Implicit measurement at the service of mental health: assessment and intervention as the two sides of the same coin

Scientific research in psychology is intrinsically bound to the measurement of variables that are per nature highly complex, changeable, and most often unobservable. The design of measurement methods is mostly focused on the attempt to capture the main features of the psychological attribute of interest. The last fifteen years have seen a massive development and use of a new set of measurement instruments that go under the name of implicit measures, which accomplishes the primary goal of indexing psychological attributes interchangeably defined as automatic, uncontrollable, unconscious, impulsive, or implicit. The primary goal of the present work was to explore the implicitness feature of implicit measures and their functioning. The research covered the experimentation of several implicit measures in two different contexts within the broader domain of mental health: the automatic components of stigmatizing attitudes and behaviours towards people affected by a mental disease (Part 1) and the impulsive, automatic processes implied within people affected by a mental disease, more specifically, by an alcohol addiction disorder (Part 2). Part 1 of this dissertation is concerned with the design of two Implicit Association Tests targeting two aspects of mental illness stigma, namely, aetiological beliefs and prejudicial attitudes. The main objectives were to verify whether these two measures could be used as assessment techniques in this particular framework and to explore the plausible existence of implicit complements of mental illness stigma. Part 2 doubled the perspective of this research by experimenting implicit measurement techniques as means for change by adapting them to retrain the implicit processes they were initially designed to assess. The study took the form of a Randomised Clinical Trial with alcohol addict outpatients in which the combination of two training paradigms targeting maladaptive impulsive processes towards alcohol (i.e., attentional bias and approach bias) is examined. In both studies, the measurement properties of the implicit measures developed and their meaning in relation to the theoretical to-be-measured psychological attributes have been explored within a Rasch modelling perspective, through the application of the Many-Facet Rasch Measurement (MFRM) model. In Part 1, the MFRM model allowed disentangling the different ‘ingredients’ contributing to the emergence of the IATs effect and highlighting how implicit aetiological beliefs and evaluative associations with mental illness are multifaceted aspects. Semantic and evaluative implicit associations with mental illness resulted to be dependent on diagnostic categories and differently determined by biologic semantic associations and by a positive association primacy, respectively. Further, the MFRM evidenced the functioning of the IAT at the microscopic level. In Part 2, analysis of data of a group of participants at pre- and post-intervention assessment sessions evidenced the first promising results of the RCT: although participants did not show a substantial change in their alcohol attentional and approach bias measures, the MFRM showed a changing process in action. Experimental conditions showed to have a differential effect in bringing in a decrease and/or a reversal of the two cognitive biases. The MFRM contributed to the exploration of the dimensional and theoretical status of the two cognitive bias implicit measures and provided informative clues about their general and domain- specific features. Further, the MFRM retrieved first evidence about a differential effect of the stimuli used in improving control processes over the impulsive reactions towards alcohol. The intertwined elements of this work, namely, implicit measurement, mental health, and Rasch modelling, have been combined in the attempt not only to clarify the benefits of implicit methods in psychology, but also to unravel what it actually means to use implicit measures. The combination with a rigorous modelling approach indeed demonstrated both the limitations and the strength of this new family of instruments

Etiological beliefs, treatments, stigmatizing attitudes toward schizophrenia. What do Italians and Israelis think?

Background: Although scientific research on the etiology of mental disorders has improved the knowledge of biogenetic and psychosocial aspects related to the onset of mental illness, stigmatizing attitudes and behaviors are still very prevalent and pose a significant social problem. Aim: The aim of this study was to deepen the knowledge of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics, such as culture and religion of the perceiver. More precisely, the main purpose is the definition of a structure of variables, namely perceived dangerousness, social closeness, and avoidance of the ill person, together with the beliefs about the best treatment to be undertaken and the sick person' gender, capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned. Method: The study involved 305 university students, 183 from the University of Padua, Italy, and 122 from the University of Haifa, Israel. For the analyses, a latent class analysis (LCA) approach was chosen to identify a latent categorical structure accounting for the covariance between the observed variables. Such a latent structure was expected to be moderated by cultural background (Italy versus Israel) and religious beliefs, whereas causal beliefs, recommended treatment, dangerousness, social closeness, and public avoidance were the manifest variables, namely the observed indicators of the latent variable. Results: Two sets of results were obtained. First, the relevance of the manifest variables as indicators of the hypothesized latent variable was highlighted. Second, a two-latent-class categorical dimension represented by prejudicial attitudes, causal beliefs, and treatments concerning schizophrenia was found. Specifically, the differential effects of the two cultures and the religious beliefs on the latent structure and their relations highlighted the relevance of the observed variables as indicators of the expected latent variable. Conclusion: The present study contributes to the improvement of the understanding of how attitudes toward people with mental illness are affected by specific personal beliefs and characteristics of the perceiver. The definition of a structure of variables capable of describing the complexity of the stigma construct in particular as far as schizophrenia is concerned was achieved from a cross-cultural perspective

What's in a Trial? On the Importance of Distinguishing Between Experimental Lab Studies and Randomized Controlled Trials: The Case of Cognitive Bias Modification and Alcohol Use Disorders

OBJECTIVE: Recently, the National Institutes of Health (NIH) redefined clinical trials to include any study involving behavioral or biomedical interventions. In line with a general framework from experimental medicine, we argue that it is crucial to distinguish between experimental laboratory studies aimed at revealing psychological mechanisms underlying behavior and randomized controlled trials (RCTs) in clinical samples aimed at testing the efficacy of an intervention. METHOD: As an illustration, we reviewed the current state of the evidence on the efficacy of cognitive bias modification (CBM) interventions in alcohol use disorders. RESULTS: A recent meta-analysis "cast serious doubts on the clinical utility of CBM interventions for addiction." That analysis combined experimental laboratory studies and RCTs. We demonstrated that, when studies are differentiated regarding study type (experimental laboratory study or RCT), mode of delivery (controlled experiment or Internet), and population (healthy volunteers or patients), the following effects are found: (a) short-lived effects of CBM on drinking behavior in experimental laboratory studies in students, but only when the bias is successfully manipulated; (b) small but robust effects of CBM on treatment outcome when administered as an adjunct to established treatments in clinical settings in RCTs with alcohol-dependent patients; and (c) nonspecific effects (reduced drinking irrespective of condition) in RCTs of CBM administered online to problem drinkers. CONCLUSIONS: We discuss how CBM might be improved when it is better integrated into regular treatment, especially cognitive behavioral therapy, and we conclude that disregarding the difference between experimental laboratory studies and RCTs can lead to invalid conclusions

Combining web-based attentional bias modification and approach bias modification as a self-help smoking intervention for adult smokers seeking online help: Double-blind randomized controlled trial

Background: Automatically activated cognitive motivational processes such as the tendency to attend to or approach smoking-related stimuli (ie, attentional and approach bias) have been related to smoking behaviors. Therefore, these cognitive biases are thought to play a role in maintaining smoking behaviors. Cognitive biases can be modified with cognitive bias modification (CBM), which holds promise as an easy-access and low-cost online intervention. However, little is known about the effectiveness of online interventions combining two varieties of CBM. Targeting multiple cognitive biases may improve treatment outcomes because these biases have been shown to be relatively independent. Objective: This study aimed to test the individual and combined effects of two web-based CBM varieties-attentional bias modification (AtBM) and approach bias modification (ApBM)-in a double-blind randomized controlled trial (RCT) with a 2 (AtBM: Active versus sham) × 2 (ApBM: Active versus sham) factorial design. Methods: A total of 504 adult smokers seeking online help to quit smoking were randomly assigned to 1 of 4 experimental conditions to receive 11 fully automated CBM training sessions. To increase participants' intrinsic motivation to change their smoking behaviors, all participants first received brief, automated, tailored feedback. The primary outcome was point prevalence abstinence during the study period. Secondary outcomes included daily cigarette use and attentional and approach bias. All outcomes were repeatedly self-assessed online from baseline to the 3-month follow-up. For the examination of training effects on outcome changes, an intention-to-treat analysis with a multilevel modeling (MLM) approach was adopted. Results: Only 10.7% (54/504) of the participants completed all 11 training sessions, and 8.3% (42/504) of the participants reached the 3-month follow-up assessment. MLM showed that over time, neither AtBM or ApBM nor a combination of both differed from their respective sham training in point prevalence abstinence rates (P=.17, P=.56, and P=.14, respectively), and in changes in daily cigarette use (P=.26, P=.08, and P=.13, respectively), attentional bias (P=.07, P=.81, and P=.15, respectively), and approach bias (P=.57, P=.22, and P=.40, respectively), while daily cigarette use decreased over time across conditions for all participants (P<.001). Conclusions: This RCT pro

Implicit measurement at the service of mental health: assessment and intervention as the two sides of the same coin

Scientific research in psychology is intrinsically bound to the measurement of variables that are per nature highly complex, changeable, and most often unobservable. The design of measurement methods is mostly focused on the attempt to capture the main features of the psychological attribute of interest. The last fifteen years have seen a massive development and use of a new set of measurement instruments that go under the name of implicit measures, which accomplishes the primary goal of indexing psychological attributes interchangeably defined as automatic, uncontrollable, unconscious, impulsive, or implicit. The primary goal of the present work was to explore the implicitness feature of implicit measures and their functioning. The research covered the experimentation of several implicit measures in two different contexts within the broader domain of mental health: the automatic components of stigmatizing attitudes and behaviours towards people affected by a mental disease (Part 1) and the impulsive, automatic processes implied within people affected by a mental disease, more specifically, by an alcohol addiction disorder (Part 2). Part 1 of this dissertation is concerned with the design of two Implicit Association Tests targeting two aspects of mental illness stigma, namely, aetiological beliefs and prejudicial attitudes. The main objectives were to verify whether these two measures could be used as assessment techniques in this particular framework and to explore the plausible existence of implicit complements of mental illness stigma. Part 2 doubled the perspective of this research by experimenting implicit measurement techniques as means for change by adapting them to retrain the implicit processes they were initially designed to assess. The study took the form of a Randomised Clinical Trial with alcohol addict outpatients in which the combination of two training paradigms targeting maladaptive impulsive processes towards alcohol (i.e., attentional bias and approach bias) is examined. In both studies, the measurement properties of the implicit measures developed and their meaning in relation to the theoretical to-be-measured psychological attributes have been explored within a Rasch modelling perspective, through the application of the Many-Facet Rasch Measurement (MFRM) model. In Part 1, the MFRM model allowed disentangling the different ‘ingredients’ contributing to the emergence of the IATs effect and highlighting how implicit aetiological beliefs and evaluative associations with mental illness are multifaceted aspects. Semantic and evaluative implicit associations with mental illness resulted to be dependent on diagnostic categories and differently determined by biologic semantic associations and by a positive association primacy, respectively. Further, the MFRM evidenced the functioning of the IAT at the microscopic level. In Part 2, analysis of data of a group of participants at pre- and post-intervention assessment sessions evidenced the first promising results of the RCT: although participants did not show a substantial change in their alcohol attentional and approach bias measures, the MFRM showed a changing process in action. Experimental conditions showed to have a differential effect in bringing in a decrease and/or a reversal of the two cognitive biases. The MFRM contributed to the exploration of the dimensional and theoretical status of the two cognitive bias implicit measures and provided informative clues about their general and domain- specific features. Further, the MFRM retrieved first evidence about a differential effect of the stimuli used in improving control processes over the impulsive reactions towards alcohol. The intertwined elements of this work, namely, implicit measurement, mental health, and Rasch modelling, have been combined in the attempt not only to clarify the benefits of implicit methods in psychology, but also to unravel what it actually means to use implicit measures. The combination with a rigorous modelling approach indeed demonstrated both the limitations and the strength of this new family of instruments.La ricerca scientifica in psicologia è intrinsecamente legata alla misurazione di variabili che per natura sono mutevoli, presentano un’elevata complessità e molto spesso non sono direttamente osservabili. Lo sviluppo di metodi di misurazione è funzionale alla ricerca di un mezzo per mettere in luce le diverse sfaccettature della variabile psicologica di interesse. Gli ultimi quindici anni hanno assistito ad un enorme sviluppo e applicazione di un nuovo insieme di strumenti di misura note come misure implicite, le quali hanno come scopo primario quello di quantificare quelle variabili psicologiche definite come automatiche, incontrollabili, inconsce, impulsive, o implicite. L’obiettivo principale di questo lavoro è stato quello di esplorare la natura propriamente implicita di alcune di queste misure, insieme al loro funzionamento. Il progetto di ricerca ha incluso la sperimentazione di alcuni metodi di misura impliciti in due diversi contesti all’interno del più ampio ambito della salute mentale: da una parte lo studio delle componenti automatiche nei processi di stigmatizzazione nei confronti di persone affette da un qualche disturbo mentale (Parte 1); dall’altra la considerazione dei processi impulsivi e automatici in persone affette da uno specific disturbo mentale, quale la dipendenza dal alcol (Parte 2). La Parte 1 della tesi include lo sviluppo di due Implicit Association Tests destinati alla valutazione di due aspetti inerenti lo stigma verso la malattia mentale: le credenze eziologiche e gli atteggiamenti pregiudiziali. Gli obiettivi principali hanno riguardato la verifica del possibile utilizzo di queste misure come strumenti di valutazione in questo specifico ambito, e nel contempo dell’effettiva esistenza di una controparte implicita nell’espressione dello stigma verso la malattia mentale. Nella Parte 2 la prospettiva ha assunto un’ulteriore duplice veste attraverso la sperimentazione delle tecniche di misurazione implicita come strumenti di cambiamento, attraverso il loro adattamento alla funzione di training di quei processi impliciti inizialmente misurati. Lo studio ha preso la forma di un Trial Clinico Randomizzato (TCR) con pazienti ambulatoriali dipendenti da alcol, nel quale è valutata la somministrazione di una combinazione di due training per il trattamento dei processi cognitivi automatici disfunzionali (i.e., bias attentivo e di approccio) implicati nella dipendenza da alcol. In entrambi gli studi sono state esplorate sia le proprietà misurative degli strumenti sviluppati, sia la loro relazione con l’ipotetica variabile psicologica misurata all’interno di una prospettiva di modellazione a tratti latenti, attraverso l’applicazione del Many-Facet Rasch Measurement model (MFRM). I risultati ottenuti nella Parte 1 mostrano come il modello MFRM sia riuscito a separare i diversi ‘ingredienti’ che contribuiscono all’emergere dell’effetto IAT evidenziando come le credenze eziologiche implicite e l’atteggiamento implicito nei confronti della malattia mentale siano multi-sfaccettati. Le associazioni semantiche e valutative nei confronti della malattia mentale sembrano cambiare in funzione della categoria diagnostica e sono rispettivamente determinate da associazioni con l’area semantica biologica e da un effetto primacy di associazioni positive. Il modello MFRM ha inoltre reso evidente il funzionamento dello IAT a livello microscopico. Nella Parte 2, l’analisi di un gruppo di partecipanti nelle sessioni di pre- e post- assessment ha dato i primi, promettenti risultanti sull’efficacia del TCR: nonostante al momento i partecipanti non abbiamo menifestato un significativo cambiamento nelle misure del bias attentivo e di approccio verso l’alcol, il modello MFRM ha dimostrato comunque che c’è effettivamente in atto un processo di cambiamento. Le condizioni sperimentali hanno prodotto un effetto discriminante nell’ottenere la diminuzione o il rovesciamento dei due bias cognitivi. Il modello ha inoltre contribuito all’esplorazione della dimensionalità e delle ipotesi teoriche alla base delle due misure implicite dei bias, dando suggerimenti rilevanti circa le loro caratteristiche dominio-generali e dominio-specifiche. Un ulteriore risultato riguarda un primo riscontro di un effetto esercitato dagli stimoli utilizzati nelle due misure nell’aumentare i processi di controllo degli impulsi nei confronti dell’alcol. In conclusione, l’intreccio tra misurazione implicita, salute mentale, e modelli di Rasch è nato allo scopo non solo di chiarire i benefici dell’utilizzo delle misure implicite in psicologia, ma anche per svelare che cosa significa effettivamente la misurazione implicita, mostrando sia i limiti che i punti di forza di questa nuova famiglia di strumenti attraverso la combinazione con un approccio metodologico e modellistico rigoroso

An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy.

The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT

Stimulus, latency parameter estimate (), standardized contrast values for block order by general accuracy levels, and standardized latency index <i>S(L)</i>.

a<p>Words; ^bPictures; *<i>p</i>≤.05; **<i>p</i><.01.</p

Stimulus format, latency parameter estimate (), Standard Error (<i>SE</i>), and Infit and Outfit statistics for each MIPI-IAT stimulus.

<p>Stimulus format, latency parameter estimate (), Standard Error (<i>SE</i>), and Infit and Outfit statistics for each MIPI-IAT stimulus.</p

Accuracy by block order interaction effects on stimuli parameter estimates for each MIPI-IAT target and attribute category: mean latency parameter estimates ().

<p>Accuracy by block order interaction effects on stimuli parameter estimates for each MIPI-IAT target and attribute category: mean latency parameter estimates ().</p