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KARABULUT, ŞEYDA

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KARABULUT

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ŞEYDA

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    PublicationOpen Access
    Depression, anxiety, and sleep quality of caregivers of children with spinal muscular atrophy
    (2023-03-01) ERGENEKON, ALMALA PINAR; YILMAZ YEĞİT, CANSU; SELÇUK, MERVE; KARABULUT, ŞEYDA; ÖZTÜRK THOMAS, GÜLTEN; ERDEM ERALP, ELA; ÜNVER, OLCAY; KARADAĞ, BÜLENT TANER; GÖKDEMİR, YASEMİN; ERGENEKON A. P., Gumus Z., YILMAZ YEĞİT C., Cenk M., Gulieva A., Kalyoncu M., SELÇUK M., KARABULUT Ş., ÖZTÜRK G., ERDEM ERALP E., et al.
    BackgroundThe aim of this study was to evaluate the prevalence of anxiety, depression, sleep, and associated factors in caregivers of children with spinal muscular atrophy (SMA). Materials and MethodsBeck Depression Inventory (BDI), the State-Trait Anxiety Inventory-State (STAI-S), the State-Trait Anxiety Inventory-Trait (STAI-T), and Pittsburgh Sleep Quality Index (PSQI) were used to assess the anxiety, depression, and sleep quality of the caregivers of children with SMA. Higher scores indicated worse outcome for all three questionnaires. ResultsFifty-six caregivers of children with SMA were included in the study. Median age of children was 6 (3.2-10) years and mean age of the caregivers was 37.0 +/- 6.5 years. Median scores of the BDI, STAI-S, STAI-T, and PSQI were 12 (7.2-17), 35.5 (31-44), 40.5 (35-48), and 7.0 (5.0-10.0), respectively. There was a positive correlation between BDI and PSQI scores (p < 0.05). There was a negative correlation between the age of the caregivers and PSQI, BDI, STAI-T scores (p = 0.01, r = -0.341; p = 0.006, r = -0.364; p = 0.003, r = -0.395, respectively). There was a negative correlation between the age of the patients and the PSQI scores of the caregivers (p = 0.01, r = -0.33). There was a negative correlation between BDI scores and household income (p = 0.01, r = -0.34). ConclusionCaregivers of children with SMA had elevated depression and anxiety levels and they also had decreased sleep quality. Economic and social support resources are needed to help caregivers of those children.
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    PublicationOpen Access
    İdentifiying knowledge gaps by using adapted CF R.I.S.E in a low sourse setting
    (2022-11-16) GÖKDEMİR, YASEMİN; ERGENEKON, ALMALA PINAR; KARABULUT, ŞEYDA; GÖKDEMİR Y., SELÇUK M., ERGENEKON A. P., YILMAZ YEĞİT C., CENK M., Guliyeva A., Kalyoncu M., KARABULUT Ş., Uzunoğlu B., Taştan G., et al.