Effects of Micronutrients on Anxiety and Stress in Children

• Objective: Examined effects of micronutrients on children with clinically elevated stress and anxiety 23 to 36 months after experiencing a natural disaster (major earthquake). • Methods: A single-case design allocated 14 children (7 males, 7 females; aged 8-11 years; 10 with formal anxiety-disorder diagnoses) randomly to one, two or three week baselines. Participants then took eight capsules/day of a micronutrient formula (EMPowerplus) during an eight-week open-label trial. Assessment instruments were the Children’s Global Assessment Scale (CGAS), the Screen for Child Anxiety Related Emotional Disorders (SCARED), the Pediatric Emotional Distress Scale (PEDS), and the Revised Children’s Manifest Anxiety Scale (RCMAS). • Results: Symptom severity declined slightly in baseline for some children and declined much more during intervention for all children. Effect sizes at end of treatment were -1.40 (RCMAS), -1.92 (SCARED), +1.96 (CGAS) and -2.13 (PEDS). Modified Brinley plots revealed decreases in anxiety and improvements in overall functioning for 10 out of 11 completing participants. Side effects were mild and transient. • Conclusions: The study provided evidence that dietary supplementation by micronutrients reduces children’s post-disaster anxiety to a clinically significant degree. Future placebo-controlled randomised-controlled trials and treatment-comparison research is recommended to determine if this is true of anxiety in general

Being idiographic with group data: Seeing is believing without p.

Methodological reform in psychology calls for research to be more idiographic and less dependent on group statistical inference using null-hypothesis significance testing. Recommended alternatives include the use of the new statistics; attention to measurement error, reliable change, Effect Size and clinical/practical significance; more extensive use of graphs and visual analysis; and abandonment of over-reliance on p (e.g., Association for Psychological Science; Cumming; Klein; Task Force on Statistical Inference). This has major implications for applied psychology, given that the application of knowledge is almost always idiographic (i.e., to the single case) while applied research has overwhelmingly been done within the nomothetic, group statistical tradition. This paper describes a synthesis of these alternative approaches to data analysis that presents data on change over time visually for each participant, while presenting group statistics in a way consistent with the new statistics approach. This is done using Modified Brinley Plots, scatter-plots that compare individual scores at time 1 (normally pre-treatment) with scores at various times post-treatment. If the origin and axis scales are the same no or little change is shown by data points clustering on or about the 45o diagonal line. Change associated with treatment (improvement or deterioration) is shown by shifts away from the diagonal. Interpretation is enhanced by the addition of clinical cut-offs, and indicators of means, variances, confidence intervals, measurement error, reliable change, and effect sizes. Both between-group and within-group data may be presented and analysed in this way

To average or not to average? - that is the question

At its inception in the work of Skinner the nascent field of>behaviour analysis eschewed between-subject (group) averaging, Skinner (1938) remarking that [this] kind of science ? belongs on the non-statistical side (p443), and that individual prediction is of tremendous importance so long as the organism is to be treated scientifically (p444). Sidman (1960) strongly endorsed this, while allowing group averaging in specific circumstances. Nevertheless, from time to time, eminent behaviour analysts have called for the field to adopt group statistical methods requiring group averages, often on pragmatic grounds that this will help the field engage more with mainstream research. This paper will first consider why Skinner and Sidman argued as they did, and then consider several more recent arguments that support their position. The first is an argument that extends and generalizes Sidman?s from a biological perspective, noting that it is variability that drives natural selection, the most central process in biology, and that natural selection is blind to the average. Stephen J Gould argues that pre-occupation with group averages risks overshadowing proper attention to variability. The second argument considers the dangers of attempting to make inferences about within-subject processes from between-subject data (Quetelet?s fallacy), and the third, relatedly, considers the implications of measurement theory that specifies that inter-individual variation can only be used to explain intra-individual variation when the measurement system is ergodic. Most measurement in psychology and behaviour analysis, however, is non-ergodic. I conclude that the field should continue to eschew group averaging as a matter of principle, except in the instances that fit the conditions specified by Sidman and with due attention to variability (Gould)

Evidence fit for evidence-based practice: Implications for the curriculum and new ways of looking at data.

Current proposals for methodological reform in psychology call for research to be more idiographic and less dependent on group averaging and null-hypothesis statistical testing. This paper reviews this development in the context of evidence-based practice and considers several major changes in the methodology curriculum required if reform is to occur and if evidence is to be fit for use in evidence-based practice. These changes include the teaching of the new statistics (estimation, confidence intervals, effect sizes, and meta-analysis); visual analysis techniques for the display of individual data in group contexts; replication; single-case research designs; and more sophisticated statistical tools (e.g., P-factor analysis). The presentation will focus on the construction and interpretation of modified Brinley plots, a technique for analysing change over time that is particularly suitable for idiographic analysis of outcome research in behavioural and cognitive-behavioral therapies. Modified Brinley plots are scatter-plots that compare individual scores at time 1 (normally pre-treatment) with scores at various times post-treatment. If the origin and axis scales are the same no or little change is shown by data points clustering on or about the 45o diagonal line. Change associated with treatment (improvement or deterioration) is shown by shifts away from the diagonal. Interpretation is aided by the addition of clinical cut-offs, and indicators of means, variances, confidence intervals, measurement error, reliable change, and effect sizes. Both between-group and within-group data may be presented and analysed with these plots, and they form the basis of new visual displays for group research using single-case research designs

The analysis of change: Innovations in the visual analysis of data

Methodological reform in psychology calls for research to be more idiographic and less dependent on group statistical inference. Recommended alternatives include more extensive use of graphs and visual analysis. This paper describes the construction and interpretation of modified Brinley plots, a technique for analysing treatment outcomes for individuals within groups that is particularly suitable for outcome research of psychological therapies. Modified Brinley plots are scatter-plots that compare individual scores at time 1 (normally pre-treatment) with scores at various times post-treatment. If the origin and axis scales are the same no or little change is shown by data points clustering on or about the 45o diagonal line. Change over time (improvement or deterioration) is shown by shifts away from the diagonal. Interpretation is aided by the addition of clinical cut-offs, and by the use of the Reliable Change Index (based on measurement error). In addition to displaying individuals’ data, these graphs may also display group effects such as means, variances, confidence intervals, and effect sizes. Both between-group and within-group data may be presented and analysed this way and large amounts of data can be efficiently presented and clearly understood within one figure. This talk may be particularly helpful to students planning research into within-participant change over time

Analysing therapeutic change using modified Brinley plots: History, construction, and interpretation

Available online 20 September 2016The paper reviews the history, construction and interpretation of modified Brinley plots, a scatter-plot used in therapy outcome research to compare each individual participant’s scores on the same dependent variable at time one (normally pre-treatment baseline; X-axis) with scores at selected times during or after treatment (Y-axis). Since 1965 eponymously named Brinley plots have occasionally been used in experimental psychology to display group mean data. Between 1979 and 1995 a number of clinical researchers modified Brinley plots to show individuals’ data but these plots have received little subsequent use. When constructed with orthogonal axes having the same origin and scale values, little or no change over time is shown by individuals’ data points lying on or closely about the diagonal (45 0o) while the magnitude and direction of any improvement (or deterioration), outliers, and the extent of replication across cases shows via dispersion of points away from 45 0o. Interpretation is aided by displaying reliable change boundaries, clinical cut-offs, means, variances, confidence intervals, and effect sizes directly on the graph. Modified Brinley plots are directly informative about individual change during therapy in the context of concurrent change in others in the same (or a different) condition, clearly show if outcomes are replicated and if they are clinically significant, and make nomothetic group information, notably effect sizes, directly available. They usefully compliment other forms of analysis in therapy outcome research

Innovation in the analysis of therapeutic change: Combining both idiographic and nomothetic approaches in one visual analysis

For decades there have been calls for clinical research in psychology to be more idiographic and less dependent on group statistical inference, because what applies in aggregate (nomothetic research) does not necessarily apply to any specific individual (idiographic application). Recommended alternatives include more extensive use of graphs and visual analysis of data. This presentation describes the history, construction and interpretation of modified Brinley plots, a technique for analysing treatment outcomes for individuals within groups that is particularly suitable for therapy outcome research, especially during the treatment-development phase when full randomized controlled trials may be premature. Modified Brinley plots are scatter-plots that compare individual scores at time 1 (normally pretreatment) with scores at various times post-treatment. If the origin and axis scales of the graph are the same no or little change is shown by data points clustering on or about the 45o diagonal line. Change over time (improvement or deterioration) is shown by shifts away from the diagonal. Interpretation is aided by the addition of clinical cut-offs, and by the use of the Reliable Change Index (based on measurement error), features which partition the graph space into meaningful zones. In addition to displaying individuals’ data, these graphs may also display group effects such as means, variances, confidence intervals, and effect sizes. Both between-group and within-group data may be presented and analysed this way and large amounts of data can be efficiently presented and clearly understood within one figure

The Scientist-Practitioner in the 21st C: Responding to evidence that the evidence-base for practice is flawed.

The ideal of the scientist-practitioner as the basis for applied psychology was one of the great achievements of 20th C psychology. Unfortunately, the idea became inextricably linked to the adoption by Psychology of a research methodology (I call it the Standard Model) based on a fusion of the ideas of Fisher and of Neyman and Pearson that are internally incompatible, and poorly adapted to the needs of applied research. Methodological criticism of the Standard Model has grown in intensity and comprehensiveness in the past 50 years. It has been almost completely ignored by researchers. We now have the paradox of applied psychologists, as scientist-practitioners, being expected to conduct evidence-based practice, while researchers themselves persistently ignore the evidence that their methods are flawed. I will review some of this history, and consider some of the ways that we might change our methods to better meet the needs of scientist-practitioners and evidence-based practice. I will particularly discuss the utility of single-case research approaches to applied practice

Psychology in the 21st C – Getting over our addiction to p so our research can be evidence for our practice.

Psychology in the 21st C – Getting over our addiction to p so our research can be evidence for our practice Neville M Blampied University of Canterbury In the middle years of the 20th C two things happened that had far-reaching impacts on psychology. The first was the invention by R.A Fisher and other statisticians of modern factorial research designs, requiring random assignment of participants to conditions and statistical inference based on null-hypothesis statistical tests (NHST) of group averages. By the mid 1950’s researchers in psychology were ‘addicted to p’ and the use of NHST became essential for research to be published. The second development occurring at almost the same time, was the development by the American Psychological Association of the scientist-practitioner model of clinical practice. This ideal rapidly became the dominant model for university training of clinical psychologists in the USA and has been generalised to the training of applied psychologists in general and across the world. Not surprisingly, the ‘scientist’ part of the scientist-practitioner ideal became closely associated with NHST-based research. Clinical and applied research has for nearly 50 years thus also been ‘addicted to p’, dominated by the search for statistical significance among group mean differences rather than clinical or practical significance and unable legitimately to make inferences about individual clients. The contemporary rise of the evidence-based practice movement, which can be considered a reformulation of the scientist-practitioner model, has brought sharply into focus again what has also been known for most of those 50 years: Our research methods, and especially our data analysis methods, are poorly adapted to the needs of practice. Research is about ideal, abstract, average types; practice is about individuals in all their diversity and variability. Furthermore, there is now an emergent ‘crisis’ in psychology due to the recognition that much of our research fails to replicate. I will review this lamentable history, and then consider some of the ways that we can adapt our research practices to make them much better adapted to evidence-based practice. These include the use of single—case research designs and novel methods of visual analysis of data. Reference: Blampied, N.M. (2013). Single-case research and the scientist-practitioner ideal in applied psychology. In G. Madden (Editor-in-chief). Handbook of Behavior Analysis Vol 1. (pp 177 – 197). Washington, DC: American Psychological Association