Narrative identity in addictive disorders: a conceptual review

Narrative identity allows individuals to integrate their personal experiences into a coherent and meaningful life story. Addictive disorders appear to be associated with a disturbed sense of self, reflected in problematic and disorganized self-narratives. In recent literature, a growing body of research has highlighted how narrative approaches can make a dual contribution to the understanding of addiction: on the one hand, by revealing crucial aspects of self structure, and, on the other, by supporting the idea that addiction is a disorder related to unintegrated self-states in which dissociative phenomena and the resulting sense of 'loss of self' are maladaptive strategies for coping with distress. This conceptual review identified the main measures of narrative identity, i.e., narrative coherence and complexity, agency, and emotions, and critically examines 9 quantitative and qualitative studies (out of 18 identified in literature), that have investigated the narrative dimension in people with an addictive disorder in order to provide a synthesis of the relationship between self, narrative and addiction. These studies revealed a difficulty in the organization of narrative identity of people with an addictive disorder, which is reflected in less coherent and less complex autobiographical narratives, in a prevalence of passivity and negative emotions, and in a widespread presence of themes related to a lack of self-efficacy. This review points out important conceptual, methodological and clinical implications encouraging further investigation of narrative dimension in addiction.

Collective self-understanding: A linguistic style analysis of naturally occurring text data

Understanding what groups stand for is integral to a diverse array of social processes, ranging from understanding political conflicts to organisational behaviour to promoting public health behaviours. Traditionally, researchers rely on self-report methods such as interviews and surveys to assess groups' collective self-understandings. Here, we demonstrate the value of using naturally occurring online textual data to map the similarities and differences between real-world groups' collective self-understandings. We use machine learning algorithms to assess similarities between 15 diverse online groups' linguistic style, and then use multidimensional scaling to map the groups in two-dimensonal space (N=1,779,098 Reddit comments). We then use agglomerative and k-means clustering techniques to assess how the 15 groups cluster, finding there are four behaviourally distinct group types - vocational, collective action (comprising political and ethnic/religious identities), relational and stigmatised groups, with stigmatised groups having a less distinctive behavioural profile than the other group types. Study 2 is a secondary data analysis where we find strong relationships between the coordinates of each group in multidimensional space and the groups' values. In Study 3, we demonstrate how this approach can be used to track the development of groups' collective self-understandings over time. Using transgender Reddit data (N= 1,095,620 comments) as a proof-of-concept, we track the gradual politicisation of the transgender group over the past decade. The automaticity of this methodology renders it advantageous for monitoring multiple online groups simultaneously. This approach has implications for both governmental agencies and social researchers more generally. Future research avenues and applications are discussed.

Computerized text and voice analysis of patients with chronic schizophrenia in art therapy

This explorative study of patients with chronic schizophrenia aimed to clarify whether group art therapy followed by a therapist-guided picture review could influence patients' communication behaviour. Data on voice and speech characteristics were obtained via objective technological instruments, and these characteristics were selected as indicators of communication behaviour. Seven patients were recruited to participate in weekly group art therapy over a period of 6 months. Three days after each group meeting, they talked about their last picture during a standardized interview that was digitally recorded. The audio recordings were evaluated using validated computer-assisted procedures, the transcribed texts were evaluated using the German version of the LIWC2015 program, and the voice recordings were evaluated using the audio analysis software VocEmoApI. The dual methodological approach was intended to form an internal control of the study results. An exploratory factor analysis of the complete sets of output parameters was carried out with the expectation of obtaining typical speech and voice characteristics that map barriers to communication in patients with schizophrenia. The parameters of both methods were thus processed into five factors each, i.e., into a quantitative digitized classification of the texts and voices. The factor scores were subjected to a linear regression analysis to capture possible process-related changes. Most patients continued to participate in the study. This resulted in high-quality datasets for statistical analysis. To answer the study question, two results were summarized: First, text analysis factor called Presence proved to be a potential surrogate parameter for positive language development. Second, quantitative changes in vocal emotional factors were detected, demonstrating differentiated activation patterns of emotions. These results can be interpreted as an expression of a cathartic healing process. The methods presented in this study make a potentially significant contribution to quantitative research into the effectiveness and mode of action of art therapy.

Does resilience mediate the association between mental health symptoms and linguistic markers of trauma processing? Analyzing the narratives of women survivors of intimate partner violence

Intimate partner violence (IPV) is a serious issue for women from all cultures and backgrounds. Studies on the negative consequences of violence suggest that women with a history of abuse are more likely to display depressive and PTSD symptoms. However, recent research has focused on the mechanisms underpinning resilience and the processing of traumatic memories, including linguistic markers and how they may reflect the mental health of traumatized individuals. In this study, we analyzed trauma narratives to investigate whether resilience mediates the impact of PTSD and depression symptoms on five trauma-processing mechanisms (cognitive processing, emotional processing, perceived threat to life, self-perspective, and integration of traumatic memories). Forty-three abused women (mean age = 38.74 years; SD = 9.41) wrote about their traumatic experiences and completed instruments assessing their levels of PTSD, depression, and resilience. We used LIWC software to analyze the women's narratives in terms of linguistic markers of psychological processing. Mediation analysis indicated that resilience fully mediated the impact of mental health symptoms on emotional processing, perceived threat to life, and integration of traumatic memories and partially mediated cognitive processing and self-perspective. We discuss the clinical implications of these findings, emphasizing the need to focus on the resources and strengths of women survivors of abuse in designing targeted psychological interventions.

Linguistic Predictors of Psychological Adjustment in Healthcare Workers during the COVID-19 Pandemic

COVID-19 broke out in China in December 2019 and rapidly became a worldwide pandemic that demanded an extraordinary response from healthcare workers (HCWs). Studies conducted during the pandemic observed severe depression and PTSD in HCWs. Identifying early predictors of mental health disorders in this population is key to informing effective treatment and prevention. The aim of this study was to investigate the power of language-based variables to predict PTSD and depression symptoms in HCWs. One hundred thirty-five HCWs (mean age = 46.34; SD = 10.96) were randomly assigned to one of two writing conditions: expressive writing (EW n = 73) or neutral writing (NW n = 62) and completed three writing sessions. PTSD and depression symptoms were assessed both pre- and post-writing. LIWC was used to analyze linguistic markers of four trauma-related variables (cognitive elaboration, emotional elaboration, perceived threat to life, and self-immersed processing). Changes in PTSD and depression were regressed onto the linguistic markers in hierarchical multiple regression models. The EW group displayed greater changes on the psychological measures and in terms of narrative categories deployed than the NW group. Changes in PTSD symptoms were predicted by cognitive elaboration, emotional elaboration, and perceived threat to life; changes in depression symptoms were predicted by self-immersed processing and cognitive elaboration. Linguistic markers can facilitate the early identification of vulnerability to mental disorders in HCWs involved in public health emergencies. We discuss the clinical implications of these findings.

State of Mind Assessment in Relation to Adult Attachment and Text Analysis of Adult Attachment Interviews in a Sample of Patients with Anorexia Nervosa

BACKGROUND

Attachment theory represents one of the most important references for the study of the development of an individual throughout their life cycle and provides the clinician with a profound key for the purposes of understanding the suffering that underlies severe psychopathologies such as eating disorders. As such, we conducted a cross-sectional study with a mixed-methods analysis on a sample of 32 young women with anorexia nervosa (AN); this study was embedded in the utilized theoretical framework with the following aims: 1. to evaluate the state of mind (SoM) in relation to adult attachment, assuming a prevalence of the dismissing (DS) SoM and 2. to analyze the linguistic attachment profile emerging from the transcripts of the AAIs.

METHODS

Interviews were transcribed verbatim, coded, and analyzed using the linguistic inquiry and word count (LIWC) method.

RESULTS

The results were observed to be consistent with the referenced literature. The prevalence of a DS SoM (68.75%) is observed in the study sample, whereas the results of the lexical analysis of the stories deviate from expectations. Notably, the lexical results indicate the coexistence of the dismissing and entangled aspects at the representational level.

CONCLUSIONS

The study results suggest a high level of specificity in the emotional functioning of patients with AN, with a focusing on a pervasive control of emotions that is well illustrated by the avoidant/ambivalent (A/C) strategy described in Crittenden's dynamic-maturational model. These findings and considerations have important implications for clinical work and treatment, which we believe must be structured on the basis of starting from a reappraisal of emotional content.

Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study

Background

The ability to objectively measure the severity of depression and anxiety disorders in a passive manner could have a profound impact on the way in which these disorders are diagnosed, assessed, and treated. Existing studies have demonstrated links between both depression and anxiety and the linguistic properties of words that people use to communicate. Smartphones offer the ability to passively and continuously detect spoken words to monitor and analyze the linguistic properties of speech produced by the speaker and other sources of ambient speech in their environment. The linguistic properties of automatically detected and recognized speech may be used to build objective severity measures of depression and anxiety.

Objective

The aim of this study was to determine if the linguistic properties of words passively detected from environmental audio recorded using a participant’s smartphone can be used to find correlates of symptom severity of social anxiety disorder, generalized anxiety disorder, depression, and general impairment.

Methods

An Android app was designed to collect periodic audiorecordings of participants’ environments and to detect English words using automatic speech recognition. Participants were recruited into a 2-week observational study. The app was installed on the participants’ personal smartphones to record and analyze audio. The participants also completed self-report severity measures of social anxiety disorder, generalized anxiety disorder, depression, and functional impairment. Words detected from audiorecordings were categorized, and correlations were measured between words counts in each category and the 4 self-report measures to determine if any categories could serve as correlates of social anxiety disorder, generalized anxiety disorder, depression, or general impairment.

Results

The participants were 112 adults who resided in Canada from a nonclinical population; 86 participants yielded sufficient data for analysis. Correlations between word counts in 67 word categories and each of the 4 self-report measures revealed a strong relationship between the usage rates of death-related words and depressive symptoms (r=0.41, P<.001). There were also interesting correlations between rates of word usage in the categories of reward-related words with depression (r=–0.22, P=.04) and generalized anxiety (r=–0.29, P=.007), and vision-related words with social anxiety (r=0.31, P=.003).

Conclusions

In this study, words automatically recognized from environmental audio were shown to contain a number of potential associations with severity of depression and anxiety. This work suggests that sparsely sampled audio could provide relevant insight into individuals’ mental health.

How Can Poetry Support the Understanding of Psychotic Experiences? - A Conceptual Review

OBJECTIVE

The therapeutic application of poetry for those who have experienced psychosis remains under researched and potentially undervalued. This paper presents a conceptual review exploring the relationship between poetry and psychosis, based on a synthesis of existing literature.

RESEARCH DESIGN AND METHODS

The review identified papers from a range of sources and disciplines. Initial searches were undertaken using databases CINAHL, PsycINFO and ASSIA; this search was then followed up with a library search for key texts and a further search for associated grey literature involving exploring blogs and conference presentations. The data was then synthesized based on methods from both narrative review and thematic analysis to generate a conceptual framework.

RESULTS

The results reveal a conceptual framework comprised of three domains: i) psychotic language as meaningful poetics, ii) poetry as an expression of psychosis and iii) poetic exchange as therapeutic practice. The conceptual framework proposes that not only can psychosis be understood as meaningful poetics, but also that poetry may offer meaningful linguistic opportunities to aid the expression and narration of self and experiences. The potential for extending our understanding of the poetry in this way is analogous to forms of talking therapy, and this may be a base for extending understanding and communicative practice for a range of mental health professions.

CONCLUSION

The conceptual framework suggests a novel understanding of psychosis in relation to poetry, moving away from traditional biomedical paradigms and placing importance upon individual narratives.

Effects of expressive writing and use of cognitive words on meaning making and post-traumatic Growth

Expressive writing can enhance cognitive processing and improve stress regulation. Particularly, the use of cognitive words (i.e., insightful and causal words) in writing may be associated with the process of meaning making and promotion of post-traumatic growth (PTG). The aim of the present study was to determine how expressive writing and the use of causal and insightful cognitive words influenced meaning making and PTG during writing. In total, 52 traumatized university students were recruited and randomly assigned to one of two writing conditions involving either an expressive writing task or a neutral writing task. The results showed that participants who engaged in expressive (vs. neutral) writing showed higher scores on the presence of meaning and PTG in the post-writing, self-report questionnaires. Moreover, writing task (expressive or neutral) and frequency of causal and insightful cognitive words were both significant predictors of meaning, which in turn led to high levels of PTG. In conclusion, the use of causal and insightful words might be a fundamental cognitive process for developing meaning in writing, which is essential for our further understanding of meaning making and PTG.

Dynamical Relations in the Self-Pattern

The notion of a self-pattern, as developed in the pattern theory of self (Gallagher, 2013), which holds that the self is best explained in terms of the kind of reality that pertains to a dynamical pattern, acknowledges the importance of neural dynamics, but also expands the account of self to extra-neural (embodied and enactive) dynamics. The pattern theory of self, however, has been criticized for failing to explicate the dynamical relations among elements of the self-pattern (e.g., Kyselo, 2014; Beni, 2016; de Haan et al., 2017); as such, it seems to be nothing more than a mere list of elements. We'll argue that the dynamics of a self-pattern are reflected in three significant and interrelated ways that allow for investigation. First, a self-pattern is reflectively reiterated in its narrative component. Second, studies of psychiatric or neurological disorders can help us understand the precise nature of the dynamical relations in a self-pattern, and how they can fail. Third, referencing predictive processing accounts, neuroscience can also help to explicate the dynamical relations that constitute the self-pattern.

Early Linguistic Markers of Trauma-Specific Processing Predict Post-trauma Adjustment

Identifying early predictors for psychiatric disorders, such as post-traumatic stress disorder (PTSD), is crucial for effective treatment and prevention efforts. Obtaining such predictors is challenging and methodologically limited, for example by individuals' distress, arousal, and reduced introspective ability. We investigated the predictive power of language-based, implicit markers of psychological processes (N = 163) derived from computerized text-analysis of trauma and control narratives provided within 18 days post-trauma. Trauma narratives with fewer cognitive processing words (indicating less cognitive elaboration), more death-related words (indicating perceived threat to life), and more first-person singular pronouns (indicating self-immersed processing) predicted greater PTSD symptoms at 6 months. These effects were specific to trauma narratives and held after controlling for early PTSD symptom severity and verbal intelligence. When self-report questionnaires of related processes were considered together with the trauma narrative linguistic predictors, use of more first-person singular pronouns remained a significant predictor alongside self-reported mental defeat. Language-based processing markers may complement questionnaire measures in early forecasting of post-trauma adjustment.

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals

Background

Linguistic analysis of publicly available Twitter feeds have achieved success in differentiating individuals who self-disclose online as having schizophrenia from healthy controls. To date, limited efforts have included expert input to evaluate the authenticity of diagnostic self-disclosures.

Objective

This study aims to move from noisy self-reports of schizophrenia on social media to more accurate identification of diagnoses by exploring a human-machine partnered approach, wherein computational linguistic analysis of shared content is combined with clinical appraisals.

Methods

Twitter timeline data, extracted from 671 users with self-disclosed diagnoses of schizophrenia, was appraised for authenticity by expert clinicians. Data from disclosures deemed true were used to build a classifier aiming to distinguish users with schizophrenia from healthy controls. Results from the classifier were compared to expert appraisals on new, unseen Twitter users.

Results

Significant linguistic differences were identified in the schizophrenia group including greater use of interpersonal pronouns (P<.001), decreased emphasis on friendship (P<.001), and greater emphasis on biological processes (P<.001). The resulting classifier distinguished users with disclosures of schizophrenia deemed genuine from control users with a mean accuracy of 88% using linguistic data alone. Compared to clinicians on new, unseen users, the classifier’s precision, recall, and accuracy measures were 0.27, 0.77, and 0.59, respectively.

Conclusions

These data reinforce the need for ongoing collaborations integrating expertise from multiple fields to strengthen our ability to accurately identify and effectively engage individuals with mental illness online. These collaborations are crucial to overcome some of mental illnesses’ biggest challenges by using digital technology.

Emotional word usage in groups at risk for schizophrenia-spectrum disorders: An objective investigation of attention to emotion

Both extreme levels of social anhedonia (SocAnh) and extreme levels of perceptual aberration/magical ideation (PerMag) indicate increased risk for schizophrenia-spectrum disorders and are associated with emotional deficits. For SocAnh, there is evidence of self-reported decreased trait positive affect and abnormalities in emotional attention. For PerMag, there is evidence of increased trait negative affect and increased attention to negative emotion. Yet, the nature of more objective emotional abnormalities in these groups is unclear. The goal of this study was to assess attention to emotions more objectively in a SocAnh, PerMag, and control group by using a positive (vs. neutral) mood induction procedure followed by a free writing period. Linguistic analyses revealed that the SocAnh group used fewer positive emotion words than the control group, with the PerMag group falling in between the others. In addition, both at-risk groups used more negative emotion words than the control group. Also, for the control group only, those in the positive mood induction used more positive emotion words, suggesting their emotions influenced their linguistic expression. Overall, SocAnh is associated with decreased positive emotional expression and at-risk groups are associated with increased negative emotional expression and a decreased influence of emotions on linguistic expression.

Computational Psychiatry in Borderline Personality Disorder

PURPOSE OF REVIEW

We review the literature on the use and potential use of computational psychiatry methods in Borderline Personality Disorder.

RECENT FINDINGS

Computational approaches have been used in psychiatry to increase our understanding of the molecular, circuit, and behavioral basis of mental illness. This is of particular interest in BPD, where the collection of ecologically valid data, especially in interpersonal settings, is becoming more common and more often subject to quantification. Methods that test learning and memory in social contexts, collect data from real-world settings, and relate behavior to molecular and circuit networks are yielding data of particular interest.

SUMMARY

Research in BPD should focus on collaborative efforts to design and interpret experiments with direct relevance to core BPD symptoms and potential for translation to the clinic.

Language and hope in schizophrenia-spectrum disorders

Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples.

Self-reference in psychosis and depression: a language marker of illness

BACKGROUND

Language use is of increasing interest in the study of mental illness. Analytical approaches range from phenomenological and qualitative to formal computational quantitative methods. Practically, the approach may have utility in predicting clinical outcomes. We harnessed a real-world sample (blog entries) from groups with psychosis, strong beliefs, odd beliefs, illness, mental illness and/or social isolation to validate and extend laboratory findings about lexical differences between psychosis and control subjects.

METHOD

We describe the results of two experiments using Linguistic Inquiry and Word Count software to assess word category frequencies. In experiment 1, we compared word use in psychosis and control subjects in the laboratory (23 per group), and related results to subject symptoms. In experiment 2, we examined lexical patterns in blog entries written by people with psychosis and eight comparison groups. In addition to between-group comparisons, we used factor analysis followed by clustering to discern the contributions of strong belief, odd belief and illness identity to lexical patterns.

RESULTS

Consistent with others' work, we found that first-person pronouns, biological process words and negative emotion words were more frequent in psychosis language. We tested lexical differences between bloggers with psychosis and multiple relevant comparison groups. Clustering analysis revealed that word use frequencies did not group individuals with strong or odd beliefs, but instead grouped individuals with any illness (mental or physical).

CONCLUSIONS

Pairing of laboratory and real-world samples reveals that lexical markers previously identified as specific language changes in depression and psychosis are probably markers of illness in general.

Lexical analysis in schizophrenia: how emotion and social word use informs our understanding of clinical presentation

BACKGROUND

The words people use convey important information about internal states, feelings, and views of the world around them. Lexical analysis is a fast, reliable method of assessing word use that has shown promise for linking speech content, particularly in emotion and social categories, with psychopathological symptoms. However, few studies have utilized lexical analysis instruments to assess speech in schizophrenia. In this exploratory study, we investigated whether positive emotion, negative emotion, and social word use was associated with schizophrenia symptoms, metacognition, and general functioning in a schizophrenia cohort.

METHODS

Forty-six participants generated speech during a semi-structured interview, and word use categories were assessed using a validated lexical analysis measure. Trained research staff completed symptom, metacognition, and functioning ratings using semi-structured interviews.

RESULTS

Word use categories significantly predicted all variables of interest, accounting for 28% of the variance in symptoms and 16% of the variance in metacognition and general functioning. Anger words, a subcategory of negative emotion, significantly predicted greater symptoms and lower functioning. Social words significantly predicted greater metacognition.

CONCLUSIONS

These findings indicate that lexical analysis instruments have the potential to play a vital role in psychosocial assessments of schizophrenia. Future research should replicate these findings and examine the relationship between word use and additional clinical variables across the schizophrenia-spectrum.

Differential lexical correlates of social cognition and metacognition in schizophrenia; a study of spontaneously-generated life narratives

OBJECTIVES

Social cognition and metacognition have been identified as important cognitive domains in schizophrenia, which are separable from general neurocognition and predictive of functional and treatment outcomes. However, one challenge to improved models of schizophrenia has been the conceptual overlap between the two. One tool used in previous research to develop cognitive models of psychopathology is language analysis. In this article we aimed to clarify distinctions between social cognition and metacognition in schizophrenia using computerized language software.

METHODS

Fifty-eight (n=58) individuals with schizophrenia completed the Metacognitive Assessment Scale Abbreviated and measures of social cognition using the Hinting, Eyes, BLERT and Picture Arrangement test. A lexical analysis of participants' speech using Language Inquiry and Word Count software was conducted to examine relative frequencies of word types. Lexical characteristics were examined for their relationships to social cognition and metacognition.

RESULTS

We found that lexical characteristics indicative of cognitive complexity were significantly related to level of metacognitive capacity while social cognition was related to second-person pronoun use, articles, and prepositions, and pronoun use overall. The relationships between lexical variables and metacognition persisted after controlling for demographics, verbal intelligence, and overall word count, but the same was not true for social cognition.

CONCLUSIONS

Our findings provided support for the view that metacognition requires more synthetic and complex verbal and linguistic operations, while social cognition is associated with the representation and clear identification of others.

Word use in first-person accounts of schizophrenia

BACKGROUND

Language use is often disrupted in patients with schizophrenia; novel computational approaches may provide new insights.

AIMS

To test word use patterns as markers of the perceptual, cognitive and social experiences characteristic of schizophrenia.

METHOD

Word counting software was applied to first-person accounts of schizophrenia and mood disorder.

RESULTS

More third-person plural pronouns ('they') and fewer first-person singular pronouns ('I') were used in schizophrenia than mood disorder accounts. Schizophrenia accounts included fewer words related to the body and ingestion, and more related to religion. Perceptual and causal language were negatively correlated in schizophrenia accounts but positively correlated in mood disorder accounts.

CONCLUSIONS

Differences in pronouns suggest decreased self-focus or perhaps even an understanding of self as other in schizophrenia. Differences in how perceptual and causal words are correlated suggest that long-held delusions represent a decreased coupling of explanations with sensory experience over time.

A null relationship between media multitasking and well-being

There is a rapidly increasing trend in media-media multitasking or MMM (using two or more media concurrently). In a recent conference, scholars from diverse disciplines expressed concerns that indulgence in MMM may compromise well-being and/or cognitive abilities. However, research on MMM's impacts is too sparse to inform the general public and policy makers whether MMM should be encouraged, managed, or minimized. The primary purpose of the present study was to develop an innovative computerized instrument – the Survey of the Previous Day (SPD) – to quantify MMM as well as media-nonmedia and nonmedia-nonmedia multitasking and sole-tasking. The secondary purpose was to examine whether these indices could predict a sample of well-being related, psychosocial measures. In the SPD, participants first recalled (typed) what they did during each hour of the previous day. In later parts of the SPD, participants analysed activities and their timing and duration for each hour of the previous day, while relevant recall was on display. Participants also completed the Media Use Questionnaire. The results showed non-significant relationship between tasking measures and well-being related measures. Given how little is known about the associations between MMM and well-being, the null results may offer some general reassurance to those who are apprehensive about negative impacts of MMM.

Changes in natural language use as an indicator of psychotherapeutic change in personality disorders

Word use has been shown to reflect various psychological processes and psychological change. This study examines the self-view in personality disorders (PDs) and its change over the course of therapy using the Linguistic Inquiry and Word Count analysis procedure. A sample of 299 participants with PDs and 108 community control participants wrote short essays about their lives. Patients repeated the assignment three times over two years and completed assessments of PD-pathology, general psychopathology, PD-beliefs, and quality of life. Results show that as hypothesized the use of words in the 1st Person Singular Pronouns, Negative Emotion, Causation, Past and Future Tense Verbs categories significantly declines over the course of treatment, while the use of Present Tense Verbs and Positive Emotion increases. These categories tend to distinguish patients from non-patients prior to treatment. We also found 12 additional word categories changing over time, including Word Count and Negations. Change in word use statistically predicts better treatment outcome on all outcome measures (p < .001). Reductions in the use of Negative Emotion Words and Negations are the strongest predictors of outcome. The non-hypothesized role of Negations was explored and seemed to reflect that PD-patients miss a lot in their lives. Reduction of what they miss seems central to recovery. This issue seems relatively neglected in theoretical and treatment models of PDs. An increased focus on what patients miss in their lives might improve our understanding and treatment of PDs. In sum, Negative Emotion and Negation word categories appear to reflect key treatment targets.

A laboratory study of affectivity in schizotypy: subjective and lexical analysis

Affective dysfunction is a defining schizotypy feature; yet the majority of studies examining affective dysfunction have largely relied on self-report of trait affect, which reflects only one dimension of emotional experience. Emerging research has explored a second dimension, state affect, using laboratory manipulation, with most finding that schizotypal participants report experiencing less positive/more negative affect than controls. This study expands upon this topic by examining patterns of state affect in psychometrically identified schizotypy through self-report and lexical expression in reaction to emotionally valenced photos. Overall, the schizotypy group reported less positive/more negative affect across affect induction conditions. Both schizotypy and control groups' affect ratings were similar following the unpleasant stimuli; but the schizotypy group's ratings remained significantly less positive/more negative than the control group following the pleasant stimuli. This pattern suggests that the schizotypy group experienced a deficit in emotional reactivity compared to controls in pleasant situations. The schizotypy group also used a higher percentage of negative words and a lower percentage of positive words in vocalized reactions during the pleasant, but not unpleasant, affect induction condition. These results reveal a specific pattern of "in-the-moment" affective dysfunction unique to pleasant situations that is consistent across both subjective experience and lexical expression.

Dissociation in self-narrative

We review different analytic approaches to narratives by those with psychopathological conditions, and we suggest that the interpretation of such narratives are complicated by a variety of phenomenological and hermeneutical considerations. We summarize an empirical study of narrative distance in narratives by non-pathological subjects, and discuss how the results can be interpreted in two different ways with regard to the issue of dissociation.