Gratitude : a basis for positive psychology interventions with a clinical population

This thesis includes a literature review that summarises the types of psychological research that have been conducted into gratitude, including the research conceptualising and developing assessments around it and exploring its associations with wellbeing, personality, social interaction, and health. The review focuses specifically on the research examining the relationship of gratitude to anxiety, depression and sleep, providing an outline of current theories about the relationship of positive affect to wellbeing, and a summary of the evidence to date. It is noted that there is comparatively little research on the impact of gratitude on anxiety and sleep but promising findings about the role of gratitude in the treatment of depression. Taken together, it is argued, the current research supported the need for trials of gratitude interventions specifically with clinical populations. Finally, the review looks at the literature of experimental interventions using gratitude. Particular emphasis is given to what has been learnt through these trials that might guide the focus and design of future research.

There follows the report of a randomized wait-list controlled pre-post trial of a gratitude diary intended to extend the research into the efficacy of gratitude diaries in the treatment of clinical populations with depression, anxiety and sleep difficulties. It was hypothesised that after completing a brief gratitude diary for three weeks, participants would have lower scores on measures of depression, anxiety, and perceived sleep difficulties, and higher scores on a measure of life satisfaction. These results were also expected to be evident at three-week follow-up. In a randomised waitlist-controlled trial with repeated measures pre-, post- and follow-up design, participants (N=109, from Australia) aged 18-64 years with a current self-reported diagnosis of an anxiety disorder and/or depression, took part in a self-help study via the internet. After completing the diary participants had lower scores on measures of depression, anxiety and perceived sleep difficulties and higher scores on a measure of subjective wellbeing than immediately pre-intervention. In addition, they had improved scores on a measure of stress. At three-week follow-up scores on depression and perceived sleep difficulties were no longer significantly different from pre-intervention, however improvements for subjective wellbeing and stress at post-intervention were maintained. At follow-up scores for anxiety had not only been maintained but had improved significantly beyond post-intervention results. This trial provides support for the use of gratitude diaries as a short-term intervention with a clinical population. Different patterns of anxiety and depression scores raise the possibility that gratitude interventions work differently to address depression and anxiety symptoms and provide support for the idea that gratitude interventions may have sustainable effects on anxiety symptoms.

Nutritional psychiatry research: an emerging discipline and its intersection with global urbanization, environmental challenges and the evolutionary mismatch

In 21st-century public health, rapid urbanization and mental health disorders are a growing global concern. The relationship between diet, brain function and the risk of mental disorders has been the subject of intense research in recent years. In this review, we examine some of the potential socioeconomic and environmental challenges detracting from the traditional dietary patterns that might otherwise support positive mental health. In the context of urban expansion, climate change, cultural and technological changes and the global industrialization and ultraprocessing of food, findings related to nutrition and mental health are connected to some of the most pressing issues of our time. The research is also of relevance to matters of biophysiological anthropology. We explore some aspects of a potential evolutionary mismatch between our ancestral past (Paleolithic, Neolithic) and the contemporary nutritional environment. Changes related to dietary acid load, advanced glycation end products and microbiota (via dietary choices and cooking practices) may be of relevance to depression, anxiety and other mental disorders. In particular, the results of emerging studies demonstrate the importance of prenatal and early childhood dietary practices within the developmental origins of health and disease concept. There is still much work to be done before these population studies and their mirrored advances in bench research can provide translation to clinical medicine and public health policy. However, the clear message is that in the midst of a looming global epidemic, we ignore nutrition at our peril.

Indigenous students' persistence in higher education in Australia: contextualising models of change from psychology to understand and aid students' practices at a cultural interface

The need to address the substantial inequities that exist between Indigenous and non-Indigenous Australians in higher education is widely recognised. Those factors that affect the performance of Indigenous students in tertiary education have been reasonably well documented across different institutions, disciplines, and programme levels but there has, to date, been less consideration of the processes by which Indigenous students either persist or desist in higher education. This paper aims to present a conceptual understanding of academic persistence that can inform the delivery of tailored academic support interventions to Indigenous students who are at high risk of leaving higher education.

Enhancing critical analysis and problem-solving skills in undergraduate psychology: An evaluation of a collaborative learning and problem-based learning approach

Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills. © 2013 The Australian Psychological Society.

Assessing the clinical competence of psychology students through Objective Structured Clinical Examinations (OSCEs): student and staff views

Objective Structured Clinical Examinations (OSCEs) are a well-known, reliable, and valid assessment method used across the healthcare sector. In the present study, we applied OSCEs in three units within professional postgraduate psychology courses, with the broad aims of identifying staff and student perceptions of the assessment. At the conclusion of each OSCE, staff and students completed a feedback questionnaire that contained both scaled and open-ended questions. Results suggest that clinical psychology OSCEs can be stressful for students, but are also well regarded. Both staff and students felt that the OSCEs were realistic, valid, and aligned well with professional practice. Students reported differences in the way in which they prepared for the OSCEs compared with a written exam or other form of assessment, while staff noted that models of OSCE development must be flexible, to adequately assess the objectives of individual units. Further, because they can be a costly exercise, OSCEs need to be applied judiciously within the tertiary sector.

Evolutionary optimization: a big data perspective

Stochastic search techniques such as evolutionary algorithms (EA) are known to be better explorer of search space as compared to conventional techniques including deterministic methods. However, in the era of big data like most other search methods and learning algorithms, suitability of evolutionary algorithms is naturally questioned. Big data pose new computational challenges including very high dimensionality and sparseness of data. Evolutionary algorithms' superior exploration skills should make them promising candidates for handling optimization problems involving big data. High dimensional problems introduce added complexity to the search space. However, EAs need to be enhanced to ensure that majority of the potential winner solutions gets the chance to survive and mature. In this paper we present an evolutionary algorithm with enhanced ability to deal with the problems of high dimensionality and sparseness of data. In addition to an informed exploration of the solution space, this technique balances exploration and exploitation using a hierarchical multi-population approach. The proposed model uses informed genetic operators to introduce diversity by expanding the scope of search process at the expense of redundant less promising members of the population. Next phase of the algorithm attempts to deal with the problem of high dimensionality by ensuring broader and more exhaustive search and preventing premature death of potential solutions. To achieve this, in addition to the above exploration controlling mechanism, a multi-tier hierarchical architecture is employed, where, in separate layers, the less fit isolated individuals evolve in dynamic sub-populations that coexist alongside the original or main population. Evaluation of the proposed technique on well known benchmark problems ascertains its superior performance. The algorithm has also been successfully applied to a real world problem of financial portfolio management. Although the proposed method cannot be considered big data-ready, it is certainly a move in the right direction.

Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: a particle swarm optimization technique

 Partial shading is one of the unavoidable complications in the field of solar power generation. Although the most common approach in increasing a photovoltaic (PV) array’s efficiency has always been to introduce a bypass diode to the said array, this poses another problem in the form of multi-peaks curves whenever the modules are partially shaded. To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (MPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This study aims to employ an evolutionary algorithm technique, also known as particle swarm optimization, in MPP detection. VC 2014 Author(s).