Diglossia Correlates With Prodromal Symptoms of Psychosis Among First-Generation Migrants
Department of Anatomy, School of Medicine, Trinity College Dublin, Dublin, Ireland
Department of Psychiatry, Kuwait Center for Mental Health, Asimah, Kuwait
Department of Surgery, Farwaniya Hospital, Farwaniya, Kuwait
Department of Special Education, The Public Authority for Applied Education and Training, Farwaniya, Kuwait
Department of Psychiatry, Kuwait Center for Mental Health, Asimah, Kuwait
Abstract
Background and Hypothesis
We have previously hypothesized that diglossia may be a risk factor for psychosis, drawing from observations on migration, ethnicity, social adversity, and language disturbances among others. However, empirical data on this association and the tools necessary for its measurement are limited.
Study Design
In a cross-sectional online sample of first-generation migrants residing in majority English-speaking countries, a response-based decision tree was introduced to classify the sociolinguistic profiles of 1497 participants as either with or without diglossia. Using multivariate logistic regression, the association of diglossia with psychosis risk screening outcomes in the Prodromal Questionnaire-16 was calculated, adjusting for demographic and linguistic confounders. Differences in the symptom categories endorsed between the 2 groups were also examined.
Study Results
Diglossia was identified in 18.4% of participants and was associated with an adjusted odds ratio of 2.58 for a positive risk screening outcome. Other significant factors included subjective social status, hearing difficulty, age, sex, country of residence, education level, and cannabis consumption. The effects of ethnicity, age at migration, fluency, relationship, and employment status were no more significant in the multivariate model. Finally, the largest differences in the proportion of positively responding participants between the two groups were found in symptoms relating to thought insertion and thought broadcasting.
Conclusions
In a sociolinguistic hierarchical framework, diglossia is correlated with prodromal symptoms of psychosis in first-generation migrants.
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Keywords: language, diglossia, ethnicity, prodromal symptoms of psychosis, hearing difficulty, cannabis
Article notes
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Collection date 2022 Jan.
Introduction
In a sympathetic exchange during Freud’s newfound fate in exile, a fellow psychoanalyst, de Saussure, attempts to vicariously describe the adversities of life as a migrant.1 The former replies: “Everything you say is correct, but you have left out that one thing which the emigrant feels as particularly painful. It is—one can only say: The loss of the language in which one has lived and thought and which, despite all efforts to empathize, one will never be able to replace with another.” 2
Migrants are up to 3 times more likely to develop psychosis than natives.3 In pursuit of an explanatory basis, the elevated risk was found to persist despite adjustments for potentially heightened, yet nonspecific exposures, such as socioeconomic disadvantage,3 cannabis misuse,4 ethnicities,5 and urbanicity6 among a range of psychosocial stressors corresponding to the general population. However, distinctive to migrants are the experiences that may discouragingly be seen as the inevitable conflicts of old and new, or the familiar and unfamiliar.7 Language is pertinent to this proposition not only as a source of mismatch, but also due to its theorized influence on thought and perception.8 It is perhaps of no coincidence that schizophrenia, a disorder of thought and perception, is intertwined with language on multiple levels, including the phenomenological,9 the developmental,10 and potentially the diagnostic through natural language processing methods.11
On the etiological front, we have proposed that diglossia, a sociolinguistic phenomenon, may be a risk factor for schizophrenia or a common denominator behind some of its observations; These include associations with language disturbances, migration, urbanicity, ethnicity, and social adversity, as well as potential neuroanatomical correlates with the functional laterality of language.12 Despite limitations, efforts have since shown that sociolinguistic factors may indeed play a role in psychosis.13 In particular, a binary measure of linguistic distance combining the historical divergence between the first and second languages of migrants with fluency in the latter, was investigated with conflicting results,14,15 necessitating a closer investigation of the sociolinguistic elements, if any.16
Diglossia refers to the context in which there is a functional difference in the use of 2 (or more) language forms, such that a (H)igh form is preferred for formal, relatively important functions in education, employment, and politics, whilst a (L)ow form is reserved for informal, familiar settings as in daily discourse with family and friends.17,18 Besides differentiation in function and prestige, the 2 language forms vary in the conditions of their acquisition; Although naturally acquired as a first language or dialect early in life, the more familiar L becomes an obstacle to educational, linguistic, and socioeconomic progression.19 On the other hand, H is later encountered in an imposed setting such as schooling, or migration in this instance, as the key towards social and professional gain.20 While this H-L relationship is straightforwardly appreciable with dialects in the face of a national standard,21 the introduction of an entirely different language in bilingualism brings an important consideration, in which the additional language may instead be perceived as desirable or advantageous for higher societal functions.22 The differential mechanisms by which some foreign languages are met with social and institutional resistance while others are seen to hold value are speculative, but the interlinguistic context of the latter scenario lacks the H-L sociocultural compartmentalization which is characteristic of diglossia. As such, a hierarchical relationship in which the mother tongue contends unfavorably with a prestigious, imposed, and socially desired language summarizes the individual experience of diglossia.23
This phenomenon arises from the temporal and spatial linguistic changes in communities in the face of a resistant and highly codified standard, which lead to notable differences in pronunciation, vocabulary, and grammar.24 This can become the baseline sociolinguistic situation as in Arabic-speaking countries,25 or can be associated with specific ethnic or regional communities as is the case with African-American Vernacular English.26,27 It can also be a consequence of transcultural events such as migration, giving rise to linguistic discordance in the first instance, and possibly the eventual formation of stable multiethnolects in association with urbanicity, as is the case with the Multicultural London English dialect.28,29 Within this theoretical framework, this study seeks to introduce a measure of diglossia and preliminarily examine its relationship with the prodromal symptoms of psychosis in first-generation migrants.
Methods
Participants
In a cross-sectional survey, participants were recruited from an online crowdsourcing platform (Prolific Academic) which pre-selects participants based on previously given responses. To target a pool of first-generation migrants, the survey was made available to participants who have indicated that they currently reside in an English-majority speaking country, and that they have moved to the country they are now living in. A balanced sample of males and females was prespecified. Further requirements of the platform include acceptable fluency in English, an age of 18 years or older, and residence in an OECD country. The survey was made available to eligible participants who opted in on a first-come, first-served basis over a duration of 2 days as the required sample size was reached. Their migrant status and residence in a majority English-speaking area were confirmed within the questionnaire. Each participant received a token of ~1$ following the completion of the questionnaire as per the platform’s policy. Responses were fully anonymous to further promote genuine self-reporting.
The sociodemographic variables included age, sex, country of residence, ethnicity, the highest level of education, employment status, long-term relationship (>1 year), and cannabis consumption as covariates. Potentially important language-related confounders included age at migration, self-rated fluency in the majority language (English), and hearing difficulty. Subjective social status was obtained using the McArthur scale30 as a correlate of socioeconomic status across different countries and currencies.31 The participant is shown a symbolic picture of the “social ladder” and asked to place themselves on the steps numbered 1 to 10 based on their relative judgment of personal socioeconomic indicators such as wealth, education, and employment. Beyond its correlation with objective socioeconomic measures, the scale was shown to be independently associated with general health,31,32 and more recently with mental disorders across the DSM-IV.33
The Prodromal Questionnaire
The Prodromal Questionnaire-16 (PQ-16) is a self-reported screening tool for psychosis risk which consists of 16 True/False statements.34 To enable widespread use, the 16 items were condensed from the original 92-item questionnaire on the basis of predictive validity.35 A cutoff score of 6 or more endorsed items constitutes a positive screening outcome that warrants further assessment with high sensitivity (87%) and specificity (87%) for at-risk mental states.34 It has since been validated in various languages and settings,36 including the general non-help-seeking and online populations.37 The threshold score of 6 or more items was used as the main binary outcome measure of this study to calculate and test the classification tree proportions of potentially at-risk participants, and perform logistic regression analyses.38 The PQ-16 in this study demonstrated good internal consistency with Cronbach’s α = 0.80, as also reported in the original study.34
A Measure for Diglossia
Given the lack of previous tools for capturing diglossia, a response-based decision tree for individual classification was contextualized from Fishman’s account of the 4 sociolinguistic speech profiles enumerated thereafter.18 Firstly, to establish if there is any functional differentiation of language forms, participants were provided 3 options to the question: “How different is the way you speak at home (eg, with family) from the preferred language in formal settings (eg, in work/ school)?.” Those who responded with “No difference—I speak the same language” were considered unexposed: “(1) Neither diglossia nor bilingualism.” To factor in exposure due to dialectic variation, an option for “Some difference—I speak in a different dialect,” along with “Complete difference—I speak a different language” constituted a positive response for functional differentiation. A dialect was prior defined with examples in an attention-checking question as “a variety of a language with different pronunciation, words, and grammar from other forms of the same language.” 39 Next, those who have indicated English as their first language among the exposed group were classified into, “(2) Diglossia without bilingualism.” Finally, to distinguish those with a potentially advantageous non-English first language, “(3) Bilingualism without diglossia,” from those with an unfavorable “L” language as a prerequisite for, and “(4) Diglossia with bilingualism,” they were asked, “Do you feel that your first language puts you at a disadvantage in terms of life opportunities (eg, work/ school)?.” The decision tree resulted in 2 final groups of participants with and without diglossia (figure 1). To facilitate the classification process and verify significant differences in the proportions of participants meeting the threshold of ≥6 PQ-16 items in each dichotomy, an Interactive Chi-Squared Automatic Interaction Detection (CHAID) model was used (SPSS Modeler version 18.2.1, IBM Corp., Armonk, N.Y., USA).
Pilot and Sample Size Estimation
The questionnaire was administered to a pilot of 50 participants to estimate the required sample size and optimize the clarity and understandability of the items according to feedback. Beyond the inclusion of attention-checking questions, no major changes were subsequently made. Calculation of the sample size estimate was performed on G*Power software (version 3.1.9.6) using Demidenko’s method for logistic regression.40 Out of the 50 participants, 11(22%) were classified with diglossia, 4(36.4%) of whom satisfied the PQ-16 cutoff score for a positive screening outcome. Out of the 39(78%) remaining participants without diglossia, 10(25.6%) met the PQ-16 cutoff score. In addition, 10% of the variability was assumed to be explained by other predictors as approximated by the preliminary regression model. This yielded an odds ratio of 1.66 as the estimated effect size. The required sample size to detect this effect with 95% power at an alpha of 0.05 was 1471 participants. The questionnaire was made available to 1500 participants, with 3 duplicate entries removed following the data collection leaving a total of 1497 participants in the analysis.
Data Analysis
Data analysis were performed using Minitab 19 (Minitab LLC, PA USA) and figures were illustrated using Graphpad Prism 9. Descriptive statistics shown in table 1 for the 1497 participants according to sociolinguistic profile (with and without diglossia) employ the median, interquartile range, frequency, and percentage as appropriate. Differences between the 2 groups for each of the variables were tested using chi-squared tests (χ2) for categorical variables and the Mann-Whitney test for numeric variables (table 1). Significance testing was performed at the 0.05 error level. In addition, univariate and multivariate logistic regression analyses were carried out to assess the relationship of the sociodemographic predictors with the risk screening outcome (PQ-16 score ≥6) as the binary dependent variable. Lack of multicollinearity between the predictors was verified using the Variance Inflation Factor (VIF) with a range of 1.06–2.07. The odds ratios (OR) and 95% Confidence Intervals (95% CI) for each of the predictors are reported. Lastly, the percentages of participants with and without diglossia who positively endorsed each of the PQ-16 items are presented.
| Variable | Without Diglossia N = 1221 | With Diglossia N = 276 | Total N = 1497 | χ2/MWU; P-value | ||||
|---|---|---|---|---|---|---|---|---|
| F | % | F | % | F | % | |||
| Current residence | - The United Kingdom | 446 | 36.5% | 115 | 41.7% | 561 | 37.5% | .0646 |
| - The United States | 407 | 33.3% | 69 | 25.0% | 476 | 31.8% | ||
| - Canada | 208 | 17.0% | 63 | 22.8% | 271 | 18.1% | ||
| - Australia | 99 | 8.1% | 23 | 8.3% | 122 | 8.1% | ||
| - New Zealand | 35 | 2.9% | 3 | 1.1% | 38 | 2.5% | ||
| - Ireland | 26 | 2.1% | 3 | 1.1% | 29 | 1.9% | ||
| Age | Median [IQR] | 31[24–40] | 31[24–37] | 31[24–39] | .1411 | |||
| Age-at-migration | Median [IQR] | 18[7–26] | 21[15–28] | 18[8–26] | <.0001 | |||
| Sex | Female | 598 | 49.0% | 153 | 55.4% | 751 | 50.2% | .0526 |
| Male | 623 | 51.0% | 123 | 44.6% | 746 | 49.8% | ||
| Ethnicity | White | 510 | 41.8% | 104 | 37.7% | 614 | 41.0% | <.0001 |
| Asian | 422 | 34.6% | 92 | 33.3% | 514 | 34.3% | ||
| Black | 99 | 8.1% | 50 | 18.1% | 149 | 10.0% | ||
| Latino | 79 | 6.5% | 10 | 3.6% | 89 | 5.9% | ||
| Middle Eastern/ Arab | 53 | 4.3% | 6 | 2.2% | 59 | 3.9% | ||
| Mixed | 24 | 2.0% | 7 | 2.5% | 31 | 2.1% | ||
| Other | 34 | 2.8% | 7 | 2.5% | 41 | 2.7% | ||
| Education | - Postgraduate degree | 334 | 27.4% | 97 | 35.1% | 431 | 28.8% | .0813 |
| - Undergraduate degree | 482 | 39.5% | 97 | 35.1% | 579 | 38.7% | ||
| - Technical & Vocational | 164 | 13.4% | 32 | 11.6% | 196 | 13.1% | ||
| - School education | 241 | 19.7% | 50 | 18.1% | 291 | 19.4% | ||
| Relationship | No | 283 | 23.2% | 62 | 22.5% | 345 | 23.0% | .7992 |
| Yes | 938 | 76.8% | 214 | 77.5% | 1152 | 77.0% | ||
| Employment | Employed | 792 | 64.9% | 184 | 66.7% | 976 | 65.2% | .2711 |
| Student/ In training | 252 | 20.6% | 62 | 22.5% | 314 | 21.0% | ||
| Unemployed | 177 | 14.5% | 30 | 10.9% | 207 | 13.8% | ||
| Hearing difficulty | No | 1177 | 96.4% | 258 | 93.5% | 1435 | 95.9% | .0280 |
| Yes | 44 | 3.6% | 18 | 6.5% | 62 | 4.1% | ||
| Cannabis consumption | Never | 729 | 59.7% | 156 | 56.5% | 885 | 59.1% | .3313 |
| Ever | 492 | 40.3% | 120 | 43.5% | 612 | 40.9% | ||
| English fluency | Median [IQR] | 10[9–10] | 10[8–10] | 10[9–10] | .0025 | |||
| Subjective social status | Median [IQR] | 6[5–7] | 6[5–7] | 6[5–7] | .2286 | |||
| PQ-16 total score | Median [IQR] | 2[1–5] | 4[2–7] | 3[1–5] | <.0001 | |||
| Risk screening outcome (PQ-16 Cutoff ≥6) | Negative | 997 | 81.7% | 172 | 62.3% | 1169 | 78.1% | <.0001 |
| Positive | 224 | 18.3% | 104 | 37.7% | 328 | 21.9% |
Ethical Approval
Approval was obtained from the ethical review board of the Ministry of Health, Kuwait (1889/2021). Informed consent was obtained prior to the completion of the survey.
Results
A total of 1497 participants were migrants from 124 different countries with 75 first language varieties. Most participants were current residents of the United Kingdom (37.5%) or the United States (31.8%), with a median age of 31, and age at the migration of 18 years. The proportion of males (49.8%) and females (50.2%) was almost equal. The most common ethnicities were White (41%) and Asian (34.3%). In addition, most were employed (65.2%), have been in a relationship lasting 1 year or longer (77%), obtained at least an undergraduate degree (67.5%), and never consumed cannabis (59.1%). Self-rated fluency in English was reported with a median of 10, and a subjective social status median of 6. Participants with hearing loss comprised 4.1% of the sample. Overall, the median PQ-16 score was 3, with 328 participants (21.9%) noted as having endorsed the cutoff score of 6 or more items indicating a positive screening outcome. table 1 displays the characteristics of the total study sample and according to the sociolinguistic profile (with vs without diglossia).
Out of the 1497 participants, 276 (18.4%) were classified with diglossia, and 1221 (81.6%) without. The 2 groups were similar in composition with regard to their current residence, age, sex, education level, relationship status, employment status, subjective social status, and history of cannabis consumption (P > .05). A significant difference was observed between the proportions of their ethnicities (P < .0001); Black ethnicity was the largest contributor to this difference, comprising 18.1% of those with diglossia and only 8.1% of those without. All remaining differences in ethnicity proportions were less than 5 percentage points between the 2 groups. Participants with diglossia were less fluent in English, older of age-at-migration, and more likely to have reported hearing difficulty (P < .05). The median PQ-16 score for those with diglossia was 4[IQR 2–7], compared to 2[IQR 1–5] for those without diglossia (P < .0001). The difference in the distribution of the total PQ-16 scores between the 2 groups is illustrated in figure 2. In addition, 37.7% of participants with diglossia endorsed the PQ-16 cutoff score, compared to 18.3% of participants without diglossia (P < .0001).
Table 2 lists each of the variables’ association with the screening outcome (PQ-16 score ≥6) as the dependent variable firstly in a univariate logistic regression analysis, followed by a multivariate model incorporating diglossia as an independent variable, along with the confounding variables of age, age-at-migration, sex, country of residence, ethnicity, the highest level of education, employment status, subjective social status, long-term relationship (>1 year), cannabis consumption, English fluency, and hearing difficulty. In the unadjusted univariate analysis, diglossia was significantly predictive of satisfying the PQ-16 threshold, along with decreasing age and age-at-migration, female sex, ethnicity (Black, Middle Eastern/Arab, and “Other”), Education (Technical & vocational/School education), Employment status (Student/In training), hearing difficulty, cannabis consumption, and a lower subjective social status. Following adjustment for confounders in the multivariate model, diglossia remained a highly significant predictor (adj. OR, 2.58). The significant OR also persisted for age (adj. OR, 0.96), female sex (adj. OR, 1.41), education (adj. OR, 1.89), hearing difficulty (adj. OR, 3.31), subjective social status (adj. OR, 0.80) and cannabis consumption (adj. OR, 1.37). The effects of age at migration, ethnicity, relationship, and employment status were no longer significant. Self-rated fluency in English was insignificant in both analyses. Finally, residence in Australia was revealed to be associated with significantly lower odds for a positive screening outcome after adjustment when compared to the United Kingdom (adj. OR, 0.53).
| Variable [Reference] | Univariate | Multivariate | |||
|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | ||
| Current residence [vs the United Kingdom] | United States | 0.88 | (0.65, 1.18) | 0.73 | (0.52, 1.04) |
| Canada | 1.20 | (0.86, 1.68) | 0.96 | (0.65, 1.41) | |
| Australia | 0.59 | (0.34, 1.00) | 0.53 | (0.29, 0.95) | |
| New Zealand | 0.63 | (0.26, 1.55) | 0.81 | (0.31, 2.08) | |
| Ireland | 1.08 | (0.45, 2.58) | 1.09 | (0.43, 2.79) | |
| Age [years] | 0.96 | (0.94, 0.97) | 0.96 | (0.94, 0.97) | |
| Age-at-migration [years] | 0.99 | (0.97, 0.99) | 1.00 | (0.99, 1.02) | |
| Sex [vs Male] | Female | 1.54 | (1.20, 1.97) | 1.41 | (1.07, 1.86) |
| Ethnicity [vs White] | Asian | 1.08 | (0.81, 1.45) | 1.05 | (0.73, 1.52) |
| Black | 1.63 | (1.08, 2.46) | 1.33 | (0.84, 2.12) | |
| Latino | 1.54 | (0.92, 2.56) | 1.24 | (0.69, 2.21) | |
| Middle Eastern/Arab | 1.83 | (1.01, 3.29) | 1.91 | (0.99, 3.67) | |
| Mixed | 0.80 | (0.30, 2.13) | 0.64 | (0.22, 1.87) | |
| Other | 2.16 | (1.10, 4.24) | 2.09 | (0.99, 4.40) | |
| Education [vs Postgraduate degree] | Undergraduate degree | 1.35 | (0.97, 1.87) | 1.15 | (0.80, 1.65) |
| Technical & vocational | 2.29 | (1.53, 3.41) | 1.89 | (1.19, 2.99) | |
| School education | 2.36 | (1.64, 3.38) | 1.43 | (0.92, 2.22) | |
| Relationship [vs Yes] | No | 1.44 | (1.09, 1.90) | 0.94 | (0.67, 1.32) |
| Employment [vs Employed] | Student/In training | 1.80 | (1.35, 2.41) | 1.04 | (0.73, 1.49) |
| Unemployed | 1.36 | (0.95, 1.94) | 1.08 | (0.72, 1.62) | |
| Hearing difficulty [vs No] | Yes | 2.71 | (1.61, 4.56) | 3.31 | (1.80, 6.08) |
| Cannabis consumption [vs Never] | Ever | 1.42 | (1.11, 1.81) | 1.37 | (1.03, 1.81) |
| English fluency [Scale 0–10] | 1.00 | (0.90, 1.12) | 1.05 | (0.93, 1.20) | |
| Subjective social status [Scale 1–10] | 0.77 | (0.71, 0.83) | 0.80 | (0.73, 0.87) | |
| Sociolinguistic profile [vs Without diglossia] | With diglossia | 2.69 | (2.03, 3.57) | 2.58 | (1.89, 3.54) |
Finally, to gain an insight into the symptomatic differences between the 2 groups, each of the PQ-16 item categories41 was examined for the percentage of endorsing participants with and without diglossia. There was a higher percentage of positive respondents with diglossia across all 16 items, though the relative patterns of endorsement were broadly consistent; The most endorsed items in both groups pertained to absorption (déjà vu) experiences (49.6% with diglossia and 37.8% without diglossia), social anxiety (48.2% and 36.9%) and avolition (43.5% and 32.5%) (figure 3A). The largest differences between the 2 groups were found in experiences of thought insertion and thought broadcast, where an additional 14.6% and 13.6% of those with diglossia responded positively, compared to the percentage of those without diglossia (figure 3B). The smallest observed increases were in items relating to voices (4.6%) and visual symptoms (1.3%).
Discussion and Conclusions
In an online sample of migrants residing in English-speaking countries, diglossia was associated with 2.58 times higher odds of a positive prodromal screening outcome indicative of at-risk mental states for psychosis. Measurement of this association was enabled by the introduction of a response-based classification model of diglossia which incorporates dialectic variation, accounts for sociolinguistic variance in bilingualism, and possesses an integrated social component. Although mostly speculative, several theoretical and observational lines of exploration surface from these results, along with key limitations.
Firstly, by directing the classical characterization of diglossia in speech communities as a whole to the individual, the model relies on a self-ascribed method of categorization. While limited by the conceivable need for introspective ability and openness to interpretation, a personal judgment of the interplay between language forms is highlighted as an underlying determinant. These subjective, comparative, hierarchical assessments emerge as a broad theme as also indicated by the predictive effect of the McArthur scale, which although intended to be a cross-country approximate measure of socioeconomic status, has shown to be a more potent predictor than some of the more objective elements examined, such as relationship and employment status. A 1-step increase in subjective social status resulted in 20% lower odds of a positive screening outcome, keeping all else constant. In viewing language as an instrument for determining and navigating positions within social hierarchies,42–45 a tentative route for diglossia in dopaminergic dysregulation is envisaged; Parallels can be drawn with the neurotransmitter’s roles in the establishment and maintenance of social hierarchical structures,46–49 language novelty and acquisition,50–52 as well as it’s an asymmetrical activity in driving the functional hemispheric lateralization of language production.53,54
Secondly, diglossia is a socially conditional exposure in this hierarchical framework; Only in relation to another language does one’s naturally acquired features of language use constitute an exposure, which implicates settings of intergroup communication with an H language as a prerequisite, and social withdrawal as an adaptive avoidance strategy.55,56 Furthermore, evidence refuting pre-migratory explanations in favor of post-migratory environmental factors57 is consistent with the conditional context of diglossia. Although not investigated in this study, diglossia can also be a persistent exposure across generations as a viable explanation of the elevated risk for schizophrenia in both first- and second-generation migrants,58 given the dynamics of language acquisition in children from their parents.59 The effect of diglossia persisted after adjusting for language-related covariates including age-at-migration, fluency, and ethnicity which were insignificant in explaining any of the outcome variation. However, the sample was insufficiently powered to detect small differences between 7 categories of ethnicity, and an adequate level of fluency was a requirement for users of the survey platform. This may have underestimated both the proportion of diglossic participants and the perceived risk of diglossia, given their slightly lower fluency and recent evidence on the effect of majority-language proficiency on psychosis risk from a retrospective study of 2 million migrants.60 As such, fluency in the majority language as an indicator of language impediment in the traditional sense, did not appear to be a determining factor in this study. Other significant sociodemographic variables included age, education level, and cannabis consumption, as already established in the literature. In addition, country-level differences (Australia vs UK adj. OR 0.53) may involve any of a wide a range of immigrational, social, and health policies61 in the differential psychosis risk for migrants. Out of keeping with the literature is the higher odds of a positive screening outcome in females (adj. OR 1.41), which brings into question either the generalizability of the sample or the measurement tool; The PQ-16 produces greater sensitivity for psychosis risk in females perhaps owing to the predominance of positive symptoms reflected by the items.35 Although some studies have identified a lower language proficiency at migration among females in comparison with males, the evidence of a potential interplay between gender differences in language proficiency and mental disorders remains insufficient.62 Notably, the significantly higher odds ratio for females in this study persists despite adjustment for self-rated fluency in the multivariate model.
Thirdly, hearing difficulty at any degree also demonstrated a significantly high odds ratio for a positive screening outcome, as documented previously.63 The expandable concept of diglossia,64 for the purpose of a unifying argument at least, can perhaps be extended beyond strict descriptions of languages and dialects to include any nonstandard, yet personally familiar speech or communication mode which may be perceived as an L and is in contention with a more desirable and advantageous H language. The expressive speech impediments and overall language impairment caused by hearing difficulty may be an example of this speculation.65 The association of schizophrenia with autism spectrum disorder,66 is another likely capturable instance of this extended notion of diglossia.
Finally, a clue on diglossia’s possible contribution to psychotic experiences is presented by the largest proportional differences observed in symptoms of thought broadcast and insertion, with perceptual abnormalities affected to a lesser extent. The abstract connection of thought passivity to the hierarchical nature of diglossia may be reflective of a pathologic manifestation of linguistic relativity, in which features of the language are believed to exert an effect on processes of individual thought.67
The study is limited by using a screening tool as an efficient measure of psychosis risk in a large online sample. Future case-control or cohort studies examining established diagnoses of psychosis will be better equipped to investigate diglossia as a potential risk factor. For future validation of these findings, the utility of the presented model may also be extended to general populations in investigating the excess risk in urban areas for instance, as well as comparisons of native populations where diglossia is differentially prevalent. In conclusion, our findings on the prodromal symptoms of psychosis highlight diglossia as a potentially important sociolinguistic exposure.
Acknowledgments
None.
Contributor Information
Mohammad Alherz, Department of Anatomy, School of Medicine, Trinity College Dublin, Dublin, Ireland; Department of Psychiatry, Kuwait Center for Mental Health, Asimah, Kuwait; Department of Surgery, Farwaniya Hospital, Farwaniya, Kuwait.
Hashemiah Almusawi, Department of Special Education, The Public Authority for Applied Education and Training, Farwaniya, Kuwait.
Ammar Alsayegh, Department of Psychiatry, Kuwait Center for Mental Health, Asimah, Kuwait.
Funding
None.
Conflicts of interest
None.
References
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References
- 1.Marinelli L, Titheridge J. “Body missing” at berggasse 19. Am Imago. 2009;66(2):161–167. http://www.jstor.org/stable/26305494.
- 2.Sigmund Freud. (1922) Sigmund freud papers: general correspondence, -1996; Saussure, Raymond de, 1922 to 1928, 1938. - 1928. [Manuscript/Mixed Material] Retrieved from the Library of Congress, https://www.loc.gov/item/mss3999001136/.
- 3.Selten JP, Van Der Ven E, Termorshuizen F. Migration and psychosis: a meta-analysis of incidence studies. Psychol Med. 2020;50(2):303–313. doi: 10.1017/S0033291719000035.
- 4.Veen N, Selten JP, Hoek HW, Feller W, Van Der Graaf Y, Kahn R. Use of illicit substances in a psychosis incidence cohort: a comparison among different ethnic groups in the Netherlands. Acta Psychiatr Scand. 2002;105(6):440–443. doi: 10.1034/J.1600-0447.2002.01222.X.
- 5.Coid JW, Kirkbride JB, Barker D, et al. Raised incidence rates of all psychoses among migrant groups: findings from the East London first episode psychosis study. Arch Gen Psychiatry. 2008;65(11):1250–1258. doi: 10.1001/ARCHPSYC.65.11.1250.
- 6.Hollander AC, Dal H, Lewis G, Magnusson C, Kirkbride JB, Dalman C. Refugee migration and risk of schizophrenia and other non-affective psychoses: cohort study of 1.3 million people in Sweden. BMJ. 2016;352:1–8. doi: 10.1136/BMJ.I1030.
- 7.Oberg K. Cultural shock: adjustment to new cultural environments. Missiology: An International Review. 1960;os-7(4):177–182. doi: 10.1177/009182966000700405.
- 8.Whorf BL. Science and linguisitics. In: Carrol JB, ed. Language, Thought and Real. Vol 19(1); 1956:207–219. http://www.ncbi.nlm.nih.gov/pubmed/2714970. Cambridge, MA: MIT press. Accessed January 20, 2022.
- 9.Hinzen W, Rosselló J. The linguistics of schizophrenia: thought disturbance as language pathology across positive symptoms. Front Psychol. 2015;6:971. doi: 10.3389/fpsyg.2015.00971.
- 10.Vourdas A, Pipe R, Corrigall R, Frangou S. Increased developmental deviance and premorbid dysfunction in early onset schizophrenia. Schizophr Res. 2003;62(1–2):13–22. doi: 10.1016/S0920-9964(02)00429-2.
- 11.Corcoran CM, Cecchi GA. Using language processing and speech analysis for the identification of psychosis and other disorders. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020;5(8):770. doi: 10.1016/J.BPSC.2020.06.004.
- 12.Alherz M, Almusawi H, Barry DS. Diglossia in the etiology of schizophrenia: a hypothesis. J Nerv Ment Dis. 2019;207(11):987–992. doi: 10.1097/NMD.0000000000001067.
- 13.Jongsma HE, Gayer-Anderson C, Van Der Ven E, et al. Authors’ reply to “on the existence of a linguistic distance in schizophrenia.” Psychol Med. Published online 2020;52(4):1–2. doi: 10.1017/S0033291720003013.
- 14.Jongsma HE, Gayer-Anderson C, Tarricone I, et al. Social disadvantage, linguistic distance, ethnic minority status and first-episode psychosis: results from the EU-GEI case-control study. Psychol Med. Published online 2020;51(9):1–13. doi: 10.1017/S003329172000029X.
- 15.Garrido-Torres N, Alameda L, Cristóbal JP, et al. Examining the relationship between psychosis and immigration in Spain: the effect of cannabis use and language barrier in a large psychosis sample. J Psychiatr Res. 2022;145:361–365. doi: 10.1016/J.JPSYCHIRES.2021.11.005.
- 16.Alherz M. On the existence of a linguistic distance in schizophrenia. Psychol Med. Published online July 23, 2020; 52(4):1–2. doi: 10.1017/S0033291720002585.
- 17.Ferguson CA. Diglossia. Word. 1959;15(2):325–340. doi: 10.1080/00437956.1959.11659702.
- 18.Fishman JA. Bilingualism with and without diglossia; diglossia with and without bilingualism. J Soc Issues. 1967;23(2):29–38. doi: 10.1111/j.1540-4560.1967.tb00573.x.
- 19.Sayahi L. A moving target: literacy development in situations of diglossia and bilingualism. Arab J Appl Linguist. 2016;1(1):1–18. https://www.arjals.com/ajal/article/view/42.
- 20.Dorais LJ. Bilingualism and diglossia in the Canadian eastern arctic. Arctic. 1989;42(3):199–207. https://www.jstor.org/stable/40510821. Accessed March 4, 2022.
- 21.Auer P. Europe’s sociolinguistic unity, or: a typology of European dialect/standard constellations. In: Delbecque N, van der Auwera J, Geeraerts D, eds. Perspectives on Variation: Sociolinguistic, Historical, Comparative. Mouton de Gruyter; 2005:8–42. Berlin, Germany. doi: 10.1515/9783110909579.7.
- 22.Mehmedbegovic D. Engaging with linguistic diversity in global cities: arguing for “language hierarchy free” policy and practice in education. Open Linguist. 2017;3(1):540–553. doi: 10.1515/opli-2017-0027.
- 23.Eckert P. Diglossia: separate and unequal. Linguistics. 1980;18(11-12):1053–1064. doi: 10.1515/ling.1980.18.11-12.1053.
- 24.Khubchandani L. Diglossia revisited. Ocean Linguist. 1985;20:199–211. https://www.jstor.org/stable/20006723. Accessed March 12, 2022.
- 25.Myhill J. The effect of diglossia on literacy in Arabic and other languages. In: Saiegh-Haddad, E, Joshi, M, eds. Handbook of Arabic Literacy. Dordrecht: Springer; 2014:197–223. doi: 10.1007/978-94-017-8545-7_9.
- 26.Ogbu JU. Beyond language: ebonics, proper English, and identity in a Black-American Speech Community. Am Educ Res J. 1999;36(2):147. doi: 10.2307/1163537.
- 27.Rickford JR. Geographical diversity, residential segregation, and the vitality of African American vernacular English and its speakers. Transform Anthropol. 2010;18(1):28–34. doi: 10.1111/j.1548-7466.2010.01067.x.
- 28.Cheshire J, Nortier JM, Adger D. Emerging multiethnolects in Europe. Queen Mary’s Occas Pap Adv Linguist. 2015;33:1–27. https://dspace.library.uu.nl/handle/1874/322096.
- 29.Pauwels A. Diglossic communities in transition: the cases of the Limburgs and Swabian speech communities in Australia. Int J Soc Lang. 1988;1988(72):85–100. doi: 10.1515/ijsl.1988.72.85.
- 30.Adler N, Epel E, Castellazzo G, Ickovics J. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol. 2000;19(6):586–592. doi: 10.1037//0278-6133.19.6.586.
- 31.Adler N, Singh-Manoux A, Schwartz J, Stewart J, Matthews K, Marmot MG. Social status and health: a comparison of British civil servants in Whitehall-II with European- and African-Americans in CARDIA. Soc Sci Med. 2008;66(5):1034–1045. doi: 10.1016/J.SOCSCIMED.2007.11.031.
- 32.Miyakawa M, Magnusson Hanson LL, Theorell T, Westerlund H. Subjective social status: its determinants and association with health in the Swedish working population (the SLOSH study). Eur J Public Health. 2012;22(4):593–597. doi: 10.1093/EURPUB/CKR064.
- 33.Scott KM, Al-Hamzawi AO, Andrade LH, et al. Associations between subjective social status and DSM-IV mental disorders: results from the World Mental Health Surveys. JAMA Psychiatry. 2014;71(12):1400–1408. doi: 10.1001/JAMAPSYCHIATRY.2014.1337.
- 34.Ising HK, Veling W, Loewy RL, et al. The validity of the 16-item version of the Prodromal Questionnaire (PQ-16) to screen for ultra high risk of developing psychosis in the general help-seeking population. Schizophr Bull. 2012;38(6):1288–1296. doi: 10.1093/SCHBUL/SBS068.
- 35.de Jong Y, Mulder CL, Boon A, Coenders E, van der Gaag M. Cross validation of the Prodromal questionnaire 16-item version in an adolescent help-seeking population. Schizophr Bull Open. 2020;1(1):1–8. doi: 10.1093/SCHIZBULLOPEN/SGAA033.
- 36.Savill M, D’Ambrosio J, Cannon TD, Loewy RL. Psychosis-risk screening in different populations using the Prodromal Questionnaire - a systematic review. Early Interv Psychiatry. 2018;12(1):3. doi: 10.1111/EIP.12446.
- 37.McDonald M, Christoforidou E, Van Rijsbergen N, et al. Using online screening in the general population to detect participants at clinical high-risk for psychosis. Schizophr Bull. 2019;45(3):600. doi: 10.1093/SCHBUL/SBY069.
- 38.Clarke S, Hanna D, Davidson S, Shannon C, Mulholland C. The association between sleep quality and attenuated psychotic symptoms. Early Interv Psychiatry. 2021;15(4):837–848. doi: 10.1111/EIP.13020.
- 39.Oxford Dictionary. Dialect noun - Definition, pictures, pronunciation and usage notes | Oxford Advanced Learner’s Dictionary. Oxford Advanced Learner’s Dictionary. Published 2022. https://www.oxfordlearnersdictionaries.com/definition/english/dialect. Accessed March 28, 2022.
- 40.Demidenko E. Sample size determination for logistic regression revisited. Stat Med. 2007;26(18):3385–3397. doi: 10.1002/SIM.2771.
- 41.Cosgrave J, Haines R, van Heugten-van der Kloet D, et al. The interaction between subclinical psychotic experiences, insomnia and objective measures of sleep. Schizophr Res. 2018;193:204. doi: 10.1016/J.SCHRES.2017.06.058.
- 42.Lupyan G, Dale R. Language structure is partly determined by social structure. PLoS One. 2010;5(1):1–10. doi: 10.1371/JOURNAL.PONE.0008559.
- 43.Luhman R. On language use and social structure. Stud Socioling. 1973;9(2):97–125. https://www.jstor.org/stable/23255195. Accessed March 12, 2022.
- 44.Guy GR. Language, social class, and status. In: Mesthrie R, ed. The Cambridge Handbook of Sociolinguistics. Cambridge Handbooks in Language and Linguistics. Cambridge: Cambridge University Press; 2011:159–185. doi: 10.1017/CBO9780511997068.015.
- 45.Mallinson C. Social class, social status, and stratification: revisiting familiar concepts in sociolinguistics. Univ Pennsylvania Work Pap Linguist. 2007;13(2):149–163. https://repository.upenn.edu/pwpl/vol13/iss2/12/. Accessed March 25, 2022.
- 46.Cervenka S, Gustavsson JP, Halldin C, Farde L. Association between striatal and extrastriatal dopamine D2-receptor binding and social desirability. Neuroimage. 2010;50(1):323–328. doi: 10.1016/J.NEUROIMAGE.2009.12.006.
- 47.Yamaguchi Y, Lee YA, Goto Y. Dopamine in socioecological and evolutionary perspectives: implications for psychiatric disorders. Front Neurosci. 2015;9:219. doi: 10.3389/fnins.2015.00219.
- 48.Roy-Byrne P. Dopamine Levels and Social Dominance. NEJM J Watch. Published online 2002. https://www.jwatch.org/jp200204250000004/2002/04/25/dopamine-levels-and-social-dominance. Accessed March 25, 2022.
- 49.Amaral IM, Hofer A, Rawas RE. Is it possible to shift from down to top rank? A focus on the Mesolimbic Dopaminergic system and cocaine abuse. Biomedicines. 2021;9(8):1–13. doi: 10.3390/BIOMEDICINES9080877.
- 50.Shellshear L, Macdonald AD, Mahoney J, et al. Levodopa enhances explicit new-word learning in healthy adults: a preliminary study. Hum Psychopharmacol. 2015;30(5):341–349. doi: 10.1002/HUP.2480.
- 51.Ripollés P, Ferreri L, Mas-Herrero E, et al. Intrinsically regulated learning is modulated by synaptic dopamine signaling. Elife. 2018;7:1–23. doi: 10.7554/ELIFE.38113.
- 52.Wong PCM, Morgan-Short K, Ettlinger M, Zheng J. Linking neurogenetics and individual differences in language learning: the dopamine hypothesis. Cortex. 2012;48(9):1091. doi: 10.1016/J.CORTEX.2012.03.017.
- 53.Fuertinger S, Zinn JC, Sharan AD, Hamzei-Sichani F, Simonyan K. Dopamine drives left-hemispheric lateralization of neural networks during human speech. J Comp Neurol. 2018;526(5):920–931. doi: 10.1002/cne.24375.
- 54.Hull R, Vaid J. Bilingual language lateralization: a meta-analytic tale of two hemispheres. Neuropsychologia. 2007;45(9):1987–2008. doi: 10.1016/J.NEUROPSYCHOLOGIA.2007.03.002.
- 55.Palaniyappan L, Venkatasubramanian G. The Bayesian brain and cooperative communication in schizophrenia. J Psychiatry Neurosci. 2022;47(1):E48–E54. doi: 10.1503/JPN.210231.
- 56.Ike KGO, de Boer SF, Buwalda B, Kas MJH. Social withdrawal: an initially adaptive behavior that becomes maladaptive when expressed excessively. Neurosci Biobehav Rev. 2020;116:251–267. doi: 10.1016/J.NEUBIOREV.2020.06.030.
- 57.Morgan C, Charalambides M, Hutchinson G, Murray RM. Migration, ethnicity, and psychosis: toward a sociodevelopmental model. Schizophr Bull. 2010;36(4):655–664. doi: 10.1093/SCHBUL/SBQ051.
- 58.Bourque F, Van Der Ven E, Malla A. A meta-analysis of the risk for psychotic disorders among first- and second-generation immigrants. Psychol Med. 2011;41(5):897–910. doi: 10.1017/S0033291710001406.
- 59.Weisleder A, Fernald A. Talking to children matters: early language experience strengthens processing and builds vocabulary. Psychol Sci. 2013;24(11):2143. doi: 10.1177/0956797613488145.
- 60.Anderson KK, Le B, Edwards J. Comparing risk factors for non-affective psychotic disorders with common mental disorders among migrant groups: a 25-year retrospective cohort study of 2 million migrants. Schizophr Bull. Published online March 4, 2022;48(5):1011–1020. doi: 10.1093/SCHBUL/SBAC021.
- 61.Kirkbride JB, Hollander AC. Migration and risk of psychosis in the Canadian context. CMAJ. 2015;187(9):637. doi: 10.1503/CMAJ.150494.
- 62.Montemitro C, D’Andrea G, Cesa F, et al. Language proficiency and mental disorders among migrants: a systematic review. Eur Psychiatry. 2021;64(1):e49. doi: 10.1192/J.EURPSY.2021.2224.
- 63.Linszen MMJ, Brouwer RM, Heringa SM, Sommer IE. Increased risk of psychosis in patients with hearing impairment: review and meta-analyses. Neurosci Biobehav Rev. 2016;62:1–20. doi: 10.1016/J.NEUBIOREV.2015.12.012.
- 64.Martin-Jones M. Diglossia. In: Frawley W, ed. International Encyclopedia of Linguistics. 2nd ed. Oxford University Press; 2003:435–438. Oxford, United Kingdom. https://books.google.com.kw/books?id=6ftQEAAAQBAJ&pg=PA437&lpg=PA437&dq=fluid+concept+of+diglossia&source=bl&ots=SVG_I081iv&sig=ACfU3U2u7hFeOYdUfXzoExLQXLd8zfCV6g&hl=en&sa=X&ved=2ahUKEwiIktnt7ev2AhUSMewKHUX8C-0Q6AF6BAghEAM#v=onepage&q=fluid concept of diglossia&f=false. Accessed March 29, 2022.
- 65.Cupples L, Ching TYC, Button L, et al. Language and speech outcomes of children with hearing loss and additional disabilities: identifying the variables that influence performance at five years of age. Int J Audiol. 2018;57(suppl 2):S93–S104. doi: 10.1080/14992027.2016.1228127.
- 66.Zheng Z, Zheng P, Zou X. Association between schizophrenia and autism spectrum disorder: a systematic review and meta-analysis. Autism Res. 2018;11(8):1110–1119. doi: 10.1002/AUR.1977.
- 67.Lund N. Language and Thought. Taylor and Francis; 2003. London, United Kingdom. doi: 10.4324/9780203695012.