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临床试验/NCT06444100
NCT06444100尚未招募不适用

Predictors of Child Abuse Among School Going Children and Impact of Structural Training on Child Abuse Among School Teachers of Dhulikhel Municipality

Kathmandu University School of Medical Sciences0 个研究点目标入组 206 人开始时间: 2024年6月15日最近更新:
适应症

试验速览

阶段
不适用
状态
尚未招募
入组人数
206
主要终点
Predictors of Child Abuse among School Going Children

研究概览

简要总结

Child abuse stands as a global public health crisis, impeding the natural growth and development of children. The repercussions of abuse extend beyond immediate trauma, resulting in heightened medical costs and enduring health consequences that may persist into adulthood. These consequences encompass a spectrum of issues, including attachment disorders, behavioral abnormalities, depression, post-traumatic stress disorder, altered neurobiological structures, suicidal ideation, risky sexual practices, and susceptibility to sexually transmitted infections. The detrimental impact of any form of child abuse lingers into the adult lives of affected individuals.

This study aims to determine the Predictors of Child Abuse among School Going Children and the Impact of Structural Training on Child Abuse Among School Teachers of Dhulikhel Municipality in selected schools of Dhulikhel Municipality. Employing descriptive-analytical, true-experimental, and qualitative research designs, the study involves children aged ≥ 11 and teachers across diverse schools. A purposeful sample technique will be used to select teachers to explore school teachers' strategies in supporting students experiencing childhood violence. A simple stratified sampling technique will be used to select schools and a simple random sampling technique will be used to select the required number of students. Subsequently, one group of teachers undergoes comprehensive training on child protection recognition and response, while another does not. Following a two-week intervention, Investigators will conduct a posttest to evaluate teachers' knowledge and attitudes. To ensure clarity, both standard and self-constructed research tools will be translated into Nepali. Subsequently, these tools will be employed for data collection. The gathered information will be entered into an Excel datasheet and later transferred to Stata version 13 for a comprehensive analysis involving both descriptive and inferential statistics.

详细描述

This study aims to determine Predictors of Child Abuse among School Going Children and Impact of Structural Training on Child Abuse Among School Teachers of Dhulikhel Municipality in selected schools of Dhulikhel Municipality. Employing descriptive-analytical, true-experimental, and qualitative research designs, the study involves children aged ≥ 11 and teachers across diverse schools Study Population The participants-I Investigator purposefully selected teachers who are teaching in private and public schools of Dhulikhel municipality. The participants-II All children aged 11-18 years of age studying in different schools (public and private) of Dhulikhel Municipality. The participants-III Teachers are teaching in different schools in Dhulikhel Municipality which are selected by using a stratified random sampling technique.

Number of participants and Justification :

The first type of participants is 20-30 for focus group discussion. (3-5 group) The second type of participant is 421 students which is based on sample size calculation.

The Third type of participant is 206 teachers which is based on sample size calculation by taking 40% of the mean different knowledge score /SD to maintain optimum sample size.

Sampling Technique Sample-I Among the 26 schools, there are 8 private schools and 18 government schools. A stratified random sampling technique will be used to select 50% of the schools. From these selected schools, a list of teachers was obtained and categorized based on age, education level, gender, experience, and ethnic group. The required sample numbers will be purposefully selected from these groups, considering their characteristics such as interest and expressiveness. Sample-II In Dhulikhel Municipality, there are a total of 26 schools, encompassing both public and private institutions. To ensure a representative sample, 50% of these schools will be chosen utilizing the stratified random sampling technique. This method involves categorizing the schools based on certain criteria and then randomly selecting schools from each category. Subsequently, a proportionate stratified sampling technique will be employed to determine the necessary number of students from the selected schools. From these chosen schools, classes spanning grades 6 to 12 will be selected using a simple random sampling technique. To ensure a representative group, a proportionnâtes stratified sampling technique will be applied to determine the required number of participants. Sample-III Selected schools will be divided into two groups: an intervention group, where teachers of selected schools will receive training on child abuse, and a control group without training. A comparative analysis will then evaluate the effectiveness of the intervention by assessing teachers' knowledge and attitudes towards child abuse.

研究设计

研究类型
Interventional
分配方式
Non Randomized
干预模型
Parallel
主要目的
Prevention
盲法
Single (Participant)

入排标准

性别
All
接受健康志愿者

入选标准

  • Teachers from various selected secondary schools, both public and private, in Dhulikhel Municipality, Nepal.

排除标准

  • Teachers from primary-level schools and refuse to take part in the study.

结局指标

主要结局

Predictors of Child Abuse among School Going Children

时间窗: 1 year

Schools will be chosen through simple stratified sampling, and students via simple random sampling.The prevalence of child abuse will be assessed using the Child Abuse Screening Tool for Children (ICAST-C) through anonymous and ethically sound surveys.

次要结局

  • Impact of Structural Training on Child Abuse Among School Teachers in selected schools of Dhulikhel Municipality(6 months)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Sita Karki

Associate Professor

Kathmandu University School of Medical Sciences

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