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      Shifting to Tele-Creative Arts Therapies during the COVID-19 Pandemic: An International Study on Helpful and Challenging Factors

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          Abstract

          The COVID-19 pandemic has led to an unprecedented shift to online treatment. For the creative arts therapies (CATs) – a healthcare profession that involves the intentional use of the visual art, drama, music, dance, and poetry within a therapeutic relationship – this shift has been highly consequential for practice. This study examined (a) how the COVID-19 pandemic has impacted clinical practice in the CATs, and (b) the features characterizing online practice in an international sample of 1206 creative arts therapists aged 22-86 (92% female). It aimed to identify changes in the use of the arts in therapy, resources that contributed to the delivery of therapy, and the role of therapists’ creative self-efficacy in adapting to these changes. Respondents completed close and open-ended questions providing examples of what does and does not work in online practice. The results indicate that creative self-efficacy plays a meaningful role in buffering the impact of therapists’ computer comfort on their perceived difference in online clinical practice; confidence in one’s abilities positively contributed to their adaptation to online practice. The qualitative analysis yielded four main categories: the challenges of tele-CATs, continuing the therapeutic process through tele-CATs, adaptations for tele-CATs, and future directions. Overall, the results present a timely report on the inevitable transition of the CATs to online practice.

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          A power primer.

          Jacob Cohen (1992)
          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            COVID-19 and mental health: A review of the existing literature

            Ravi Philip Rajkumar (2020)
            Highlights • Subsyndromal mental health concerns are a common response to the COVID-19 outbreak. • These responses affect both the general public and healthcare workers. • Depressive and anxiety symptoms have been reported in 16–28% of subjects screened. • Novel methods of consultation, such as online services, can be helpful for these patients. • There is a need for further long-term research in this area, especially from other countries
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              Is Open Access

              Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis

              Hae-Young Kim (2013)
              As discussed in the previous statistical notes, although many statistical methods have been proposed to test normality of data in various ways, there is no current gold standard method. The eyeball test may be useful for medium to large sized (e.g., n > 50) samples, however may not useful for small samples. The formal normality tests including Shapiro-Wilk test and Kolmogorov-Smirnov test may be used from small to medium sized samples (e.g., n 2.1 Kurtosis is a measure of the peakedness of a distribution. The original kurtosis value is sometimes called kurtosis (proper) and West et al. (1996) proposed a reference of substantial departure from normality as an absolute kurtosis (proper) value > 7.1 For some practical reasons, most statistical packages such as SPSS provide 'excess' kurtosis obtained by subtracting 3 from the kurtosis (proper). The excess kurtosis should be zero for a perfectly normal distribution. Distributions with positive excess kurtosis are called leptokurtic distribution meaning high peak, and distributions with negative excess kurtosis are called platykurtic distribution meaning flat-topped curve. 2) Normality test using skewness and kurtosis A z-test is applied for normality test using skewness and kurtosis. A z-score could be obtained by dividing the skew values or excess kurtosis by their standard errors. As the standard errors get smaller when the sample size increases, z-tests under null hypothesis of normal distribution tend to be easily rejected in large samples with distribution which may not substantially differ from normality, while in small samples null hypothesis of normality tends to be more easily accepted than necessary. Therefore, critical values for rejecting the null hypothesis need to be different according to the sample size as follows: For small samples (n < 50), if absolute z-scores for either skewness or kurtosis are larger than 1.96, which corresponds with a alpha level 0.05, then reject the null hypothesis and conclude the distribution of the sample is non-normal. For medium-sized samples (50 < n < 300), reject the null hypothesis at absolute z-value over 3.29, which corresponds with a alpha level 0.05, and conclude the distribution of the sample is non-normal. For sample sizes greater than 300, depend on the histograms and the absolute values of skewness and kurtosis without considering z-values. Either an absolute skew value larger than 2 or an absolute kurtosis (proper) larger than 7 may be used as reference values for determining substantial non-normality. Referring to Table 1 and Figure 1, we could conclude all the data seem to satisfy the assumption of normality despite that the histogram of the smallest-sized sample doesn't appear as a symmetrical bell shape and the formal normality tests for the largest-sized sample were rejected against the normality null hypothesis. 3) How strict is the assumption of normality? Though the humble t test (assuming equal variances) and analysis of variance (ANOVA) with balanced sample sizes are said to be 'robust' to moderate departure from normality, generally it is not preferable to rely on the feature and to omit data evaluation procedure. A combination of visual inspection, assessment using skewness and kurtosis, and formal normality tests can be used to assess whether assumption of normality is acceptable or not. When we consider the data show substantial departure from normality, we may either transform the data, e.g., transformation by taking logarithms, or select a nonparametric method such that normality assumption is not required.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Arts Psychother
                Journal ID (iso-abbrev): Arts Psychother
                Title: The Arts in Psychotherapy
                Publisher: Elsevier Ltd.
                ISSN (Print): 0197-4556
                ISSN (Electronic): 1873-5878
                Publication date PMC-release: 22 February 2022
                Publication date (Electronic): 22 February 2022
                Electronic Location Identifier: 101898
                Affiliations
                [a ]School of Creative Arts Therapies, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
                [b ]New York University, New York, NY
                [c ]Lesley University, Cambridge, MA
                Author notes
                [* ]Correspondence to: School of Creative Arts Therapies, Faculty of Social Welfare and Health Sciences, University of Haifa, Israel. 199 Aba Khoushy Av. Mount Carmel, Haifa 3498838, Israel.
                Article
                Publisher Item ID: S0197-4556(22)00019-3 Publisher ID: 101898
                DOI: 10.1016/j.aip.2022.101898
                PMC ID: 8860746
                PubMed ID: 35221415
                SO-VID: b06447c2-322c-4528-b540-3833cbe6ca92
                Copyright © © 2022 Elsevier Ltd. All rights reserved.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 27 August 2021
                Date revision received : 2 February 2022
                Date accepted : 18 February 2022
                Categories
                Subject: Article

                Keywords: creative arts therapies,tele-therapy,coronavirus,creative self-efficacy,corona covid-19, tele-creative arts therapies
                Data availability:
                Keywords: creative arts therapies, tele-therapy, coronavirus, creative self-efficacy, corona covid-19, tele-creative arts therapies

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