7 research outputs found

    Use of Pie Charts in Cognitive Therapies

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    One of the major goals of cognitive therapy is to generate cognitive restructuring for clients. While generating cognitive restructuring plenty of cognitive interventions can be useful. One of those interventions is building a Pie Chart (PC) prepared collaboratively with clients. In literature large amount of example related to target areas of PC has been stated. Investigating reasons of an event or a situation, appraising ones responsibility, testing catastrophic evaluations regarding a life event, challenging labeling thoughts and setting goals are some of the major target areas of PC. When using PC it is aimed at expanding perspectives of clients and helping them achieve an objective point of view towards life events and situations. The goal of the current paper is to explain the target areas for PC as a tool for cognitive restructuring. Key Words: Cognitive Therapy, Cognitive Restructuring, Pie Chart Technique [JCBPR 2016; 5(1.000): 38-43

    Comparing Diagnostic Tools in Personality Disorders

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    Personality Disorder is defined as; continually self experience and behavioral pattern which has great variations of individual cultural normal expectations. Several diagnostic tools were developed for diagnosing personality disorders. In our study consistency of different diagnostic tools used for thhe diagnosis of personality disorders were evaluated. 39 inpatients diagnosed as personality disorder from Diskapi Yildirim Beyazit Traning and Reseach Hospital were recruited into the study. Psychotic patients are excluded from the study. Sociodemographic Information Form, MMPI and PBQ scales were given all the patients. Both PBQ personality subscales and MMPI PD scales were compared with semi-structured SCID-II interview diagnoses. Findings suggest less correlation than expected. Relatively higher correlation was found between PBQ personality subscales and MMPI-PD. Most common psychiatric comorbid disorder was depression. These findings suggest that further studies are needed for the development of diagnostic tools which take the differences of self report scales and clinical evalution into consideration. Beside, the differences of the categorical and dimensional classification of personality disorders should be bear in mind in evaluation of this patient group. [JCBPR 2016; 5(1.000): 22-27

    Measuring Cognitive Errors Using the Cognitive Distortions Scale (CDS): Psychometric Properties in Clinical and Non-Clinical Samples

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    The Cognitive Distortions Scale was developed to assess thinking errors using case examples in two domains: interpersonal and personal achievement. Although its validity and reliability has been previously demonstrated in non-clinical samples, its psychometric properties and scoring has not yet been evaluated. The aim of the current study was to evaluate the psychometric properties of the Cognitive Distortions Scale in two Turkish samples and to examine the usefulness of the categorical scoring system. A total of 325 individuals (Sample 1 and Sample 2) were enrolled in this study to assess those psychometric properties. Our Sample 1 consisted of 225 individuals working as interns at the Diskapi Yildirim Beyazit Teaching and Research Hospital and Sample 2 consisted of 100 patients diagnosed with depression presenting to the outpatient unit of the same Hospital. Construct validity was assessed using the Beck Depression Inventory, the State Trait Anxiety Inventory, the Dysfunctional Attitude Scale, and the Automatic Thought Questionnaire. Factor analyses supported a one-factor model in these clinical and non-clinical samples. Cronbach's alpha values were excellent in both the non-clinical and clinical samples (0.933 and 0.918 respectively). Cognitive Distortions Scale scores showed significant correlation with relevant clinical measures. Study Cognitive Distortions Scale scores were stable over a time span of two weeks. This study showed that the Cognitive Distortions Scale is a valid and reliable measure in clinical and non-clinical populations. In addition, it shows that the categorical exists/does not exist scoring system is relevant and could be used in clinical settings

    Premenstrual Symptom Screening Tool: A Useful Tool for DSM-5 Premenstrual Dysphoric Disorder

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    Aim: To assess the usefulness of Premenstrual Symptoms Screening Tool (PSST) in detecting Premenstrual Dysphoric Syndrome (PMDD) and Premenstrual Syndrome (PMS) in a Turkish sample. Material and Method: One hundred and eighteen women were included in the study. Participants were menstruating women, between the ages of 18 and 49 years who work in various departments of Diskapi Yildirim Beyazit Teaching and Research Hospital. Sociodemographic data collection form, PSST, and Symptom Check List (SCL-90-R) were given to the participants, filled out by participants and checked out by researchers. Participants were divided into three groups (i.e., women with subthreshold premenstrual symptoms, women with PMDD, and women with PMS) according to the scores they get on the PSST. These groups were compared according to PSST scores and SCL-90-R scores. Results: Internal consistency was excellent (Cronbach alpha=0.928) for the items of the tool. In this sample, the prevalence of the PMDD and PMS were 15.2 % (n=18) and 32.2 % (n=38) respectively. When we compare the scores on SCL-90-R sub-scales there were significant differences between the PMDD, PMS, and women with subthreshold groups. Besides there were significant differences for the three groups in terms of percentages of women who reported moderate to severe symptoms on the four items that are essential to PMDD diagnosis. Discussion: Premenstrual Symptoms Screening Tool is a useful tool to detect candidates for PMDD and moderate to severe PMS

    The correlations between the individual items of CDS and BDI, STAI-S, and STAI-T.

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    <p>Pearson correlation coefficients were calculated between the variables.</p><p>*Statistically significant at the level of p<0.05.</p><p>**Statistically significant at the level of p<0.001.</p><p>The correlations between the individual items of CDS and BDI, STAI-S, and STAI-T.</p

    The means, standard deviations and comparisons of BDI, STAI, CDS, and DAS scales' scores between the clinical and non-clinical samples.

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    <p>STAI = State Trait Anxiety Inventory, IP = Interpersonal subscale of CDS, PA = Personal Achievement subscale of CDS, DAS = Dysfunctional Attitudes Scale.</p><p>T tests were performed using Bonferroni correction. Accordingly p value was set p<0.005.</p><p>*Statistically significant differences between the two groups.</p><p>The means, standard deviations and comparisons of BDI, STAI, CDS, and DAS scales' scores between the clinical and non-clinical samples.</p
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