118 research outputs found

    Assistive technology in Australia: integrating theory and evidence into action

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    Background: Occupational therapists use a range of strategies to influence the relationship between person, environment and occupation and facilitate people's participation and inclusion in society. Technology is a fundamental environmental factor capable of enabling inclusion, and occupational therapy models articulate a role for assistive technology (AT) devices and services, but there is a gap between theory, research and practice. The context of AT provision in Australia presents systemic barriers that prevent optimal application of AT devices and services for societal health promotion and in individualised solutions. Methods: The Integrating Theory, Evidence and Action method (ITEA) was used to answer the question ‘How can occupational therapy support AT provision to enable older people and people with disability?’ A wide range of sources were systematically analysed to explore the complexities of AT provision in Australia. Results: The International Classification of Functioning, Disability and Health (ICF) and IMPACT2 model are used as frameworks to reconstruct evidence into statements that summarise the theory, process and outcomes of AT provision. Analysis of the influence of the global disability rights and local policies and AT provision systems is used to highlight important aspects for occupational therapists to consider in research and practice. Pragmatic recommendations are provided to enable practitioners to translate theory and evidence into action. Conclusion AT provision can be improved by focusing on evidence for and congruence between theory, process and outcomes, rather than isolated interventions. Occupational therapists should consider the influence of contextual factors on practice, and work with consumers to improve access and equity in AT provision systems

    A transdisciplinary perspective of chronic stress in relation to psychopathology throughout life span development

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    The allostatic load (AL) model represents an interdisciplinary approach to comprehensively conceptualize and quantify chronic stress in relation to pathologies throughout the life cycle. This article first reviews the AL model, followed by interactions among early adversity, genetics, environmental toxins, as well as distinctions among sex, gender, and sex hormones as integral antecedents of AL. We next explore perspectives on severe mental illness, dementia, and caregiving as unique human models of AL that merit future investigations in the field of developmental psychopathology. A complimenting transdisciplinary perspective is applied throughout, whereby we argue that the AL model goes beyond traditional stress–disease theories toward the advancement of person-centered research and practice that promote not only physical health but also mental healt

    Association of Prognostic Understanding with Health Care Use among Older Adults with Advanced Cancer: A Secondary Analysis of a Cluster Randomized Clinical Trial

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    Importance: A poor prognostic understanding regarding curability is associated with lower odds of hospice use among patients with cancer. However, the association between poor prognostic understanding or prognostic discordance and health care use among older adults with advanced incurable cancers is not well characterized. Objective: To evaluate the association of poor prognostic understanding and patient-oncologist prognostic discordance with hospitalization and hospice use among older adults with advanced cancers. Design, Setting, and Participants: This was a post hoc secondary analysis of a cluster randomized clinical trial that recruited patients from October 29, 2014, to April 28, 2017. Data were collected from community oncology practices affiliated with the University of Rochester Cancer Center National Cancer Institute Community Oncology Research Program. The parent trial enrolled 541 patients who were aged 70 years or older and were receiving or considering any line of cancer treatment for incurable solid tumors or lymphomas; the patients' oncologists and caregivers (if available) were also enrolled. Patients were followed up for at least 1 year. Data were analyzed from January 3 to 16, 2021. Main Outcomes and Measures: At enrollment, patients and oncologists were asked about their beliefs regarding cancer curability (100%, >50%, 50%, 5 years; answers of >5 years reflected poor prognostic understanding). Any difference between oncologist and patient in response options was considered discordant. Outcomes were any hospitalization and hospice use at 6 months captured by the clinical research associates. Results: Among the 541 patients, the mean (SD) age was 76.6 (5.2) years, 264 of 540 (49%) were female, and 486 of 540 (90%) were White. Poor prognostic understanding regarding curability was reported for 59% (206 of 348) of patients, and poor prognostic understanding regarding life expectancy estimates was reported for 41% (205 of 496) of patients. Approximately 60% (202 of 336) of patient-oncologist dyads were discordant regarding curability, and 72% (356 of 492) of patient-oncologist dyads were discordant regarding life expectancy estimates. Poor prognostic understanding regarding life expectancy estimates was associated with lower odds of hospice use (adjusted odds ratio, 0.30; 95% CI, 0.16-0.59). Discordance regarding life expectancy estimates was associated with greater odds of hospitalization (adjusted odds ratio, 1.64; 95% CI, 1.01-2.66). Conclusions and Relevance: This study highlights different constructs of prognostic understanding and the need to better understand the association between prognostic understanding and health care use among older adult patients with advanced cancer. Trial Registration: ClinicalTrials.gov Identifier: NCT02107443

    Stress Biomarkers as Outcomes for HIV+ Prevention: Participation, Feasibility and Findings Among HIV+ Latina and African American Mothers

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    Mothers living with HIV (MLH) are at high risk for acute and chronic stress, given challenges related to their HIV status, ethnicity, economic and urban living conditions. Biomarkers combined into a composite index show promise in quantifying psychosocial stress in healthy people, but have not yet been examined among MLH. According, we examined potential biomarker correlates of stress [cortisol and catecholamines from home-collected urine and basic health indicators (blood pressure, height and weight, waist-to-hip ratio) measured during an interview] among 100 poor African American and Latina mothers MLH and demographic-matched control mothers without HIV (n = 50). Participants had been enrolled in a randomized controlled trial about 18 months earlier and had either received (MLH-I) or were awaiting (MLH-W) the psychosocial intervention. Participation was high, biomarkers were correctly collected for 93% of cases, and a complete composite biomarker index (CBI) calculated for 133 mothers (mean age = 42). As predicted, MLH had a significantly higher CBI than controls, but there was no CBI difference across ethnicity or intervention group. CBI predicted CD4 counts independently after controlling for age, years since diagnosis, prior CD4 counts, medication adherence, and depression symptoms. The study demonstrates acceptability, feasibility and potential utility of community-based biomarker collections in evaluating individual differences in psychosocial stress

    Reaction time in adolescence, cumulative allostatic load, and symptoms of anxiety and depression in adulthood:The west of Scotland twenty-07 study

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    Objective: to examine the relation between reaction time in adolescence and subsequent symptoms of anxiety and depression and investigate the mediating role of sociodemographic measures, health behaviors, and allostatic load.Methods: participants were 705 members of the West of Scotland Twenty-07 Study. Choice reaction time was measured at age 16. At age 36 years, anxiety and depression were assessed with the 12-item General Health Questionnaire (GHQ) and the Hospital Anxiety and Depression Scale (HADS), and measurements were made of blood pressure, pulse rate, waist-to-hip ratio, and total and high-density lipoprotein cholesterol, C-reactive protein, albumin, and glycosolated hemoglobin from which allostatic load was calculated.Results: in unadjusted models, longer choice reaction time at age 16 years was positively associated with symptoms of anxiety and depression at age 36 years: for a standard deviation increment in choice reaction time, regression coefficients (95% confidence intervals) for logged GHQ score, and square-root–transformed HADS anxiety and depression scores were 0.048 (0.016–0.080), 0.064 (0.009–0.118), and 0.097 (0.032–0.163) respectively. Adjustment for sex, parental social class, GHQ score at age 16 years, health behaviors at age 36 years and allostatic load had little attenuating effect on the association between reaction time and GHQ score, but weakened those between reaction time and the HADS subscales. Part of the effect of reaction time on depression was mediated through allostatic load; this mediating role was of borderline significance after adjustment.Conclusions: adolescents with slower processing speed may be at increased risk for anxiety and depression. Cumulative allostatic load may partially mediate the relation between processing speed and depressio

    Social support and Quality of Life: a cross-sectional study on survivors eight months after the 2008 Wenchuan earthquake

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    <p>Abstract</p> <p>Background</p> <p>The 2008 Wenchuan earthquake resulted in extensive loss of life and physical and psychological injuries for survivors. This research examines the relationship between social support and health-related quality of life for the earthquake survivors.</p> <p>Methods</p> <p>A multistage cluster sampling strategy was employed to select participants from 11 shelters in nine counties exposed to different degrees of earthquake damage, for a questionnaire survey. The participants were asked to complete the Short Form 36 and the Social Support Rating Scale eight months after the earthquake struck. A total of 1617 participants returned the questionnaires. The quality of life of the survivors (in the four weeks preceding the survey) was compared with that of the general population in the region. Multivariate logistic regression analysis and canonical correlation analysis were performed to determine the association between social support and quality of life.</p> <p>Results</p> <p>The earthquake survivors reported poorer quality of life than the general population, with an average of 4.8% to 19.62% reduction in scores of the SF-36 (p < 0.001). The multivariate logistic regression analysis showed that those with stronger social support were more likely to have better quality of life. The canonical correlation analysis found that there was a discrepancy between actual social support received and perceived social support available, and the magnitude of this discrepancy was inversely related to perceived general health (rs = 0.467), and positively related to mental health (rs = 0.395).</p> <p>Conclusion</p> <p>Social support is associated with quality of life in the survivors of the earthquake. More attention needs to be paid to increasing social support for those with poorer mental health.</p

    Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition

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    Physiological dysregulation may underlie aging and many chronic diseases, but is chal-lenging to quantify because of the complexity of the underlying systems. Recently, we de-scribed a measure of physiological dysregulation, DM, that uses statistical distance to assess the degree to which an individual’s biomarker profile is normal versus aberrant. However, the sensitivity of DM to details of the calculation method has not yet been sys-tematically assessed. In particular, the number and choice of biomarkers and the defini-tion of the reference population (RP, the population used to define a “normal” profile) may be important. Here, we address this question by validating the method on 44 common clinical biomarkers from three longitudinal cohort studies and one cross-sectional survey. DMs calculated on different biomarker subsets show that while the signal of physiological dysregulation increases with the number of biomarkers included, the value of additional markers diminishes as more are added and inclusion of 10-15 is generally sufficient. As long as enough markers are included, individual markers have little effect on the final met-ric, and even DMs calculated from mutually exclusive groups of markers correlate with each other at r~0.4-0.5. We also used data subsets to generate thousands of combina-tions of study populations and RPs to address sensitivity to differences in age range, sex, race, data set, sample size, and their interactions. Results were largely consistent (but not identical) regardless of the choice of RP; however, the signal was generally clearer with a younger and healthier RP, and RPs too different from the study population per-formed poorly. Accordingly, biomarker and RP choice are not particularly important in most cases, but caution should be used across very different populations or for fine-scale analyses. Biologically, the lack of sensitivity to marker choice and better performance of younger, healthier RPs confirm an interpretation of DM physiological dysregulation and as an emergent property of a complex system
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