2 results
Insight into impaired social functioning in dementia
- Andrew Sommerlad, Jessica Grothe, Sumiyo Umeda, Manabu Ikeda, Hideki Kanemoto, Gill Livingston, Melanie Luppa, Katherine P. Rankin, Steffi G. Riedel-Heller, Susanne Röhr, Maki Suzuki, Jonathan Huntley
-
- Journal:
- International Psychogeriatrics / Volume 35 / Issue S1 / December 2023
- Published online by Cambridge University Press:
- 02 February 2024, pp. 19-20
-
- Article
-
- You have access Access
- Export citation
-
Background:
People with dementia commonly have impaired social functioning and may not recognise this. This lack of insight may result in worse outcomes for the person and their family carers. We aimed to characterise insight into social functioning in dementia, and describe its association with dementia severity.
Methods:Observational cross-sectional study of people aged >65 years with clinically diagnosed dementia and their family informants recruited from three sites in Germany, Japan and the United Kingdom. We used the Social Functioning in Dementia scale (SF-DEM), which assesses three domains: “spending time with other people” (domain 1), “communicating with other people” (domain 2), and “sensitivity to other people” (domain 3). We calculated lack of insight into social functioning as the discrepancy between the ratings of the participants with dementia and their informant. We described this discrepancy and the proportion of people with dementia whose rating was overestimated, congruent or underestimated compared to their family informant. We calculated the association between SF-DEM discrepancy score and total mini-mental status examination (MMSE) score and recall and attention/concentration subdomains.
Results:In 108 participants with dementia (50.9% women), mean age = 78.9 (standard deviation, SD 6.5) years, and mean MMSE score = 22.7 (SD 3.7). Ratings of patients and informants for domain 1 did not differ, but patient-rating was higher than carer-rating for domain 2 (patient-rated score 11.2 (2.5), carer-rated score 10.1 (3.4); p = 0.003) and domain 3 (patient-rated score 9.7 (2.4), carer-rated score 8.1 (2.8); p < 0.001). Sixty (55.6%) people with dementia overestimated their overall social functioning, 30 (27.8%) underestimated, and 18 (16.7%) gave ratings congruent with their family informant. Performance on the MMSE, and its sub-domains was not associated with SF-DEM discrepancy score.
Conclusions:We found that insight varies according to subdomains of social functioning, with people with dementia rating their communication and sensitivity differently, and usually higher than their carers. Researchers and clinicians should consider insight into social functioning in dementia as a multidimensional, rather than a unified, concept. Clinicians should help family members understand and adapt by explaining their relative with dementia’s lack of insight about aspects of their social functioning.
Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
- David Benrimoh, Myriam Tanguay-Sela, Kelly Perlman, Sonia Israel, Joseph Mehltretter, Caitrin Armstrong, Robert Fratila, Sagar V. Parikh, Jordan F. Karp, Katherine Heller, Ipsit V. Vahia, Daniel M. Blumberger, Sherif Karama, Simone N. Vigod, Gail Myhr, Ruben Martins, Colleen Rollins, Christina Popescu, Eryn Lundrigan, Emily Snook, Marina Wakid, Jérôme Williams, Ghassen Soufi, Tamara Perez, Jingla-Fri Tunteng, Katherine Rosenfeld, Marc Miresco, Gustavo Turecki, Liliana Gomez Cardona, Outi Linnaranta, Howard C. Margolese
-
- Journal:
- BJPsych Open / Volume 7 / Issue 1 / January 2021
- Published online by Cambridge University Press:
- 06 January 2021, e22
-
- Article
-
- You have access Access
- Open access
- HTML
- Export citation
-
Background
Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction.
AimsAifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction.
MethodTwenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback.
ResultsAll 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction.
ConclusionsThe simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.