Affective language and transdiagnostic symptom burden in clinically referred adolescents: a multicenter Turkish sentence-completion study

Abstract

Self-report scales dominate adolescent mental-health assessment but depend on symptom recognition and disclosure. Participant-generated language offers a complementary window on affective processes, yet most evidence comes from adult, English-language, community, or social-media data, leaving clinically referred adolescents and structurally different languages such as Turkish understudied. Sentence-completion tasks are clinically familiar but interpreted qualitatively, yielding no quantitative index. In this multicenter cross-sectional study, 445 clinically referred adolescents (aged 10–18 years; 55.1% girls) from three Turkish child and adolescent psychiatry outpatient clinics completed a 24-item sentence-completion task, the Children’s Depression Inventory (CDI), and the Strengths and Difficulties Questionnaire (SDQ). Completions were analyzed with a Turkish Linguistic Inquiry and Word Count (LIWC) dictionary at whole-response and thematic levels. Because anger and sadness words are nested within the broader negative-emotion category, negative-emotion language was separated into anger, sadness, and other negative emotion, so that each coefficient referred lexical items. Partial correlations and hierarchical regressions related these components, positive-emotion language, and first-person singular reference to symptom severity, controlling for age, sex, word count, and study site, with false-discovery-rate correction. Negative-emotion language was positively associated with depressive symptoms, total difficulties, emotional symptoms, and conduct problems ( r = 0.25 to 0.35), whereas positive-emotion language showed inverse associations. After decomposition, the affective-language block explained 8.1–13.3% of incremental variance, and anger and sadness each contributed beyond general negative tone. The anger coefficient exceeded the sadness coefficient in the conduct-problems model but not in the depressive or emotional-symptoms models. First-person singular reference, which included Turkish verbal morphology and tracked referential context, was unrelated to symptom severity, and no cognitive-process, third-person, or social-content category yielded a detectable association in exploratory screening. The negative-emotion–depression association was of comparable magnitude at all three sites, and the findings persisted after diagnostic adjustment and without the minimum word-count criterion. Affective language in brief Turkish sentence-completion responses therefore tracked dimensional symptom burden, while the absence of a first-person effect under a morphology-informed operationalization underscores the need for cross-linguistically valid measures of self-reference. Automated analysis offers a way of rendering a clinically familiar task quantifiable, as a complementary research measure rather than a standalone diagnostic tool.