Do self‐assessment and self‐directed support undermine traditional social work with disabled people?

In recent years, self‐assessment and self‐directed support have become mainstream options within disability services. The Disabled People’s Movement has advocated the need for such change for a long time but this has been persistently resisted by many social workers. In this article, it will be argued that both self‐assessment and self‐directed support undermine traditional social work and that social workers need to begin to work alongside disabled people, rather than ‘for’ disabled people, in order to achieve substantial system change.     

Preliminary Development and Validation of the Social and Emotional Health Survey for Secondary School Students

This study reports on the preliminary development and validation of the Social and Emotional Health Survey (SEHS) with a sample of 4,189 (51 % female) California students in Grades 8, 10, and 12. The SEHS was designed to measure the psychological building blocks of adolescents’ positive mental health and is operationalized in the present study by a theoretical model comprised of 12 measured indicators that form four first-order domains (belief-in-self, belief-in-others, emotional competence, and engaged living) that, in turn, contribute to one underlying, second-order meta-construct called covitality. This study was the first to investigate the validity and utility of the adolescent covitality construct, which is conceptualized as the synergistic effect of positive mental health resulting from the interplay among multiple positive-psychological building blocks. Findings from confirmatory factor analyses, invariance analysis, and latent means testing all supported the theoretical model underlying the SEHS, indicating that the second-order covitality model was the best fit for both males and females. Results from a path-modeling analysis indicated that covitality was a strong predictor of students’ subjective well-being (operationalized as a composite of life satisfaction, positive affect, and negative affect), and findings from additional concurrent validity analyses indicated that adolescents’ covitality level was significantly associated with self-reported academic achievement, perceptions of school safety, substance use, and experiences of depressive symptoms. Implications for theory, practice, and future research are discussed.     

Life Satisfaction as a Distinguishing Indicator of College Student Functioning: Further Validation of the Two-Continua Model of Mental Health

The two-continua model of mental health contends that both psychological distress and psychological well-being make related-yet-distinct contributions to our understanding of human health and its relations with other quality of life outcomes. Using self-reported somatization, depression, and anxiety symptoms as indicators of psychological distress and self-reported life satisfaction as an indicator of psychological well-being, the present study classified participants into one of four mental-health-status groups—mentally healthy, mentally unhealthy, symptomatic yet content, or asymptomatic yet discontent—and investigated between-group differences across three key indicators of college student functioning: academic achievement, interpersonal connectedness, and physical health. Findings provide further validation for the two-continua model of mental health among college students, showing that, when considered in conjunction with clinical symptoms, life satisfaction serves as a distinguishing indicator of college students functioning across academic, social, and physical health domains—as well as a strong predictor of the absence or presence of clinical symptoms and comorbidity. Implications for theory, practice, and future research are discussed.     

Perceptions of Partners' Attributions for Depression in Relation to Perceptions of Support and Conflict in Romantic Relationships

People's attributions for their own psychological problems are linked to their interpersonal behaviors and attitudes. However, depressed individuals' inferences about their romantic partners' attributions for their depressive symptoms have yet to be studied in relation to their perceptions of relationship quality. This study examined perceived support from and conflict with partners in relation to perceptions of partners' attributions for depression in 165 individuals experiencing at least mild depressive symptoms. After controlling for relevant demographic characteristics, perceived internal/controllable psychological attributions were related to greater perceived conflict and lower perceived support, and perceived controllable biological attributions were related to greater perceived conflict. Perceived external/uncontrollable psychological and uncontrollable biological attributions were unrelated to perceived support and conflict. Findings suggest that perceived attributions may help explain the link between depression, support, and conflict in romantic relationships.     

Space-time generation of high intensity patterns using growth-interaction processes

We describe a novel spatial-temporal algorithm for generating packing structures of disks and spheres, which not only incorporates all the attractive features of existing algorithms but is also more flexible in defining spatial interactions and other control parameters. The advantage of this approach lies in the ability of marks to exploit to best advantage the space available to them by changing their size in response to the interaction pressure of their neighbours. Allowing particles to move in response to such pressure results in high-intensity packing. Indeed, since particles may temporarily overlap, even under hard-packing scenarios, they possess a greater potential for rearranging themselves, and thereby creating even higher packing intensities than exist under other strategies. Non-overlapping pattern structures are achieved simply by allowing the process to ‘burn-out’ at the end of its development period. A variety of different growth-interaction regimes are explored, both symmetric and asymmetric, and the convergence issues that they raise are examined. We conjecture that not only may this algorithm be easily generalised to cover a large variety of situations across a wide range of disciplines, but that appropriately targeted generalisations may well include established packing algorithms as special cases.     

Estimating likelihoods for spatio-temporal models using importance sampling

This paper describes how importance sampling can be applied to estimate likelihoods for spatio-temporal stochastic models of epidemics in plant populations, where observations consist of the set of diseased individuals at two or more distinct times. Likelihood computation is problematic because of the inherent lack of independence of the status of individuals in the population whenever disease transmission is distance-dependent. The methods of this paper overcome this by partitioning the population into a number of sectors and then attempting to take account of this dependence within each sector, while neglecting that between-sectors. Application to both simulated and real epidemic data sets show that the techniques perform well in comparison with existing approaches. Moreover, the results confirm the validity of likelihood estimates obtained elsewhere using Markov chain Monte Carlo methods.     

Lee–Carter mortality forecasting: a parallel generalized linear modelling approach for England and Wales mortality projections

Summary. The paper presents a reinterpretation of the model underpinning the Lee–Carter methodology for forecasting mortality (and other vital) rates. A parallel methodology based on generalized linear modelling is introduced. The use of residual plots is proposed for both methods to aid the assessment of the goodness of fit. The two methods are compared in terms of structure and assumptions. They are then compared through an analysis of the gender- and age-specific mortality rates for England and Wales over the period 1950–1998 and through a consideration of the forecasts generated by the two methods. The paper also compares different approaches to the forecasting of life expectancy and considers the effectiveness of the Coale–Guo method for extrapolating mortality rates to the oldest ages.     

Likelihood estimation for stochastic compartmental models using Markov chain methods

This paper presents a method for estimating likelihood ratios for stochastic compartment models when only times of removals from a population are observed. The technique operates by embedding the models in a composite model parameterised by an integer k which identifies a switching time when dynamics change from one model to the other. Likelihood ratios can then be estimated from the posterior density of k using Markov chain methods. The techniques are illustrated by a simulation study involving an immigration-death model and validated using analytic results derived for this case. They are also applied to compare the fit of stochastic epidemic models to historical data on a smallpox epidemic. In addition to estimating likelihood ratios, the method can be used for direct estimation of likelihoods by selecting one of the models in the comparison to have a known likelihood for the observations. Some general properties of the likelihoods typically arising in this scenario, and their implications for inference, are illustrated and discussed.