While evaluation approaches for community-academic research groups are established, few tools exist for academic institutional advisory groups across multi-core centers and research, education, and clinical care missions. Institutional advisory group evaluation should consider group processes and their impact on community-centered outcomes. This study describes the community-engaged development of a mixed-method evaluation approach to address this gap and presents pilot outcomes across an NIH-funded center.

We utilized a Community of Practice model to co-develop a survey with 14 community and academic representatives of four advisory groups. The final survey included five categories of group process and four categories of outcomes. Storytelling sessions with community partners explored areas where the survey identified discrepancies in perspectives between community and academic team members, as well as areas with lower scores.

Nine community and 14 academic (staff and faculty) partners completed the survey. Respondents positively assessed group process outcomes (shared values, leadership, community-centeredness, and decision-making), and slightly less positive assessments of institutional outcomes. Storytelling sessions confirmed the overall satisfaction of community partners but highlighted actionable concerns within power-sharing, decision-making, funding equity, and trust-building.

The results of this equity-centered evaluation suggest the utility and importance of participatory, mixed-methods approaches to evaluating community-academic institutional advisory groups.

Suicidal behaviors (SB) in bipolar disorder (BD) are major adverse outcomes that may influence disease progression. While staging models exist for psychiatric disorders, none include suicide. This study aims to stratify suicidal risk in BD, propose a staging model for SB, and assess its clinical utility.

Participants from the FondaMental Advanced Centers of Expertise for Bipolar Disorder (FACE-BD) cohort were categorized into five stages (St) based on SB: St0 (no suicidal ideation [SI]), St1 (SI but no suicide attempt [SA]), St2a (non-severe/violent SA), St2b (severe /violent SA), and St3 (multiple SAs). Stages were analyzed based on demographic, clinical, cognitive, and biological characteristics using logistic regression.

Key differences emerged between stages. St1 showed longer untreated illness and higher lability and lower functioning than St0. St2a was linked to anxiety, substance use disorders, and longer disorder duration, while male gender and lithium bitherapy were protective. St2b exhibited shorter untreated illness and higher childhood trauma (CTQ) scores, with male gender and alcohol use as risk factors. St3 was associated with BD-II, alcohol use, longer disorder duration, and more depressive episodes, but less anxiety. No biochemical or cognitive differences were found across stages. The model was significantly associated with SA occurrence (LRT = 28.74, p < 0.0001).

This staging model for suicidality in BD provides a multifaceted approach to risk stratification and predictive insights, although further refinement is needed.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).

Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.

Physical pain is a common issue in people with bipolar disorder (BD). It worsens mental health and quality of life, negatively impacts treatment response, and increases the risk of suicide. Lithium, which is prescribed in BD as a mood stabilizer, has shown promising effects on pain.

This naturalistic study included 760 subjects with BD ( FACE-BD cohort) divided in two groups: with and without self-reported pain (evaluated with the EQ-5D-5L questionnaire). In this sample, 176 subjects were treated with lithium salts. The objectives of the study were to determine whether patients receiving lithium reported less pain, and whether this effect was associated with the recommended mood-stabilizing blood concentration of lithium.

Subjects with lithium intake were less likely to report pain (odds ratio [OR] = 0.59, 95% confidence interval [CI], 0.35–0.95; p = 0.036) after controlling for sociodemographic variables, BD type, lifetime history of psychiatric disorders, suicide attempt, personality traits, current depression and anxiety levels, sleep quality, and psychomotor activity. Subjects taking lithium were even less likely to report pain when lithium concentration in blood was ≥0.5 mmol/l (OR = 0.45, 95% CI, 0.24–0.79; p = 0.008).

This is the first naturalistic study to show lithium’s promising effect on pain in subjects suffering from BD after controlling for many confounding variables. This analgesic effect seems independent of BD severity and comorbid conditions. Randomized controlled trials are needed to confirm the analgesic effect of lithium salts and to determine whether lithium decreases pain in other vulnerable populations.

Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample.

The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo’s Older Americans Normative Studies (MOANS) norms.

Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6–27% variance explained), sex (0–13%), and education (2–10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS.

Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

To examine the prevalence of malnutrition among children and adolescents visiting Kanti Children’s Hospital (KCH) and identify predictors associated with malnutrition. Results will guide the development of a newly established nutrition programme at KCH.

This cross-sectional pilot study recruited children and adolescents over a 1-month period. Nutritional anthropometrics (height, weight and mid-upper arm circumference (MUAC)) and socio-demographic questionnaires were administered. Clinical data were abstracted from the medical chart.

KCH in Kathmandu, Nepal.

370 children and adolescents.

Most participants were male (65·1 %); mean age was 3·9 years (±3·4 years). The prevalence of stunting was 25·9 %, wasting was 17·3 % and 24·0 % when classified by BMI-for-age Z-score or MUAC, respectively. Two percent of participants were overweight. Notably, 32·1 % of children ≥5 years were classified with wasting based on MUAC-for-age Z-score, which is higher than that observed in children <5 (20·2 %). Food insecurity was reported among 58·2 % of children with stunting and 34·0 % with wasting. Chronic medical conditions predicted stunting and wasting. The lowest level of wealth predicted stunting, while ethnicity predicted wasting. Ethnicity and education level predicted food insecurity.

We found that the prevalence of stunting and wasting at KCH are higher than previously published studies in Nepal. Malnutrition persists beyond 5 years, and we identified several predictors of malnutrition. Increased provision of and access to clinical nutrition programmes is an essential need for KCH. Twinning programs that provide local clinicians with increased opportunities for education and mentorship of local staff remains a pressing need in Nepal.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).

Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.

The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.

Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Understanding parents’ communication preferences and how parental and child characteristics impact satisfaction with communication is vital to mitigate communication challenges in the cardiac ICU.

This cross-sectional survey was conducted from January 2019 to March 2020 in a paediatric cardiac ICU with parents of patients admitted for at least two weeks. Family satisfaction with communication with the medical team was measured using the Communication Assessment Tool for Team settings. Clinical characteristics were collected via Epic, Pediatric Cardiac Critical Care Consortium local entry and Society for Thoracic Surgeons Congenital Heart Surgery Databases. Associations between communication score and parental mood, stress, perceptions of clinical care, and demographic characteristics along with patient demographic and clinical characteristics were examined. Multivariable ordinal models were conducted with characteristics significant in bivariate analysis.

In total, 93 parents of 84 patients (86% of approached) completed surveys. Parents were 63% female and 70% White. Seventy per cent of patients were <6 months old at admission, 25% had an extracardiac abnormality, and 80% had a cardiac surgery this admission. Parents of children with higher pre-surgical risk of mortality scores (OR 2.875; 95%CI 1.076–7.678), presence of surgical complications (72 [63.0, 75.0] vs. 64 [95%CI 54.6, 73] (p = 0.0247)), and greater satisfaction with care in the ICU (r = 0.93922; p < 0.0001) had significantly higher communication scores.

These findings can prepare providers for scenarios with higher risk for communication challenges and demonstrate the need for further investigation into interventions that reduce parental anxiety and improve communication for patients with unexpected clinical trajectories

The objective of the present policy analysis was to understand how a disinvestment approach to the process of health technology assessment (HTA), applied to the field of medical devices, might help Italian policymakers to properly spend the resources in healthcare.

Previous international and national experiences in disinvestment for medical devices were reviewed. Precious insights for the rational expenditure of the resources were derived by assessing the evidence available.

The disinvestment of ineffective or inappropriate technologies or interventions with an inadequate value-for-money ratio has become a growing priority for National Health Systems. Different international disinvestment experiences of medical devices were identified and described through a rapid review. Although most of them have a strong theoretical framework, their practical application remains difficult. In Italy, there are no examples of large and complex HTA-based disinvestment practices, but their importance is becoming increasingly acknowledged, especially given the need to prioritize the funds provided by Recovery and Resilience Plan.

Anchoring decisions on health technologies without reassessing the current technological landscape through a robust HTA model might expose to the risk of not ensuring the best employment of the resources available. Thus, it is necessary to develop a strong HTA ecosystem in Italy through adequate consultation with stakeholders to enable a data-driven and evidence-based prioritization of resources toward choices characterized by high value for both patients and society as a whole.

Suicide is a major public health problem and a cause of premature mortality. With a view to prevention, a great deal of research has been devoted to the determinants of suicide, focusing mostly on individual risk factors, particularly depression. In addition to causes intrinsic to the individual, the social environment has also been widely studied, particularly social isolation. This paper examines the social dimension of suicide etiology through a review of the literature on the relationship between suicide and social isolation.

Medline searches via PubMed and PsycINFO were conducted. The keywords were “suicid*” AND “isolation.”

Of the 2,684 articles initially retrieved, 46 were included in the review.

Supported by proven theoretical foundations, mainly those developed by E. Durkheim and T. Joiner, a large majority of the articles included endorse the idea of a causal relationship between social isolation and suicide, and conversely, a protective effect of social support against suicide. Moreover, the association between suicide and social isolation is subject to variations related to age, gender, psychopathology, and specific circumstances. The social etiology of suicide has implications for intervention and future research.

Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide.

A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords.

Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings.

AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified.

This study sought to identify coronavirus disease 2019 (COVID-19) risk communication materials distributed in Jamaica to mitigate the effects of the disease outbreak. It also sought to explore the effects of health risk communication on vulnerable groups in the context of the pandemic.

A qualitative study was conducted, including a content analysis of health risk communications and in-depth interviews with 35 purposively selected elderly, physically disabled, persons with mental health disorders, representatives of government agencies, advocacy and service groups, and caregivers of the vulnerable. Axial coding was applied to data from the interviews, and all data were analyzed using the constant comparison technique.

Twelve of the 141 COVID-19 risk communication messages directly targeted the vulnerable. All participants were aware of the relevant risk communication and largely complied. Barriers to messaging awareness and compliance included inappropriate message medium for the deaf and blind, rural location, lack of Internet service or digital devices, limited technology skills, and limited connection to agencies that serve the vulnerable.

The vulnerable are at increased risk in times of crisis. Accessibility of targeted information was inadequate for universal access to health information and support for vulnerable persons regardless of location and vulnerability.

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.