Critical Reflection on the Ethics of Mindfulness

Mindfulness is a way to achieve mental wellbeing that has been widely adopted as part of counselling and mental health treatment. However, there is a distinct lack of critical reflection about the origins of this technique, how it is used, and the implications it has for the beliefs of clients. The purpose of this paper is to provide a carefully considered response to the use of humanistic mindfulness. Social workers need to explain why they recommend mindfulness, and explore culturally consistent and sensitive practice, so that they are abiding by the Australian Association of Social Workers Code of ethics.

IMPLICATIONS

• The use of mindfulness in social work practice requires careful consideration as to its impact and relevance to clients’ needs.

• Mindfulness originates in philosophical traditions distinct from mental health treatment.

• In choosing to use mindfulness social workers require consistent and sensitive understanding of clients’ needs, world views, and culture.

     

Relationship building and message planning: An exploration of media challenges and strategies used during school crises at the P-12 level

Schools at the P-12 level increasingly face crises related to school shootings, violence, and other tragedies. Understanding the communication challenges schools face is paramount to assisting schools with communication before, during, and after crisis events. The current study focuses on the challenges created by media interest in such crises and the strategies implemented to overcome these challenges and provide responsible information to stakeholders. Interviews conducted with 21 school crisis teams at the P-12 level revealed that sensationalism, seeking alternative routes to information, and framing were key challenges in working with the media. In light of these challenges, administrators focused on creating media plans, building relationships with the media, being accurate but guarded, and communicating reassurance and reunification. Implications are discussed for school districts nationally.     

ESTIMATING A PARAMETER WHEN IT IS KNOWN THAT THE PARAMETER EXCEEDS A GIVEN VALUE

In some statistical problems a degree of explicit, prior information is available about the value taken by the parameter of interest, θ say, although the information is much less than would be needed to place a prior density on the parameter's distribution. Often the prior information takes the form of a simple bound, ‘θ > θ₁ ’ or ‘θ < θ₁ ’, where θ₁ is determined by physical considerations or mathematical theory, such as positivity of a variance. A conventional approach to accommodating the requirement that θ > θ₁ is to replace an estimator, , of θ by the maximum of and θ₁. However, this technique is generally inadequate. For one thing, it does not respect the strictness of the inequality θ > θ₁ , which can be critical in interpreting results. For another, it produces an estimator that does not respond in a natural way to perturbations of the data. In this paper we suggest an alternative approach, in which bootstrap aggregation, or bagging, is used to overcome these difficulties. Bagging gives estimators that, when subjected to the constraint θ > θ₁ , strictly exceed θ₁ except in extreme settings in which the empirical evidence strongly contradicts the constraint. Bagging also reduces estimator variability in the important case for which is close to θ₁, and more generally produces estimators that respect the constraint in a smooth, realistic fashion.     

Deconvolution methods for non-parametric inference in two-level mixed models

Summary.  We develop a general non-parametric approach to the analysis of clustered data via random effects. Assuming only that the link function is known, the regression functions and the distributions of both cluster means and observation errors are treated non-parametrically. Our argument proceeds by viewing the observation error at the cluster mean level as though it were a measurement error in an errors-in-variables problem, and using a deconvolution argument to access the distribution of the cluster mean. A Fourier deconvolution approach could be used if the distribution of the error-in-variables were known. In practice it is unknown, of course, but it can be estimated from repeated measurements, and in this way deconvolution can be achieved in an approximate sense. This argument might be interpreted as implying that large numbers of replicates are necessary for each cluster mean distribution, but that is not so; we avoid this requirement by incorporating statistical smoothing over values of nearby explanatory variables. Empirical rules are developed for the choice of smoothing parameter. Numerical simulations, and an application to real data, demonstrate small sample performance for this package of methodology. We also develop theory establishing statistical consistency.     

A variable-neighbourhood search algorithm for finding optimal run orders in the presence of serial correlation

The responses obtained from response surface designs that are run sequentially often exhibit serial correlation or time trends. The order in which the runs of the design are performed then has an impact on the precision of the parameter estimators. This article proposes the use of a variable-neighbourhood search algorithm to compute run orders that guarantee a precise estimation of the effects of the experimental factors. The importance of using good run orders is demonstrated by seeking D-optimal run orders for a central composite design in the presence of an AR(1) autocorrelation pattern.     

A re-evaluation of random-effects meta-analysis

Summary.  Meta-analysis in the presence of unexplained heterogeneity is frequently undertaken by using a random-effects model, in which the effects underlying different studies are assumed to be drawn from a normal distribution. Here we discuss the justification and interpretation of such models, by addressing in turn the aims of estimation, prediction and hypothesis testing. A particular issue that we consider is the distinction between inference on the mean of the random-effects distribution and inference on the whole distribution. We suggest that random-effects meta-analyses as currently conducted often fail to provide the key results, and we investigate the extent to which distribution-free, classical and Bayesian approaches can provide satisfactory methods. We conclude that the Bayesian approach has the advantage of naturally allowing for full uncertainty, especially for prediction. However, it is not without problems, including computational intensity and sensitivity to a priori judgements. We propose a simple prediction interval for classical meta-analysis and offer extensions to standard practice of Bayesian meta-analysis, making use of an example of studies of 'set shifting' ability in people with eating disorders.     

Profile of the Present Slovak Society and its Regional Differences

The article is the first attempt in assessment of the development and the present situation of social structure and stratification in Slovakia. Its principal aim is to develop the profile of the present society in Slovakia, which reflects the pace and complexity of the transformation process and its impact on society. Processing of Micro census data from 2003 led to creation of the profile of society in Slovakia at the national level based on income distribution but also knowledge on regional societies and differences between them were obtained. It was found out that the present profile of the society in Slovakia is pear-shaped which means strong representation of lower strata and weaker representation of higher middle and high strata. The profile disclosed some specific features and inconsistencies in the present society of Slovakia, which were, and still are determined by many non standard past and present phenomena and processes often disguised by reforms. The information drawn in regions has facilitated identification of the basic nature and structure of regional societies, some of their specific features and negative elements and to demonstrate their highly differentiated character.

The Best and Worst Times of Life: Narratives and Assessments of Subjective Well-Being by Anamnestic Comparative Self Assessment (ACSA) in the Eastern Cape,South Africa

The Anamnestic Comparative Self Assessment (ACSA) measure of subjective well-being (SWB) aims to reduce the problems of cultural bias and relativity to external standards by allowing people to define the endpoints or ‘anchors’ of the measurement scale. In medical terminology anamnestic denotes ‘based on memory’. The ACSA uses subjects’ memories of the best and worst periods in their lives to define the anchors of the scale. They then assess their current quality of life relative to these personal anchors. The South African pilot study tested the match between self-assessment of SWB with ACSA and the conventional single-item measures of life satisfaction and happiness used in the South African Quality of Life Trends Study and analysed the narratives of the best and worst times of life. The quota sample of 46 consisted of 26 residents of Makana district in the Eastern Cape Province, South Africa, and 20 patients undergoing treatment in the local TB hospital. Mean SWB ratings with all three measures of life satisfaction, happiness and ACSA were between 5 and 6 on a 0–10-point scale. Ratings on all three scales were positively correlated. However, on ACSA the TB patients rated their current SWB 1.84 points lower than the community respondents, suggesting a greater sensitivity of this measure. It was observed that the starting points of the life stories produced by respondents to define the anchor periods for ACSA were related to their current assessment of SWB. A typology was developed that combined the starting point of the life stories with current SWB. The majority of community respondents matched the ‘Achiever’ type who scored positively on ACSA (i.e., above the mid-point of the scale) and whose life stories started with the worst period of their lives and proceeded to the best period. The TB patients were the only respondents to represent the ‘Survivor’ type whose morale had recovered after misfortune in life. ‘Survivors’ started their narratives with the best period in their lives, then moved to the worst (often health-related) one, and gave positive ACSA ratings. Based on the qualitative analysis of narratives, it is concluded that ACSA is a sensitive measurement instrument and therefore particularly useful for monitoring the effects of treatments and social interventions in longitudinal studies. However, further research is required to verify its cross-cultural validity.