活动感知恢复量表（PRAS）：编制与验证

Perceived Restorativeness for Activities Scale (PRAS): development and validation.

作者信息

Norling J C, Sibthorp Jim, Ruddell Edward

机构信息

Dept of Health, Physical Education, and Recreation, Utah State University, Logan, UT 84322-7000, USA.

出版信息

J Phys Act Health. 2008 Jan;5(1):184-95. doi: 10.1123/jpah.5.1.184.

DOI:10.1123/jpah.5.1.184

PMID:18209263

Abstract

BACKGROUND

The purpose of this study was to develop the Perceived Restorativeness for Activities Scale (PRAS) based on the conceptual framework of attention-restoration theory (ART). ART suggests that 4 latent constructs (being away, fascination, extent, and compatibility) must be present to enable a switch from voluntary (effortful, directed) attention to involuntary (effortless) attention and facilitate restored attention.

METHOD

Data were collected from 238 participants in a variety of university exercise classes. Exploratory factor analysis reduced items to a parsimonious 12-item scale. Confirmatory factor analysis tested the best fit between a 1-dimensional versus a 4-factor solution.

RESULTS

The Cronbach alpha was .925. The significant analysis (P < .001) suggested that the model with 4 distinct subscales has the best data fit (goodness-of-fit index = .94, standardized root-mean-square residual = .041, incremental-fit index = .98, expected-cross-validation index = .66, comparative-fit index = .98). Composite reliability and variance extracted were calculated for each construct represented by ART: being away, .81, .59; fascination, .79, .63; extent, .89, .78; and compatibility, .68, .42.

CONCLUSION

The 12-item, 4-factor solution of the PRAS can help researchers understand the within-individual preconceptions toward the activity experience that can influence cognitive restoration.

摘要

背景

本研究旨在基于注意力恢复理论（ART）的概念框架开发活动感知恢复量表（PRAS）。ART表明，必须存在4个潜在结构（置身事外、吸引力、程度和兼容性），才能使注意力从主动（费力、定向）转换为被动（轻松），并促进注意力恢复。

方法

从238名参加各种大学健身课程的参与者中收集数据。探索性因素分析将项目简化为一个简洁的12项量表。验证性因素分析测试了一维与四因素解决方案之间的最佳拟合。

结果

克朗巴哈系数为0.925。显著性分析（P < .001）表明，具有4个不同子量表的模型具有最佳的数据拟合度（拟合优度指数 = 0.94，标准化均方根残差 = 0.041，增量拟合指数 = 0.98，预期交叉验证指数 = 0.66，比较拟合指数 = 0.98）。计算了ART所代表的每个结构的组合信度和提取方差：置身事外，0.81，0.59；吸引力，0.79，0.63；程度，0.89，0.78；兼容性，0.68，0.42。