The present study begins to address the need for evidence-based approaches for guiding the psychological assessment of children with Fetal Alcohol Spectrum Disorders (FASD). This project represents an important step toward increasing links between research and practice in the communication and use of assessment results for informing intervention decisions. Using a qualitative research approach, the current study contributes to knowledge about concerns with current psychological assessment practices and offers suggestions for optimization based on conversations with teachers, administrators, caregivers and allied professionals. Thematic analysis of 11 focus groups and 3 interviews (N = 60) yielded 3 major findings: the need to focus on the whole child, the necessity of an assessment process that is responsive, and building capacity in the school. This study increases the links between research and practice as we move toward a model of assessment for intervention. Such a model has a strong potential for optimizing assessment practices to better meet the needs of children with FASDs as it promotes a shift that focuses on successful child outcomes regardless of diagnosis.
This issue of the Canadian Journal of Program Evaluation (CJPE) is one of our most comprehensive to date. Not only does it include five full articles, fi ve practice notes, and two book reviews, but it also covers a wide range of evaluation-related topics, practices, and studies. I am pleased to note that our editorial team contin ues to receive high-quality submissions, and I encourage you to keep thinking of the CJPE as an outlet for your work. The articles and practice notes included in this issue focus on four recurring themes that reflect current topics in our field. First, evaluative thinking and capac ity building in non-governmental organizations is the subject of articles by Rog ers, Kelly, and McCoy, as well as by Lu, Elliot, and Perlman. Both articles provide insights into the facilitators of, and barriers to, evaluation capacity building as well as the multiple roles played by evaluators in fostering evaluative thinking amongst organizational staff members. Second, process evaluation appears to be of interest to many evaluators and researchers: Leblanc, Gervais, Dubeau and Delame focus on process evaluation for mental health initiatives, while Parrott and Carman pro vide an example of how process evaluation can contribute to program scaling-up efforts. Chechak, Dunlop, and Holosko also focus on process evaluation and its utility in evaluating youth drop-in programs. Teachers and students of evaluation may be interested in our third theme, which focuses on student contributions to evaluation, both through peer-mentoring-as described in the practice note written by LaChenaye, Boyce, Van Draanen, and Everett-and through the CES Student Evaluation Case Competition-described in a practice note written by Sheppard, Baker, Lolic, Soni, and Courtney. And fourth, we continue to advance our methodological approaches to evaluation, and this is reflected in an article on evaluation in Indigenous contexts by Chandna, Vine, Snelling, Harris, Smylie, and Manson, as well as in an article on the use of an outcome monitoring tool for performance measurement in a clinical psychology setting by Rosval, Yamin, Jamshidi, and Aubry. Czechowski, Sylvestre, and Moreau also feature methods in their practice note on secure data handling for evaluators, a key competency that continues to evolve as our data collection and storage mechanisms adapt to new technology. In addition to these articles and practice notes, this issue also features two book reviews that are sure to interest our readers. First, Bhawra provides an account of
Unsupervised classification is becoming an increasingly common method to objectively identify coherent structures within both observed and modelled climate data. However, in most applications using this method, the user must choose the number of classes into which the data are to be sorted in advance. Typically, a combination of statistical methods and expertise is used to choose the appropriate number of classes for a given study, however it may not be possible to identify a single `optimal' number of classes. In this work, we present a heuristic method, the Ensemble Difference Criterion, for determining the maximum number of classes unambiguously for modelled data where more than one ensemble member is available. This method requires robustness in the class definition between simulated ensembles of the system of interest. For demonstration, we apply this to the clustering of Southern Ocean potential temperatures in a CMIP6 climate model, and show that the data supports between four and seven classes of a Gaussian Mixture Model.
Visual data collection methods are gaining momentum in the field of qualitative research because of their ability to document the social world and experiences of participants (Banks, 2001; Rose, 2001. This study employed quilting as a data collection method to capture the experiences of 47 Fetal Alcohol Spectrum Disorder (FASD) prevention workers in the Parent Child Assistance Program (PCAP) across Alberta. Specifically, this article focuses on the process of creating the quilt, the impact that this data collection method has had on participants and researchers, as well as a discussion of our next steps and suggestions for future opportunities to use quilting methods in community-based research.
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