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The purpose of this paper is to validate measures of professional self-efficacy for detecting and responding to child abuse and neglect presentations, and then evaluate a clinical training programme for health professionals in a tertiary-level hospital in Vietnam.

A prospective, cohort design was used and professional self-efficacy was measured immediately prior to, and shortly after, training 116 nurses and doctors in emergency settings. Longer-term follow-up was measured six months later.

Linear mixed modelling showed that there was a statistically significant improvement in efficacy expectations for both suspected and known cases of child abuse and neglect between the pre- and post-test measures at zero and six weeks. These improvements did not persist to the six-month follow-up.

The training succeeded in improving detection and clinical response to child abuse and neglect presentations but not faith in the provision of ongoing support for children and families.

Practice change in emergency settings in Vietnam can be achieved using a sustainable theoretically driven training programme.

Building the capacity of health professionals to respond to cases of child abuse and neglect relies on the strength of the community and support services within which the hospital is located.

Measures of self-efficacy expectations and outcome expectations for responding to child abuse and neglect presentations in emergency settings in Vietnam are now validated.

The advent of artificial intelligence technologies, exemplified by platforms such as ChatGPT, has created a profound global impact, with a particular resonance in education. This research aims to integrate the information systems success (ISS) model with the stimulus-organism-response (SOR) paradigm to explore how information quality and service quality individually, jointly, congruently, and incongruently affect higher education students’ trust in ChatGPT, satisfaction, and continuance usage intention.

We employed a sophisticated methodology - polynomial regression with response surface analysis - and conducted our study with a sample of 468 higher education students selected in Vietnam using a three-phase stratified random sampling approach to evaluate the hypotheses developed.

The findings indicate that both information and service quality influence higher education students’ trust directly and positively in ChatGPT, satisfaction, and continuance usage intention. Moreover, a balance between information quality and service quality can increase students’ level of trust in ChatGPT, satisfaction, and intention to continue using it. Nevertheless, a significant incongruity between information quality and service quality will likely reduce trust in ChatGPT, satisfaction, and the intention to continue using the service.

This research is one of the first to offer a shred of empirical evidence about how information quality and service quality interact congruently and incongruently with each other to trigger higher education students’ trust in ChatGPT, satisfaction, and continuance usage intention of ChatGPT. It thus offers valuable insights for leveraging the benefits and mitigating potential challenges associated with adopting this innovative technology in educational settings.