Early Symptom Measurement of Post‐Stroke Depression: Development and validation of a new short version

Abstract

Aims The aim of this study was to develop and test the psychometric properties of the Early Symptom Measurement of Post‐Stroke Depression‐Short Form (ESMPSD‐SF). Background The ESMPSD is a specific measurement tool designed to detect early depressive symptoms in acute stroke patients, but it is too long for use in busy clinical settings. Design A psychometric study was conducted. Methods Five hundred and twenty‐one post‐stroke patients completed two questionnaires, the demographic and the ESMPSD questionnaire, over a period of 10 months, from July 2016–April 2017. The item reduction process was used to reduce the number of items in the ESMPSD questionnaire and consisted of item analysis, exploratory, and confirmatory factor analysis. Results The item reduction process resulted in a 12‐item short version questionnaire with evidence of acceptable construct validity and internal reliability. Four factors explaining high total variance were extracted: “low,” “guilt,” “emotional,” and “wakefulness”. Estimates of all confirmatory model fit indices met the standard criteria. All standardized factor loading estimates of the 12 items met the standard criteria and the variances explained by the items were acceptable. Moreover, internal reliability estimates of the 12‐item questionnaire were acceptable, and the corrected item‐total correlation and item‐subscale correlation also demonstrated evidence of acceptable reliability of the short form questionnaire. Conclusions The ESMPSD‐SF demonstrates evidence of acceptable reliability and validity to screen early depressive symptoms in acute stroke patients in busy clinical settings.

Development and validation of the Health Education Adherence Scale for Stroke Patients: a cross-sectional study

“…The final CFA yielded a four-factor structure for the 20-item HEAS-SP with good model fit indexes. The three item reduction process has been adopted by other researchers and was proven to be a rigorous process for item selection [ 23 , 32 , 33 ].…”

“…The item analysis included four statistical methods (critical ratio, correlation, Cronbach’s α, and factor analysis) with a series of five indicators: critical ratio, item-total correlation, corrected item-total correlation, Cronbach’s α when an item was deleted, and factor loadings. The criteria for retaining items were as follows: critical ratio ≥ 3.0, item-total correlations and corrected item-total correlations ≥ 0.40, a decrease in the Cronbach’s α value when an item was deleted, and factor loadings ≥ 0.45 [ 23 ]. Items were considered for deletion if they failed to meet three or more item analysis indicators.…”

“…Varimax rotation is suggested when items are supposed to be independent. Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) index were used to confirm the suitability of the sample for EFA, and the KMO greater than 0.60 indicated its suitability for factor analysis [ 23 ]. Items with significant factor loadings that were equal to or greater than 0.45 were considered for retention; otherwise, they were deleted [ 24 ].Factors with eigenvalues˃1 constituted the scale’s factor structure, and factor numbers were further confirmed with a scree plot [ 23 , 25 ].…”

“…Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) index were used to confirm the suitability of the sample for EFA, and the KMO greater than 0.60 indicated its suitability for factor analysis [ 23 ]. Items with significant factor loadings that were equal to or greater than 0.45 were considered for retention; otherwise, they were deleted [ 24 ].Factors with eigenvalues˃1 constituted the scale’s factor structure, and factor numbers were further confirmed with a scree plot [ 23 , 25 ]. Each selected individual factor should explain at least 5% of the total variance in health education adherence, and all the selected factors should together explain at least 60% of the variance [ 23 ].…”

Clinical Risk Factors that Predict Functional Recovery in Ischemic Stroke Patients with Pre-Stroke Depression

“…While post-stroke depression is a common occurrence and linked with poor outcome [16][17][18][19], the effect of pre-stroke depression on treatment outcome in ischemic stroke patients is not well understood. Pre-stroke depression may be associated with abnormal modification of risk factors in ischemic stroke [20,21], and may affect functional ambulatory outcome following rtPA.…”