Empowering Pacific Patients on the Weight Loss Surgery Pathway: A Co-designed Evaluation Study.

PURPOSE: Despite having the highest medical needs by population for weight loss treatment, Pacific patients in Aotearoa New Zealand face substantial levels of attrition in publicly funded weight loss surgery programs. In collaboration with the Auckland City Hospital bariatric surgery team, a Pacific-led preoperative weight loss surgery program was co-designed, delivered, and evaluated between 2020 and 2023. MATERIALS AND METHODS: This was a single-arm, prospective co-designed evaluation study that took place at Auckland City Hospital in Aotearoa New Zealand. Participants were Pacific patients (n = 14) referred to the weight loss surgery program. Survey and video diaries were analyzed to determine if the program had the potential to increase Pacific patient retention through the preoperative stage of weight loss surgery, increase surgery completion rates, and improve the quality of treatment experiences. RESULTS: Nine out of 14 participants attended all preoperative sessions. Six participants subsequently underwent weight loss surgery. Program components that had positive impacts on patient success and satisfaction were accessibility, information quality, having Pacific role models, cultural safety, and the group support system. The patients found the program to be culturally anchored and there was support for the implementation of the program going forward. CONCLUSION: This study demonstrated how a culturally anchored intervention can increase patient retention for those patients who may not respond to mainstream treatment. Adjusting existing preoperative weight loss surgery programs to integrate Pacific-led models of healthcare has the potential to increase Pacific patient resiliency to follow through with surgery.

Wellbeing measures for workers: a systematic review and methodological quality appraisal.

Introduction: Increasing attention on workplace wellbeing and growth in workplace wellbeing interventions has highlighted the need to measure workers' wellbeing. This systematic review sought to identify the most valid and reliable published measure/s of wellbeing for workers developed between 2010 to 2020. Methods: Electronic databases Health and Psychosocial Instruments, APA PsycInfo, and Scopus were searched. Key search terms included variations of [wellbeing OR "well-being"] AND [employee* OR worker* OR staff OR personnel]. Studies and properties of wellbeing measures were then appraised using Consensus-based Standards for the selection of health Measurement Instruments. Results: Eighteen articles reported development of new wellbeing instruments and eleven undertook a psychometric validation of an existing wellbeing instrument in a specific country, language, or context. Generation and pilot testing of items for the 18 newly developed instruments were largely rated 'Inadequate'; only two were rated as 'Very Good'. None of the studies reported measurement properties of responsiveness, criterion validity, or content validity. The three instruments with the greatest number of positively rated measurement properties were the Personal Growth and Development Scale, The University of Tokyo Occupational Mental Health well-being 24 scale, and the Employee Well-being scale. However, none of these newly developed worker wellbeing instruments met the criteria for adequate instrument design. Discussion: This review provides researchers and clinicians a synthesis of information to help inform appropriate instrument selection in measurement of workers' wellbeing. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=79044, identifier: PROSPERO, CRD42018079044.

Validation of the Music Therapy Assessment Tool for Awareness in Disorders of Consciousness With the Coma Recovery Scale-Revised.

OBJECTIVE: To examine (1) the concurrent validity of the Music Therapy Assessment Tool for Awareness in Disorders of Consciousness (MATADOC) with the criterion standard Coma Recovery Scale-Revised (CRS-R) for outcomes of awareness in patients with prolonged disorders of consciousness (PDoC), (2) the relationship between MATADOC items and CRS-R function subscales in similar domains, and (3) determine if items/function subscales measure different constructs. DESIGN: A prospective multicentric blinded study with repeated concurrent measures. SETTING: Three inpatient rehabilitation units. PARTICIPANTS: Convenience sample of 74 adults with PDoC (N=74). MAIN OUTCOME MEASURES: The MATADOC protocol elicits behavioral responsiveness using live music in 5 tasks. A total score ranges 0-10 scoring behaviors across 14-items. The CRS-R uses a language-based protocol and scores observed responses ranging from 0-23 in 6 function subscales. Both measures were delivered at 4 concurrent time points over 2 weeks. RESULTS: Fair (κ=0.238, P=.006) ranging to moderate (κ=0.419, P<.001) significant agreement was found between CRS-R and MATADOC diagnostic outcomes. Fair-borderline moderate significant agreement was found for overall diagnostic outcomes across all diagnostic categories (κ=0.397, P=.001). There was moderate significant agreement between measures for motor scores (0.551≤κ≤0.571, P<.001) and visual outcomes (0.192≤κ≤0.415, .001≤P<.005) but no agreement for item/function subscale outcomes assessing auditory responsiveness. Exploratory factor analysis of all items showed 2 factors, suggesting that MATADOC and CRS-R measure the same underlying latent variable (awareness) in different ways and could complement each other for diagnosis and intervention purposes. This was supported by scale analysis, which showed increased reliability when the 2 scales are used together rather than separately. CONCLUSIONS: Unlike the CRS-R, the music-based MATADOC scores auditory localization for complexity of response and categorizes these behaviors as conscious rather than reflexive. The MATADOC may supplement the CRS-R, having a particular role in interdisciplinary programming for providing a more robust assessment of auditory responsiveness because of using nonverbal musical stimuli.

Fear avoidance and return to work after mild traumatic brain injury.

OBJECTIVES: Fear avoidance is associated with symptom persistence after mild traumatic brain injury (mTBI). In this study, we investigated whether fear avoidance was associated with other outcomes such as return to work-related activity (RTW). MATERIALS AND METHODS: We analyzed associations between fear avoidance and RTW 6-9 months after mTBI, in two merged prospective mTBI cohorts. Adult participants aged 16 or over (n=175), presenting to outpatient services in New Zealand within 3 months of their injury, who were engaged in work-related activity at the time of injury, were included. Participants completed the Fear Avoidance Behavior after Traumatic Brain Injury (FAB-TBI) questionnaire at enrollment and 6 months later. Associations between FAB-TBI scores and RTW outcome were analyzed using multivariate approaches. RESULTS: Overall, 53% of participants had RTW by 6-9 months after mTBI. While early fear avoidance was weakly associated with RTW, persistent high fear avoidance between study assessments or increasing avoidance with time were associated with greater odds of still being off work 6-9 months after injury. CONCLUSIONS: Pervasive and increasing avoidance of symptom triggers after mTBI were associated with lower rates of RTW 6-9 months after mTBI. Further research is needed to better understand transition points along the recovery trajectory where fear avoidance behaviors fade or increase after mTBI.

Machine learning and network analysis for diagnosis and prediction in disorders of consciousness.

BACKGROUND: Prolonged Disorders of Consciousness (PDOC) resulting from severe acquired brain injury can lead to complex disabilities that make diagnosis challenging. The role of machine learning (ML) in diagnosing PDOC states and identifying intervention strategies is relatively under-explored, having focused on predicting mortality and poor outcome. This study aims to: (a) apply ML techniques to predict PDOC diagnostic states from variables obtained from two non-invasive neurobehavior assessment tools; and (b) apply network analysis for guiding possible intervention strategies. METHODS: The Coma Recovery Scale-Revised (CRS-R) is a well-established tool for assessing patients with PDOC. More recently, music has been found to be a useful medium for assessment of coma patients, leading to the standardization of a music-based assessment of awareness: Music Therapy Assessment Tool for Awareness in Disorders of Consciousness (MATADOC). CRS-R and MATADOC data were collected from 74 PDOC patients aged 16-70 years at three specialist centers in the USA, UK and Ireland. The data were analyzed by three ML techniques (neural networks, decision trees and cluster analysis) as well as modelled through system-level network analysis. RESULTS: PDOC diagnostic state can be predicted to a relatively high level of accuracy that sets a benchmark for future ML analysis using neurobehavioral data only. The outcomes of this study may also have implications for understanding the role of music therapy in interdisciplinary rehabilitation to help patients move from one coma state to another. CONCLUSIONS: This study has shown how ML can derive rules for diagnosis of PDOC with data from two neurobehavioral tools without the need to harvest large clinical and imaging datasets. Network analysis using the measures obtained from these two non-invasive tools provides novel, system-level ways of interpreting possible transitions between PDOC states, leading to possible use in novel, next-generation decision-support systems for PDOC.

Depression, anxiety and worry in young Pacific adults in New Zealand during the COVID-19 pandemic.

OBJECTIVE: To measure symptoms of anxiety, depression and hopelessness in a sample of young Pacific adults living in Auckland, New Zealand during the 2020/2021 COVID-19 pandemic and identify protective factors. METHODS: Participants were 267 Pacific adults (58% female) who completed a survey online. Analyses included descriptive statistics, correlations, linear regression and symptom network analysis. RESULTS: Around 25% of the sample scored in the range for moderate to severe anxiety and 10% for moderate to severe depression on standard measures. Almost 40% indicated that they found the first lockdown very stressful and 55% noted that some members of their family found it stressful. Only 16% worried about COVID-19 and their future quite a bit or constantly, while another 25% worried sometimes. Self-compassion and Pacific Identity had moderate, negative correlations, and Worry about COVID-19 had weak positive correlations, with anxiety, depression, hopelessness and perceived stress. CONCLUSION: These results suggest that, while the prevalence of depression and anxiety are quite high among this population, fostering ethnic identity and self-compassion in Pacific children and adolescents might protect against developing depression and anxiety.

Prolonged disorders of consciousness: identification using the UK FIM + FAM and cohort analysis of outcomes from a UK national clinical database.

PURPOSE: 1: To determine whether Total UK FIM + FAM scores can identify patients in VS/MCS. 2: Using the identified cut-off points, to examine outcomes from specialist rehabilitation. METHODS: Part 1: Retrospective analysis of a consecutive clinical cohort (n = 388) presenting to a single specialist PDOC evaluation programme 2007-2021. FIM + FAM scores were analysed by PDOC diagnosis to define cut-off points for vegetative (VS) and minimally conscious states (MCS). Part 2: Multicentre cohort analysis of prospectively-collected clinical outcomes data from the UK Rehabilitation Outcomes Collaborative database of adults in PDOC registered 2011-2020 (n = 2384 in 68 centres). RESULTS: Cut-off points of ≤31 and 32-35 in FIM + FAM total scores respectively identified patients in VS/MCS-Minus and MCS-Plus. Approximately 365 PDOC patients are admitted to specialist rehabilitation units in England each year. By discharge, 43% have emerged into consciousness and demonstrate a wide range of disability. A few reached full independence, but the majority remained severely dependent. Nevertheless, those who emerged generated mean net life-time savings of over £436,000 (£400 million for this cohort). CONCLUSION: In absence of a dedicated PDOC registry, FIM + FAM scores can identify patients in VS/MCS at population level. Identifying those who emerge and providing timely rehabilitation generates cost-savings well-exceeding the cost of the evaluation/rehabilitation programme.Implications for rehabilitationThe UK National Health Service currently collects no systematic data to identify patients in PDOC, so we have no accurate information on how many patients there are, where they are managed or what their outcomes are.In the absence of more direct data, total FIM + FAM scores of < =31 and 32-35 respectively can be used to identify patients in vegetative and minimally conscious states.Of the 365 or so patients admitted to specialist rehabilitation units per year, 43% emerge into consciousness leaving about 150 patients per year in PDOC states that are likely to be permanent.Identifying those who emerge and providing timely rehabilitation generates cost-savings that pay for the entire PDOC evaluation/rehabilitation programme many times over.

General well-being of intensive care nurses: A prototype analysis.

BACKGROUND: Prototype analyses of well-being have identified central characteristics and prototypicality for New Zealand teachers, lawyers, adolescents, and work well-being of nurses. What has not yet been explored is the broad construct of well-being in intensive care nurses. AIMS: To identify intensive care nurses' conceptions of general well-being and investigate whether their general well-being is prototypically organized. DESIGN: Prototype analysis. METHODS: Three linked studies conceptualize well-being in this prototype analysis. In study 1, nurses reported features of well-being. Study 2 investigated the organization of these features. Study 3 sought confirmation of prototypical organization. RESULTS: Sixty-five New Zealand nurses participated. For study 1 (n = 23), the most frequently reported elements of well-being included physical health (n = 26), work-life balance (n = 20), and personal relationships (n = 18). For study 2 (n = 25), the highest rated elements included mental and emotional health, [general] health, work-life balance, and love. Work-life balance, physical health, and personal relationships were in the top five most frequently reported and were rated in the top 12 most central. Overall, ratings of centrality and the number of times reported were positively correlated (r = 0.33, P < .005). For study 3 (n = 17), confirmatory analyses did not reach statistical significance (P = .15). CONCLUSIONS: Physical health, work-life balance, and personal relationships are key characteristics of well-being for intensive care nurses. Mental, emotional, and general health and work-life balance were considered most important for well-being. RELEVANCE TO CLINICAL PRACTICE: Physical health, work-life balance, and personal relationships are key characteristics of well-being for intensive care nurses. These characteristics of the broad construct of well-being are helpful in both defining and identifying conceptual models of well-being that may be used to inform the development and measurement of well-being programmes.

Prediction of emergence from prolonged disorders of consciousness from measures within the UK rehabilitation outcomes collaborative database: a multicentre analysis using machine learning.

PURPOSE: Predicting emergence from prolonged disorders of consciousness (PDOC) is important for planning care and treatment. We used machine learning to examine which variables from routine clinical data on admission to specialist rehabilitation units best predict emergence by discharge. MATERIALS AND METHODS: A multicentre national cohort analysis of prospectively collected clinical data from the UK Rehabilitation Outcomes (UKROC) database 2010-2018. Patients (n = 1170) were operationally defined as "still in PDOC" or "emerged" by their total UK Functional Assessment Measure (FIM + FAM) discharge score. Variables included: Age, aetiology, length of stay, time since onset, and all items of the Neurological Impairment Scale, Rehabilitation Complexity Scale, Northwick Park Dependency Scale, and the Patient Categorisation Tool. After filtering, prediction of emergence was explored using four techniques: binary logistic regression, linear discriminant analysis, artificial neural networks, and rule induction. RESULTS: Triangulation through these techniques consistently identified characteristics associated with emergence from PDOC. More severe motor impairment, complex disability, medical and behavioural instability, and anoxic aetiology were predictive of non-emergence, whereas those with less severe motor impairment, agitated behaviour and complex disability were predictive of emergence. CONCLUSIONS: This initial exploration demonstrates the potential opportunities to enhance prediction of outcome using machine learning techniques to explore routinely collected clinical data. Implications for rehabilitationPredicting emergence from prolonged disorders of consciousness is important for planning care and treatment.Few evidence-based criteria exist for aiding clinical decision-making and existing criteria are mostly based upon acute admission data.Whilst acknowledging the limitations of using proxy data for diagnosis of emergence, this study suggests that key items from the UKROC dataset, routinely collected on admission to specialist rehabilitation some months post injury, may help to predict those patients who are more (or less) likely to regain consciousness.Machine learning can help to enhance our understanding of the best predictors of outcome and thus assist with clinical decision-making in PDOC.

The post-ICU presentation screen (PICUPS) and rehabilitation prescription (RP) for intensive care survivors part I: Development and preliminary clinimetric evaluation.

Background: Patients who have had prolonged stays in intensive care have ongoing rehabilitation needs. This is especially true of COVID-19 ICU patients, who can suffer diverse long-term ill effects. Currently there is no systematic data collection to guide the needs for therapy input for either of these groups nor to inform planning and development of rehabilitation services. These issues could be resolved in part by the systematic use of a clinical tool to support decision-making as patients progress from the Intensive Care Unit (ICU), through acute hospital care and onwards into rehabilitation. We describe (i) the development of such a tool (the Post-ICU Presentation Screen (PICUPS)) and (ii) the subsequent preparation of a person-centred Rehabilitation Prescription (RP) to travel with the patient as they continue down the care pathway. Methods: PICUPS development was led by a core group of experienced clinicians representing the various disciplines involved in post-ICU rehabilitation. Key constructs and item-level descriptors were identified by group consensus. Piloting was performed as part of wider clinical engagement in 26 acute hospitals across England. Development and validation of such a tool requires clinimetric analysis, and this was based on classical test theory. Teams also provided feedback about the feasibility and utility of the tool. Results: Initial PICUPS design yielded a 24-item tool. In piloting, a total of 552 records were collated from 314 patients, of which 121 (38.5%) had COVID-19. No obvious floor or ceiling effects were apparent. Exploratory factor analysis provided evidence of uni-dimensionality with strong loading on the first principal component accounting for 51% of the variance and Cronbach's alpha for the full-scale score 0.95 - although a 3-factor solution accounted for a further 21%. The PICUPS was responsive to change both at full scale- and item-level. In general, positive responses were seen regarding the tool's ability to describe the patients during their clinical course, engage and flag the relevant professionals needed, and to inform what should be included in an RP. Conclusions: The PICUPS tool has robust scaling properties as a clinical measure and is potentially useful as a tool for identifying rehabilitation needs as patients step down from ICU and acute hospital care.

Strengthening Community End-of-Life Care through Implementing Measurement-Based Palliative Care.

The increasing demand for palliative care in New Zealand presents a potential threat to the quality of service delivery. One strategy to overcome this is through the implementation of valid and reliable patient-reported outcome measures. This mixed-methods study aimed to (1) implement measurement-based palliative care (MBPC) in a community palliative care service in Auckland, New Zealand; (2) evaluate the clinical utility of MBPC perceived by clinicians; (3) describe patient characteristics as measured by the Integrated Palliative Care Outcome Scale (IPOS), the Australasian Modified Karnofsky Performance Scale (AKPS), and Phase of Illness (POI); and (4) evaluate the internal consistency of the IPOS. Participants were over 18 years of age from a community outpatient palliative care service. In a phased approach to implementation, healthcare staff were educated on each instrument used for patient assessment. Uptake and internal consistency were evaluated through descriptive statistics. An interpretive descriptive methodology was used to explore the clinical utility of MBPC through semi-structured interviews with seven clinical staff members. Individual patient assessments (n = 1507) were undertaken predominantly on admission, with decreasing frequency as patients advanced through to the terminal phase of their care. Mean total IPOS scores were 17.97 (SD = 10.39, α = 0.78). The POI showed that 65% of patients were in the stable phase, 20% were in the unstable phase, 9% were in the deteriorating phase, and 2% were in the terminal phase. Clinicians reported that MBPC facilitated holistic and comprehensive assessments, as well as the development of a common interdisciplinary language. Clinicians expressed discomfort using the psychosocial and spiritual items. Measurement-based palliative care was only partially implemented but it was valued by staff and perceived to increase the quality of service delivery. Future research should determine the optimal timing of assessments, cultural responsivity for Maori and Pacific patients, and the role of MBPC in decision support for clinicians.

Measuring health consumers' engagement at the governance level: development and validation of the Middlemore Consumer Engagement Questionnaire.

AIM: To develop and validate a questionnaire to measure health CE at governance level. METHOD: This study used qualitative and quantitative methods (including focus groups, cognitive interviews and an international survey), and consisted of two phases. In Phase 1, an initial list of items was generated and refined with feedback from health consumer representatives. In Phase 2, a draft survey was distributed to n=227 consumers from New Zealand, Australia and Canada. The benefit and relevance of using the questionnaire was explored through face-to-face interviews with five CE leaders from New Zealand healthcare organisations. RESULTS: The proposed questionnaire comprises 25 statements relating to CE. Respondents indicate their level of agreement with the statements on a five-point Likert-type scale. Focus group and cognitive interview participants found the questionnaire relevant and easy to understand. The questionnaire scores correlated with the PPEET, another instrument measuring consumer engagement, and showed excellent internal consistency (Cronbach's alpha=0.97), unidimensionality and test-retest reliability (r=0.84). CONCLUSION: The proposed questionnaire measures CE at governance level and can be used for international comparisons and benchmarking. It showed sound psychometric properties and its value and relevance was recognised by health consumer representatives and leaders with CE roles in New Zealand healthcare organisations.

Intelligent Palliative Care Based on Patient-Reported Outcome Measures.

CONTEXT: The growth of patient reported outcome measures data in palliative care provides an opportunity for machine learning to identify patterns in patient responses signifying different phases of illness. OBJECTIVES: The study will explore if machine learning and network analysis can identify phases in patient palliative status through symptoms reported on the Integrated Palliative Care Outcome Scale (IPOS). METHODS: A partly cross-sectional and partially longitudinal observational study was undertaken using the Australasian Karnofsky Performance Scale (AKPS); Integrated Palliative Care Outcome Scale (IPOS); Phase of Illness (POI). Patient palliative records (n = 1507, 65% stable, 20% unstable, 9% deteriorating, 2% terminal) from 804 adult patients enrolled in a New Zealand palliative care service were analysed using a combination of statistical, machine learning and network analysis techniques. RESULTS: Data from IPOS showed considerable variation with phase. Also, network analysis showed clear associations between items by phase. Six machine learning techniques identified the most important variables for predicting possible transition between phases of illness. Network analysis for all patients showed that Poor Appetite and Loss of Energy were central IPOS items, with Loss of Energy linked to Drowsiness, Shortness of Breath and Lack of Mobility on the one hand, and Poor Appetite linked to Nausea, Vomiting, Constipation and Sore and Dry Mouth on the other. CONCLUSION: These preliminary results, when coupled with the latest technological developments in mobile apps and wearable technology, could point the way to increased use of digital therapeutics in continuous palliative care monitoring.

Positive Outcomes: Validity, reliability and responsiveness of a novel person-centred outcome measure for people with HIV.

OBJECTIVES: Despite successful treatment, people living with HIV experience persisting and burdensome multidimensional problems. We aimed to assess the validity, reliability and responsiveness of Positive Outcomes, a patient-reported outcome measure for use in clinical practice. METHODS: In all, 1392 outpatients in five European countries self-completed Positive Outcomes, PAM-13 (patient empowerment), PROQOL-HIV (quality of life) and FRAIL (frailty) at baseline and 12 months. Analysis assessed: (a) validity (structural, convergent and divergent, discriminant); (b) reliability (internal consistency, test-retest); and (c) responsiveness. RESULTS: An interpretable four-factor structure was identified: 'emotional wellbeing', 'interpersonal and sexual wellbeing', 'socioeconomic wellbeing' and 'physical wellbeing'. Moderate to strong convergent validity was found for three subscales of Positive Outcomes and PROQOL (ρ = -0.481 to -0.618, all p < 0.001). Divergent validity was found for total scores with weak ρ (-0.295, p < 0.001). Discriminant validity was confirmed with worse Positive Outcomes score associated with increasing odds of worse FRAIL group (4.81-fold, p < 0.001) and PAM-13 level (2.28-fold, p < 0.001). Internal consistency for total Positive Outcomes and its factors exceeded the conservative α threshold of 0.6. Test-retest reliability was established: those with stable PAM-13 and FRAIL scores also reported median Positive Outcomes change of 0. Improved PROQOL-HIV score baseline to 12 months was associated with improved Positive Outcomes score (r = -0.44, p < 0.001). CONCLUSIONS: Positive Outcomes face and content validity was previously established, and the remaining validity, reliability and responsiveness properties are now demonstrated. The items within the brief 22-item tool are designed to be actionable by health and social care professionals to facilitate the goal of person-centred care.

Stroke survivors' expectations and post-intervention perceptions of mindfulness training: A qualitative study.

Depression and anxiety are common sequelae of stroke, occurring in at least one-third of patients. This study evaluated the acceptability and feasibility of providing mindfulness training (MT) to stroke survivors with the aim of reducing depression and anxiety. Following a six-week one-on-one MT course, 17 participants were interviewed. The median age of participants was 71, and 10 participants were male. This paper focuses on participants' expectations of the MT and their views about its impact on their everyday lives. Conventional content analysis was used for coding and analysis. A single theme, Seizing rehabilitation opportunities, was captured in relation to expectations of MT, and four themes provided information relating to participants' perceived impact of the course: Calming the mind, Reduced reactivity, Remedying physical symptoms, and Not quite there yet.Most participants knew little about mindfulness before the MT and did not have specific goals in mind when volunteering to take part. The findings suggest that most participants considered MT beneficial through reducing stress and giving them additional skills to cope with their everyday lives. A tailored mindfulness intervention may be a useful adjunct to other rehabilitation therapies for stroke survivors.

Generalizability theory distinguishes between state and trait anxiety.

Accurate distinction between state and trait anxiety is necessary for assessment and monitoring of individual anxiety levels over time and developing effective interventions to reduce anxiety. Generalizability theory (G-theory) is a suitable method to distinguish between state and trait and to evaluate reliability of test scores and sources of measurement error in the assessment of affective conditions. We applied G-theory to the widely used 40-item State and Trait Anxiety Inventory (STAI) completed by 139 participants on three occasions separated by 2-week intervals. The results show that both subscales of the STAI demonstrated excellent reliability for test scores in measuring trait anxiety with high generalizability of scores across occasions and persons (G = 0.84-0.92). The most dynamic aspects of state anxiety were identified in both subscales including satisfaction, nervousness, feelings of pleasure, perceived failure, calmness, feeling inadequate, and sensitivity to disappointments and this informed the development of a more sensitive state anxiety scale presented here. The STAI trait subscale and the proposed sensitive state subscale can be used to more accurately distinguish between state and trait anxiety. The most dynamic aspects of anxiety identified using G-theory are more amenable and need to be considered as the primary target of interventions aiming at reducing anxiety. More comprehensive assessment of state anxiety may benefit from the development of a longer scale informed by G-theory. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Cognitive Effect Following a Blended (Face to Face and Videoconference-Delivered) Format Mindfulness Training.

While evidence supports the feasibility of online mindfulness training (MT), the effect of this approach on cognition remains unclear. The present study investigated changes in cognition following a newly developed 6-week videoconference-delivered MT program on cognitive function in two groups. The first group (n = 17) had two baseline assessments prior to MT [3 weeks after group two (n = 15)] to allow for evaluation of practice and learning effects. Four participants from each group were excluded from the final analysis due to missing data. Following MT, there was an improvement in switching of attention, working memory, executive function, and social cognition, but some of these effects were not easily accounted for by learning or practice effects. No significant changes were found on tasks measuring sustained attention, cognitive flexibility and inhibition, information processing, and sensory-motor function. Our findings suggest that domain-specific cognition might be enhanced by a brief videoconference-delivered MT, and larger, controlled studies to delineate the effects of online MT on subdomains of cognition are needed.

Psychometric properties of the Chinese Parent Version of the Autism Spectrum Rating Scale: Rasch analysis.

LAY ABSTRACT: The Autism Spectrum Rating Scale is a behavioural rating scale completed by parents and teachers that is useful for identifying children with an autism spectrum disorder. The development of a modified Autism Spectrum Rating Scale suitable for use in China is important for the identification of children in China with an autism spectrum disorder. In this study, we examined the Modified Chinese Autism Spectrum Rating Scale using a statistical technique known as Rasch analysis. Rasch analysis tests whether the questionnaire meets the standards for modern scientific measurement. We used Rasch analysis to examine data from 2013 children in China including 420 diagnosed with an autism spectrum disorder who had been rated by a parent or grandparent. After removing a small number of items (questions), the Modified Chinese Autism Spectrum Rating Scale met the stringent criteria for Rasch measurement. The availability of a reliable and precise tool for assessing behaviours characteristic of an autism spectrum disorder in Chinese children will improve the identification and diagnosis of autism spectrum disorder in China, thus enabling better provision of support services.

A novel way to quantify schizophrenia symptoms in clinical trials.

BACKGROUND: A major problem in quantifying symptoms of schizophrenia is establishing a reliable distinction between enduring and dynamic aspects of psychopathology. This is critical for accurate diagnosis, monitoring and evaluating treatment effects in both clinical practice and trials. MATERIALS AND METHODS: We applied Generalizability Theory, a robust novel method to distinguish between dynamic and stable aspects of schizophrenia symptoms in the widely used Positive and Negative Symptom Scale (PANSS) using a longitudinal measurement design. The sample included 107 patients with chronic schizophrenia assessed using the PANSS at five time points over a 24-week period during a multi-site clinical trial of N-Acetylcysteine as an add-on to maintenance medication for the treatment of chronic schizophrenia. RESULTS: The original PANSS and its three subscales demonstrated good reliability and generalizability of scores (G = 0.77-0.93) across sample population and occasions making them suitable for assessment of psychosis risks and long-lasting change following a treatment, while subscales of the five-factor models appeared less reliable. The most enduring symptoms represented by the PANSS were poor attention, delusions, blunted affect and poor rapport. More dynamic symptoms with 40%-50% of variance explained by patient transient state including grandiosity, preoccupation, somatic concerns, guilt feeling and hallucinatory behaviour. CONCLUSIONS: Identified dynamic symptoms are more amendable to change and should be the primary target of interventions aiming at effectively treating schizophrenia. Separating out the dynamic symptoms would increase assay sensitivity in trials, reduce the signal to noise ratio and increase the potential to detect the effects of novel therapies in clinical trials.

Psychometric evaluation of the leg activity measure (LegA) for outcome measurement in people with brain injury and spasticity.

PURPOSE: The aim of this study is to evaluate the properties of the Leg Activity measure according to COnsensus-based Standards for the selection of health Measurement INstruments. METHOD: Participants were assessed at baseline, one day, 6 weeks and 12 weeks, following treatment for leg spasticity with botulinum toxin and physical interventions. RESULTS: In stage 1, 64 participants were recruited to evaluate the initial psychometric properties of Leg Activity measure. In stage 2, 100 additional participants were recruited, to evaluate the scaling properties. Total sample of 164 participants was used. Construct validity was supported for "passive function", "active function" and "impact on quality of life". Cronbach's alpha was 0.86, 0.97 and 0.87 respectively for the scales. Item level test-retest agreement ranged from 91-97% (Kappa 0.75-0.95). Following treatment for spasticity (n = 64), the Leg Activity measure "passive function" and "impact on life" scales were responsive to change. Principal components analysis confirmed the constructs and a unidimensional Rasch Partial Credit Model was subsequently established for each scale. Transformation to an interval scale was achieved. Using the ordinal-to-interval conversion tables, parametric statistical analysis may be used. CONCLUSION: The study provides support for the Leg Activity measure being valid, reliable and responsive.Implications for rehabilitationThe Leg Activity measure is the only published self-report measure in the current literature that addresses passive and active function as well as impact on quality of life, of the paretic leg in a comprehensive manner.The initial evaluation of Leg Activity measure psychometric properties, in relation to the COnsensus-based Standards for the selection of health Measurement INstruments checklist and Medical Outcomes Trust Quality Criteria, supports its measurement properties for clinical and research use.The Leg Activity measure as a valid, reliable and responsive tool for the evaluation of treatment in leg spasticity including condition specific (spasticity) quality-of-life.