Psychometric Properties of a Simplified Chinese Version of the Secondary Trauma Questionnaire in a Potentially Traumatized Study Sample

Yan, Ya-jun; Jiang, Lichen; Hu, Muli; Xu, Xin; Jin, Zhishuai; Song, Yu; Lu, Zhang-xiu; Chen, You-qiao; Li, Na-Ni; Su, Jun; Wu, Daxing; Xiao, Tao

doi:10.3389/fpsyg.2020.00767

Cited by 2 publications

(2 citation statements)

References 44 publications

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“…The tool includes a total of 17 different questions that measure stress using five-point, self-rating scales with responses ranging from 1 to 5, with 1 = never and 5 = very often. The questions are clustered into the three elements of STS: (i) intrusion (questions 2, 3, 6, 10, and 13), (ii) arousal (questions 4, 8, 11, 15, and 16), and (iii) avoidance (questions 1, 5, 7, 9, 12, 14, and 17) [ 24 , 25 ]. In its assessment of stress levels, the questionnaire focuses on the respondents’ experiences in the last seven days.…”

Section: Materials and Designmentioning

confidence: 99%

Exposure to secondary traumatic stress and its related factors among emergency nurses in Saudi Arabia: a mixed method study

Alshammari,

Alanazi,

Kreedi

et al. 2024

BMC Nurs

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Background Emergency department (ED) nurses are exposed to the risk of secondary traumatic stress (STS), which poses a threat not only to nurses’ health and psychological well-being but also adversely affects the execution of their professional duties. The quality and outcome of their nursing services are negatively affected by STS. Purpose The purpose of this study is to comprehensively investigate the prevalence and intensity of Secondary Traumatic Stress (STS) among Emergency Department (ED) nurses. It aims to identify and analyze the socio-demographic, occupational, and psychological factors that influence the severity and variation of STS experienced by these nurses. Methods The study utilized a sequential explanatory mixed methods approach, including two phases. Phase 1 employed a cross-sectional study design, utilizing a convenience sample of 181 nurses to explore the levels of STS and the factors associated with it. Following this, Phase 2 was structured as a qualitative descriptive study, which involved conducting semi-structured interviews with a purposefully selected group of ten ED nurses. Data collection took place at three major hospitals in Saudi Arabia during the period from January to June 2022. Results A total of 181 participants were included in the study. The mean STSS score reported by the nurses was 51 (SD = 13.23) out of the maximum possible score of 85, indicating severe STS among ED nurses. Factors associated with an increase in the levels of STS among ED nurses included being female, older in age, married, possessing higher education and experience, having a positive relationship with colleagues, receiving organisational support, and dealing with a higher number of trauma cases. Several themes emerged from the qualitative interviews including: ED Characteristics: Dual Impact on STS, Emotional Resonance and Vulnerability, Personal Life Stressors, The Ability to Cope, and Social Support. Conclusion and implications for practice Future strategies and interventions targeting STS should be prioritized to effectively manage its impact on ED nurses. It is crucial to develop targeted interventions that address the specific factors contributing to STS, as identified in this study. Additionally, these findings aim to enhance awareness among nursing administrators, managers, and supervisors about the critical factors associated with STS. This awareness is essential for accurately assessing and developing interventions that mitigate STS among nursing staff.

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Section: Materials and Designmentioning

confidence: 99%

Exposure to secondary traumatic stress and its related factors among emergency nurses in Saudi Arabia: a mixed method study

Alshammari,

Alanazi,

Kreedi

et al. 2024

BMC Nurs

View full text Add to dashboard Cite

show abstract

“…The sample size was calculated depending on number of independent variables in prediction model. The sample size was at least 10 times more than the number of independent variables (21). Assuming that each factor requires at least 10 cases for verification and the follow-up loss rate is 10%, the expected sample size should be at least 233 cases, with the formula: 21×10÷0.9=233.…”

Section: Assessment Of the Sample Sizementioning

confidence: 99%

Construction and validation of risk prediction model for deep vein thrombosis in acute exacerbations of chronic obstructive pulmonary disease based on serum angiopoietin 2 levels

He¹,

Sun²,

Zhang³

et al. 2021

Ann Palliat Med

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Background: This study aims to establish a predictive risk model for deep vein thrombosis (DVT) in patients with acute exacerbation chronic obstructive pulmonary disease (AECOPD) based on serum angiopoietin 2 (Ang-2) levels.Methods: The research sample consisted of 650 patients with AECOPD admitted to the First Affiliated Hospital of Chengdu Medical College from January 2019 to January 2021, who were subsequently divided into a modeling group and a verification group. A univariate analysis was performed on the identified risk factors for DVT in AECOPD, and the significant factors were then incorporated into a multivariate logistic regression model to screen for the independent predictors of DVT. A nomogram was constructed, and a receiver operating characteristic curve (ROC), Hosmer-Lemeshow test, decision curve, and clinical impact curve in the modeling and validation cohort were used to analyze the discrimination power, calibration, and clinical validity of the predictive risk nomogram model of AECOPD with comorbid DVT.Results: Univariate and multivariate logistic regression analyses showed that lower limb edema, BMI, diabetes, respiratory failure, D-dimer, and serum Ang-2 were risk factors for DVT in AECOPD. A nomogram model for predicting AECOPD with comorbid DVT was successfully established. The AUC values for the modeling group and the verification group were 0.844 (95% CI: 0.808-0.932) and 0.755 (95% CI: 0.679-0.861), respectively. According to the Hosmer-Lemeshow test, the P values of the nomogram in the modeling group and the verification group were 0.124 and 0.086, respectively. The decision curve and clinical impact curve suggested that most patients can benefit from this prediction model, and the predicted probability of the model was essentially the same as the actual clinical probability of DVT. Conclusions:The predictive risk nomogram model of AECOPD with comorbid DVT based on serum Ang-2 levels has good discrimination power, calibration, and clinical influence. The model is a good fit and has a high predictive value, which helps clinicians identify AECOPD patients at high risk of DTV and formulate corresponding prevention and treatment measures.

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Psychometric Properties of a Simplified Chinese Version of the Secondary Trauma Questionnaire in a Potentially Traumatized Study Sample

Cited by 2 publications

References 44 publications

Exposure to secondary traumatic stress and its related factors among emergency nurses in Saudi Arabia: a mixed method study

Exposure to secondary traumatic stress and its related factors among emergency nurses in Saudi Arabia: a mixed method study

Construction and validation of risk prediction model for deep vein thrombosis in acute exacerbations of chronic obstructive pulmonary disease based on serum angiopoietin 2 levels

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