Dataset_Child Abuse Identification and Reporting among Parents in Abakaliki, Ebonyi State, Nigeria.sav

This dataset was generated and analyzed for the study "Child Abuse Identification and Reporting among Parents in Abakaliki, Ebonyi State, Nigeria". <br> Data were entered and analyzed using IBM Statistical Package for Social Sciences software version 21.0. Continuous variables were summarized as mean and standard deviation, while categorical variables were summarized as frequency and proportions. Eleven questions assessed parents’ knowledge of child abuse, responses were yes, no, and not sure. Each correct response was scored one mark, while wrong responses were scored zero, the score ranging from 0 to 11. The mean score was used to dichotomize the knowledge score into ‘good’ and ‘poor’ knowledge. Respondents whose scores were seven and above were categorized as having ‘good’ knowledge, while scores below seven were regarded as ‘poor’ knowledge of child abuse. An independent sample <em>t</em>-test and analysis of variance were used to compare the differences in the mean of the knowledge of child abuse by the socio-demographic variables. Parents’ attitudes towards child abuse were assessed on 10 Likert scale questions. Positive responses were scored as five marks for strongly agree, four marks for agreeing, three marks for undecided, two marks for disagree, and one mark for strongly disagree. Reverse scoring was done for negative questions thereby resulting in a score range of 10 to 50. The mean attitude score was used as a cut-off to dichotomize the response into positive and negative attitudes. Accordingly, respondents with attitude scores of 39 and above were categorized as ‘positive attitudes’ to child abuse, while those who scored 38 and below were classified as having a ‘negative attitude’ to child abuse. Child abuse identification was determined for parents’ ability to correctly identify acts that constitute abuse. Hence, 39 questions covering acts of physical, sexual, and psychological abuse, including child neglect were asked. A score of one mark was awarded to each correct answer, while zero mark was given for incorrect responses. The mean respondent score for each type of abuse was used to dichotomize the respondents into two groups. Participants below the mean score were categorized as not being able to identify the particular type of child abuse. Chi-square and logistic regression were used to identify predictors of child abuse identification. Child abuse reporting was measured by asking the parents if they would notify the authorities (Police, Child welfare, or Non-governmental agencies) of an event of child abuse. Their responses were recorded as yes or no responses. Chi-square test of association and logistic regression were used to identify factors associated with child abuse reporting.