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Aim: This article explores ways of maximising engagement of intellectual disability staff as research participants, research advisers and research implementers. Method: The authors describe and reflect on a three-phased strategy in recruiting front-line staff (n = 690) working for intellectual disability service providers (n = 25) to participate in a UK-wide anonymous online survey about death, dying and bereavement. Results: Important elements in engaging participants were: involving stakeholders at all stages of the research process, which includes: building relationships with participating organisations; enlisting organisational management support at all levels; an attractive and well laid-out collection tool; a well-structured recruitment strategy; time and flexibility; and a varied and targeted dissemination strategy. However, the recruitment method had limitations, in particular around representativeness, bias and generalisability. Conclusions: Staff in intellectual disability services can be enthusiastic and invaluable research participants. Active engagement between researchers, participating organisations and stakeholder groups is key to ensuring involvement of intellectual disability staff with research.

Background: Within learning disability research, it is important to involve people with learning disabilities at all stages, but there are limited opportunities for them to learn about the research process or to gain research skills. Method: An eight-session research training course for people with learning disabilities was developed and piloted at a university in London. The focus was on understanding the research process and gaining practical skills in collecting, analysing and presenting research data. Training methods were experimental, with an emphasis on learning by experience in a "fun" way. Results: Ten people with learning disabilities completed the course, showing great enthusiasm and commitment. During the final sessions, students developed and conducted their own research projects, choosing "Employment" as their research topic. The training methods were well received. Benefits included an increase in confidence and new work opportunities for several of the students. This paper was co-authored by the tutors and most of the course graduates. Conclusion: It is possible for people with learning disabilities to become skilled researchers, but in order to do so, it is important that they have adequate training opportunities. Funding should be made available for more such courses.

Background: Illness and death are part of life for everyone, including people with intellectual disabilities. This study investigated the extent to which staff communicate about death with people with intellectual disability facing terminal illness or bereavement. Method: Staff who support people with intellectual disability in the UK (n = 690) completed an electronic survey. Detailed data were obtained from staff where a client had died in the past 12 months (n = 111), was terminally ill (n = 41) or had been bereaved (n = 200). Analysis included descriptive and chi-squared statistics. Results: 52.6% of people with intellectual disability who were terminally ill were told about their illness, and 18.1% were told they would die. Of those experiencing an anticipated bereavement, 32.4% of staff said no one talked about this with them beforehand. A quarter of staff had received training on end of life or bereavement. Conclusion: Death affects many people with intellectual disability. Staff require training and support in communicating death.

Background: Commonly offered as supportive care, therapist-led online support groups (OSGs) are a cost-effective way to provide support to individuals affected by cancer. One important indicator of a successful OSG session is group cohesion; however, monitoring group cohesion can be challenging due to the lack of nonverbal cues and in-person interactions in text-based OSGs. The Artificial Intelligence-based Co-Facilitator (AICF) was designed to contextually identify therapeutic outcomes from conversations and produce real-time analytics., Objective: The aim of this study was to develop a method to train and evaluate AICF's capacity to monitor group cohesion., Methods: AICF used a text classification approach to extract the mentions of group cohesion within conversations. A sample of data was annotated by human scorers, which was used as the training data to build the classification model. The annotations were further supported by finding contextually similar group cohesion expressions using word embedding models as well. AICF performance was also compared against the natural language processing software Linguistic Inquiry Word Count (LIWC)., Results: AICF was trained on 80,000 messages obtained from Cancer Chat Canada. We tested AICF on 34,048 messages. Human experts scored 6797 (20%) of the messages to evaluate the ability of AICF to classify group cohesion. Results showed that machine learning algorithms combined with human input could detect group cohesion, a clinically meaningful indicator of effective OSGs. After retraining with human input, AICF reached an F 1 -score of 0.82. AICF performed slightly better at identifying group cohesion compared to LIWC., Conclusions: AICF has the potential to assist therapists by detecting discord in the group amenable to real-time intervention. Overall, AICF presents a unique opportunity to strengthen patient-centered care in web-based settings by attending to individual needs., International Registered Report Identifier (irrid): RR2-10.2196/21453., (©Yvonne W Leung, Elise Wouterloot, Achini Adikari, Jinny Hong, Veenaajaa Asokan, Lauren Duan, Claire Lam, Carlina Kim, Kai P Chan, Daswin De Silva, Lianne Trachtenberg, Heather Rennie, Jiahui Wong, Mary Jane Esplen. Originally published in JMIR Cancer (https://cancer.jmir.org), 22.07.2024.)