Analysis of decision-making processes and semantic processing in the context of ADHD

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00039054

Enrollment

Registered

2026-01-20

Start date

2026-07-01

Completion date

Unknown

Last updated

2026-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

F90.0

Interventions

Group 1: Study arm 1 includes adult participants with a confirmed diagnosis of attention-deficit/hyperactivity disorder (ADHD). Participants complete a single computer-based linguistic prediction task

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Confirmed diagnosis of attention-deficit/hyperactivity disorder (ADHD) according to ICD-10-GM F90.0 (ADHD group) or absence of any psychiatric diagnosis (control group) Sufficient German language proficiency to understand instructions and complete the task Ability to participate in computer-based testing (physically and cognitively) Written informed consent

Exclusion criteria

Exclusion criteria: Current neurological disorders or severe psychiatric comorbidities Presence of significant visual, reading, or language impairments Current medication substantially affecting attention, reaction time, or cognitive processing Inability to provide informed consent

Design outcomes

Primary

Measure	Time frame
Primary endpoints include mean reaction time per participant, variance of reaction times, and the semantic distance between predicted and target words. These endpoints are assessed during a single computer-based linguistic prediction task. Data collection is fully automated via the test software. Semantic distance is calculated after data collection using a script based on vector space models to quantify semantic similarity.	—

Measure

Time frame

Primary endpoints include mean reaction time per participant, variance of reaction times, and the semantic distance between predicted and target words. These endpoints are assessed during a single computer-based linguistic prediction task. Data collection is fully automated via the test software. Semantic distance is calculated after data collection using a script based on vector space models to quantify semantic similarity.

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Secondary

Measure	Time frame
Secondary endpoints include intra-individual reaction time variability, error rate (e.g., unintelligible or missing responses), exploratory analyses of response patterns, and temporal changes in prediction accuracy throughout the task. Additionally, associations between reaction time and semantic distance as well as the influence of sociodemographic variables are examined. Data are collected during the same computer-based task and through a brief sociodemographic questionnaire.	—

Measure

Time frame

Secondary endpoints include intra-individual reaction time variability, error rate (e.g., unintelligible or missing responses), exploratory analyses of response patterns, and temporal changes in prediction accuracy throughout the task. Additionally, associations between reaction time and semantic distance as well as the influence of sociodemographic variables are examined. Data are collected during the same computer-based task and through a brief sociodemographic questionnaire.

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Countries

Germany

Contacts

Public ContactOliver Grimm

Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Universitätsklinikum Frankfurt am Main

o.grimm@med.uni-frankfurt.de+496963014784

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Jun 11, 2026