Examining the validity of the Mini-Mental State Examination (MMSE) and its domains using network analysis.

BACKGROUND: The Mini-Mental State Examination (MMSE) is the most widely used standardised screener for impairments across a range of cognitive domains. However, the degree to which its domains (orientation, registration, attention, recall, language, and visuospatial) capture cognitive functioning measured using standardised neuropsychological tests is unclear. METHOD: A longitudinal research design with four biannual assessments over a 6-year period was used with an initial sample of 1037 older adults (aged above 70 years). Participants completed MMSE and neuropsychological tests at each assessment. Network analysis was utilised to investigate unique associations among the MMSE and its domains and neuropsychological test performance at each time point. RESULTS: The total MMSE and two of its domains, language and recall, were associated with neuropsychological memory performance. The MMSE orientation, registration and visuospatial domains did not have any unique associations with neuropsychological performance. No stable internal interconnections between MMSE domains were found over time. The association of total MMSE as well as its recall domain with neuropsychological memory performance remained very similar over the 6-year period. CONCLUSIONS: The present study adds evidence to the validity of the MMSE and supports the clinical usage of the MMSE, whereby the total score is used for screening patients with or without cognitive impairments, with repeated administration to monitor cognitive changes over time, to inform intervention. However, the tool is not able to diagnose the cases for changes in specific cognitive domains and as such, should not replace a complete neuropsychological assessment.

Which fatigue scale should I use? A Rasch analysis of two fatigue scales in inflammatory conditions.

OBJECTIVES: This study aimed to assess the psychometric properties of two widely used fatigue scales in a sample of patients with inflammatory conditions. METHODS: Rasch analysis was used to examine scale reliability, item bias, unidimensionality and overall fit to the Rasch model. Sub-test methodology was utilised to attempt to improve model fit for the CFQ and BRAF-MDQ. RESULTS: Initial analysis displayed strong reliability (PSI=0.89 0.96), alongside a lack of item bias in both scales. However, evidence for unidimensionality was not found for either scale. Overall fit to the Rasch model was marginal for the CFQ, and misfitting for the BRAF-MDQ. Local dependency was observed, as well as significant item misfit for both scales. Sub-test modifications resulted in the best model fit for the BRAF-MDQ (χ2(16)=15.77, p=0.469) and the CFQ (χ2(25)=15.49, p=0.929). Modifications resulted in improved fit, reductions in measurement error, and the production of ordinal-to-interval conversion tables for both scales. Conversion tables apply the benefits of enhanced measurement accuracy, valid comparison of BRAF-MDQ and CFQ scores to other interval-level data, appropriate use in parametric statistics, and enhanced precision in clinical cut-off scores-without the need to change administration format. CONCLUSION: The BRAF-MDQ and CFQ are valid, reliable tools for fatigue assessment. Psychometric indices and content factors suggest the CFQ is suited to measuring general fatigue, particularly when response burden is a concern, while the BRAF-MDQ should be used in clinical presentations where other symptoms are severe and the impact of fatigue on daily living, emotional, and social well-being is of interest.

Network of mental activities, cognitive function and depression in older men and women.

BACKGROUND: Evidence suggests that lifestyle activities impact cognitive and mental health in older populations. However, how lifestyle factors are associated with one another, and which factors are most important for cognitive function and mental health has received comparatively little attention. DESIGN: Bayesian-Gaussian network analysis was used to investigate unique associations between mental activities (MA; i.e., activities involving cognitive engagement), global cognition, and depression at three time-points in a large sample of older adults (baseline, 2 years, and 4 years follow-up). SETTING: This study used longitudinal data from participants living in Australia and participating in the Sydney Memory and Ageing Study. PARTICIPANTS: The sample included 998 participants (55% female) aged between 70 and 90, without a diagnosis of dementia at baseline. MEASUREMENTS: Neuropsychological assessment of global cognition, self-reported depressive symptoms, and self-reported information about daily MA. RESULTS: Cognitive functioning was positively associated with playing tabletop games and using the internet in both sexes at all time-points. MA were differentially linked in men and women. Depression was not consistently associated with MA in men across the three time-points; women who visited artistic events consistently had lower depression scores. CONCLUSIONS: Engaging with tabletop games and using the internet was associated with better cognition in both sexes, however sex acted as a modifier for other associations. These findings are useful for future investigations that consider interactive associations between MA, cognition, and mental health in older adults, and their possible roles in promoting healthy aging.

Using network analysis to validate domains of the modified telephone interview for cognitive status.

BACKGROUND: The modified Telephone Interview for Cognitive Status (TICS-M) is a widely used tool for assessing global cognitive functions and screening for cognitive impairments. The tool was conceptualised to capture various cognitive domains, but the validity of such domains has not been investigated against comprehensive neuropsychological assessments tools. Therefore, this study aimed to explore the associations between the TICS-M domains and neuropsychological domains to evaluate the validity of the TICS-M domains using network analysis. MATERIALS AND METHODS: A longitudinal research design was used with a large sample of older adults (aged above 70 years; n = 1037 at the baseline assessment) who completed the TICS-M and comprehensive neuropsychological assessments biennially. We applied network analysis to identify unique links between the TICS-M domains and neuropsychological test scores. RESULTS: At baseline, there were weak internal links between the TICS-M domains. The TICS-M memory and language domains were significantly related to their corresponding neuropsychological domains. The TICS-M attention domain had significant associations with executive function and visuospatial abilities. The TICS-M orientation domain was not significantly associated with any of the five neuropsychological domains. Despite an attrition of almost 50% at wave four, weak internal links between the TICS-M domains and most associations between TICS-M and neuropsychological domains that were found initially, remained stable at least over two waves within the 6-year period. CONCLUSIONS: This study supports the overall structural validity of the TICS-M screener in assessing enduring global cognitive function. However, separate TICS-M cognitive domains should not be considered equivalent to the analogous neuropsychological domains.

Enhancing precision of the Telephone Interview for Cognitive Status-Modified (TICS-M) using the Rasch model.

The Telephone Interview for Cognitive Status-modified (TICS-M) is a well-established and widely used screening instrument for dementia and assessment of global cognitive function in older people. This study aimed to evaluate the psychometric properties of the TICS-M and to enhance the accuracy of the instrument using Rasch methodology. Partial Credit Rasch model was applied to the TICS-M scores. The sample selected for Rasch analysis consisted of 432 participants aged 70-90 years (M = 78.85, SD = 4.73) including 195 males (237 females), and 132 (30.56%) of whom were diagnosed with dementia after the baseline assessment. Initial analysis indicated good reliability of the TICS-M assessment scores, but there were three misfitting items and local dependency issues. Combining locally dependent and misfitting items into super-items achieved the best Rasch model fit for the TICS-M. This modification improved reliability of the assessment scores and resulted in no misfitting items, no local dependency, strict unidimensionality, and invariance across individual factors such as participants age, sex, diagnosis, and in-person neuropsychological assessment scores. Satisfying Rasch model expectations allowed for creation of a transformation table to convert raw TICS-M scores into interval-level data, which improves precision of the instrument. In summary, the TICS-M assessment scores demonstrated excellent reliability as reflected by Person Separation Index (PSI = 0.86) and met expectations of the unidimensional Rasch model after minor adjustments. The ordinal-to-interval transformation table can be used to increase accuracy of the TICS-M without altering its current format. These findings contribute to more accurate assessments of cognitive decline in older people and screening for conditions such as dementia. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating depression anxiety and stress assessment before and during the COVID-19 pandemic using generalisability theory.

The current study investigated the assessment of depression, anxiety, and stress during normal and COVID-19 pandemic conditions. Generalisability theory (G-theory) was applied to examine stable and dynamic aspects of psychological distress and the overall reliability of the Depression, Anxiety and Stress Scales (DASS-21), using data from two independent samples collected on three occasions with 2- to 4-week intervals. The US data (n = 115) was collected before the COVID-19 pandemic, and the New Zealand (NZ) data (n = 114) was obtained during the pandemic. The total DASS-21 demonstrated excellent reliability in measuring enduring symptoms of psychological distress (G = .94-.96) across both samples. While all DASS-21 subscales demonstrated good reliability with the pre-pandemic US sample, the subscales' reliability was below an acceptable level for the NZ sample. Findings from this study indicate that the overall psychological distress is enduring and can be reliably measured by the DASS-21 across different conditions and populations, while shifts across depression, anxiety and stress levels are likely during emergency and uncertainty, as seen in the COVID-19 pandemic.

Measuring distress in older population: Rasch analysis of the Kessler Psychological Distress Scale.

OBJECTIVES: The 10-item Kessler Psychological Distress Scale (K-10) is a widely applied distress measure; however, its psychometric properties were not established with older populations using advanced methodology. The aim of this study was to examine psychometric properties of the K-10 through application of Rasch methodology and if possible, develop an ordinal-to-interval conversion to improve its reliability in older populations. METHOD: The Partial Credit Rasch Model was applied to analyse K-10 scores of the sample including 490 participants (56.3 % females) aged 70 to 90 years and without dementia from the Sydney Memory and Ageing Study (MAS). RESULTS: The initial analysis of the K-10 showed poor reliability and significant deviation from the expectations of the Rasch model. The best model fit was evident after correcting disordered thresholds and creating two testlet models to address local dependency between items (χ2(35) = 29.87, p = 0.71). The modified K-10 demonstrated strict unidimensionality, enhanced reliability and scale invariance across personal factors, such as sex, age, and education and permitted development of ordinal-to-interval transformation algorithms. LIMITATIONS: Ordinal-to-interval conversion can only be applied for older adults with complete data. CONCLUSIONS: The K-10 satisfied principles of fundamental measurement defined by Rasch model after minor modifications. Clinicians and researchers can transform K-10 raw scores into interval-level data using converging algorithms published here without altering the original scale response format, which increases reliability of the K-10.

Establishing conversion of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly scores into interval-level data across multiple samples using Rasch methodology.

BACKGROUND: The 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) is a well-validated and widely-used measure of cognitive changes (CCs) among older adults. This study aimed to use Rasch methodology to establish psychometric properties of the IQCODE-16 and validate the existing ordinal-to-interval transformation algorithms across multiple large samples. METHODS: A Partial Credit Rasch model was employed to examine psychometric properties of the IQCODE-16 using data (n = 918) from two longitudinal studies of participants aged 57-99 years: the Older Australian Twins Study (n = 450) and the Canberra Longitudinal Study (n = 468), and reusing the Sydney Memory and Ageing Study (MAS) sample (n = 400). RESULTS: Initial analyses indicated good reliability for the IQCODE-16 (Person Separation Index range: 0.82-0.90). However, local dependency was identified between items, with several items showing misfit to the model. Replicating the existing Rasch solution could not reproduce the best Rasch model fit for all samples. Combining locally dependent items into three testlets resolved all misfit and local dependency issues and resulted in the best Rasch model fit for all samples with evidence of unidimensionality, strong reliability, and invariance across person factors. Accordingly, new ordinal-to-interval transformation algorithms were produced to convert the IQCODE-16 ordinal scores into interval data to improve the accuracy of its scores. CONCLUSIONS: The findings of this study support the reliability and validity of the IQCODE-16 in measuring CCs among older adults. New ordinal-to-interval conversion tables generated using samples from multiple independent datasets are more generalizable and can be used to enhance the precision of the IQCODE-16 without changing its original format. An easy-to-use converter has been made available for clinical and research use.

Mindfulness-Based Attention Training in the Navy: A Feasibility Study.

Mind wandering is common during daily activities and is even more prevalent under stressful conditions, which could lead to lapses in attention and poor performance. Newly recruited military personnel who undergo demanding training often experience high levels of stress. It is therefore imperative to find ways to foster mental health and avoid performance deterioration related to mind wandering in times of intense military training. This feasibility study investigated the effectiveness of an established low-dose mindfulness-based intervention (MBI), called Mindfulness-based Attention Training (MBAT), on mind wandering, attentional performance, and well-being, delivered by a facilitator who was taught how to deliver MBAT. A sample of newly recruited Royal New Zealand Navy (RNZN) Junior Officers (n = 17) undergoing demanding training participated in the 8-week long MBI with one weekly contact session. Measures of well-being and the Sustained Attention to Response Task (SART) were completed 4 weeks prior to the MBAT, at the start of the MBAT, at the end of the MBAT and 4 weeks after completion of the MBAT. Results suggest that MBAT might protect from performance decline during intense training and enhance levels of well-being at follow-up. These findings highlight the valuable role of mindfulness as a component in military training.

Implications for COVID-19 vaccine uptake: A systematic review.

BACKGROUND: Globally, increasing coronavirus disease (COVID-19) vaccination coverage remains a major public health concern in the face of high rates of COVID-19 hesitancy among the general population. We must understand the impact of the determinants of COVID-19 vaccine uptake when designing national vaccination programmes. We aimed to synthesise nationwide evidence regarding COVID-19 infodemics and the demographic, psychological, and social predictors of COVID-19 vaccination uptake. METHODS: We systematically searched seven databases between July 2021 and March 2022 to retrieve relevant articles published since COVID-19 was first reported on 31 December 2019 in Wuhan, China. Of the 12,502 peer-reviewed articles retrieved from the databases, 57 met the selection criteria and were included in this systematic review. We explored COVID-19 vaccine uptake determinants before and after the first COVID-19 vaccine roll-out by the Food and Drug Authority (FDA). RESULTS: Increased COVID-19 vaccine uptake rates were associated with decreased hesitancy. Concerns about COVID-19 vaccine safety, negative side effects, rapid development of the COVID-19 vaccine, and uncertainty about vaccine effectiveness were associated with reluctance to be vaccinated. After the US FDA approval of COVID-19 vaccines, phobia of medical procedures such as vaccine injection and inadequate information about vaccines were the main determinants of COVID-19 vaccine hesitancy. CONCLUSION: Addressing effectiveness and safety concerns regarding COVID-19 vaccines, as well as providing adequate information about vaccines and the impacts of pandemics, should be considered before implementation of any vaccination programme. Reassuring people about the safety of medical vaccination and using alternative procedures such as needle-free vaccination may help further increase vaccination uptake.

A Pilot Study of Application of the Stroke Riskometer Mobile App for Assessment of the Course and Clinical Outcomes of COVID-19 among Hospitalized Patients.

INTRODUCTION: Early determination of COVID-19 severity and health outcomes could facilitate better treatment of patients. Different methods and tools have been developed for predicting outcomes of COVID-19, but they are difficult to use in routine clinical practice. METHODS: We conducted a prospective cohort study of inpatients aged 20-92 years, diagnosed with COVID-19 to determine whether their individual 5-year absolute risk of stroke at the time of hospital admission predicts the course of COVID-19 severity and mortality. The risk of stroke was determined by the Stroke Riskometer mobile application. RESULTS: We examined 385 patients hospitalized with COVID-19 (median age 61 years). The participants were categorized based on COVID-19 severity: 271 (70.4%) to the "not severe" and 114 (29.6%) to the "severe" groups. The median risk of stroke the next day after hospitalization was significantly higher among patients in the severe group (2.83, 95% CI: 2.35-4.68) versus the not severe group (1.11, 95% CI: 1.00-1.29). The median risk of stroke and median systolic blood pressure (SBP) were significantly higher among non-survivors (12.04, 95% CI: 2.73-21.19) and (150, 95% CI: 140-170) versus survivors (1.31, 95% CI: 1.14-1.52) and (134, 95% CI: 130-135), respectively. Those who spent more than 2.5 h a week on physical activity were 3.1 times more likely to survive from COVID-19. Those who consumed more than one standard alcohol drink a day, or suffered with atrial fibrillation, or had poor memory were 2.5, 2.3, and 2.6 times more likely not to survive from COVID-19, respectively. CONCLUSIONS: High risk of stroke, physical inactivity, alcohol intake, high SBP, and atrial fibrillation are associated with severity and mortality of COVID-19. Our findings suggest that the Stroke Riskometer app could be used as a simple predictive tool of COVID-19 severity and mortality.

The Impact of a Mindfulness App on Postnatal Distress.

Objectives: The present study investigated the effectiveness of an 8-week mindfulness mobile phone app on women's depression, anxiety, stress and mindful attention/awareness in the postnatal period. Methods: The study enrolled 99 mothers of a child under 1 year old, and randomly assigned them to intervention (n = 49, mean age = 31.11, SD = 4.30, years) and control (n = 50, mean age = 31.35, SD = 5.29, years) groups. Multiple regression examined intervention effects on depression, anxiety, stress and mindful attention/awareness measured post-intervention and at 4-week follow-up, controlling for the baseline and post-intervention measurement of the specific outcome, respectively. Results: The intervention group showed significant decreases in depression, anxiety and stress levels and an increase of mindful attention/awareness post-intervention compared to the control group, with medium to large effect sizes after controlling for effects of corresponding variables at baseline. The intervention group showed further decrease in depression and stress levels and an increase in mindful attention/awareness at 4 weeks post-intervention compared to the control group, with small to medium effect sizes, after controlling for effects of corresponding variables at post-intervention. Conclusions: The outcomes of the study suggest that delivery of mindfulness via smartphones could be a viable and affordable resource for reducing postnatal depression, anxiety and stress.

Effects of Mindful Practices on Terror of Mortality: A Randomized Controlled Trial.

Objectives: Early Buddhist thought clearly recognizes the need for learning how to face one's own mortality, for which purpose mindfulness practice has a central role to play. Fear of death has also been studied in cognitive psychology, leading to what is known as the terror management theory. Actual research evidence in psychology has already shown that mindfulness practice may reduce fear and anxiety in general. However, there is a lack of research examining the specific effects of brief mindfulness practices on the fear of death and dying. In this study we tested the hypothesis that brief mindfulness practices used daily over a period of 6 weeks will result in a reduction of the fear of death and dying when compared to brief contemplative practices used as an active control condition. Methods: Participants (n = 89) were randomly assigned to the mindfulness (n = 44) and the contemplation (n = 45) conditions and completed validated scales measuring four distinct fears related to either the process of dying or the final event of death (dying of oneself, death of oneself, dying of others, and death of others), mindfulness, and self-compassion at baseline, post-intervention (at 6 weeks) and follow up (1‒3 weeks after the end of the 6-week intervention). ANOVA was used to investigate the effects of both interventions on outcome variables over time and between groups. Results: Both mindfulness and contemplative practices were equally effective in reducing fear related to dying of oneself and death of others while increasing fear of dying of others, mindfulness, and self-compassion. No significant intervention effects were found for fear related to death of oneself only. Conclusions: These results suggest that fears related to dying of oneself and death of others can be reduced using both mindfulness and contemplative practices that may simultaneously increase mindfulness and self-compassion. Supplementary Information: The online version contains supplementary material available at 10.1007/s12671-022-01967-8.

Investigating Stable and Dynamic Aspects of the Vietnamese Self-Compassion Scale using Generalisability Theory.

Objectives: Evaluating comprehensive reliability of the Vietnamese Self-Compassion Scale (VSCS) and its ability to distinguish between trait (stable) vs state (dynamic) aspects of self-compassion using Generalisability Theory (G-Theory) is necessary. This investigation contributes to both reliability and validity of research that uses the VSCS to measure self-compassion in Vietnamese adults. Methods: In a sample of 155 Vietnamese adults who completed the VSCS at three occasions that were each 2 weeks apart, a G-study was conducted to measure reliability and trait vs state aspects of each VSCS subscale and the short-form VSCS, and a D-study was conducted to examine the effects of removing subscales on overall scale reliability as well as evaluate trait vs state aspects of each item. Results: With G-coefficients of 0.93-0.98, both the complete and short-form VSCS (VSCS-SF) demonstrated excellent reliability in measuring trait self-compassion. Three of the six subscales-self-judgement, mindfulness, and kindness-also demonstrated excellent reliability, with G-coefficients of 0.82-0.85. Eighteen of the 26 items measured trait more than state. The remaining eight items reflected a mixture of trait and state, but this did not affect overall reliability. Conclusions: This study indicated that the VSCS, VSCS-SF, and three VSCS subscales reliably measured trait self-compassion, with scores generalisable across the Vietnamese population and occasions. Thus, overall self-compassion levels remained stable over time, which is useful for evaluating the effectiveness of an intervention because significant changes of self-compassion are likely to be long-lasting. Supplementary Information: The online version contains supplementary material available at 10.1007/s12671-022-01950-3.

Networks of inflammation, depression, and cognition in aging males and females.

BACKGROUND: Prioritizing the maintenance of healthy cognitive aging and personalizing preventive interventions to enhance their effectiveness is crucial as the global population ages. Systemic inflammation and depression in older people have been associated with decreased levels of cognition but results have been inconsistent. AIMS: To explore the interactive network of inflammation, depression and cognition by sex in older people. METHODS: We used novel network analysis to explore the unique associations between inflammatory biomarkers, depression, cognition, and somatic, genetic, and lifestyle risk factors in an older (aged 70-90 years), non-demented, community-dwelling sample from the longitudinal Sydney Memory and Aging Study (N = 916) at baseline and at a two-year follow-up. RESULTS: The networks of biomarkers, depression, cognition, and relevant covariates were significantly different between males and females. A stable negative link between depression and cognition was found in females only; a stable positive association between biomarker interleukin-6 and depression was found in females only; and a stable positive association between biomarker interleukin-8 and alcohol was found in females only. For both males and females, a stable, positive relationship was found between the presence of APOE-ε4 gene and biomarker C-reactive protein; between education and cognition; and between biomarker interleukin-6 and all other biomarkers. CONCLUSIONS: These findings suggest different psychophysiological mechanisms underlie the interactive network of biomarkers, depression and cognition in males and females that should be considered when designing personalized preventive interventions to maintain cognitively healthy aging.

Investigating Predictors of Psychological Distress for Healthcare Workers in a Major Saudi COVID-19 Center.

This study investigated the relationship between fear of COVID-19, previous exposure to COVID-19, perceived vulnerability to disease, sleep quality, and psychological distress among healthcare workers (HCWs) in Taif city in Saudi Arabia, which has a population of 702,000 people. A cross-sectional study design was adopted. HCWs (n = 202) completed a survey containing the Fear of COVID-19 Scale (FCV-19S), Perceived Vulnerability to Disease (PVD), Pittsburgh Sleep Quality Index (PSQI), and Depression, Anxiety, and Stress Scale (DASS-21). FCV-19S and sleep quality were significant predictors for psychological distress. Female gender was a significant predictor for depression and stress. Single, divorced, and widowed marital status were predictive for anxiety. FCV-19S was weakly correlated with PVD but moderately with depression, anxiety, and stress. Of the two PVD subscales, perceived infectability was weakly correlated with psychological distress. PVD and previous experience with COVID-19 were not significant predictors. Sleep quality and FCV-19S were major predictors of psychological distress. Findings indicated that poor sleep quality was strongly associated with psychological distress, while fear of COVID-19 had a moderate association. Such results support the need to design and implement psychological programs to assist HCWs in dealing with the psychological impact of this ongoing pandemic.

Applying Rasch methodology to examine and enhance precision of the Edinburgh Postnatal Depression Scale.

BACKGROUND: The 10-item Edinburgh Postnatal Depression Scale (EPDS) is a widely used depression measure with acceptable psychometric properties, but it uses ordinal scaling that has limited precision for assessment of outcomes in clinical and research settings. This study aimed to apply Rasch methodology to examine and enhance psychometric properties of the EPDS by developing ordinal-to-interval conversion algorithm. METHODS: The Partial Credit Rasch model was implemented using a sample of 621 mothers of infants (birth to 2 years old) who completed the EPDS as a part of a larger online survey. RESULTS: Initial analysis indicated misfit to the Rasch model attributed to local dependency between individual EPDS items. The best model fit was achieved after combining six locally dependent items into three super-items resulting in non-significant item-trait interaction (χ2(49) = 46.61, p < 0.57), strong reliability (PSI = 0.86), unidimensionality and item invariance across personal factors such as age and mothers' education. This permitted generation of ordinal-to-interval conversion algorithms derived from person estimates of the Rasch model. LIMITATIONS: Ordinal-to-interval conversion cannot be applied for individuals with missing data. CONCLUSIONS: The EPDS met expectations of the unidimensional Rasch model after internal modifications, and its precision can be enhanced by using ordinal-to-interval conversion tables published in this article without the need to alter the original scale format. Scores derived from these conversion tables should decrease error and improve conformity with statistical assumptions in both clinical and research use of the EPDS, making monitoring of clinical status and outcomes more accurate.

Mindfulness Buffers the Effect of Inauthenticity on Depression.

OBJECTIVES: Pressures in daily life limit one's ability to be authentic and research shows that inauthenticity can be detrimental to mental health. Mindfulness is known to have a protective effect on mental health through an accepting and nonjudgmental stance. This study aimed to establish whether mindfulness buffers the relationship between inauthenticity and depression. METHOD: A cross-sectional sample of employed individuals in New Zealand (n=301) completed an online survey assessing their levels of authenticity, mindfulness, and depression. RESULTS: Findings indicate that authenticity and mindfulness together explain 29% of variance in depression. In addition, mindfulness can buffer the negative impact of low authenticity on depression. CONCLUSION: Inauthenticity is related to higher levels of depression, but mindfulness is able to buffer this impact. These findings imply that engaging in mindfulness practice may be beneficial for mental health when individuals experience reduced authenticity.

Rasch analysis of the Back Pain Attitudes Questionnaire (Back-PAQ).

CONTEXT: As psychosocial factors have been recognised as significant predictors of the recovery trajectory from chronic back pain, the 34-item Back Pain Attitudes Questionnaire (Back-PAQ) was developed based on themes obtained from patient interviews, but previous psychometric analyses with a general population sample revealed uncertainty around the factor structure of the instrument. OBJECTIVES: To provide more detailed information about the psychometric properties of the Back-PAQ when used with participants from the general population and also to test the internal validity of the tool for use with General Practitioners (GPs). METHODS: After applying partial-credit Rasch analysis with a sample of participants from the general population (n = 600), a replication analysis was conducted with a sample of GPs (n = 184). This approach permitted examination of sample-specific personal factors for differential item functioning. Subtests were used to differentiate between local dependency due to underlying dimensionality from local dependency due to method effects. RESULTS: A unidimensional fit to the Rasch model was achieved after 14 misfitting items had been deleted. The final 20-item solution also fit with a sample of 184 GPs. In both cases, the Back-PAQ-20 demonstrated good reliability (PSI ≥ 0.80), with no evidence of differential item functioning by personal factors. CONCLUSION: The ordinal-to-interval conversion algorithms presented here further enhance the precision of the scale and permit analysis of Back-PAQ-20 scores using parametric statistics. The present study provided evidence for valid and reliable assessment of the back pain recovery beliefs of both users as well as providers of health services.IMPLICATIONS FOR REHABILITATIONPsychosocial factors have been recognised as significant predictors of the recovery trajectory from chronic back pain.The 34-item Back Pain Attitudes Questionnaire (Back-PAQ) was developed based on themes obtained from patient interviews, but previous psychometric analyses with a general population sample revealed uncertainty around the factor structure of the instrument.The 20-item version of the Back Pain Attitudes Questionnaire (Back-PAQ) is shown here to have strong psychometric properties for administration with users and providers of health services.

Machine learning, artificial intelligence and the prediction of dementia.

PURPOSE OF REVIEW: Artificial intelligence and its division machine learning are emerging technologies that are increasingly applied in medicine. Artificial intelligence facilitates automatization of analytical modelling and contributes to prediction, diagnostics and treatment of diseases. This article presents an overview of the application of artificial intelligence in dementia research. RECENT FINDINGS: Machine learning and its branch Deep Learning are widely used in research to support in diagnosis and prediction of dementia. Deep Learning models in certain tasks often result in better accuracy of detection and prediction of dementia than traditional machine learning methods, but they are more costly in terms of run times and hardware requirements. Both machine learning and Deep Learning models have their own strengths and limitations. Currently, there are few datasets with limited data available to train machine learning models. There are very few commercial applications of machine learning in medical practice to date, mostly represented by mobile applications, which include questionnaires and psychometric assessments with limited machine learning data processing. SUMMARY: Application of machine learning technologies in detection and prediction of dementia may provide an advantage to psychiatry and neurology by promoting a better understanding of the nature of the disease and more accurate evidence-based processes that are reproducible and standardized.