Assessment of Psychiatric Symptomatology in Bilingual Psychotic Patients: A Systematic Review and Meta-Analysis

Erkoreka, Leire; Ozamiz-Etxebarria, Naiara; Ruiz, O. Arbeo; Ballesteros, Javier

doi:10.3390/ijerph17114137

Cited by 7 publications

(3 citation statements)

References 36 publications

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“…Our study comprised predominantly English-speaking participants, but some cohorts included French-, Dutch-, and German-speaking participants. Limited research is available on whether language affects reporting of psychiatric symptomatology (Erkoreka et al, 2020). Participants might have undergone evaluation at different points in time in relation to the timing of suicidal behaviors or thoughts, and recall bias could lower the concordance between instruments.…”

Section: Discussionmentioning

confidence: 99%

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

Campos¹,

Velzen²,

Veltman³

et al. 2023

Neuropsychology

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Objective: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. Method: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA–Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. Results: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15–0.97; r range: 0.21–0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. Conclusions: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality.

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Section: Discussionmentioning

confidence: 99%

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

Campos¹,

Velzen²,

Veltman³

et al. 2023

Neuropsychology

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“…The diagnosis of mental health and neurodegenerative disorders is an intricate and multifaceted process, which traditionally involves a combination of clinical evaluation, neuropsychological testing, biomarker analysis, and neuroimaging techniques. Clinicians rely on structured interviews and standardized questionnaires [23] to ascertain the presence of symptomatology consistent with diagnostic criteria, such as those outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM) [17] or the International Classification of Diseases (ICD). Neuropsychological assessments [78] provide a quantitative measure of cognitive functions, including memory, attention, language, and executive function, which can be indicative of specific neurocognitive disorders.…”

Section: Existing Methods Of Mental Health and Neurogenerative Disord...mentioning

confidence: 99%

Precognition of mental health and neurogenerative disorders using AI-parsed text and sentiment analysis

Biró,

Cuesta-Vargas,

Szilágyi

2023

Acta Universitatis Sapientiae, Informatica

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The paper examines the potential of artificial intelligence (AI) in parsing text and conducting sentiment analysis to identify early markers of mental health and neurodegenerative disorders. Through the analysis of textual data, we investigate whether AI can provide a noninvasive, continuous, and objective complement to traditional diagnostic practices. Background: the early detection of mental health (such as depression, anxiety, psychotic disorders, Alzheimer’s disease and dementia) and neurodegenerative disorders (like Parkinson’s disease) remains a critical challenge in clinical practice. Traditional diagnostic methods rely on clinical evaluations that may be subjective and episodic. Recent advancements in AI and natural language processing (NLP) have opened new avenues for precognitive health assessments, suggesting that variations in language and expressed sentiments in written text can serve as potential biomarkers for these conditions. Materials and Methods: the research used a dataset comprising various forms of textual data, including anonymized social media interactions, transcripts from patient interviews, and electronic health records. NLP algorithms were deployed to parse the text, and machine learning models were trained to identify language patterns and sentiment changes. The study also incorporated a sentiment analysis to gauge emotional expression, a key component of mental health diagnostics. Results: the AI models were able to identify language use patterns and sentiment shifts that correlated with clinically validated instances of mental health symptoms and neurodegenerative conditions. Notably, the models detected an increased use of negative a ect words, a higher frequency of first-person singular pronouns, and a decrease in future tense in individuals with depression. For neurode-generative conditions, there was a notable decline in language complexity and semantic coherence over time. Conclusions: the implemented pipeline of AI-parsed text and sentiment analysis appears to be a promising tool for the early detection and ongoing monitoring of mental health and neurodegenerative disorders. However, these methods are supplementary and cannot replace the nuanced clinical evaluation process. Future research must refine the AI algorithms to account for linguistic diversity and context, while also addressing ethical considerations regarding data use and privacy. The integration of AI tools in clinical settings necessitates a multidisciplinary approach, ensuring that technological advancements align with patient-centered care and ethical standards.

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“…It has been hypothesized that schizophrenia arose as a manifestation of the genetic evolution towards the capacity for language (Berlim, Mattevi, Belmonte-de-Abreu, & Crow, 2003), and disruptions in discourse are a key feature of thought disorder (Covington et al, 2005). Among people who are bilingual, the clinical presentation of psychotic symptoms may differ based on the language used for assessment, with more severe symptoms present when assessments are in the first language (Erkoreka, Ozamiz-Etxebarria, Ruiz, & Ballesteros, 2020). Advances in linguistic computational approaches suggest that language abnormalities are a potential biomarker for diagnosis and prognosis of psychotic disorders (De Boer, Brederoo, Voppel, & Sommer, 2020).…”

Section: Introductionmentioning

confidence: 99%

Lost in translation? Deciphering the role of language differences in the excess risk of psychosis among migrant groups

Anderson,

Khan,

Edwards

et al. 2024

Psychol. Med.

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Background Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups. Methods Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992–2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors. Results Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01–1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06–1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates. Conclusion We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.

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Assessment of Psychiatric Symptomatology in Bilingual Psychotic Patients: A Systematic Review and Meta-Analysis

Cited by 7 publications

References 36 publications

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

Precognition of mental health and neurogenerative disorders using AI-parsed text and sentiment analysis

Lost in translation? Deciphering the role of language differences in the excess risk of psychosis among migrant groups

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