Exposure to the troubles in Northern Ireland, memory functioning, and social activity engagement: results from NICOLA.

We investigated the potential impact of a cohort traumatic exposure, the Troubles in Northern Ireland, on memory functioning in later life, and the potential moderating effect of social activity engagement. Using data from 6571 participants aged 60 + in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) cohort, we used a structural equation modelling framework to explore associations between traumatic exposure during the Troubles and memory functioning. As expected, social activity engagement was positively associated with memory functioning, ß = .102. Traumatic exposure was also positively associated with memory functioning, ß = .053. This association was stronger at low levels of social activity engagement; among those with higher levels, there was little association, interaction ß = - 0.054. The positive association between traumatic exposure during the Troubles and memory functioning was not moderated by the age at which the exposures occurred (based on analysis of a subsample with available data), interaction ß = - 0.015. We conclude that superior memory functioning was associated with higher levels of traumatic exposure during the Troubles, particularly among those with lower levels of social activity engagement, and regardless of the age at which the exposures occurred. Future longitudinal analyses are required to build on these results, which potentially have implications for life-course epidemiology, in relation to critical periods for traumatising experiences. Supplementary Information: The online version contains supplementary material available at 10.1007/s10433-022-00683-5.

Implementation of personalised medicine policies in mental healthcare: results from a stated preference study in the UK.

BACKGROUND: Public support for the implementation of personalised medicine policies (PMPs) within routine care is important owing to the high financial costs involved and the potential for redirection of resources from other services. AIMS: We aimed to determine the attributes of a PMP most likely to elicit public support for implementation. We also aimed to determine whether such support differed between a depression PMP and one for cystic fibrosis. METHOD: In a discrete-choice experiment, paired vignettes illustrating both the current model of care (CMoC) and a hypothetical PMP for either depression or cystic fibrosis were presented to a representative sample of the UK public (n = 2804). Each vignette integrated varying attributes, including anticipated therapeutic benefit over CMoC, and the annual cost to the taxpayer. Respondents were invited to express their preference for either the PMP or CMoC within each pair. RESULTS: The financial cost was the most important attribute influencing public support for PMPs. Respondents favoured PMP implementation where it benefited a higher proportion of patients or was anticipated to be more effective than CMoC. A reduction in services for non-eligible patients reduced the likelihood of support for PMPs. Respondents were more willing to fund PMPs for cystic fibrosis than for depression. CONCLUSIONS: Cost is a significant factor in the public's support for PMPs, but essential caveats, such as protection for services available to PMP-ineligible patients, may also apply. Further research should explore the factors contributing to condition-specific nuances in public support for PMPs.

Food insecurity and brain health in adults: A systematic review.

Food insecurity has been associated with adverse effects on physical health and well-being in both high and low-income countries, but effects on brain health are not clear. The purpose of this systematic review was to determine the relationship between food insecurity and important brain health outcomes in adults including depression, stroke, cognitive impairment and dementia. Electronic databases were searched to find studies which investigated relations between food insecurity and predefined brain health outcomes. Thirty studies met the inclusion criteria for review of which 23 were conducted in high income countries and seven in low- or middle-income countries. Most studies (n = 24) were cross-sectional, five were prospective and 1 was a case-control design. Seven studies reporting outcomes relating to cognitive performance and 24 relating to depression. No studies investigated relations between food insecurity and stroke or dementia. There was substantial heterogeneity in the populations studied as well as measures of food insecurity and outcomes which made comparisons between studies difficult. Overall, the findings highlighted that individuals who were food insecure had increased likelihood of depressive symptoms and poorer global cognition than those who were food secure. It is possible that social support and food aid programmes attenuate the effects of food insecurity on depressive symptoms. Future research is needed to determine whether interventions to alleviate food insecurity can benefit brain health in vulnerable populations.

Utility of fractional exhaled nitric oxide suppression as a prediction tool for progression to biologic therapy.

RATIONALE: The utility of fractional exhaled nitric oxide (F ENO) suppression (FeNOSuppT) to identify non-adherence to inhaled corticosteroid (ICS) treatment has previously been reported, but whether it can predict clinical outcome remains unclear. OBJECTIVES: We examined the utility of FeNOSuppT in prediction of progression to biologic agents or discharge from specialist care. METHODS: FeNOSuppT was measured at home using remote monitoring technology of inhaler use alongside daily F ENO measurement over 7 days. Long-term clinical outcomes in terms of progression to biologic agent or discharge from specialist care were compared for non-suppressors and suppressors. MEASUREMENTS AND MAIN RESULTS: Of the 162 subjects, 135 successfully completed the test with 81 (60%) positive F ENO suppression tests. Subjects with a negative FeNOSuppT were more likely to proceed to biologic therapy (39 of 54 patients, 72%) compared to those with a positive FeNOSuppT (35 of 81 patients, 43%, p=0.001). In subjects with a positive FeNOSuppT, predictors of progression to biologic therapy included higher dose of maintenance steroid at initial assessment and prior intensive care unit admission. These subjects had a significant rise in F ENO between post-suppression test and follow-up (median, 33 (IQR 25-55) versus 71 (IQR 24-114); p=0.009), which was not explained by altered corticosteroid dose. CONCLUSIONS: A negative FeNOSuppT correlates with progression to biologic therapy. A positive FeNOSuppT, with subsequent maintenance of "optimised" F ENO, predicts a subgroup of patients in whom asthma control is preserved with adherence to high-dose ICS/long-acting ß2 agonist and who can be discharged from specialist care.

Factors influencing transition to care homes for people with dementia in Northern Ireland.

INTRODUCTION: The increasing number of people with dementia (PwD) is a significant health and financial challenge for countries. PwD often transition to a care home. This study explored factors predicting transition to care homes for PwD and the place and causes of death. METHODS: Data about dementia medication, care home transitions, demographic characteristics, deaths, and hospital admissions were extracted from national databases from 2010 to 2016. RESULTS: PwD (n = 25,418) were identified through prescriptions of dementia medication, from which 11,930 transitioned to care homes. A logistic regression showed that increased age, female sex, living in less deprived and urban areas, and hospital admissions predicted this transition. PwD who transition to care homes are more likely to die there. The most common cause of death was dementia. DISCUSSION: Certain demographic characteristics are significant predictors for care home transitions and they should be considered in the development of early community-based care services to delay transitions. In the last decades, dementia has been reported more frequently in death certificates.

Living alone for people on dementia medication: related use of drugs.

Approximately one-third of people with dementia in the United Kingdom live alone. People living alone with dementia may receive different treatment for dementia and may have different comorbidities compared to people who live with a caregiver. This study explored differences in medication and demographic characteristics between people living alone with dementia and those living with a caregiver in Northern Ireland. People with dementia were identified through the first date that a dementia management medication was prescribed between 2010 and 2016. In total, 25,418 people were prescribed a dementia management medication. Data for whether people with dementia lived alone was extracted through the National Health Application and Infrastructure Services and from national datasets through the Honest Broker Service. Approximately 35% (n= 8,828) of people with dementia in Northern Ireland lived alone. People with dementia who lived alone were younger (mean= 75 years, SD= 8.50) compared to people who lived with a caregiver (mean= 77 years, SD= 7.82). Binary logistic regression highlighted that people who lived alone were more likely to be treated with donepezil medication for dementia and less likely to receive antidepressants. These findings indicate that living alone did not affect treatment for dementia and comorbidity medication in people on dementia medication.

Factors Associated with Mortality Including Nursing Home Transitions: A Retrospective Analysis of 25,418 People Prescribed Anti-Dementia Drugs in Northern Ireland.

BACKGROUND: Understanding factors associated with mortality after a dementia diagnosis can provide essential information to the person with dementia, their family, and caregivers. To date very little is known about the factors associated with mortality after a dementia diagnosis in Northern Ireland. OBJECTIVE: To determine how demographic and other factors such as deprivation and comorbidity medications influence mortality rates after a dementia diagnosis in Northern Ireland and whether these factors are influenced through nursing home transitions. METHODS: 25,418 people prescribed anti-dementia medication were identified through the enhanced prescribing database between 2010 and 2016. The impact of covariates including age, gender, marital status, deprivation measure, urban/rural classification, and comorbidity medications were examined using cox proportional hazard models with hazard ratios (HR) and 95% confidence intervals. RESULTS: Between 2010 and 2016, 12,129 deaths occurred, with 114 deaths/1,000 person years. Males had significantly higher mortality rates in comparison to females (HR = 1.28; 95% CI = 1.23-1.33); this was true regardless of whether the person with dementia transitioned to a nursing home. People prescribed anti-dementia drugs living with lower levels of deprivation had significantly lower mortality rates in comparison to people living with the highest levels of deprivation (HR = 0.93; 95% CI = 0.89-0.97). Diabetic (HR = 1.18; 95% CI = 1.07-1.29) and anti-arrhythmic (HR = 2.44; 95% CI = 1.01-5.91) medication in particular significantly influenced mortality. CONCLUSION: Male gender, higher comorbidity medications, and living in areas of higher deprivation significantly increased mortality rates for people prescribed anti-dementia drugs in our study population. When comorbidity medications were classified, only anti-arrhythmia and diabetic medications significantly increased mortality. Future research should continue to investigate factors which influence mortality after a dementia diagnosis.

Physician-Specific Maximum Acceptable Risk in Personalized Medicine: Implications for Medical Decision Making.

BACKGROUND: In discrete-choice experiments (DCEs), respondents are presented with a series of scenarios and asked to select their preferred choice. In clinical decision making, DCEs allow one to calculate the maximum acceptable risk (MAR) that a respondent is willing to accept for a one-unit increase in treatment efficacy. Most published studies report the average MAR for the whole sample, without conveying any information about heterogeneity. For a sample of psychiatrists prescribing drugs for a series of hypothetical patients with schizophrenia, this article demonstrates how heterogeneity accounted for in the DCE modeling can be incorporated in the derivation of the MAR. METHODS: Psychiatrists were given information about a group of patients' responses to treatment on the Positive and Negative Syndrome Scale (PANSS) and the weight gain associated with the treatment observed in a series of 26 vignettes. We estimated a random parameters logit (RPL) model with treatment choice as the dependent variable. RESULTS: Results from the RPL were used to compute the MAR for the overall sample. This was found to be equal to 4%, implying that, overall, psychiatrists were willing to accept a 4% increase in the risk of an adverse event to obtain a one-unit improvement of symptoms - measured on the PANSS. Heterogeneity was then incorporated in the MAR calculation, finding that MARs ranged between 0.5 and 9.5 across the sample of psychiatrists. LIMITATIONS: We provided psychiatrists with hypothetical scenarios, and their MAR may change when making decisions for actual patients. CONCLUSIONS: This analysis aimed to show how it is possible to calculate physician-specific MARs and to discuss how MAR heterogeneity could have implications for medical practice.

The Influence of Genotype Information on Psychiatrists' Treatment Recommendations: More Experienced Clinicians Know Better What to Ignore.

BACKGROUND: This study applies attribute nonattendance to medical decision making. We aimed to demonstrate how this type of analysis can be used in medical decision making to assess whether psychiatrists were influenced in their treatment recommendations by information on the genotype of a patient, despite knowing the patient's response to treatment as measured by the Positive and Negative Syndrome Scale. A patient's genetic information may be used to predict their response to therapy; such information, however, becomes redundant, and should not influence decisions, once a clinician knows the patient's actual response to treatment. METHODS: Sixty-seven psychiatrists were presented with patients' pre- or post-treatment scores on the Positive and Negative Syndrome Scale for two hypothetical treatments for schizophrenia. Psychiatrists were also informed whether the patient possessed a genotype linked to hyper-responsiveness to one of the treatments, and were asked to recommend one of these two treatments. Attribute nonattendance assessed whether the information on genotype influenced psychiatrists' treatment recommendations. RESULTS: Years of experience predicted whether psychiatrists were influenced by the genetic information. Psychiatrists with 1 year or less of experience had a 46% probability of considering genetic information, whereas psychiatrists with at least 15 years of experience had a lower probability (7%). CONCLUSIONS: Psychiatrists and other clinicians should be cautious about allowing a patient's genetic information to carry unnecessary weight in their clinical decision making.

How Do Psychiatrists Apply the Minimum Clinically Important Difference to Assess Patient Responses to Treatment?

Symptom report scales are used in clinical practice to monitor patient outcomes. Using them permits the definition of a minimum clinically important difference (MCID) beyond which a patient may be judged as having responded to treatment. Despite recommendations that clinicians routinely use MCIDs in clinical practice, statisticians disagree about how MCIDs should be used to evaluate individual patient outcomes and responses to treatment. To address this issue, we asked how clinicians actually use MCIDs to evaluate patient outcomes in response to treatment. Sixty-eight psychiatrists made judgments about whether hypothetical patients had responded to treatment based on their pre- and posttreatment change scores on the widely used Positive and Negative Syndrome Scale. Psychiatrists were provided with the scale's MCID on which to base their judgments. Our secondary objective was to assess whether knowledge of the patient's genotype influenced psychiatrists' responder judgments. Thus, psychiatrists were also informed of whether patients possessed a genotype indicating hyperresponsiveness to treatment. While many psychiatrists appropriately used the MCID, others accepted a far lower posttreatment change as indicative of a response to treatment. When psychiatrists accepted a lower posttreatment change than the MCID, they were less confident in such judgments compared to when a patient's posttreatment change exceeded the scale's MCID. Psychiatrists were also less likely to identify patients as responders to treatment if they possessed a hyperresponsiveness genotype. Clinicians should recognize that when judging patient responses to treatment, they often tolerate lower response thresholds than warranted. At least some conflate their judgments with information, such as the patient's genotype, that is irrelevant to a post hoc response-to-treatment assessment. Consequently, clinicians may be at risk of persisting with treatments that have failed to demonstrate patient benefits.