Back

Public knowledge and attitude towards epilepsy and its associated factors in Debre Berhan, North Shoa, Amhara Region, Ethiopia, 2018/19. Community based cross sectional study

dargie, a. w.; engidaw, n. a.; basha, e. a.

2019-07-08 epidemiology
10.1101/19001578 medRxiv
Show abstract

IntroductionEpilepsy is chronic brain disorder characterized by recurrent derangement of the nervous system due to the sudden excessive disorderly discharge of the cerebral neurons. People living with epilepsy continue to suffer from enacted or perceived stigma that is based on myths, misconceptions, and misunderstandings that have persisted for many years. Therefore, this study aimed to assess the community general knowledge and attitude towards epilepsy. MethodsCommunity-based cross-sectional study was conducted to assess public general knowledge and attitude towards epilepsy and its associated factors using structured pretested questionnaire. Data were entered into Epi data version 3.1 and transported to SPSS version 21 further analysis. Both Bivariable and Multivariable Logistic Regression was done to identify associated factors. Odds Ratios and their 95% Confidence interval were computed and variables with p-value less than 0.05 was considered significantly associated factors. Results596 study participants participated in a response rate of 98%. Among the study participants, 43.6 (95% CI: 39.6, 47.5) had poor knowledge and 41.3 (95% CI: 37.4, 45.1) had an unfavorable attitude. Being secondary education, marital status, witnessed a seizure and heard the term epilepsy were showed statistically significant association with poor knowledge about epilepsy. Level of education, low average monthly income, not witnessed a seizure, not heard the term epilepsy and distant from health facility showed statically significant association with the unfavorable attitude. ConclusionIn this study, Debre Berhan communities were found to have deficits in terms of general knowledge and attitude about epilepsy; and it should be given due attention.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.