.2.1 2D Kinetic Transport Model -- 4.2.2 Macroscopic Formulation and Diffusion Limit -- 4.2.3 Extension to Multi-Compartmental Modelling -- 4.2.4 Application to the Spatial Spread of COVID-19 in Italy in Emilia-Romagna and Lombardy Region -- 5 Concluding Remarks and Research Perspectives -- 5.1 Data sources -- References -- The COVID-19 Pandemic Evolution in Hawai`i and New Jersey: A Lesson on Infection Transmissibility and the Role of HumanBehavior -- 1 Introduction -- 2 Mathematical Models -- 2.1 Agent-Based Models -- 2.1.1 COVID-19 Agent-Based Simulator (Covasim) -- 2.2 Compartmental SEIR Models and Variants -- 2.3 Comparison of Agent-Based and Compartmental Models -- 3 Archipelagos and Islands -- 3.1 March 2020-June 2021 -- 3.1.1 CM Model Fit from March 06, 2020 to January 15, 2021 -- 3.1.2 Comparing CM and ABM Models -- 3.2 July 2021-September 2021 -- 3.3 Discussion -- 4 The Pandemic Waves in New Jersey -- 4.1 Comparing New Jersey to the US -- 4.2 Spatial and Temporal Patterns in COVID-19 Cases in New Jersey -- 4.3 Sociodemographic Variables -- 4.4 Discussion -- 5 The Use of Compartmental Models in New Jersey -- 5.1 Time-Evolution of the Basic Reproduction Number. 5.2 Infected Confirmed Cases, Hospitalizations, and Deaths -- 5.3 Discussion -- 6 Conclusion -- References -- A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process -- 1 Introduction -- 1.1 Hawkes Point Process Modeling of Infectious Diseases -- 1.2 Multivariate Hawkes Processes -- 1.3 Recursive Hawkes Processes -- 1.4 Outline -- 2 Theoretical Properties of Temporal Multivariate Recursive Hawkes Models -- 2.1 Existence -- 2.2 Mean -- 2.3 Variance -- 3 Parameter Fitting and Simulation Algorithms -- 3.1 Parameter Fitting Algorithms -- 3.1.1 Parametric (or Semi-parametric) Estimation -- 3.1.2 Temporal Version of Parameter Fitting Algorithms -- 3.2 Simulation Algorithm -- 4 Reconstruct Multivariate Point Process from Data with Imprecise Time -- 4.1 Time Reconstruction -- 4.2 Category Index Reconstruction -- 5 Numerical Experiments and Results -- 5.1 Synthetic Data Sets -- 5.1.1 Comparison Between Parametric Fitting and Non-parametric Fitting -- 5.1.2 Verification of the Parameter Fitting Algorithm -- 5.1.3 Experiments About Data Sets with Imprecise Time -- 5.2 Experiments on Real COVID-19 Data -- 5.2.1 Model Validation -- 5.2.2 Prediction Based on MRHP and Historical Information -- 6 Conclusion -- References -- Multiscale Aspects of Virus Dynamics -- 1 Introduction -- 1.1 On the Biology of the Virus -- 1.2 Modeling the Complexity of COVID-19 -- 2 Epistemic and Empirical Uncertainties in Compartmental and Individual-Based Models -- 2.1 SIR Model -- 2.2 Individual-Based Interpretation of λ -- 2.3 An Example of Modified SIR Model -- 2.4 Individuals Behind the Modified SIR Model -- 2.5 Time-Discretization -- 3 The Individual-Based Model of FlaLaFauciRiva -- 3.1 A Formula for the Parameter λ of Compartmental Models -- 3.2 Analysis of the Fluctuations -- 3.3 Simulations -- 3.4 Presence of Immunized Population and Virus Variants. Appendix -- References -- Productivity in Times of Covid-19: An Agent-Based Model Approach -- 1 Introduction -- 2 Model -- 3 Mean Field Approximation -- 4 Setting the Model Functions -- 5 Simulations -- 6 Conclusion -- References -- Transmission Dynamics and Quarantine Control of COVID-19 in Cluster Community -- 1 Introduction -- 2 Mathematical Modeling -- 2.1 Stage 1: SEIR-Type Model Without Quarantine -- 2.2 Stage 2: Transmission-Quarantine (TQ) Model -- 3 Analytic Results and Case Study for Emerging Stage -- 3.1 Analytic Results -- 3.2 A Real World Case Study for Stage 1 -- 4 Case Study and Sensitivity Analysis for Quarantine Stage -- 4.1 A Real World Study for Stage 2 -- 4.2 Sensitivity Analysis -- 5 Discussion -- Appendix: Proofs of Theorems -- References -- A 2D Kinetic Model for Crowd Dynamics with Disease Contagion -- 1 Introduction -- 2 A Simplified Two-Dimensional Kinetic Model -- 3 Discretization in Space and Time -- 4 Numerical Results -- 4.1 Tests with v = 0 -- 4.2 Tests with Prescribed Walking Velocity -- 5 A More Complex 2D Kinetic Model -- 6 Conclusions -- References -- Multiscale Derivation of a Time-Dependent SEIRD Reaction-Diffusion System for COVID-19 -- 1 Introduction -- 2 Phenomenological Modeling of Diffusion Population Dynamics -- 3 From Kinetic Theory Model to SEIRD Reaction-Diffusion System -- 3.1 Kinetic Theory Model -- 3.2 Micro-Macro Formulation -- 4 Numerical Method -- 4.1 Semi-Implicit Time Discretization -- 4.2 Fully Discrete Asymptotic Preserving Numerical Scheme in 1D -- 4.3 Boundary Conditions -- 5 Numerical Results -- 5.1 Test 1: Asymptotic Preserving Numerical Scheme Property -- 5.2 Test 2: Diffusion Effect -- 5.3 Test 3: Role of the Transmission Function -- 6 Conclusion and Perspectives -- References. |
| Record Nr. | UNISA-996490344003316 |
| Cham, Switzerland : , : Birkhäuser, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain
| Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain |
| Pubbl/distr/stampa | Cham, Switzerland : , : Birkhäuser, , [2022] |
| Descrizione fisica | 1 online resource (314 pages) |
| Disciplina | 016.36229 |
| Collana | Modeling and Simulation in Science, Engineering and Technology |
| Soggetto topico |
Epidemiology - Mathematical models
Epidèmies COVID-19 Models matemàtics |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-96562-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Modelling, Simulations, and Social Impact of Evolutionary Virus Pandemics -- 1 Aims and Plan of the Chapter -- 2 On the Contents of the Edited Book -- 3 Reasonings on Research Perspectives -- References -- Understanding COVID-19 Epidemics: A Multi-Scale ModelingApproach -- 1 Introduction -- 2 Mathematical Modeling Applied to Infectious Diseases: COVID-19 as a Case Study -- 2.1 The SIR and SHAR Models -- 2.2 The SHARUCD Modeling Framework -- 2.3 Modeling the Implementation of Control Measures -- 2.4 The Refined SHARUCD Model -- 2.4.1 Further Refinements: Detection Rate and Import -- 3 KTAP Modeling Framework -- 3.1 Modeling Contagion, Progression, and Recovery -- 3.2 Application of the KTAP Model to Selected Case Studies -- 3.2.1 Effect of Lockdown Measures and Restrictions Lifting -- 3.2.2 Effect of Heterogeneity -- 4 Discussion -- References -- Kinetic Modelling of Epidemic Dynamics: Social Contacts, Control with Uncertain Data, and Multiscale Spatial Dynamics -- 1 Introduction -- 2 Kinetic Modelling of Social Heterogeneity in Epidemic Dynamics -- 2.1 Modelling Contact Heterogeneity -- 2.1.1 Kinetic Model for Contact Formation -- 2.1.2 Quasi-Invariant Scaling and Steady States -- 2.1.3 The Macroscopic Social-SIR Dynamics -- 2.1.4 A Social-SIR Model with Saturated Incidence Rate -- 2.1.5 Extrapolation of the Shape of the Incidence Rate from Data -- 2.2 The Interplay Between Economy and the Pandemic -- 2.2.1 Wealth Exchanges in Epidemic Modelling -- 2.2.2 Fokker-Planck Scaling and Steady States -- 2.2.3 The Formation of Bimodal Wealth Distributions -- 2.2.4 The Increase of Wealth Inequalities -- 3 Social Control and Data Uncertainty -- 3.1 Control of Socially Structured Models -- 3.1.1 Optimal Control Formulation -- 3.1.2 Feedback Controlled Compartmental Models.
3.1.3 Containment in Homogeneous Social Mixing Dynamics -- 3.2 Dealing with Data Uncertainty -- 3.2.1 Feedback Controlled and Socially Structured Models with Uncertain Inputs -- 3.2.2 Application to the COVID-19 Outbreak -- 4 Multiscale Transport Models -- 4.1 Spatial Dynamics on Networks -- 4.1.1 1D Hyperbolic Compartmental Model -- 4.1.2 Macroscopic Formulation and Diffusion Limit -- 4.1.3 Extension to Multi-Compartmental Modelling -- 4.1.4 Network Modelling -- 4.1.5 Effect of Spatially Heterogeneous Environments in Hyperbolic and Parabolic Configuration -- 4.1.6 Application to the Emergence of COVID-19 in Italy -- 4.2 Realistic Geographical Settings -- 4.2.1 2D Kinetic Transport Model -- 4.2.2 Macroscopic Formulation and Diffusion Limit -- 4.2.3 Extension to Multi-Compartmental Modelling -- 4.2.4 Application to the Spatial Spread of COVID-19 in Italy in Emilia-Romagna and Lombardy Region -- 5 Concluding Remarks and Research Perspectives -- 5.1 Data sources -- References -- The COVID-19 Pandemic Evolution in Hawai`i and New Jersey: A Lesson on Infection Transmissibility and the Role of HumanBehavior -- 1 Introduction -- 2 Mathematical Models -- 2.1 Agent-Based Models -- 2.1.1 COVID-19 Agent-Based Simulator (Covasim) -- 2.2 Compartmental SEIR Models and Variants -- 2.3 Comparison of Agent-Based and Compartmental Models -- 3 Archipelagos and Islands -- 3.1 March 2020-June 2021 -- 3.1.1 CM Model Fit from March 06, 2020 to January 15, 2021 -- 3.1.2 Comparing CM and ABM Models -- 3.2 July 2021-September 2021 -- 3.3 Discussion -- 4 The Pandemic Waves in New Jersey -- 4.1 Comparing New Jersey to the US -- 4.2 Spatial and Temporal Patterns in COVID-19 Cases in New Jersey -- 4.3 Sociodemographic Variables -- 4.4 Discussion -- 5 The Use of Compartmental Models in New Jersey -- 5.1 Time-Evolution of the Basic Reproduction Number. 5.2 Infected Confirmed Cases, Hospitalizations, and Deaths -- 5.3 Discussion -- 6 Conclusion -- References -- A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process -- 1 Introduction -- 1.1 Hawkes Point Process Modeling of Infectious Diseases -- 1.2 Multivariate Hawkes Processes -- 1.3 Recursive Hawkes Processes -- 1.4 Outline -- 2 Theoretical Properties of Temporal Multivariate Recursive Hawkes Models -- 2.1 Existence -- 2.2 Mean -- 2.3 Variance -- 3 Parameter Fitting and Simulation Algorithms -- 3.1 Parameter Fitting Algorithms -- 3.1.1 Parametric (or Semi-parametric) Estimation -- 3.1.2 Temporal Version of Parameter Fitting Algorithms -- 3.2 Simulation Algorithm -- 4 Reconstruct Multivariate Point Process from Data with Imprecise Time -- 4.1 Time Reconstruction -- 4.2 Category Index Reconstruction -- 5 Numerical Experiments and Results -- 5.1 Synthetic Data Sets -- 5.1.1 Comparison Between Parametric Fitting and Non-parametric Fitting -- 5.1.2 Verification of the Parameter Fitting Algorithm -- 5.1.3 Experiments About Data Sets with Imprecise Time -- 5.2 Experiments on Real COVID-19 Data -- 5.2.1 Model Validation -- 5.2.2 Prediction Based on MRHP and Historical Information -- 6 Conclusion -- References -- Multiscale Aspects of Virus Dynamics -- 1 Introduction -- 1.1 On the Biology of the Virus -- 1.2 Modeling the Complexity of COVID-19 -- 2 Epistemic and Empirical Uncertainties in Compartmental and Individual-Based Models -- 2.1 SIR Model -- 2.2 Individual-Based Interpretation of λ -- 2.3 An Example of Modified SIR Model -- 2.4 Individuals Behind the Modified SIR Model -- 2.5 Time-Discretization -- 3 The Individual-Based Model of FlaLaFauciRiva -- 3.1 A Formula for the Parameter λ of Compartmental Models -- 3.2 Analysis of the Fluctuations -- 3.3 Simulations -- 3.4 Presence of Immunized Population and Virus Variants. Appendix -- References -- Productivity in Times of Covid-19: An Agent-Based Model Approach -- 1 Introduction -- 2 Model -- 3 Mean Field Approximation -- 4 Setting the Model Functions -- 5 Simulations -- 6 Conclusion -- References -- Transmission Dynamics and Quarantine Control of COVID-19 in Cluster Community -- 1 Introduction -- 2 Mathematical Modeling -- 2.1 Stage 1: SEIR-Type Model Without Quarantine -- 2.2 Stage 2: Transmission-Quarantine (TQ) Model -- 3 Analytic Results and Case Study for Emerging Stage -- 3.1 Analytic Results -- 3.2 A Real World Case Study for Stage 1 -- 4 Case Study and Sensitivity Analysis for Quarantine Stage -- 4.1 A Real World Study for Stage 2 -- 4.2 Sensitivity Analysis -- 5 Discussion -- Appendix: Proofs of Theorems -- References -- A 2D Kinetic Model for Crowd Dynamics with Disease Contagion -- 1 Introduction -- 2 A Simplified Two-Dimensional Kinetic Model -- 3 Discretization in Space and Time -- 4 Numerical Results -- 4.1 Tests with v = 0 -- 4.2 Tests with Prescribed Walking Velocity -- 5 A More Complex 2D Kinetic Model -- 6 Conclusions -- References -- Multiscale Derivation of a Time-Dependent SEIRD Reaction-Diffusion System for COVID-19 -- 1 Introduction -- 2 Phenomenological Modeling of Diffusion Population Dynamics -- 3 From Kinetic Theory Model to SEIRD Reaction-Diffusion System -- 3.1 Kinetic Theory Model -- 3.2 Micro-Macro Formulation -- 4 Numerical Method -- 4.1 Semi-Implicit Time Discretization -- 4.2 Fully Discrete Asymptotic Preserving Numerical Scheme in 1D -- 4.3 Boundary Conditions -- 5 Numerical Results -- 5.1 Test 1: Asymptotic Preserving Numerical Scheme Property -- 5.2 Test 2: Diffusion Effect -- 5.3 Test 3: Role of the Transmission Function -- 6 Conclusion and Perspectives -- References. |
| Record Nr. | UNINA-9910595039903321 |
| Cham, Switzerland : , : Birkhäuser, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Psychosis and personality disorders : unmet needs in early diagnosis and treatment / / edited by Paola Rocca and Silvio Bellino
| Psychosis and personality disorders : unmet needs in early diagnosis and treatment / / edited by Paola Rocca and Silvio Bellino |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (161 pages) |
| Disciplina | 016.36229 |
| Soggetto topico | Personality disorders |
| ISBN | 3-031-09058-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- 1: Trajectories Toward Bipolar Disorder or Schizophrenia in FEP and High-Risk Mental State -- 1.1 Introduction -- 1.2 Genetics -- 1.3 Cognitive Impairment -- 1.4 Neuroimaging -- 1.5 Prodromes -- 1.6 Conclusions -- References -- 2: New Strategies to Improve Cognitive Symptom Domain in the Treatment of Schizophrenia -- 2.1 Introduction -- 2.2 Pharmacological Treatment to Improve Cognitive Functioning in Schizophrenia -- 2.2.1 Cognitive Functioning in Schizophrenia: Focus on Treatment Management -- 2.2.2 Cognitive Functioning in Schizophrenia: Focus on Metabolic Profile -- 2.2.3 Cognitive Functioning in Schizophrenia: Focus on First- and Second-Generation Antipsychotics -- 2.2.4 Cognitive Functioning in Schizophrenia: Focus on Long-Acting Injectable (LAI) Antipsychotics -- 2.2.5 Cognitive Functioning in Schizophrenia: Focus on Antidepressants -- 2.2.6 Cognitive Functioning in Schizophrenia: Focus on New Pharmacological Targets -- 2.3 Non-pharmacological Interventions to Improve Cognitive Functioning in Schizophrenia: Focus on Cognitive Remediation -- 2.4 What Is Cognitive Remediation and How Does It Work? -- 2.5 Cognitive Remediation: Focus on Social and Nonsocial Cognition -- 2.5.1 Cognitive Remediation: Focus on Psychosocial Functioning -- 2.5.2 Cognitive Remediation: Focus on Clinical Symptoms -- 2.6 Conclusions and Future Directions -- References -- 3: Psychotic Disorders and Substance Abuse Comorbidity: Characteristics and Treatment -- 3.1 Introduction -- 3.2 Epidemiology -- 3.3 Psychosis and (Ab)use of Substances -- 3.3.1 Psychosis and Cannabis -- 3.3.2 Psychosis and (Met)Amphetamines -- 3.3.3 Psychosis and Alcohol -- 3.3.4 Psychosis and Tobacco -- 3.4 Mechanisms Underlying Comorbidity -- 3.4.1 Auto-Medication -- 3.4.2 Early Childhood Adversity.
3.4.3 Common Underlying Neurobiological Factors -- 3.5 Screening and Diagnosis on SUD -- 3.6 Treatment -- 3.6.1 General Aspects -- 3.6.2 Psychosocial Interventions -- 3.6.3 Pharmacological Aspects -- 3.6.3.1 Antipsychotic Medications -- 3.6.3.2 Medications Used for Substance Abuse Treatment -- Treatment of Alcohol Use Disorders -- Smoking -- Opiate Use Disorders -- 3.6.4 Organizational Aspects -- 3.7 Conclusions -- References -- 4: Recovery from Psychosis: Definition, Paradoxes, and Clinical Implications -- 4.1 Introduction -- 4.2 Historical Views of Outcome from Psychosis: The Rule and Alure of Pessimism -- 4.3 The Emergence of Recovery as the Expected Outcome from Psychosis -- 4.4 Two Emerging Challenges or Paradoxes from Research on Recovery from Psychosis -- 4.5 Metacognition and Paradoxes Posed by the Study of Recovery -- 4.6 General Implications for Recovery-Oriented Practice and Conclusions -- References -- 5: Cluster A Personality Disorders and Potential for Early Intervention in Psychosis: Challenges and Opportunities -- 5.1 Cluster A Personality Disorders (CAPD): Classification and Symptoms -- 5.2 Relationship between Cluster A Personality Disorders and Schizophrenia -- 5.3 Cluster A Personality Disorders and Clinically High-Risk States for Psychosis -- 5.4 Interventions for Treating Cluster A Personality Disorders -- 5.5 Pharmacological Interventions for Cluster A Personality Disorders -- 5.5.1 Non-pharmacological Interventions for Cluster A Personality Disorders -- 5.6 Challenges and Opportunities for Research and Treatment of Cluster A Personality Disorder -- 5.7 Conclusions -- References -- 6: Risk Factors of Early Onset of Borderline Personality Disorder: A Conceptual Model -- 6.1 Borderline Personality Disorder: A Complex Diagnosis -- 6.2 Environmental Factors -- 6.3 Temperament and Personality Traits. 6.4 Early Psychopathological Features -- 6.5 Brain Imaging Findings in Early-Onset BPD -- 6.6 Early Treatments -- 6.7 A Conceptual Model of Risk Factors for Early-Onset BPD -- References -- 7: Clinical Evaluation and Intervention of Emerging Psychosis: A Mentalization-Informed Perspective -- 7.1 SSPDs and Mentalizing: Is There a Connection? -- 7.2 Risk and Resilience in SSPD: A Developmental Account -- 7.2.1 Mentalizing in the Premorbid Period -- 7.2.2 Mentalizing in the CHR Period -- 7.3 Clinical Implications of an Integrative Mentalization-Informed Perspective on SSPDs -- 7.4 Conclusion -- References -- 8: Personality Disorders and Suicidality -- 8.1 Introduction -- 8.1.1 Personality Disorders and Suicidality -- 8.1.1.1 Developmental Trajectories of Self-injury Behaviors and Borderline Personality Disorders -- 8.1.1.2 Temperament and Character Correlates of Personality and Suicidality -- 8.1.2 Eysenck Personality Questionnaire -- 8.1.3 Temperament and Character Inventory -- 8.1.4 TEMPS-A -- 8.1.5 Shedler-Westen Assessment Procedure -- 8.1.6 The Big Five -- 8.2 Interpersonal Theory of Suicide -- 8.3 Conclusions -- References. |
| Record Nr. | UNINA-9910616371103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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