Mental health nurses’ attitudes, behaviour, experience and knowledge regarding adults with a diagnosis of borderline personality disorder: systematic, integrative literature review

Aims and objectives To establish whether mental health nurses responses to people with borderline personality disorder are problematic and, if so, to inform solutions to support change. Background There is some evidence that people diagnosed with borderline personality disorder are unpopular among mental health nurses who respond to them in ways which could be counter-therapeutic. Interventions to improve nurses’ attitudes have had limited success. Design Systematic, integrative literature review. Methods Computerised databases were searched from inception to April 2015 for papers describing primary research focused on mental health nurses’ attitudes, behaviour, experience, and knowledge regarding adults diagnosed with borderline personality disorder. Analysis of qualitative studies employed metasynthesis; analysis of quantitative studies was informed by the theory of planned behaviour. Results Forty studies were included. Only one used direct observation of clinical practice. Nurses’ knowledge and experiences vary widely. They find the group very challenging to work with, report having many training needs, and, objectively, their attitudes are poorer than other professionals’ and poorer than towards other diagnostic groups. Nurses say they need a coherent therapeutic framework to guide their practice, and their experience of caregiving seems improved where this exists. Conclusions Mental health nurses’ responses to people with borderline personality disorder are sometimes counter-therapeutic. As interventions to change them have had limited success there is a need for fresh thinking. Observational research to better understand the link between attitudes and clinical practice is required. Evidence-based education about borderline personality disorder is necessary, but developing nurses to lead in the design, implementation and teaching of coherent therapeutic frameworks may have greater benefits. Relevance to clinical practice There should be greater focus on development and implementation of a team-wide approach, with nurses as equal partners, when working with patients with borderline personality disorder.

An investigation of two real time machine learning techniques that could enhance the adaptability of game AI agents

Developers strive to create innovative Artificial Intelligence (AI) behaviour in their games as a key selling point. Machine Learning is an area of AI that looks at how applications and agents can be programmed to learn their own behaviour without the need to manually design and implement each aspect of it. Machine learning methods have been utilised infrequently within games and are usually trained to learn offline before the game is released to the players. In order to investigate new ways AI could be applied innovatively to games it is wise to explore how machine learning methods could be utilised in real-time as the game is played, so as to allow AI agents to learn directly from the player or their environment. Two machine learning methods were implemented into a simple 2D Fighter test game to allow the agents to fully showcase their learned behaviour as the game is played. The methods chosen were: Q-Learning and an NGram based system. It was found that N-Grams and QLearning could significantly benefit game developers as they facilitate fast, realistic learning at run-time.