Assessment and screening of panic disorder in cancer patients: performance of the PHQ-PD.

J Psychosom Res

Department of Neurosciences and Behavior, Medical School of Ribeirão Preto, University of São Paulo, Brazil; Barretos School of Health Sciences, Dr. Paulo Prata, Barretos, Brazil.

Published: January 2015

Objective: This study's objective was to promote the transcultural adaptation of the Patient Health Questionnaire-Panic Disorder Module (PHQ-PD) for Brazilian Portuguese and to evaluate the discriminative validity of this scale in detecting PD among cancer patients.

Methods: Adult cancer outpatients (n=400) from a specialized cancer hospital (61.50% female; 68.40% married; 56% incomplete elementary education or elementary school as the highest educational level) were assessed with the Structured Clinical Interview for DSM-IV and PHQ-PD. Using receiver operating characteristic (ROC) analyses, we determined the sensitivity and specificity values for the original PD algorithm and the PD screening.

Results: The prevalence of PD in cancer patients (8.75%) was higher than the prevalence of PD for the general population. The original PD algorithm demonstrated an accuracy of 0.66, sensitivity of 0.31 and specificity of 0.94. The PD screening question in the PHQ-PD had a sensitivity of 0.66 and a specificity of 0.75 (accuracy=0.80).

Conclusion: PD screening questions in the PHQ-PD may be useful for identifying cancer patients with PD because of the high prevalence of PD in this population and because the questionnaire's sensitivity is greater than that of the original PD algorithm. Nevertheless, researchers and clinical practitioners should consider the original PD algorithm (five items) in the PHQ-PD when they investigate PD in patients because of the algorithm's high specificity. Individuals who are found to be positive for PD on screening should be referred for assessment and a thorough psychiatric interview that focuses on the differential diagnosis of an anxiety disorder relating to cancer.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jpsychores.2014.09.001DOI Listing

Publication Analysis

Top Keywords

original algorithm
16
cancer patients
12
cancer
7
phq-pd
6
assessment screening
4
screening panic
4
panic disorder
4
disorder cancer
4
patients
4
patients performance
4

Similar Publications

Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation.

View Article and Find Full Text PDF

Flexible and modular latent transition analysis-A tutorial using R.

PLoS One

January 2025

National Institute of Public Health, University of Southern Denmark, Copenhagen K, Denmark.

Latent transition analysis (LTA) is a useful statistical modelling approach for describe transitions between latent classes over time. LTA may be characterized in terms of prevalence at each time point and through transition probabilities over time. Investigating predictors of these transitions is often of key interest.

View Article and Find Full Text PDF

Purpose: In this study, we investigated the performance of deep learning (DL) models to differentiate between normal and glaucomatous visual fields (VFs) and classify glaucoma from early to the advanced stage to observe if the DL model can stage glaucoma as Mills criteria using only the pattern deviation (PD) plots. The DL model results were compared with a machine learning (ML) classifier trained on conventional VF parameters.

Methods: A total of 265 PD plots and 265 numerical datasets of Humphrey 24-2 VF images were collected from 119 normal and 146 glaucomatous eyes to train the DL models to classify the images into four groups: normal, early glaucoma, moderate glaucoma, and advanced glaucoma.

View Article and Find Full Text PDF

In this work, bridge network model with Rayleigh distribution lifetimes is used. Two main techniques are calculated to upgrade this model: reduction and redundancy techniques. In order to compare the effectiveness of the various approaches, the survival function, the mean time to failure and gamma-fractiles for the original and upgraded model are calculated.

View Article and Find Full Text PDF

Quality-Diversity (QD) methods are algorithms that aim to generate a set of diverse and highperforming solutions to a given problem. Originally developed for evolutionary robotics, most QD studies are conducted on a limited set of domains'mainly applied to locomotion, where the fitness and the behavior signal are dense. Grasping is a crucial task for manipulation in robotics.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!