Dataset Information

Psychometric Properties of the Concise Associated Symptom Tracking Scale and Validation of Clinical Utility in the EMBARC Study.

ABSTRACT:

Objective

The authors aimed to evaluate psychometric properties of the Concise Associated Symptom Tracking (CAST) Scale and validate the clinical utility of measuring irritability by updating and replicating a previously published outcome calculator from the Combining Medications to Enhance Depression Outcomes (CO-MED) trial.

Methods

Participants were 292 adults from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study who had completed the CAST scale at baseline. The scale's five-domain (irritability, anxiety, mania, insomnia, and panic) structure was evaluated with confirmatory factor analysis. Correlations with other clinical measures were used to confirm convergent and divergent validity. Logistic regression analyses from CO-MED were used to estimate individual outcomes in EMBARC.

Results

Cronbach's alpha for the CAST scale was 0.78. Model fit for the five-domain structure was adequate (goodness of fit index=0.93, comparative fit index=0.92, root mean square error of approximation=0.06). Scores on irritability, anxiety, panic, insomnia, and mania were correlated with scores on the Anger Attack Questionnaire irritability item (r_s=0.50), Hamilton Rating Scale for Depression anxiety subscale (r_s=0.24), Mood and Anxiety Symptoms Questionnaire anxious arousal scale (r_s=0.44), Quick Inventory of Depressive Symptomatology Self-Report insomnia items (r_s=0.38), and Altman Self-Rating Mania Scale (r_s=0.39), respectively. Individual outcomes of remission (area under the curve [AUC]=0.805) and no meaningful benefit (AUC=0.779) were predicted with high accuracy among EMBARC participants using their baseline and week 4 scores for depression and irritability and model estimates from CO-MED.

Conclusions

Measuring irritability may help predict clinical course. The CAST scale is a valid measure of depression-associated symptoms, including irritability.

SUBMITTER: Minhajuddin A

PROVIDER: S-EPMC9175787 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Psychometric Properties of the Concise Associated Symptom Tracking Scale and Validation of Clinical Utility in the EMBARC Study.

Minhajuddin Abu A Jha Manish K MK Fatt Cherise Chin CC Trivedi Madhukar H MH

Psychiatric research and clinical practice 20200909 1

<h4>Objective</h4>The authors aimed to evaluate psychometric properties of the Concise Associated Symptom Tracking (CAST) Scale and validate the clinical utility of measuring irritability by updating and replicating a previously published outcome calculator from the Combining Medications to Enhance Depression Outcomes (CO-MED) trial.<h4>Methods</h4>Participants were 292 adults from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study who had co ...[more]

PMID: 36101888

Similar Datasets

Project description:BackgroundWe report on the psychometric properties of the 16-item Concise Associated Symptom Tracking Scale self-report scale and its clinical utility.MethodsThe 5-domain (irritability, anxiety, mania, insomnia, and panic) structure of Concise Associated Symptom Tracking Scale was validated with confirmatory factor analysis in Combining Medications to Enhance Depression Outcomes trial participants at baseline (n=664). Correlations with other clinical measures were used for convergent and divergent validity. In participants with at least one postbaseline visit (n=630), worsening in each Concise Associated Symptom Tracking Scale domain was defined as ≥1.28 SD increase from baseline for each visit (weeks 1, 2, 4, and 6) only. Worsening in any domain (except mania) was defined as overall worsening. Association of domain-specific and overall worsening with remission was tested with logistic regression analyses.ResultsThe 5-domain structure had adequate model fit on confirmatory factor analysis (GFI=0.93, CFI=0.89, and RMSEA=0.07). Scores on anxiety, panic, insomnia, and mania significantly correlated with Hamilton Rating Scale for Depression anxiety subscale (rs=0.27), Psychiatric Diagnostic Screening Questionnaire-panic scale (rs=0.35), sum of 3 Quick Inventory of Depressive Symptomatology Self-Report insomnia items (rs=0.55), and Altman Self-Rating Mania scale (rs=0.41), respectively. From baseline to week 6, 5.2%, 7.5%, 47.6%, 15.6%, 6.2%, and 27.6% participants (n=630) experienced irritability, anxiety, mania, insomnia, panic, and overall worsening, respectively. Participants with overall worsening were less likely to remit (31.6%) than those without any worsening (43.9%; odds ratio=0.53, 95% CI=0.36, 0.78).ConclusionThe 16-item Concise Associated Symptom Tracking Scale self-report has acceptable psychometric properties. Clinically significant worsening of irritability, anxiety, insomnia, or panic with antidepressant treatment is associated with poorer outcomes.

Project description:BackgroundSelf-absorption refers an excessive, persistent, and rigid preoccupation with information regarding the self. This study aims to introduce the Self-Absorption Scale (SAS) into China with an assessment of its latent variable structure, network structure, psychometric properties, and clinical utility in a nonclinical Chinese sample.Methods209 participants completed the translated SAS as well as the Short General Health Questionnaire (GHQ-12), rumination subscale of the Rumination-Reflection Questionnaire (RRQ), the Mindful Attention Awareness Scale (MAAS), the Private Self-Consciousness Scale (PrSCS), the Obsessive-Compulsive Inventory-Revised (OCI-R) and the Dissociative Experiences Scale (DES-II). In addition, 30 respondents completed the Chinese version of the SAS and retested it 2 weeks later.ResultsThe Chinese version of the SAS (CH-SAS) had a desirable two-correlated-factor structure with the reverse scored item removed, which was invariant across different genders. The core items in the network structure of the CH-SAS were related to excessive self-immersion, uncontrollability and anxiety aspects of self-absorption. The Cronbach's alpha coefficient for the CH-SAS was 0.903 while the McDonald's omega coefficient was 0.916 and the test-retest reliability was 0.908. The CH-SAS and its two subscales had moderate positive correlations with the rumination subscale of the RRQ (ranging from 0.474 to 0.616; p < .001) and the GHQ-12 (ranging from 0.479 to 0.538; p < .001), and moderate negative correlations with the MAAS (ranging from - 0.413 to - 0.360; p < .001). The PrSCS has almost no correlation with the CH-SAS and PrSAS (p > .05), and its correlation with the PubSAS was significant at the 0.05 level, with a remarkably low correlation coefficient (r = .157). The hierarchical regression analysis suggested that the CH-SAS can significantly predict the severity of OCD beyond factors such as depression, anxiety, rumination, dissociation, and mindful attention awareness.ConclusionsThe CH-SAS demonstrates excellent reliability, including internal consistency and test-retest reliability. Additionally, it exhibits favorable structural validity, as well as strong evidence of convergent and divergent validity. Furthermore, the self-absorption measured using the CH-SAS contributed significantly to the prediction of OCD beyond other relevant psychological factors, suggesting its clinical utility.

Project description:BackgroundAlzheimer's disease (AD) is the most frequent cause of cognitive impairment. Community knowledge of the disease has proven to be a very important aspect of the development of interventions and the evaluation of their effectiveness. However, it is necessary to have standardized and recognized tools in different languages. The aim of the current study was to develop a cross-cultural adaptation of the Spanish Dementia Knowledge Assessment Scale (DKAS-S) and to assess their psychometric properties with cohorts of health students and professional and non-professional caregivers of AD patients from several regions of Spain.MethodsWe developed and translated the DKAS into Spanish following the forward-back-forward translation procedure. Then, we performed a cross-sectional study to assess the validity, reliability and feasibility of the DKAS-S. We also performed an analysis to obtain test-retest reliability measures. The study was performed in four medical centres across three regions in Spain. From May to September 2019, we administered the scale to students, professional and non-professional caregivers; including a subgroup of non-professional caregivers of patients with early-onset AD (< 65 years).ResultsEight hundred forty-six volunteer participants completed the DKAS-S: 233 students (mean age 26.3 ± 9.2 years), 270 professional caregivers (mean age 42.5 ± 11.7 years) and 343 non-professional caregivers of AD patients. (mean age was 56.4 ± 13.16). The DKAS-S showed good internal consistency (Cronbach's α = 0.819) and good test-retest reliability (time 1: 28.1 ± 8.09 vs time 2: 28.8 ± 7.96; t = - 1.379; p = 0.173). Sensitivity to change was also significant in a subgroup of 31 students who received education related to AD and dementias between each administration (time 1: 25.6 ± 6.03) to (time 2: 32.5 ± 7.12; t = - 5.252, p = 0.000). The validity of the construct was verified by confirmatory factor analysis, although there were challenges in the inclusion of some items in the original 4 factors.ConclusionsThe 25-item DKAS-S showed good psychometric properties for validity and reliability and the factorial analysis when it was administered to a population of students and professional and non-professional caregivers. It was a useful instrument for measuring levels of knowledge about dementia in Spanish population.

Dataset Information

Psychometric Properties of the Concise Associated Symptom Tracking Scale and Validation of Clinical Utility in the EMBARC Study.

Objective

Methods

Results

Conclusions

Publications

Psychometric Properties of the Concise Associated Symptom Tracking Scale and Validation of Clinical Utility in the EMBARC Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets