Linguagem e fluência verbal: processamento cognitivo, fatores sociodemográficos, psicossociais, funcionais e reconhecimento de expressões faciais de emoções em idosos

• Ano de defesa: 2020
• Autor(a) principal: Francisco, Helen Capeleto
• Orientador(a): Pavarini, Sofia Cristina Iost
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Enfermagem - PPGEnf
• Palavras-chave em Português: Idoso; Envelhecimento; Linguagem; Expressão facial; Potencial evocado; P300
• Palavras-chave em Inglês: Elderly; Aging; Language; Event-related potentials; Facial expression
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::ENFERMAGEM; CIENCIAS DA SAUDE::FONOAUDIOLOGIA
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/12812

Skills such as language and verbal fluency may decline with aging. The general objective of this dissertation was to investigate the relationship between language and verbal fluency with other cognitive processes in addition to factors associated to good language performance among elderly individuals enrolled in primary health care services of a city in the interior of São Paulo, Brazil. Three studies were developed: the first analyzed the relationship between cognitive processing, language and verbal fluency among elderly individuals (N=149). The following instruments were used: a questionnaire for sociodemographic characterization and the Addenbrooke's Cognitive Examination-Revised to assess language and verbal fluency. Cognitive processing (P300) was assessed using a device that captures potentials elicited in auditory tasks. Descriptive and correlation analyses were performed. A negative correlation was found between language and the P300 latency and a positive correlation between verbal fluency and P300 amplitude. Comprehension and naming tasks presented a negative correlation with latency. Repetition tasks revealed a positive correlation with the amplitude. Thus, a relationship was found between latency and P300 amplitude measures as well as between language skills and verbal fluency. These findings suggest that language is correlated with P300 latency and verbal fluency is correlated with amplitude. The second paper identified the sociodemographic, psychosocial and functional factors associated with the performance of elderly individuals in the language and verbal fluency domains (N=149). A questionnaire was used for sociodemographic characterization along with the revised version of the Addenbrooke's Cognitive Examination-Revised (verbal fluency and language), Geriatric Depression Scale, Perceived Stress Scale, Medical Outcomes Study, WHOQOL-OLD, and the Instrumental Activities of Daily Living Scale. The sample was divided into terciles according language performance and verbal fluency: T1 with the best performance, T2 with an average performance, and T3 with the worst performance. The performances of T1 and T3 in language and verbal fluency were analyzed using univariate binary regression analysis while multivariate analysis was used for the independent variables: age, sex, education, family income, depression symptoms, stress, social support, quality of life, and functionality. The variables associated with language in the analysis of T1 and T3 were: schooling (OR=1.578, CI 95% 1.152 – 2.161), income (OR= 1.001, CI 95% 1.000 – 1.003) and functionality (OR= 1.571, CI 95% 1.015 – 2.433). The factors associated with verbal fluency were: education (OR=1.525, CI 95% 1.254-1.855) and functionality (OR=1.357, CI 95% 1.081-1.703). Education and functionality were important factors associated with language performance and verbal fluency, while income was associated with language only. The third study verified whether language and the recognition of emotional facial expressions were related with better/worst language performance of elderly individuals. A total of 118 elderly individuals enrolled in primary health care services were assessed. Sociodemographic data were collected along with language performance using the revised version of Addenbrooke's Cognitive Examination-Revised and recognition of facial expressions of emotion. The language results were correlated to the results concerning recognition of facial expressions of emotion. The sample was divided into terciles according to the language tasks (T1 best performance, T2 average performance, and T3 worst performance. The performances of T1xT3 groups in the facial recognition task were compared for each emotion (anger, disgust, fear, joy, sorrow, and surprise) and intensity (40%, 60%, 80%, 100% and total). Most of the sample was composed of women (84.7%), aged 70.5 years old on average with an average of 3.5 years of schooling. Recognition of emotions such as disgust and surprise presented a moderate positive correlation with language, while recognition of fear presented a negative and weak correlation with poor magnitude. T1 presented the best performance in recognizing disgust and surprise while T3 presented the best performance in recognizing fear. Intensities 80% and 100% presented statistically superior results in T1 in comparison with T3. Language therefore, was correlated with the recognition of emotions such as disgust, fear and surprise. The group with the best language performance also presented the best performance in recognizing disgust and surprise and all the higher intensities. These findings are expected to contribute to a better understanding of language and verbal fluency among elderly individuals facing a health aging process and cognitive decline, aiding the diagnosis, prognosis and clinical practice.