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Inform Health Soc Care. 2016;41(3):211-29. doi: 10.3109/17538157.2015.1008490. Epub 2015 Aug 13.

Predictors affecting personal health information management skills.

Author information

1
a Division of Biomedical Informatics , College of Public Health & School of Library and Information Science, College of Communication and Information, University of Kentucky , Lexington , KY , USA .
2
b Department of Epidemiology , Sanders-Brown Center on Aging, University of Kentucky , Lexington , KY , USA.

Abstract

OBJECTIVES:

This study investigated major factors affecting personal health records (PHRs) management skills associated with survey respondents' health information management related activities.

METHODS:

A self-report survey was used to assess individuals' personal characteristics, health knowledge, PHR skills, and activities. Factors underlying respondents' current PHR-related activities were derived using principal component analysis (PCA). Scale scores were calculated based on the results of the PCA, and hierarchical linear regression analyses were used to identify respondent characteristics associated with the scale scores. Internal consistency of the derived scale scores was assessed with Cronbach's α.

RESULTS:

Among personal health information activities surveyed (N = 578 respondents), the four extracted factors were subsequently grouped and labeled as: collecting skills (Cronbach's α = 0.906), searching skills (Cronbach's α = 0.837), sharing skills (Cronbach's α = 0.763), and implementing skills (Cronbach's α = 0.908). In the hierarchical regression analyses, education and computer knowledge significantly increased the explanatory power of the models. Health knowledge (β = 0.25, p < 0.001) emerged as a positive predictor of PHR collecting skills.

CONCLUSIONS:

This study confirmed that PHR training and learning should consider a full spectrum of information management skills including collection, utilization and distribution to support patients' care and prevention continua.

KEYWORDS:

Hierarchical regression analysis, personal health records, personal information management, principal component analysis

PMID:
26268728
PMCID:
PMC4845745
[Available on 2017-09-01]
DOI:
10.3109/17538157.2015.1008490
[Indexed for MEDLINE]
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