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Analysis of ehealth search perspectives among female college students in the health professions using Q methodology.

Stellefson M, Hanik B, Chaney JD, Tennant B - J. Med. Internet Res. (2012)

Bottom Line: The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information.Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task.These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Digital Health and Wellness, Department of Health Education and Behavior, University of Florida, Gainesville, FL, USA. mstellefson@ufl.edu

ABSTRACT

Background: The current "Millennial Generation" of college students majoring in the health professions has unprecedented access to the Internet. Although some research has been initiated among medical professionals to investigate the cognitive basis for health information searches on the Internet, little is known about Internet search practices among health and medical professional students.

Objective: To systematically identify health professional college student perspectives of personal eHealth search practices.

Methods: Q methodology was used to examine subjective perspectives regarding personal eHealth search practices among allied health students majoring in a health education degree program. Thirteen (n = 13) undergraduate students were interviewed about their attitudes and experiences conducting eHealth searches. From the interviews, 36 statements were used in a structured ranking task to identify clusters and determine which specific perceptions of eHealth search practices discriminated students into different groups. Scores on an objective measure of eHealth literacy were used to help categorize participant perspectives.

Results: Q-technique factor analysis of the rankings identified 3 clusters of respondents with differing views on eHealth searches that generally coincided with participants' objective eHealth literacy scores. The proficient resourceful students (pattern/structure coefficient range 0.56-0.80) described themselves as using multiple resources to obtain eHealth information, as opposed to simply relying on Internet search engines. The intermediate reluctant students (pattern/structure coefficient range 0.75-0.90) reported engaging only Internet search engines to locate eHealth information, citing undeveloped evaluation skills when considering sources of information located on the Internet. Both groups of advanced students reported not knowing how to use Boolean operators to conduct Internet health searches. The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information. Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task.

Conclusions: Subjective perspectives of eHealth search practices differed among students possessing different levels of eHealth literacy. These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet.

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Final distribution of Q sort procedure (Q sort table).
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figure1: Final distribution of Q sort procedure (Q sort table).

Mentions: These representative statements were then rank-ordered by the study participants in what is known as a Q sort task. To complete the Q sort, participants were instructed to order the statements according to which statements described them the most and which described them the least when considering their attitudes and experiences conducting eHealth searches. This encouraged participants to sort the cards such that the completed sort would have the shape of a triangle. Columns at both extremes of the triangle possess one card and each column incrementally closer to the center possesses an additional card, with the middlemost column containing 6 cards (thus resembling a quasi-normal distribution). Each participant’s Q sort consisted of 11 columns. The leftmost column was assigned a score of –5 (least descriptive) and the rightmost column was assigned a score of +5 (most descriptive). Figure 1 provides a visual illustration of the quasi-normal distribution of each participant’s Q sort.


Analysis of ehealth search perspectives among female college students in the health professions using Q methodology.

Stellefson M, Hanik B, Chaney JD, Tennant B - J. Med. Internet Res. (2012)

Final distribution of Q sort procedure (Q sort table).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3376519&req=5

figure1: Final distribution of Q sort procedure (Q sort table).
Mentions: These representative statements were then rank-ordered by the study participants in what is known as a Q sort task. To complete the Q sort, participants were instructed to order the statements according to which statements described them the most and which described them the least when considering their attitudes and experiences conducting eHealth searches. This encouraged participants to sort the cards such that the completed sort would have the shape of a triangle. Columns at both extremes of the triangle possess one card and each column incrementally closer to the center possesses an additional card, with the middlemost column containing 6 cards (thus resembling a quasi-normal distribution). Each participant’s Q sort consisted of 11 columns. The leftmost column was assigned a score of –5 (least descriptive) and the rightmost column was assigned a score of +5 (most descriptive). Figure 1 provides a visual illustration of the quasi-normal distribution of each participant’s Q sort.

Bottom Line: The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information.Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task.These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Digital Health and Wellness, Department of Health Education and Behavior, University of Florida, Gainesville, FL, USA. mstellefson@ufl.edu

ABSTRACT

Background: The current "Millennial Generation" of college students majoring in the health professions has unprecedented access to the Internet. Although some research has been initiated among medical professionals to investigate the cognitive basis for health information searches on the Internet, little is known about Internet search practices among health and medical professional students.

Objective: To systematically identify health professional college student perspectives of personal eHealth search practices.

Methods: Q methodology was used to examine subjective perspectives regarding personal eHealth search practices among allied health students majoring in a health education degree program. Thirteen (n = 13) undergraduate students were interviewed about their attitudes and experiences conducting eHealth searches. From the interviews, 36 statements were used in a structured ranking task to identify clusters and determine which specific perceptions of eHealth search practices discriminated students into different groups. Scores on an objective measure of eHealth literacy were used to help categorize participant perspectives.

Results: Q-technique factor analysis of the rankings identified 3 clusters of respondents with differing views on eHealth searches that generally coincided with participants' objective eHealth literacy scores. The proficient resourceful students (pattern/structure coefficient range 0.56-0.80) described themselves as using multiple resources to obtain eHealth information, as opposed to simply relying on Internet search engines. The intermediate reluctant students (pattern/structure coefficient range 0.75-0.90) reported engaging only Internet search engines to locate eHealth information, citing undeveloped evaluation skills when considering sources of information located on the Internet. Both groups of advanced students reported not knowing how to use Boolean operators to conduct Internet health searches. The basic hubristic students (pattern/structure coefficient range 0.54-0.76) described themselves as independent procrastinators when searching for eHealth information. Interestingly, basic hubristic students represented the only cluster of participants to describe themselves as (1) having received instruction on using the Internet to conduct eHealth searches, and (2) possessing relative confidence when completing a search task.

Conclusions: Subjective perspectives of eHealth search practices differed among students possessing different levels of eHealth literacy. These multiple perspectives present both challenges and opportunities for empowering college students in the health professions to use the Internet to obtain and appraise evidence-based health information using the Internet.

Show MeSH
Related in: MedlinePlus