Hospice patients and caregivers who are members of sexual and gender minority groups (i.e., LGBTQ+) have reported experiencing unmet needs at end of life (EOL). Negative experiences often stem from challenging interactions with healthcare providers due to ineffective or poor communication and providers’ heteronormative assumptions and biases. Few studies, however, examine hospice care team (HCT) providers’ knowledge, experience, and opinions related to EOL care for LGBTQ+ patients and caregivers despite this being identified as a gap in competency and education. We sought to examine HCT providers’ perceptions regarding (1) awareness of LGBTQ+ patients and caregivers; (2) knowledge of specific or unique needs; and (3) opinions on best care and communication practices.

Six focus groups conducted with HCT providers (n = 48) currently delivering hospice care in three US states were audio-recorded and transcribed. Data were content coded (κ = 0.77), aggregated by topical categories, and descriptively summarized.

Participants were mostly white and non-Hispanic (n = 43, 89.6%), cisgender female (n = 42, 87.5%), heterosexual (n = 35, 72.9%), and religious (n = 33, 68.8%); they averaged 49 years of age (range 26–72, SD = 11.66). Awareness of LGBTQ+ patients and caregivers depended on patient or caregiver self-disclosure and contextual cues; orientation and gender identity data were not routinely collected. Many viewed being LGBTQ+ as private, irrelevant to care, and not a basis for people having specific or unique EOL needs because they saw EOL processes as universal, and believed that they treat everyone equally. Providers were more comfortable with patients of lesbian or gay orientation and reported less comfort and limited experience caring for transgender and gender-diverse patients or caregivers.

Many HCT members were unaware of specific issues impacting the EOL experiences of LGBTQ+ patients and caregivers, or how these experiences may inform important care and communication needs at EOL.

To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls.

At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035).

We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.

The UK National Institute for Health and Clinical Excellence (NICE) has recommended that cost-effectiveness analysis includes the EQ–5D; however, this is often not implemented in the area of mental health.

To assess the appropriateness of using the EQ–5D to measure improvements in mental health.

Seventy-seven participants with psychosis were rated according to the EQ–5D and seven measures of mental health at both pre- and post-intervention. To assess construct validity we compared the (pre-intervention) mean EQ–5D scores for those with milder and more severe scores, according to each of the seven measures. To assess responsiveness we estimated the mean EQ–5D change score for those who improved (post-intervention), according to each of the measures.

The mean EQ–5D score was more favourable for both those with milder scores (mean difference: 0.044 to 0.301) and for those who improved post-intervention (mean change: 0.029 to 0.117).

This suggests the EQ–5D should be considered for use in future cost-effectiveness studies in the area of mental health.