Effectiveness of a Behavioural Management Training on Knowledge and Self-efficacy of Speech Therapists in Managing Children with Neurodevelopmental Disorders in Lagos State, Nigeria.

Abstract

Background: Challenging behaviours are highly prevalent among children with neurodevelopmental disorders (NDDs), particularly those with speech impairments. Speech and language therapists in low- and middle-income countries, including Nigeria, frequently encounter these behaviours during service delivery but often report limited training in effective behavioural management approaches such as Functional Behavioural Analysis (FBA). This study aimed to evaluate the effectiveness of a behavioural management training programme on the knowledge and self-efficacy of speech therapists managing children with NDDs. Methodology: A quasi-experimental one-group pre-post intervention design was employed, conducted in three phases: baseline, intervention, and post-intervention. Sixteen participants were recruited using purposive sampling. Pre- and post-intervention knowledge and self-efficacy related to challenging behaviour management were assessed. Data was analysed using descriptive and inferential statistics. Results: The intervention resulted in significant improvements in both knowledge and self-efficacy. Mean knowledge scores increased from 10.69 (± 1.40) at baseline to 11.50 (± 0.73) post-intervention. Self-efficacy scores also improved significantly, rising from 5.06 (± 2.08) to 7.50 (± 1.21). The effect size (Cohen's d = 1.03) indicates a large effect, suggesting that the intervention is potentially effective in improving participants' skills and confidence in managing challenging behaviours. Conclusion: Behavioural management training based on FBA appears effective in improving knowledge and self-efficacy among speech and language therapists working with children with NDDs. Integrating such training into professional development programmes may strengthen service delivery, improve access to care, and optimise outcomes for children in low-resource settings.