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Psychometric evaluation of the post‐discharge surgical recovery scale
Author(s) -
Berg Katarina,
Idvall Ewa,
Nilsson Ulrica,
Årestedt Kristofer Franzén,
Unosson Mitra
Publication year - 2010
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2009.01197.x
Subject(s) - cronbach's alpha , medicine , ceiling effect , exploratory factor analysis , descriptive statistics , scale (ratio) , pearson product moment correlation coefficient , correlation , receiver operating characteristic , internal consistency , physical therapy , correlation coefficient , psychometrics , statistics , clinical psychology , mathematics , physics , alternative medicine , geometry , pathology , quantum mechanics
Rationale, aim and objectives Day surgery patients are discharged after a short period of postoperative surveillance, and reliable and valid instruments for assessment at home are needed. The aim of this study was to evaluate the psychometric properties of a Swedish version of the post‐discharge surgical recovery (PSR) scale, an instrument to monitor the patient's recovery after day surgery, in terms of data quality, internal consistency, dimensionality and responsiveness. Methods Data were collected on postoperative days 1 and 14 and included 525 patients. Data quality and internal consistency were evaluated using descriptive statistics, correlation analyses and Cronbach's α. The dimensionality of the scale was determined through an exploratory factor analysis. Responsiveness was evaluated using the standardized response mean and the area under the receiver operating characteristics curve (AUC). The correlation between change score in PSR and change score in self‐rated health was assessed using Pearson's correlation coefficient. Patients' ability to work and their self‐rated health on postoperative day 14 were used as external indicators of change. Results Six items showed floor or ceiling effects. Cronbach's coefficient α was 0.90 and the average inter‐item correlation coefficient was 0.44 after the deletion of two items. The items were closely related to each other, and a one‐factor solution was decided on. A robust ability to detect changes in recovery (standardized response mean = 1.14) was shown. The AUC for the entire scale was 0.60. When initial PSR scores were categorized into three intervals, the ability to detect improved and non‐improved patients varied (AUC 0.58–0.81). There was a strong correlation between change scores in PSR and health (0.63). Conclusions The Swedish version of the PSR scale demonstrates acceptable psychometric properties of data quality, internal consistency, dimensionality and responsiveness. In addition to previous findings, these results strengthen the PSR scale as a potential instrument of recovery at home.