Look at Me: Early Gaze Engagement Enhances Corticospinal Excitability During Action Observation

Direct gaze is a powerful social cue able to capture the onlooker's attention. Beside gaze, head and limb movements as well can provide relevant sources of information for social interaction. This study investigated the joint role of direct gaze and hand gestures on onlookers corticospinal excitability (CE). In two experiments we manipulated the temporal and spatial aspects of observed gaze and hand behavior to assess their role in affecting motor preparation. To do this, transcranial magnetic stimulation (TMS) on the primary motor cortex (M1) coupled with electromyography (EMG) recording was used in two experiments. In the crucial manipulation, we showed to participants four video clips of an actor who initially displayed eye contact while starting a social request gesture, and then completed the action while directing his gaze toward a salient object for the interaction. This way, the observed gaze potentially expressed the intention to interact. Eye tracking data confirmed that gaze manipulation was effective in drawing observers' attention to the actor's hand gesture. In the attempt to reveal possible time-locked modulations, we tracked CE at the onset and offset of the request gesture. Neurophysiological results showed an early CE modulation when the actor was about to start the request gesture looking straight to the participants, compared to when his gaze was averted from the gesture. This effect was time-locked to the kinematics of the actor's arm movement. Overall, data from the two experiments seem to indicate that the joint contribution of direct gaze and precocious kinematic information, gained while a request gesture is on the verge of beginning, increases the subjective experience of involvement and allows observers to prepare for an appropriate social interaction. On the contrary, the separation of gaze cues and body kinematics can have adverse effects on social motor preparation. CE is highly susceptible to biological cues, such as averted gaze, which is able to automatically capture and divert observer's attention. This point to the existence of heuristics based on early action and gaze cues that would allow observers to interact appropriately

The Behavior-Driven Observation. Definition and development of an adaptive observational assessment

The observation in psychological assessment provides clinicians with a variety of useful insights about the symptoms of mental disorders. Nonetheless, the application of observational instruments has decreased during the last years, mainly due to their administration complexity and time consumption. A consequence of this general reduction in application is that some innovations fruitfully applied by other psychological assessment instruments, such as the self-reports, are still unexplored. For instance, little focus has been put on the possibility of implementing observational measures with adaptive algorithms. In observational assessment, these algorithms have been applied only by some software developed for observers training; their implementation in observational assessment instruments is still an open challenge. The aim of the present Ph.D. project is to develop an observational adaptive instrument able to help clinicians to generate accurate behavioral response patterns reducing, simultaneously, the time of the observational assessment. The definition of such an instrument has been a sequential process that started from a deep analysis of the items that should be observed, followed by the consideration of how to observe each of them. These first issues were accounted in Chapter 1, in which an overview of the literature was performed in order to examine all the features necessary to adequately conduct an observational assessment. A specific attention was dedicated on the possible biases that could affect raters, leading to higher probabilities of false positive and negatives on the observed behaviors. Finally, the state of the art relative to the application of adaptive algorithms in observational assessments was introduced and discussed. The second step toward the definition of the expected instrument consisted in defining a non adaptive checklist evaluating the behaviors of a mental disorder, possibly based on a formal methodology. In Chapter 2, the Formal Psychological Assessment (FPA) was introduced, describing its deterministic and probabilistic features. FPA is a methodology allowing to define assessment instruments starting from the relation between a set of items and a set of clinical issues of a disorder. In Chapter's end, it was shown how FPA could be extended also to observational assessment composed by multiple measures. In Chapter 3, the FPA was applied to develop the paper-and-pencil version of the final checklist. The negative symptomatology of schizophrenia was selected as the target mental disorder. A set of 138 items describing nonverbal behaviors was selected from instruments frequently used in the evaluation of schizophrenia. This list was then mapped to a list of 14 negative symptoms, selected in both scientific literature and DSM-5. The application of formal and logical steps provided by FPA led to a final checklist of 22 items, divided into two subscales, exhaustively investigating the 14 negative symptoms. In particular, it emerged how the mapping between items and investigated symptoms defined a deterministic model of assessment in which the clinician could be informed not only of which negative symptoms are evaluated by each item, but also of the relations among items. This model of assessment was later validated, in order to convert it into a probabilistic model that would have been correctly implemented into an adaptive instrument. In Chapter 4, the validation procedure is described. 172 videos of clinical interviews were observed by two independent raters, who filled the new checklist during one-zero sampling observations and generated modal response patterns for both subscales. Such patterns were used to apply the Basic local Independence Model (BLIM), a probabilistic model allowing to estimate the global fit indexes of the checklist and the false positive and negative rates for each item. Results showed adequate fit indexes for both subscales of the checklist with acceptable error rates for each item, which were extremely low especially in respect to false positive rates. The obtained probabilistic model of assessment and its parameters estimates were then used to calibrate an observational adaptive algorithm. In Chapter 5, the first version of the Behavior-Driven Observation (BDO) was introduced, namely the adaptive observational checklist proposed by the present project. After its formulation, the BDO was tested on real data by a simulation study in which both its accuracy and efficiency were examined. Results showed how the BDO algorithm was able to accurately reproduce almost all the non adaptive response patterns, with an average reduction by 38% of suggested items to complete the entire assessment. Finally, the accuracy and the efficiency of the BDO were tested during real observations, in order to understand if the BDO led to accurately replicate the non adaptive response patterns when used by human raters, with similar savings in terms of efficiency. Two independent trained raters observed twice the videos of twenty patients with a diagnosis of schizophrenia with negative symptoms, filling the two checklist's versions during observations. The observations on the same patient were far one week from each other. A very good intra-rater agreement emerged for each rater, suggesting both a good coherence over time of raters and a good ability of the BDO to replicate the response patterns of its non adaptive counterpart. Likewise, encouraging results were found in regard to BDO's efficiency: The savings in terms of suggested items were the same of the simulation study, for each rater; moreover, such savings corresponded to a reduction of the observational time. Taken together, the results of this Ph.D. project suggest that is possible to define an adaptive observational checklist able to help clinician to collect information not otherwise detectable with other assessment modalities. The BDO, in fact, could guide the observation by suggesting which behavior should be observed, taking into account the false positive/negative rates for each behavior. In this way, the accuracy of the final clinical output is increased as well as the efficiency of its generation. Such a clinical output could provide clinicians with a comprehensive set of information, such as the precise response pattern observed during the observation, the most plausible symptoms related to that response pattern and their probability values. All this information, in turn, can be finally integrated with other ones collected from different assessment instruments (e.g., interview, self-report), in order to have a broader frame of patient's condition and, maybe, set an individualized treatment

Gaze and Body Cues Interplay during Interactive Requests

Although observing other\u2019s gaze and body movements provides a crucial source of information to successfully interact with other people, it remains unclear whether observers weigh differently these cues and whether the convergence of gaze and body\u2019s directions determines facilitation effects. Here we aim to shed more light on this issue by testing the reliance upon these cues from both a behavioral and a neurophysiological perspective in a social interactive context. In Experiment 1, we manipulated the convergence between the direction of an actor\u2019s upper limb movement and gaze direction while he attempts to socially interact with the participants observing the scene. We determined the direction of gaze as well as the duration of participants\u2019 ocular fixations during the observation of the scene. In Experiment 2, we measured and correlated the effect of the body/gaze manipulation on corticospinal excitability and on the readiness to interact\u2014a disposition to engage in social situations. Eye-tracking data revealed that participants fixated chiefly the actor\u2019s head when his hand and gaze directions were divergent. Possibly a strategy to disambiguate the scene. Whereas participants mainly fixated the actor\u2019s hand when he performed an interactive request toward the participants. From a neurophysiological point of view, the more participants felt involved in the interaction, the lower was motor preparation in the muscle potentially needed to fulfill the actor\u2019s request. We contend that social contexts are more likely to elicit motor preparation compared to non-social ones, and that muscular inhibition is a necessary mechanism in order to prevent unwanted overt reactions during action observation tasks

The mediating role of scientifical-medical satisfaction between COVID-19 conspiracy beliefs and vaccine confidence: a two-waves structural equation model

Vaccine confidence has emerged as one of the most relevant psychological factors implied in the worldwide affecting the fight against COVID-19—as well as public trust in doctors, medicine, and science. Indeed, the vaccine confidence is crucial to maximize the trust in vaccines and their use for prevention, with several implications for public health. This study aimed to analyse the relationships among between vaccine confidence, conspiracy beliefs about COVID-19, and satisfaction with science and medicine in handling the COVID-19 pandemic. A longitudinal observational survey was administered to a convenience sample (n = 544; mean age 52.76 y.o., SD = 15.11; females 46.69%) from the Italian general population. A two-waves mediation model—a structural equation model technique—was used. The survey was part of a larger international project (https://osf.io/qy65b/). The model highlighted that the conspiracy beliefs about COVID-19 had a negative effect on the satisfaction with medicine and science (β = − 0.13, se = 0.03, p < .001). The latter, in turn, had a positive effect on vaccine confidence (β = 0.10, se = .05, p < .001). Interestingly, the effect of conspiracy beliefs on vaccine confidence was completely mediated by the scientifical-medical satisfaction (β = − 0.02, se = 0.01, p < .05). These results highlight how the scientifical-medical satisfaction can fully mediate the relationship between conspiracy beliefs about COVID-19 and vaccine confidence. These findings about vaccine hesitancy and confidence and disclose have implications for psychological and social interventions that could promote vaccine confidence by targeting the satisfaction with science and medicine

Predictors of stigma in a sample of mental health professionals: Network and moderator analysis on gender, years of experience, personality traits, and levels of burnout

Abstract Background. Stigma is one of the most important barriers to help-seeking and to personal recovery for people suffering from mental disorders. Stigmatizing attitudes are present among mental health professionals with negative effects on the quality of health care. Methods. Network and moderator analysis were used to identify what path determines stigma, considering demographic and professional variables, personality traits, and burnout dimensions in a sample of mental health professionals (n = 318) from six Community Mental Health Services. The survey included the Attribution Questionnaire-9, the Maslach Burnout Inventory, and the Ten-Item Personality Inventory. Results. The personality trait of openness to new experiences resulted to determine lower levels of stigma. Burnout (personal accomplishment) interacted with emotional stability in predicting stigma, and specifically, for subjects with lower emotional stability lower levels of personal accomplishment were associated with higher levels of stigma. Conclusions. Some personality traits may be accompanied by better empathic and communication skills, and may have a protective role against stigma. Moreover, burnout can increase stigma, in particular in subjects with specific personality traits. Assessing personality and burnout levels could help in identifying mental health professionals at higher risk of developing stigma. Future studies should determine whether targeted interventions in mental health professionals at risk of developing stigma may be effective in stigma prevention

Exercise addiction in athletes: Comparing two assessment instruments and willingness to stop exercise after medical advice

Exercise is overwhelmingly beneficial for physical and mental health, but for some people exercise addiction (EA) can develop and negatively impact an individual. This study sought to (a) compare the latent structure of two instruments assessing EA and (b) examine differences in attitudes toward stopping exercise, if required to on medical grounds, among exercise-addicted and non-addicted athletes. In a cross-sectional study, 1,011 athletes competing at different levels completed an anonymous on-line survey. The survey contained Exercise Dependence Scale-Revised (EDS-R), Exercise Addiction Inventory (EAI), and questions on adherence to medical prescriptions to stop exercise. We tested the latent structure of EDS-R and EAI with multigroup confirmatory factor analyses (CFA), across gender and competition level. Finally, we measured the difference of athletes' attitudes toward stopping exercise, if prescribed by a physician. Both instruments showed good fit indexes, even across gender. CFAs on EAI scores showed some violations of measurement invariance across competition level (ΔCFI = .03; ΔRMSEA = .02). On the contrary, CFAs on EDS-R scores did not show invariance violations across competition level (ΔCFI = <.01; ΔRMSEA = <.01). Finally, athletes who reached thresholds for exercise addiction, by means of EDS-R, were more prone to not follow medical prescriptions to cease exercise, independently of the competition level. These results suggest that athletes' answers on the EDS-R seem to be less affected by competition level, compared to EAI. Moreover, EDS-R outcomes could be used to identify individuals who may be unlikely to cease exercise for medical reasons, independently of their competition level

The Italian COVID-19 Psychological Research Consortium (IT C19PRC): General Overview and Replication of the UK Study

The COVID-19 pandemic represents a major stressor for the psychological health of people worldwide. In the UK, the COVID19-Psychological Research Consortium Study (C19PRC) launched to evaluate the psychological impact of COVID-19 in the general population and its implications. The project was then extended to Italy and several other countries. This article provides an overview of the Italian C19PRC study and its replication of two specific findings from the UK C19PRC. In the first part, the relationship between anxiety and somatic symptomatology is examined. In the second part, we analyze the association between several factors and psychological health outcomes: depression/anxiety, traumatic stress, COVID-19 anxiety. In line with the study conducted in the UK, an online survey was administered to the adult Italian general population. The sample included 1038 respondents (age, mean = 49.94, SD = 16.14, 51.15% females) taken from four regions: Lombardia, Veneto, Lazio, and Campania. The relationship between predictors and outcomes was evaluated by means of logistic regression models. Somatic indices showed a positive association with anxiety, worse somatic symptoms were associated with mourning a loss of a beloved one due to COVID-19 and with precarious health conditions. Females showed a higher incidence of psychological issues. No differences in anxiety, depression, and traumatic stress were found across regions but the Campania region showed the most severe somatic symptomatology. In the second analysis, the factors associated with more severe psychological outcomes (i.e., anxiety and/or depression, traumatic stress, and COVID-19 related anxiety) were younger age, the presence of minors in the household, traumatic stressors, and precarious health conditions. No differences across regions emerged. The Italian results correspond to the UK findings for anxiety, depression, and traumatic stress. Both in the UK and Italy, the factors associated with worse psychological health were gender (female), younger age, having children, pre-existing health issues (both for oneself or someone close), and the moderate/high perceived risk of contracting COVID-19 within one month. In Italy, unlike the UK, lower household income and having (had) COVID-19 were not associated with poorer mental health. The psychological impact of COVID-19 can last for months; future research should explore all aspects of the psychological burden of COVID-19 in order to implement psychological interventions and promote psychological health

Assessing the quality of studies in meta-research: review/guidelines on the most important quality assessment tools

Systematic reviews and meta‐analyses pool data from individual studies to generate a higher level of evidence to be evaluated by guidelines. These reviews ultimately guide clinicians and stakeholders in health‐related decisions. However, the informativeness and quality of evidence synthesis inherently depend on the quality of what has been pooled into meta‐research projects. Moreover, beyond the quality of included individual studies, only a methodologically correct process, in relation to systematic reviews and meta‐analyses themselves, can produce a reliable and valid evidence synthesis. Hence, quality of meta‐research projects also affects evidence synthesis reliability. In this overview, the authors provide a synthesis of advantages and disadvantages and main characteristics of some of the most frequently used tools to assess quality of individual studies, systematic reviews, and meta‐analyses. Specifically, the tools considered in this work are the Newcastle‐Ottawa scale (NOS) and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for observational studies, the Consolidated Standards of Reporting Trials (CONSORT), the Jadad scale, the Cochrane risk of bias tool 2 (RoB2) for randomized controlled trials, the Preferred Reporting Items for Systematic Reviews and Meta‐analysis (PRISMA) and the Assessment of Multiple Systematic Reviews 2 (AMSTAR2), and AMSTAR‐PLUS for meta‐analyses

The network structure of psychopathological and resilient responses to the pandemic: A multicountry general population study of depression and anxiety

Commonly identified patterns of psychological distress in response to adverse events are characterized by resilience (i.e., little to no distress), delayed (i.e., distress that increases over time), recovery (i.e., distress followed by a gradual decrease over time), and sustained (i.e., distress remaining stable over time). This study aimed to examine these response patterns during the COVID-19 pandemic. Anxiety and depressive symptom data collected across four European countries over the first year of the pandemic were analyzed (N = 3,594). Participants were first categorized into groups based on the four described patterns. Network connectivity and symptom clustering were then estimated for each group and compared. Two thirds (63.6%) of the sample displayed a resilience pattern. The sustained distress network (16.3%) showed higher connectivity than the recovery network (10.0%) group, p = .031; however, the resilient network showed higher connectivity than the delayed network (10.1%) group, p = .016. Regarding symptom clustering, more clusters emerged in the recovery network (i.e., three) than the sustained network (i.e., two). These results replicate findings that resilience was the most common mental health pattern over the first pandemic year. Moreover, they suggest that high network connectivity may be indicative of a stable mental health response over time, whereas fewer clusters may be indicative of a sustained distress pattern. Although exploratory, the network perspective provides a useful tool for examining the complexity of psychological responses to adverse events and, if replicated, could be useful in identifying indicators of protection against or vulnerability to future psychological distress

The Behavior-Driven Observation. Definition and development of an adaptive observational assessment

The observation in psychological assessment provides clinicians with a variety of useful insights about the symptoms of mental disorders. Nonetheless, the application of observational instruments has decreased during the last years, mainly due to their administration complexity and time consumption. A consequence of this general reduction in application is that some innovations fruitfully applied by other psychological assessment instruments, such as the self-reports, are still unexplored. For instance, little focus has been put on the possibility of implementing observational measures with adaptive algorithms. In observational assessment, these algorithms have been applied only by some software developed for observers training; their implementation in observational assessment instruments is still an open challenge. The aim of the present Ph.D. project is to develop an observational adaptive instrument able to help clinicians to generate accurate behavioral response patterns reducing, simultaneously, the time of the observational assessment. The definition of such an instrument has been a sequential process that started from a deep analysis of the items that should be observed, followed by the consideration of how to observe each of them. These first issues were accounted in Chapter 1, in which an overview of the literature was performed in order to examine all the features necessary to adequately conduct an observational assessment. A specific attention was dedicated on the possible biases that could affect raters, leading to higher probabilities of false positive and negatives on the observed behaviors. Finally, the state of the art relative to the application of adaptive algorithms in observational assessments was introduced and discussed. The second step toward the definition of the expected instrument consisted in defining a non adaptive checklist evaluating the behaviors of a mental disorder, possibly based on a formal methodology. In Chapter 2, the Formal Psychological Assessment (FPA) was introduced, describing its deterministic and probabilistic features. FPA is a methodology allowing to define assessment instruments starting from the relation between a set of items and a set of clinical issues of a disorder. In Chapter's end, it was shown how FPA could be extended also to observational assessment composed by multiple measures. In Chapter 3, the FPA was applied to develop the paper-and-pencil version of the final checklist. The negative symptomatology of schizophrenia was selected as the target mental disorder. A set of 138 items describing nonverbal behaviors was selected from instruments frequently used in the evaluation of schizophrenia. This list was then mapped to a list of 14 negative symptoms, selected in both scientific literature and DSM-5. The application of formal and logical steps provided by FPA led to a final checklist of 22 items, divided into two subscales, exhaustively investigating the 14 negative symptoms. In particular, it emerged how the mapping between items and investigated symptoms defined a deterministic model of assessment in which the clinician could be informed not only of which negative symptoms are evaluated by each item, but also of the relations among items. This model of assessment was later validated, in order to convert it into a probabilistic model that would have been correctly implemented into an adaptive instrument. In Chapter 4, the validation procedure is described. 172 videos of clinical interviews were observed by two independent raters, who filled the new checklist during one-zero sampling observations and generated modal response patterns for both subscales. Such patterns were used to apply the Basic local Independence Model (BLIM), a probabilistic model allowing to estimate the global fit indexes of the checklist and the false positive and negative rates for each item. Results showed adequate fit indexes for both subscales of the checklist with acceptable error rates for each item, which were extremely low especially in respect to false positive rates. The obtained probabilistic model of assessment and its parameters estimates were then used to calibrate an observational adaptive algorithm. In Chapter 5, the first version of the Behavior-Driven Observation (BDO) was introduced, namely the adaptive observational checklist proposed by the present project. After its formulation, the BDO was tested on real data by a simulation study in which both its accuracy and efficiency were examined. Results showed how the BDO algorithm was able to accurately reproduce almost all the non adaptive response patterns, with an average reduction by 38% of suggested items to complete the entire assessment. Finally, the accuracy and the efficiency of the BDO were tested during real observations, in order to understand if the BDO led to accurately replicate the non adaptive response patterns when used by human raters, with similar savings in terms of efficiency. Two independent trained raters observed twice the videos of twenty patients with a diagnosis of schizophrenia with negative symptoms, filling the two checklist's versions during observations. The observations on the same patient were far one week from each other. A very good intra-rater agreement emerged for each rater, suggesting both a good coherence over time of raters and a good ability of the BDO to replicate the response patterns of its non adaptive counterpart. Likewise, encouraging results were found in regard to BDO's efficiency: The savings in terms of suggested items were the same of the simulation study, for each rater; moreover, such savings corresponded to a reduction of the observational time. Taken together, the results of this Ph.D. project suggest that is possible to define an adaptive observational checklist able to help clinician to collect information not otherwise detectable with other assessment modalities. The BDO, in fact, could guide the observation by suggesting which behavior should be observed, taking into account the false positive/negative rates for each behavior. In this way, the accuracy of the final clinical output is increased as well as the efficiency of its generation. Such a clinical output could provide clinicians with a comprehensive set of information, such as the precise response pattern observed during the observation, the most plausible symptoms related to that response pattern and their probability values. All this information, in turn, can be finally integrated with other ones collected from different assessment instruments (e.g., interview, self-report), in order to have a broader frame of patient's condition and, maybe, set an individualized treatment.L’osservazione in psicologia può fornire al clinico molte informazioni utili riguardo i sintomi di una specifica psicopatologia. Tuttavia, l’utilizzo di strumenti osservativi sembra essere diminuito negli ultimi anni, sia a causa della loro complessità di somministrazione, sia per il tempo di compilazione che questi strumenti richiedono. Una conseguenza di questo diminuito utilizzo è l’impossibilità di raggiungere alcune innovazioni che sono state ottenute con altri strumenti psicodiagnostici, come nel caso dei self-report. Per esempio, la possibilità di implementare gli strumenti osservativi con algoritmi adattivi è tuttora inesplorata. Il presente progetto di dottorato si propone lo scopo di sviluppare uno strumento osservazionale computerizzato e adattivo che sia in grado di fornire ai clinici dei pattern comportamentali accurati in tempi ragionevolmente ridotti. La definizione di tale strumento può essere intesa come una procedura sequenziale che inizia da una profonda analisi su quali comportamenti osservare e su come osservarli. Nel Capitolo 1 si propone una disamina della letteratura concernente l’osservazione, concentrandosi su tutte le caratteristiche necessarie per definire e successivamente condurre un’adeguata osservazione. Particolare attenzione viene posta sui possibili biases che possono incorrere negli osservatori, portandoli a commettere dei falsi positivi e negativi su ciò che osservano. Infine, si prende in esame lo stato dell’arte relativo all’applicazione di algoritmi adattivi nell’assessment osservativo. Il secondo step verso la definizione dello strumento proposto consiste nel definire una checklist non adattiva che valuti i comportamenti di una determinata psicopatologia, possibilmente costruita su una metodologia formale. A tal fine, nel Capitolo 2 viene introdotto il Formal Psychological Assessment nei suoi aspetti deterministici e probabilistici. L’FPA è una metodologia formale in grado aiutare i ricercatori a definire strumenti di valutazione a partire dalle relazioni tra insiemi di item appartenenti a strumenti di valutazione e sintomi di psicopatologie. Nella parte finale del capitolo, viene discusso come sia possibile applicare l’FPA anche negli assessment osservativi caratterizzati da osservazioni multiple. Nel Capitolo 3, l’FPA viene applicato per definire una versione finale e non adattiva della checklist che possa valutare il comportamento non verbale relativo ai sintomi negativi della schizofrenia. Punto di partenza è una lista di 138 items che descrivono comportamenti non verbali, estratta da strumenti di valutazione spesso utilizzati con pazienti presentano sintomi psicotici. Tale lista è stata associata ad una lista di 14 sintomi negativi, selezionati dalla letteratura scientifica sul tema e dal DSM-5. Attraverso una serie di passaggi formali, è stata poi definita una lista finale di 22 item (suddivisi in due sottoscale) indaganti tutti i 14 sintomi negativi. L’associazione tra item e sintomi ha permesso di definire un modello di valutazione deterministico attraverso cui il clinico possa studiare non solo quali sintomi negativi sono indagati da ciascun item, ma anche quali sono le relazioni tra gli item stessi. Nel Capitolo 4 viene descritta la procedura di validazione della nuova checklist. 172 video contenenti interviste cliniche sono stati osservati da due valutatori indipendenti, che hanno compilato la checklist durante osservazioni multiple. I pattern di risposta modali generati da ogni serie di osservazioni multiple per ogni paziente sono poi stati testati con il Basic Loca Independence Model, un modello probabilistico che permette di stimare il fit globale di uno strumento ai dati e i parametri di errore per ogni item che lo compongono. I risultati hanno mostrato un fit adeguato per ognuna delle due sottoscale della checkilist, con parametri di errore bassi o medi per tutti gli item. I parametri di errore sono stati poi utilizzati per implementare la versione adattiva della checklist. Nel capitolo 5, infatti, vene introdotta la Behavior-Driven Observation (BDO), ossia la checklist computerizzata adattiva proposta in questo progetto di dottorato. Dopo una dettagliata spiegazione degli elementi che la compongono, la BDO viene testata attraverso uno studio di simulazione: in particolare, i pattern di risposta modali utilizzati per validare la checklist non adattiva sono stati simulati dall’algoritmo che sottende la BDO, al fine di testare sia la sua efficacia che la sia efficienza. I risultati hanno mostrato come l’algoritmo sia stato in grado di riprodurre la quasi totalità dei pattern di risposta non adattivi, completando l’assessment suggerendo il 38% di comportamenti in meno. Infine, la BDO è stata testata anche durante osservazioni dal vivo, al fine di comprendere se possa accuratamente replicare pattern di risposta non adattivi anche con valutatori umani. A tal fine, due valutatori indipendenti hanno osservato per due volte i video di 20 pazienti con diagnosi di schizofrenia, compilando sia BDO anche nella sua versione non adattiva. Le osservazioni su ogni paziente erano distanti una settimana. Un buon accordo interno è emerso per entrambi i valutatori, i quali hanno mostrato una buona coerenza interna nel tempo. Tale risultato ha mostrato, inoltre, come la BDO sia in grado di ottenere risultati comparabili alla sua versione non adattiva anche durante osservazioni reali e non simulate. Risultati incoraggianti sono emersi anche in termini di efficienza: il risparmio di item suggeriti dalla procedura si è rivelato essere il medesimo di quello ottenuto nello studio di simulazione, collegato ad una riduzione del tempo di valutazione. In conclusione, i risultati di questo progetto di dottorato suggeriscono come sia possibile sviluppare una checklist osservazionale adattiva, che possa aiutare i clinici nel collezionare informazioni che non possono essere collezionate mediante altri strumenti di valutazione. La BDO, infatti, potrebbe guidare il clinico, suggerendo quale comportamento osservare. Tale suggerimento risulterebbe essere molto accurato, dal momento che il rischio di commettere un errore su ogni item viene già calcolato dall’algoritmo che sottende la BDO. In questo modo, è possibile avere una consistente accuratezza sull’output clinico finale, generato anche in modo efficiente. Questo output clinico non consisterebbe in un punteggio meramente numerico, ma conterrebbe diverse informazioni, come l’intero pattern di risposta del paziente, l’insieme di sintomi più plausibile dato quel pattern ed, in aggiunta, le probabilità di osservare tali sintomi. Tutte queste informazioni, a loro volta, possono essere integrate con quelle raccolte mediante altre modalità di assessment (interviste, self-report) al fine di ottenere un quadro più ampio della condizione del paziente. In questo modo, si potrà definire un piano terapeutico individualizzato che tratti in maniera mirata quei sintomi, migliorando il processo di cura e riducendo, nel contempo, i costi dello stesso