Reliability and factor structure of the Hospital Anxiety and Depression Scale in a polytrauma clinic

Boxley, Laura; Flaherty, Jennifer M.; Spencer, Robert J.; Drag, Lauren L.; Pangilinan, Percival H.; Bieliauskas, Linas A.

doi:10.1682/jrrd.2015.05.0088

Cited by 17 publications

(12 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The HADS is a frequently used self-rating scale, comprised of subscales of anxiety and depression, developed to assess psychological distress in non-psychiatric patients. It is attractive to clinicians and researchers who need a rapid, efficient assessment [43] and has demonstrated satisfactory psychometric properties in assessing the symptom severity and caseness of anxiety disorders and depression in both somatic, psychiatric and primary care patients; in the general population as well as in different groups, including primary care patients, cognitively intact nursing home patients, and cancer inpatients [44][45][46][47][48][49][50]. Internal consistency was high in the present sample (Cronbach's α = 0.81).…”

Section: Methodsmentioning

confidence: 84%

Artificial neural networks for predicting social comparison effects among female Instagram users

Jabłońska

Zajdel

2020

PLoS ONE

View full text Add to dashboard Cite

Systematic exposure to social media causes social comparisons, especially among women who compare their image to others; they are particularly vulnerable to mood decrease, selfobjectification, body concerns, and lower perception of themselves. This study first investigates the possible links between life satisfaction, self-esteem, anxiety, depression, and the intensity of Instagram use with a social comparison model. In the study, 974 women age 18-49 who were Instagram users voluntarily participated, completing a questionnaire. The results suggest associations between the analyzed psychological data and social comparison types. Then, artificial neural networks models were implemented to predict the type of such comparison (positive, negative, equal) based on the aforementioned psychological traits. The models were able to properly predict between 71% and 82% of cases. As human behavior analysis has been a subject of study in various fields of science, this paper contributes towards understanding the role of artificial intelligence methods for analyzing behavioral data in psychology.

show abstract

Section: Methodsmentioning

confidence: 84%

Artificial neural networks for predicting social comparison effects among female Instagram users

Jabłońska

Zajdel

2020

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Furthermore, it is difficult to distinguish anxiety from depression as they are commonly comorbid and have overlapping symptoms (69). Also, factor analyses showed that anxiety and depression subscales often yield highly correlated assessments (15, 56, 70) and that the correlation was indispensable even in a bifactor model (21).…”

Section: Discussionmentioning

confidence: 99%

Psychometric Properties and Factor Structure of the Chinese Version of the Hospital Anxiety and Depression Scale in People Living With HIV

et al. 2019

View full text Add to dashboard Cite

The population of people living with HIV (PLWH) is growing in number and usually results in mental health problems that impact their quality of life. Therefore, valid instruments and screening methods for psychological disorders are of great significance. The Hospital Anxiety and Depression Scale (HADS) reveals good psychometric properties, but shows ambiguous results in factor structure. This study aims to evaluate psychometric properties in terms of the internal reliability and structure validity of the Chinese version of the HADS (C-HADS) in a large sample of PLWH in China. The C-HADS was administered to 4,102 HIV-infected adults at an HIV clinic in China. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to examine the factor structure. Measurement invariance was assessed across gender and course of infection. Internal reliability was also assessed. A bifactor model with anomalous loadings of items 7, 8, and 10 fits the data best and holds measurement invariance across gender and course of infection. Internal reliability was good with all Cronbach’s alphas > 0.70 and Spearman’s ρ between 0.30 and 0.70. The C-HADS has good psychometric properties in terms of internal reliability and structure validity of a bifactor model. The C-HADS is recommended to be used as a total scale that measures general psychological distress, instead of anxiety and depression separately, when applied to PLWH. Further studies are needed to evaluate criterion validity, the cutoff score, and the effect of wording and scoring of the HADS.

show abstract

“…The HADS produces separate total scores for anxiety and depression (scores range from 0 to 21), with higher scores indicating greater levels of anxiety or depression; scores of 5 (depression) and 7 (anxiety) or greater are considered the cut-offs for clinical screening (Singer et al, 2009). The validity (Bjelland et al, 2002) and reliability (Boxley et al, 2016) of this measure has been demonstrated.…”

Section: Anxiety and Depressionmentioning

confidence: 99%

Traumatic Stress, Attachment Style, and Health Outcomes in Cardiac Rehabilitation Patients

et al. 2020

View full text Add to dashboard Cite

Objective: Research on psychosocial risk factors in cardiovascular disease (CVD) has identified traumatic stress and attachment style as independent risk factors for the development of CVD and poor prognosis for those with established CVD. Exploring the interrelationships between these variables will inform psychosocial risk factor modeling and potential avenues for intervention. Therefore, the hypothesis that attachment style is related to health outcomes among CR patients and that traumatic stress mediates this relationship was tested.Methods: Patients in a cardiac rehabilitation program (n = 201) completed validated self-report measures of traumatic stress and attachment style at baseline (program intake). Health outcomes were assessed at baseline and 3 months, including anxiety, depression, quality of life, fasting blood glucose, glycated hemoglobin (HbA1c), and cholesterol (HDL ratio). Multivariate structural equation modeling was used to fit the data.Results: Of the 201 participants, 42 (21%) had trauma scores indicating the probable presence of posttraumatic stress disorder. Via greater levels of traumatic stress, greater attachment anxiety at baseline was indirectly related to greater anxiety, depression, fasting blood glucose, and HbA1c, and poorer physical and mental quality of life. There were no significant indirect effects on HDL ratios. Conclusion:Greater attachment anxiety predicted greater traumatic stress; this, in turn, predicted poorer health outcomes. Screening and treatment for these constructs in CVD patients is warranted.

show abstract

Reliability and factor structure of the Hospital Anxiety and Depression Scale in a polytrauma clinic

Cited by 17 publications

References 42 publications

Artificial neural networks for predicting social comparison effects among female Instagram users

Artificial neural networks for predicting social comparison effects among female Instagram users

Psychometric Properties and Factor Structure of the Chinese Version of the Hospital Anxiety and Depression Scale in People Living With HIV

Traumatic Stress, Attachment Style, and Health Outcomes in Cardiac Rehabilitation Patients

Contact Info

Product

Resources

About