26 research outputs found

    How do therapists assess suitability? A qualitative study exploring therapists' judgements of treatment suitability for depressed adolescents

    Get PDF
    BACKGROUND: Despite the need for a better understanding of treatment suitability, how it is determined by therapists in real-life practice is still unknown. The study aimed to explore how therapists working with depressed teenagers make judgements about treatment suitability across three treatment modalities: (a) Short-term Psychoanalytic Psychotherapy, (b) Cognitive Behaviour Therapy, and (c) Brief Psychosocial Intervention. METHODS: The study used a qualitative analysis within a randomised controlled trial. Therapists' judgements of treatment suitability were studied via an exploratory content analysis. This trial is registered with current controlled trials, number ISRCTN83033550. RESULTS AND DISCUSSION: A wide range of factors were considered in therapists' judgements of suitability, with significant variation in themes across treatment modalities. Although a much higher number of therapists judged the allocated treatment modality to be suitable to the client than not, many also indicated ambivalence and uncertainty towards their decision-making. This demonstrates a possibility that treatment suitability may be more accurately assessed as a continuum over multiple time points throughout treatment

    Why is mini-mental state examination performance correlated with estimated premorbid cognitive ability?

    Get PDF
    Background: Tests requiring the pronunciation of irregular words are used to estimate premorbid cognitive ability in patients with clinical diagnoses, and prior cognitive ability in normal ageing. However, scores on these word-reading tests correlate with scores on the Mini-Mental State Examination (MMSE), a widely-used screening test for possible cognitive pathology. The present study aimed to test whether the word-reading tests’ correlations with MMSE scores in healthy older people are explained by childhood IQ or education. Methods: Wechsler Test of Adult Reading (WTAR), National Adult Reading Test (NART), MMSE scores and information about education were obtained from 1024 70-year-olds, for whom childhood intelligence test scores were available. Results: WTAR and NART were positively correlated with the MMSE (r ≈ .40, p<.001). The shared variance of WTAR and NART with MMSE was significantly attenuated by about 70% after controlling for childhood intelligence test scores. Education explained little additional variance in the association between the reading tests and the MMSE. Conclusions: MMSE, which is often used to index cognitive impairment, is associated with prior cognitive ability. MMSE score is related to scores on WTAR and NART largely due to their shared association with prior ability. Obtained MMSE scores should be interpreted in the context of prior ability (or WTAR/NART score as its proxy)

    Association of facial ageing with DNA methylation and epigenetic age predictions

    Get PDF
    Data from the Lothian Birth Cohort 1921 (LBC1921). (DOCX 13 kb

    Assessing the genetic overlap between BMI and cognitive function

    Get PDF
    Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=-0.11; high body mass index (BMI)-low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)-GREML; independent samples bivariate GCTA-GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of -0.51 (s.e. 0.15) was observed using the same-sample GCTA-GREML approach compared with -0.10 (s.e. 0.08) from the independent-samples GCTA-GREML approach and -0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10 -7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at

    Predicting change in quality of life from age 79 to 90 in the Lothian Birth Cohort 1921

    Get PDF
    Purpose: Quality of life (QoL) decreases in very old age, and is strongly related to health outcomes and mortality. Understanding the predictors of QoL and change in QoL amongst the oldest old may suggest potential targets for intervention. This study investigated change in QoL from age 79 to 90 years in a group of older adults in Scotland, and identified potential predictors of that change. Method: Participants were members of the Lothian Birth Cohort 1921 who attended clinic visits at age 79 (n = 554) and 90 (n = 129). Measures at both time points included QoL (WHOQOL-BREF: four domains and two single items), anxiety and depression, objective health, functional ability, self-rated health, loneliness, and personality. Results: Mean QoL declined from age 79 to 90. Participants returning at 90 had scored significantly higher at 79 on most QoL measures, and exhibited better objective health and functional ability, and lower anxiety and depression than non-returners. Hierarchical multiple regression models accounted for 20.3–56.3% of the variance in QoL at age 90. Baseline QoL was the strongest predictor of domain scores (20.3–35.6% variance explained), suggesting that individual differences in QoL judgements remain largely stable. Additional predictors varied by the QoL domain and included self-rated health, loneliness, and functional and mood decline between age 79 and 90 years. Conclusions: This study has identified potential targets for interventions to improve QoL in the oldest old. Further research should address causal pathways between QoL and functional and mood decline, perceived health and loneliness

    Apolipoprotein E genotype does not moderate the associations of depressive symptoms, neuroticism and allostatic load with cognitive ability and cognitive aging in the Lothian Birth Cohort 1936

    Get PDF
    <div><p>Objectives</p><p>In this replication-and-extension study, we tested whether depressive symptoms, neuroticism, and allostatic load (multisystem physiological dysregulation) were related to lower baseline cognitive ability and greater subsequent cognitive decline in older adults, and whether these relationships were moderated by the E4 allele of the apolipoprotein E (<i>APOE</i>) gene. We also tested whether allostatic load mediated the relationships between neuroticism and cognitive outcomes.</p><p>Methods</p><p>We used data from the Lothian Birth Cohort 1936 (<i>n</i> at Waves 1–3: 1,028 [<i>M</i> age = 69.5 y]; 820 [<i>M</i> duration since Wave 1 = 2.98 y]; 659 [<i>M</i> duration since Wave 1 = 6.74 y]). We fitted latent growth curve models of general cognitive ability (modeled using five cognitive tests) with groups of <i>APOE</i> E4 non-carriers and carriers. In separate models, depressive symptoms, neuroticism, and allostatic load predicted baseline cognitive ability and subsequent cognitive decline. In addition, models tested whether allostatic load mediated relationships between neuroticism and cognitive outcomes.</p><p>Results</p><p>Baseline cognitive ability had small-to-moderate negative associations with depressive symptoms (<i>β</i> range = -0.20 to -0.17), neuroticism (<i>β</i> range = -0.27 to -0.23), and allostatic load (<i>β</i> range = -0.11 to 0.09). Greater cognitive decline was linked to baseline allostatic load (<i>β</i> range = -0.98 to -0.83) and depressive symptoms (<i>β</i> range = -1.00 to -0.88). However, <i>APOE</i> E4 allele possession did not moderate the relationships of depressive symptoms, neuroticism and allostatic load with cognitive ability and cognitive decline. Additionally, the associations of neuroticism with cognitive ability and cognitive decline were not mediated through allostatic load.</p><p>Conclusions</p><p>Our results suggest that <i>APOE</i> E4 status does not moderate the relationships of depressive symptoms, neuroticism, and allostatic load with cognitive ability and cognitive decline in healthy older adults. The most notable positive finding in the current research was the strong association between allostatic load and cognitive decline.</p></div

    Sex differences in reaction time mean and intraindividual variability across the life span

    No full text
    corecore