The experience of felt presence in a general population sample.

Felt presence is a widely occurring experience, but remains under-recognised in clinical and research practice. To contribute to a wider recognition of the phenomenon, we aimed to assess the presentation of felt presence in a large population sample (n = 10 447) and explore its relation to key risk factors for psychosis. In our sample 1.6% reported experiencing felt presence in the past month. Felt presence was associated with visual and tactile hallucinations and delusion-like thinking; it was also associated with past occurrence of adverse events, loneliness and poor sleep. The occurrence of felt presence may function as a marker for general hallucination proneness.

The Direct and Long-Term Effects of Raloxifene as Adjunctive Treatment for Schizophrenia-Spectrum Disorders: A Double-Blind, Randomized Clinical Trial.

BACKGROUND AND HYPOTHESIS: Several studies suggest that raloxifene, a selective estrogen receptor modulator, improves symptoms and cognition in post-menopausal women with Schizophrenia-Spectrum Disorders (SSD). We aimed to assess the effects of adjunctive raloxifene in women and men with SSD. STUDY DESIGN: This parallel, randomized, double-blind, placebo-controlled trial included adult SSD patients across the Netherlands and Belgium. Participants were stratified by age, sex, and global functioning and randomly assigned 1:1 to 12-week add-on raloxifene or placebo. Primary outcomes were symptom severity at 6, 12, and 38 weeks and cognition at 12 and 38 weeks, as measured with the Positive and Negative Syndrome Scale and the Brief Assessment of Cognition in Schizophrenia, respectively. Intention-to-treat analyses were performed using linear mixed-effect models. STUDY RESULTS: We assessed 261 patients for eligibility, of which 102 (28% female) were assigned to raloxifene (n = 52) or placebo (n = 48). Although we found no main effect of raloxifene, secondary sex-specific analysis showed that in women, raloxifene had beneficial effects on negative symptoms at week 6 (LSM -2.92; adjusted P = 0.020) and week 12 (LSM -3.12; adjusted P = 0.030), and on working memory at week 38 (LSM 0.73; adjusted P = 0.040), while having negative effects on working memory at week 38 in men (LSM -0.53; adjusted P = 0.026). The number of adverse events was similar between groups. CONCLUSIONS: Our results do not support the use of raloxifene in patients with SSD in general, but suggest female-specific beneficial effects of raloxifene on negative symptoms and working memory. Our findings encourage further research on sex-specific pharmacotherapeutic treatment.

Natural Language Processing Markers for Psychosis and Other Psychiatric Disorders: Emerging Themes and Research Agenda From a Cross-Linguistic Workshop.

This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount.

Syntactic Network Analysis in Schizophrenia-Spectrum Disorders.

BACKGROUND: Language anomalies are a hallmark feature of schizophrenia-spectrum disorders (SSD). Here, we used network analysis to examine possible differences in syntactic relations between patients with SSD and healthy controls. Moreover, we assessed their relationship with sociodemographic factors, psychotic symptoms, and cognitive functioning, and we evaluated whether the quantification of syntactic network measures has diagnostic value. STUDY DESIGN: Using a semi-structured interview, we collected speech samples from 63 patients with SSD and 63 controls. Per sentence, a syntactic representation (ie, parse tree) was obtained and used as input for network analysis. The resulting syntactic networks were analyzed for 11 local and global network measures, which were compared between groups using multivariate analysis of covariance, considering the effects of age, sex, and education. RESULTS: Patients with SSD and controls significantly differed on most syntactic network measures. Sex had a significant effect on syntactic measures, and there was a significant interaction between sex and group, as the anomalies in syntactic relations were most pronounced in women with SSD. Syntactic measures were correlated with negative symptoms (Positive and Negative Syndrome Scale) and cognition (Brief Assessment of Cognition in Schizophrenia). A random forest classifier based on the best set of network features distinguished patients from controls with 74% cross-validated accuracy. CONCLUSIONS: Examining syntactic relations from a network perspective revealed robust differences between patients with SSD and healthy controls, especially in women. Our results support the validity of linguistic network analysis in SSD and have the potential to be used in combination with other automated language measures as a marker for SSD.

Social Deafferentation and the Relation Between Loneliness and Hallucinations.

BACKGROUND AND HYPOTHESIS: The social deafferentation hypothesis (SDA) has been proposed as an explanatory mechanism of hallucinations, based on the theory that social withdrawal triggers the initial phase of schizophrenia. The current study tests the SDA by assessing how loneliness is associated with different types of hallucinations. Under the SDA, increased loneliness is hypothesized to affect the occurrence of hallucinations that carry social meaning, but not of nonsocial hallucinations. STUDY DESIGN: As part of an online survey, 2038 adolescents and young adults from the general population (median age 21 years; 75% female) filled out the Questionnaire for Psychotic Experiences, and the shortened De Jong Gierveld Loneliness Scale. Binomial logistic regression was used to investigate the effects of loneliness severity on past month prevalence of hallucinations, and on the presence of social versus nonsocial hallucinations. STUDY RESULTS: Loneliness increased the prevalence of hallucinations across modalities in the past month. Moreover, stronger degree of loneliness increased the likelihood of hearing voices or laughter, and of hallucinating being touched. Conversely, loneliness decreased the likelihood of experiencing the nonsocial hallucination of a tingling feeling. As expected, loneliness did not increase the prevalence of experiencing nonsocial hallucinations. Surprisingly, neither was loneliness associated with experiencing felt presence. CONCLUSIONS: Our results are novel in showing that loneliness specifically increases the likelihood of hearing human sounds such as voices or laughter, or feeling a human touch. Hallucinations without social meaning were not more likely to be experienced with increasing loneliness. This forms a confirmation of the SDA.

Speech as a Biomarker for Depression.

BACKGROUND: Depression is a debilitating disorder that at present lacks a reliable biomarker to aid in diagnosis and early detection. Recent advances in computational analytic approaches have opened up new avenues in developing such a biomarker by taking advantage of the wealth of information that can be extracted from a person's speech. OBJECTIVE: The current review provides an overview of the latest findings in the rapidly evolving field of computational language analysis for the detection of depression. We cover a wide range of both acoustic and content-related linguistic features, data types (i.e., spoken and written language), and data sources (i.e., lab settings, social media, and smartphone-based). We put special focus on the current methodological advances with regard to feature extraction and computational modeling techniques. Furthermore, we pay attention to potential hurdles in the implementation of automatic speech analysis. CONCLUSION: Depressive speech is characterized by several anomalies, such as lower speech rate, less pitch variability and more self-referential speech. With current computational modeling techniques, such features can be used to detect depression with an accuracy of up to 91%. The performance of the models is optimized when machine learning techniques are implemented that suit the type and amount of data. Recent studies now work towards further optimization and generalizability of the computational language models to detect depression. Finally, privacy and ethical issues are of paramount importance to be addressed when automatic speech analysis techniques are further implemented in, for example, smartphones. Altogether, computational speech analysis is well underway towards becoming an effective diagnostic aid for depression.

Semantic and Acoustic Markers in Schizophrenia-Spectrum Disorders: A Combinatory Machine Learning Approach.

BACKGROUND AND HYPOTHESIS: Speech is a promising marker to aid diagnosis of schizophrenia-spectrum disorders, as it reflects symptoms like thought disorder and negative symptoms. Previous approaches made use of different domains of speech for diagnostic classification, including features like coherence (semantic) and form (acoustic). However, an examination of the added value of each domain when combined is lacking as of yet. Here, we investigate the acoustic and semantic domains separately and combined. STUDY DESIGN: Using semi-structured interviews, speech of 94 subjects with schizophrenia-spectrum disorders (SSD) and 73 healthy controls (HC) was recorded. Acoustic features were extracted using a standardized feature-set, and transcribed interviews were used to calculate semantic word similarity using word2vec. Random forest classifiers were trained for each domain. A third classifier was used to combine features from both domains; 10-fold cross-validation was used for each model. RESULTS: The acoustic random forest classifier achieved 81% accuracy classifying SSD and HC, while the semantic domain classifier reached an accuracy of 80%. Joining features from the two domains, the combined classifier reached 85% accuracy, significantly improving on separate domain classifiers. For the combined classifier, top features were fragmented speech from the acoustic domain and variance of similarity from the semantic domain. CONCLUSIONS: Both semantic and acoustic analyses of speech achieved ~80% accuracy in classifying SSD from HC. We replicate earlier findings per domain, additionally showing that combining these features significantly improves classification performance. Feature importance and accuracy in combined classification indicate that the domains measure different, complementing aspects of speech.

Occurrence and phenomenology of hallucinations in the general population: A large online survey.

Although epidemiological studies report that hallucinations occur in 6-15% of the general population, little is known about their phenomenology. To overcome this paucity, this study investigates the phenomenological characteristics of hallucinations in the general population, by using a nationally promoted online survey to assess hallucination phenomenology in four sensory modalities, through a self-report version of the Questionnaire for Psychotic Experiences (QPE), in 10,448 participants (aged 14-88 years). The phenomenology of hallucinations was assessed if hallucinations reportedly occurred in the past month. In the past month, auditory hallucinations were reported most frequently (29.5%), followed by visual (21.5%), tactile (19.9%), and olfactory hallucinations (17.3%); hallucinations in two or more modalities were reported by 47.6%. Substantial numbers of participants rated their hallucinations as severe, due to negative content (16.0-31.6%), previous bothersome experiences (14.8-20.2%), ensuing distress (10.5-16.8%), and/or ensuing disfunctioning (12.7-17.3%). Decreased insight was found in 10.2-11.4%. Hypnagogia was reported by 9.0-10.6%, and bereavement hallucinations by 2.8%. Despite a low prevalence of delusions (7.0%), these phenomena were significantly associated with recent hallucinations, observed in up to 13.4% of the participants with hallucinations during the past week (p < 0.001). Our results indicate a wide variety of the phenomenology of hallucinations in the general population and support the existence of a phenomenological continuum.

Characterizing speech heterogeneity in schizophrenia-spectrum disorders.

Schizophrenia-spectrum disorders (SSD) are highly heterogeneous in risk factors, symptom characteristics, and disease course outcome. Although speech anomalies have long been recognized as a core symptom of SSD, speech markers are an unexplored source of symptom heterogeneity that may be informative in recognizing relevant subtypes. This study investigated speech heterogeneity and its relation to clinical characteristics in a large sample of patients with SSD and healthy controls. Speech samples were obtained from 142 patients with SSD and 147 healthy controls by means of open-ended interviews. Speech was analyzed using standardized open-source acoustic speech software. Hierarchical clustering was conducted using acoustic speech markers. Symptom severity was rated with the Positive and Negative Syndrome Scale, and cognition was assessed with the Brief Assessment of Cognition for Schizophrenia. Three speech clusters could be distinguished in the patient group that differed regarding speech properties, independent of medication use. One cluster was characterized by mild speech disturbances, while two severely impaired clusters were recognized (fragmented speakers and prolonged pausers). Both clusters with severely impaired speech had more severe cognitive dysfunction than the mildly impaired speakers. Prolonged pausers specifically had difficulties with memory-related tasks. Prolonged pausing, as opposed to fragmented speaking, related to chronic active psychosis and refractory psychotic symptoms. Based on speech clustering, subtypes of patients emerged with distinct disease trajectories, symptomatology, and cognitive functioning. The identification of clinically relevant subgroups within SSD may help to characterize distinct profiles and benefit the tailoring of early intervention and improvement of long-term functional outcome. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Towards better care for women with schizophrenia-spectrum disorders.

Women with a schizophrenia-spectrum disorder (SSD) have a better clinical profile than do men at the start of their illness but progress to the same state within the first few years of living with SSD. There are benefits to be gained across different areas in the care currently offered to women with psychosis. An important point for improvement is the early detection of female-specific signs of a first episode of psychosis, to shorten the duration of untreated psychosis, with prompt access to early intervention services. Special attention should be paid to sexual health, and to any history of childhood trauma. Antipsychotics require dosing and prescription tailored to the female physiology that consider hormonal life phases such as menopause. Switching to prolactin-sparing medications can benefit both mental and somatic health. Finally, hormone replacement therapy should be considered for postmenopausal women. By providing female-specific care, women with schizophrenia-spectrum disorders will have optimal chances to fare well.

Antipsychotic medication for women with schizophrenia spectrum disorders.

There are significant differences between men and women in the efficacy and tolerability of antipsychotic drugs. Here, we provide a comprehensive overview of what is currently known about the pharmacokinetics and pharmacodynamics of antipsychotics in women with schizophrenia spectrum disorders (SSDs) and translate these insights into considerations for clinical practice. Slower drug absorption, metabolism and excretion in women all lead to higher plasma levels, which increase the risk for side-effects. Moreover, women reach higher dopamine receptor occupancy compared to men at similar serum levels, since oestrogens increase dopamine sensitivity. As current treatment guidelines are based on studies predominantly conducted in men, women are likely to be overmedicated by default. The risk of overmedicating generally increases when sex hormone levels are high (e.g. during ovulation and gestation), whereas higher doses may be required during low-hormonal phases (e.g. during menstruation and menopause). For premenopausal women, with the exceptions of quetiapine and lurasidone, doses of antipsychotics should be lower with largest adjustments required for olanzapine. Clinicians should be wary of side-effects that are particularly harmful in women, such as hyperprolactinaemia which can cause oestrogen deficiency and metabolic symptoms that may cause cardiovascular diseases. Given the protective effects of oestrogens on the course of SSD, oestrogen replacement therapy should be considered for postmenopausal patients, who are more vulnerable to side-effects and yet require higher dosages of most antipsychotics to reach similar efficacy. In conclusion, there is a need for tailored, female-specific prescription guidelines, which take into account adjustments required across different phases of life.

Fragmented sleep relates to hallucinations across perceptual modalities in the general population.

Although previous studies reported a link between sleep problems and the occurrence of hallucinations, more detailed information is needed to translate this association into clinical practice. This study investigates sleep quality and its relation to prevalence, type, content, and phenomenology of hallucinations, using an online survey in a large population sample (n = 10,299). Based on community-based cluster analysis, four groups could be distinguished that differed in terms of sleep quality. Our results confirm previous studies in showing that poor sleep is associated with the occurrence of hallucinations, and extend previous results on a number of aspects. First, we show that particularly fragmented sleep relates to the occurrence of hallucinations. Second, we show that this is the case for hallucinations across the auditory, visual, olfactory, and tactile domains. Third, our results show that fragmented sleep not only relates to the occurrence, but also to the content, frequency, duration, and associated distress of hallucinations. Finally, compared to poor sleep, good sleep quality is associated with hallucinations that are less negative and disruptive. We conclude that sleep hygiene measures could have a large positive impact on individuals whose fragmented sleep underlies the occurrence of bothersome hallucinations.

Estrogens in schizophrenia: progress, current challenges and opportunities.

PURPOSE OF REVIEW: Schizophrenia is a heterogeneous psychiatric disorder with a different, but not necessarily milder clinical presentation in women as compared to men. These sex differences have largely been attributed to the protective role of estrogens. This article reviews the current state of estrogen research in schizophrenia. RECENT FINDINGS: Estrogens regulate important pathophysiological pathways in schizophrenia, including dopamine activity, mitochondrial function, and the stress system. Estrogen deficiency is common in both sexes and is associated with increases in psychotic symptoms. Hyperprolactinemia causes secondary estrogen deficiency and can be a reaction to stress, or secondary to prolactin-raising antipsychotics. Therefore, prolactin-sparing antipsychotics should be preferred especially in premenopausal women, who are more prone to hyperprolactinemia. Premenopausal women furthermore require lower doses of antipsychotics than men, since estrogens raise the availability and efficacy of antipsychotics. SUMMARY: The past years have established the importance of estrogens in the pathophysiology of schizophrenia and have shown its relevance to clinical practice through its influence on antipsychotic drug efficacy. Future research should focus on the neurobiological and clinical effect of contraceptives in premenopausal women with schizophrenia. Furthermore, the potential of estrogen-like augmentation with raloxifene and phytoestrogens in schizophrenia should be established in the coming years.

Raloxifene augmentation in men and women with a schizophrenia spectrum disorder: A study protocol.

Although acute psychotic symptoms are often reduced by antipsychotic treatment, many patients with schizophrenia are impaired in daily functioning due to the persistence of negative and cognitive symptoms. Raloxifene, a Selective Estrogen Receptor Modulator (SERM) has been shown to be an effective adjunctive treatment in schizophrenia. Yet, there is a paucity in evidence for raloxifene efficacy in men and premenopausal women. We report the design of a study that aims to replicate earlier findings concerning the efficacy of raloxifene augmentation in reducing persisting symptoms and cognitive impairment in postmenopausal women, and to extend these findings to a male and peri/premenopausal population of patients with schizophrenia. The study is a multisite, placebo-controlled, double-blind, randomised clinical trial in approximately 110 adult men and women with schizophrenia. Participants are randomised 1:1 to adjunctive raloxifene 120 mg or placebo daily during 12 weeks. The treatment phase includes measurements at three time points (week 0, 6 and 12), followed by a follow-up period of two years. The primary outcome measure is change in symptom severity, as measured with the Positive and Negative Syndrome Scale (PANSS), and cognition, as measured with the Brief Assessment of Cognition in Schizophrenia (BACS). Secondary outcome measures include social functioning and quality of life. Genetic, hormonal and inflammatory biomarkers are measured to assess potential associations with treatment effects. If it becomes apparent that raloxifene reduces psychotic symptoms and/or improves cognition, social functioning and/or quality of life as compared to placebo, implementation of raloxifene in clinical psychiatric practice can be considered.

Anomalies in language as a biomarker for schizophrenia.

PURPOSE OF REVIEW: After more than a century of neuroscience research, reproducible, clinically relevant biomarkers for schizophrenia have not yet been established. This article reviews current advances in evaluating the use of language as a diagnostic or prognostic tool in schizophrenia. RECENT FINDINGS: The development of computational linguistic tools to quantify language disturbances is rapidly gaining ground in the field of schizophrenia research. Current applications are the use of semantic space models and acoustic analyses focused on phonetic markers. These features are used in machine learning models to distinguish patients with schizophrenia from healthy controls or to predict conversion to psychosis in high-risk groups, reaching accuracy scores (generally ranging from 80 to 90%) that exceed clinical raters. Other potential applications for a language biomarker in schizophrenia are monitoring of side effects, differential diagnostics and relapse prevention. SUMMARY: Language disturbances are a key feature of schizophrenia. Although in its early stages, the emerging field of research focused on computational linguistics suggests an important role for language analyses in the diagnosis and prognosis of schizophrenia. Spoken language as a biomarker for schizophrenia has important advantages because it can be objectively and reproducibly quantified. Furthermore, language analyses are low-cost, time efficient and noninvasive in nature.

Atopy Increases Risk of Psychotic Experiences: A Large Population-Based Study.

Introduction: Building upon the comorbidity between atopy and schizophrenia, we conducted a large cross-sectional, observational population-based study to examine if such associations also exist between atopic disorders (eczema, allergic rhinitis, and asthma) and nonclinical psychotic experiences. Methods: We examined psychotic experiences in a Dutch population sample through an online survey (≥14 years of age). Participants filled out the Questionnaire for Psychotic Experiences, together with questions screening for atopic disorders (eczema, allergic rhinitis, and asthma). Prevalence rates were calculated; binary logistic regression was used to determine odds ratios (ORs) (age, gender, and years of education as covariates). Results: We included 6,479 participants. Individuals diagnosed with one or more atopic disorders had an increased risk of psychotic experiences as compared with controls (OR = 1.26). Analysis of individual symptoms revealed an OR of 1.27 for hallucinations, whereas delusions only showed a trend. With each additional atopic disorder, the risk of psychotic experiences increased. This was also observed for hallucinations alone but not for delusions alone. Atopy was associated with hallucinations across all modalities (OR ranging from 1.19 to 1.40). These results did not appear to be driven specifically by any one of the atopic disorders. Conclusion: In the largest population sample of adolescents and adults to date, we found that atopic disorders (asthma, eczema, and allergic rhinitis) increase the risk of psychotic experiences, in a dose-response fashion. These results provide further support for the role of immunological components in the predisposition for psychosis and can serve as a base for further research.