The Environmental Audit Screening Evaluation: Establishing Reliability and Validity of an Evidence-Based Design Tool

Current assessment tools for long-term care environments have limited generalizability or ability to be linked to specific quality outcomes. To discriminate between different care models, tools are needed to assess important elements of the environmental design. The goal of this project was to systematically evaluate the reliability and validity of the Environmental Audit Screening Evaluation (EASE) tool to better enable the identification of best models in long-term care design to maintain quality of life for persons with dementia and their caregivers.

Twenty-eight living areas (LAs) were selected from 13 sites similar in organizational/operational commitment to person-centered care but with very different LA designs. LAs were stratified into 3 categories (traditional, hybrid, and household) based primarily on architectural/interior features. Three evaluators rated each LA using the Therapeutic Environment Screening Scale (TESS-NH), Professional Environmental Assessment Protocol (PEAP), Environmental Audit Tool (EAT-HC), and EASE. One of each type of LA was reassessed approximately 1 month after the original assessment.

EASE scores were compared against the scores of 3 existing tools to evaluate its construct validity. The EAT-HC was most closely related to the EASE (r = 0.88). The PEAP and the TESS-NH were less correlated to the EASE (r = 0.82 and 0.71, respectively). Analysis of variance indicated that the EASE distinguished between traditional and home-like settings (0.016), but not hybrid LAs. Interrater and inter-occasion reliability and agreement of the EASE were consistently high.

Neither of the 2 U.S.-based existing environmental assessment tools (PEAP and TESS-NH) discriminated between the 3 models of environments. The EAT-HC was most closely aligned with the EASE and performed similarly in differentiating between the traditional and household models, but the dichotomous scoring of the EAT-HC fails to capture environmental nuances. The EASE tool is comprehensive and accounts for nuanced design differences across settings.