To perform a meta-analysis of clinical studies on the differences in treatment or research decision-making capacity among patients with Mild Cognitive Impairment (MCI), Alzheimer’s disease (AD), and healthy comparisons (HCs).

A systematic search was conducted on Medline/Pubmed, CINAHL, PsycINFO, Web of Science, and Scopus. Standardized mean differences and random-effects model were used in all cases.

The United States, France, Japan, and China.

Four hundred and ten patients with MCI, 149 with AD, and 368 HCs were included.

The studies we included in the analysis assessed decisional capacity to consent by the MacArthur Competence Assessment Tool for Treatment (MAcCAT-T), MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR), Capacity to Consent to Treatment Instrument (CCTI), and University of California Brief Assessment of Capacity to Consent (UBACC).

We identified 109 potentially eligible studies from 1672 records, and 7 papers were included in the meta-analysis. The meta-analysis showed that there was significant impairment in a decision-making capacity in MCI patients compared to the HCs group in terms of Understanding (SMD = −1.04, 95% CI: −1.31 to −0.77, P < 0.001; I2 = 52%, P = 0.07), Appreciation (SMD = −0.51, 95% CI: −0.66 to −0.36, P < 0.001; I2 = 0%, P = 0.97), and Reasoning (SMD = −0.62, 95% CI: −0.77, −0.47, P < 0.001; I2=0%, P =0.46). MCI patients scored significantly higher in Understanding (SMD = 1.50, 95% CI: 0.91, 2.09, P = 0.01, I2 = 78%, P = 0.00001) compared to patients affected by AD.

Patients affected by MCI are at higher risk of impaired capacity to consent to treatment and research compared to HCs, despite being at lower risk compared to patients affected by AD. Clinicians and researchers need to carefully evaluate decisional capacity in MCI patients providing informed consent.

Ghana is in the process of formally introducing health technology assessment (HTA) for health decision making. Similar to other low- and middle-income countries, evidence suggests that the lack of data and human capacity is a major barrier to the conduct and use of HTA. This study assessed the current human and data capacity available in Ghana to undertake HTA.

As economic evaluation (EE) forms an integral part of HTA, a systematic review of EE studies undertaken in Ghana was conducted to identify the quality and number of studies available, methods and source of data used, and local persons involved. The literature search was undertaken in EMBASE (including MEDLINE), PUBMED, and Google Scholar. The quality of studies was evaluated using the Consolidated Health Economics Evaluation Reporting Standards. The number of local Ghanaians who contributed to authorship were used as a proxy for assessing human capacity for HTA.

Thirty-one studies were included in the final review. Overall, studies were of good quality. Studies derived their effectiveness, resource utilization and cost data mainly from Ghana. The most common source of cost data was from the National Health Insurance Scheme pricing list for medicines and tariffs. Effectiveness data were mostly derived from either single study or intervention programs. Sixty out of 199 authors were Ghanaians (30 percent); these authors were mostly involved in data collection and study conceptualization.

Human capacity for HTA in Ghana is limited. To introduce HTA successfully in Ghana, policy makers would need to develop more local capacity to undertake Ghanaian-specific HTA.

People with dementia receive worse end of life care compared to those with cancer. Barriers to undertaking advanced care planning (ACP) in people with dementia include the uncertainty about their capacity to engage in such discussions. The primary aim of this study was to compare the Advance Care Planning–Capacity Assessment Vignette tool (ACP–CAV) with a semi-structured interview adapted from the MacArthur Competence Assessment Tool-Treatment (MacCAT-T). The secondary aim was to identify demographic and cognitive functioning variables that may predict whether a person has capacity to discuss ACP.

32 older people (mean age = 84.1) with a Mini-Mental State Examination of 24 or above were recruited from two retirement villages in Auckland. Participants also completed Trail Making Test Part A & Part B and Geriatric Depression Scale (GDS-15) before undertaking the two capacity assessments that were video recorded to enable further analysis by four independent old age psychiatrists.

Using the MacCAT-T as the gold standard, over half (53.1%) of the participants were considered as lacking in capacity to engage in ACP. Participants struggled with the “Understanding ACP” domain the most. Capacity was not predictable by any of the demographic or cognitive functioning variables. When compared to the gold standard, ACP–CAV was accurate in assessing capacity in 68.8% of the cases.

Clinicians should routinely explain ACP to older people and ensure they fully understand it prior to an ACP discussion. If there is any concern about their understanding, further exploration and documentation of their capacity using the capacity assessment framework would be necessary. However, capacity assessment is a complex iterative process that does not easily lend itself to screening methodology and requires a high level of clinical judgment.

Declines in financial capacity in later life may arise from both neurocognitive and/or psychiatric disorders. The influence of socio-demographic, cognitive, health, and psychiatric variables on financial capacity performance was explored.

Seventy-six healthy community-dwelling adults and 25 older patients referred for assessment of financial capacity were assessed on pertinent cognitive, psychiatric, and financial capacity measures, including Addenbrooke's Cognitive Examination – Revised (ACE-R), Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), selected Neuropsychiatric Inventory (NPI) items, Financial Competence Assessment Inventory (FCAI), and Social Vulnerability Scale (SVS).

The internal consistency of the debt management subscale of the FCAI was relatively poor in our sample. Financial capacity performance differed between controls and patients. In our sample, performance on the FCAI was predicted by Mini-Mental State Examination, IQCODE, and GAI, but not by ACE-R, GDS, NPI items, or SVS (adjusted R2 = 0.7059).

Anxiety but not depression predicted financial capacity performance, possibly reflecting relatively low variance of depressive symptoms in this sample. Current cognitive decline as measured by the informant-rated IQCODE was more highly correlated to financial capacity than either educational attainment or ACE-R scores. Lack of significance of ACE-R data may reflect the instrument's decreased sensitivity to domains relevant to financial capacity, compared with more detailed neuropsychological assessment tools. The FCAI displayed fairly robust psychometric properties apart from the debt management subscale.