Sun, Jun 7, 2026
| فارسی
Ethics code: IR.UT.IRICSS.REC.1402.038
Hanieh Bakhtiari Doulabi *1 
, Zahra Sadat Qoreishi2 , Mahdiyeh Karami3 , Mostafa Almasi dooghaee4 , Meysam Sadeghi5
, Zahra Sadat Qoreishi2 , Mahdiyeh Karami3 , Mostafa Almasi dooghaee4 , Meysam Sadeghi5
1- Institute for Cognitive Science Studies, Tehran, Iran,
2- University of social welfare and rehabilitation sciences, Tehran, Iran
3- Institute for Cognitive Science Studies, Tehran, Iran
4- Firoozgar Clinical Research Development Center (FCRDC), Iran University of Medical Sciences, Tehran, Iran
5- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
2- University of social welfare and rehabilitation sciences, Tehran, Iran
3- Institute for Cognitive Science Studies, Tehran, Iran
4- Firoozgar Clinical Research Development Center (FCRDC), Iran University of Medical Sciences, Tehran, Iran
5- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
Abstract: (19 Views)
Introduction: Mild cognitive impairment (MCI), as an early stage of cognitive decline, may be accompanied by changes in language abilities. Since language reflects an individual's mental state, a careful examination of language-related indices can play an important role in the detection and identification of this condition. This study aimed to compare cognitive and linguistic features and analyze connected speech in free speech tasks (spontaneous speech) and descriptive speech tasks (the "bird's nest" picture story) between individuals with MCI and healthy older adults.
Materials and Methods: In this cross-sectional study, 62 participants, including 25 individuals with MCI (mean age: 73.60 ± 8.12 years) and 37 healthy older adults (mean age: 69.14 ± 9.35 years), all Persian-speaking and monolingual aged 50 to 95 years, were assessed. Participants' cognitive status was evaluated using the Persian version of the Addenbrooke's Cognitive Examination-Revised (ACE-R). Furthermore, linguistic and speech motor functions were assessed using the second edition of the Persian Western Aphasia Battery (P-WAB-2) and an oral-verbal apraxia test (expressive speech section), respectively. Connected speech analysis for both tasks were performed using the "Gofte Negar" platform, and semantic and syntactic indices were extracted.
Results: Individuals with MCI showed poorer performance on cognitive and linguistic measures compared to healthy older adults, particularly in free speech tasks during connected speech analysis, indicating impairments in language processing. The total scores of the ACE-R and P-WAB-2 indicated a significant decline in cognitive-linguistic performance in the MCI group (p < 0.001). At the phonological level, no difference was observed between the two groups, indicating preserved speech motor function at this stage of impairment (apraxia score ≤ 12). In connected speech analysis during the free speech task, although no statistically significant difference was found between the two groups, mean ranks indicated that linguistic indices of the MCI group were lower. In contrast, no significant difference was observed between the two groups in the descriptive speech task.
Conclusion: Semantic and syntactic indices of spontaneous speech production can serve as sensitive linguistic markers for distinguishing individuals with MCI from healthy older adults. These linguistic changes, which emerge before the overt decline of other cognitive functions, emphasize the necessity of incorporating connected speech analysis assessments into early screening protocols. Given the subtle nature of these findings, standardization of linguistic indices based on normative criteria is essential for clinical application. Furthermore, the role of speech-language pathologists in the early diagnosis of MCI is highlighted. Future research should address a broader range of linguistic indices in connected speech to provide sensitive and efficient diagnostic support tools for the detection and identification of cognitive decline
Materials and Methods: In this cross-sectional study, 62 participants, including 25 individuals with MCI (mean age: 73.60 ± 8.12 years) and 37 healthy older adults (mean age: 69.14 ± 9.35 years), all Persian-speaking and monolingual aged 50 to 95 years, were assessed. Participants' cognitive status was evaluated using the Persian version of the Addenbrooke's Cognitive Examination-Revised (ACE-R). Furthermore, linguistic and speech motor functions were assessed using the second edition of the Persian Western Aphasia Battery (P-WAB-2) and an oral-verbal apraxia test (expressive speech section), respectively. Connected speech analysis for both tasks were performed using the "Gofte Negar" platform, and semantic and syntactic indices were extracted.
Results: Individuals with MCI showed poorer performance on cognitive and linguistic measures compared to healthy older adults, particularly in free speech tasks during connected speech analysis, indicating impairments in language processing. The total scores of the ACE-R and P-WAB-2 indicated a significant decline in cognitive-linguistic performance in the MCI group (p < 0.001). At the phonological level, no difference was observed between the two groups, indicating preserved speech motor function at this stage of impairment (apraxia score ≤ 12). In connected speech analysis during the free speech task, although no statistically significant difference was found between the two groups, mean ranks indicated that linguistic indices of the MCI group were lower. In contrast, no significant difference was observed between the two groups in the descriptive speech task.
Conclusion: Semantic and syntactic indices of spontaneous speech production can serve as sensitive linguistic markers for distinguishing individuals with MCI from healthy older adults. These linguistic changes, which emerge before the overt decline of other cognitive functions, emphasize the necessity of incorporating connected speech analysis assessments into early screening protocols. Given the subtle nature of these findings, standardization of linguistic indices based on normative criteria is essential for clinical application. Furthermore, the role of speech-language pathologists in the early diagnosis of MCI is highlighted. Future research should address a broader range of linguistic indices in connected speech to provide sensitive and efficient diagnostic support tools for the detection and identification of cognitive decline
Keywords: Mild cognitive impairment, Connected speech analysis, Language, Semantics, Syntax, Phonology
Type of Study: Research |
Received: 2025/09/7 | Accepted: 2026/06/7
Received: 2025/09/7 | Accepted: 2026/06/7
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