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Evaluation of a tool to categorize patients by reading literacy and computer skill to facilitate the computer-administered patient interview.

Publication ,  Journal Article
Lobach, DF; Hasselblad, V; Wildemuth, BM
Published in: AMIA Annu Symp Proc
2003

Past efforts to collect clinical information directly from patients using computers have had limited utility because these efforts required users to be literate and facile with the computerized information collecting system. In this paper we describe the creation and use of a computer-based tool designed to assess a user's reading literacy and computer skill for the purpose of adapting the human-computer interface to fit the identified skill levels of the user. The tool is constructed from a regression model based on 4 questions that we identified in a laboratory study to be highly predictive of reading literacy and 2 questions predictive of computer skill. When used in 2 diverse clinical practices the tool categorized low literacy users so that they received appropriate support to enter data through the computer, enabling them to perform as well as high literacy users. Confirmation of the performance of the tool with a validated reading assessment instrument showed a statistically significant difference (p=0.0025) between the two levels of reading literacy defined by the tool. Our assessment tool can be administered through a computer in less than two minutes without requiring any special training or expertise making it useful for rapidly determining users' aptitudes.

Duke Scholars

Published In

AMIA Annu Symp Proc

EISSN

1942-597X

Publication Date

2003

Volume

2003

Start / End Page

391 / 395

Location

United States

Related Subject Headings

  • Reading
  • Linear Models
  • Interviews as Topic
  • Humans
  • Educational Status
  • Computer Literacy
 

Citation

APA
Chicago
ICMJE
MLA
NLM

Published In

AMIA Annu Symp Proc

EISSN

1942-597X

Publication Date

2003

Volume

2003

Start / End Page

391 / 395

Location

United States

Related Subject Headings

  • Reading
  • Linear Models
  • Interviews as Topic
  • Humans
  • Educational Status
  • Computer Literacy