Assessing the internal consistency and temporal stability of advance directives generated by an interactive, online computer program

Jane R. Schubart, Fabian Camacho, Michael Green, Kimberly A. Rush, Benjamin Levi

Research output: Contribution to journalArticle

Abstract

Objective Evaluate the internal consistency and temporal stability of advance directives (ADs) generated by an interactive, online computer program. Methods 33 participants completed the program at three visits, 2 weeks apart. Agreement rates were calculated for the General Wishes component of the AD. The test-retest method was used to examine the temporal stability of the Specific Wish for Treatment component which contains five clinical scenarios. Results General Wishes remained stable with 94% selecting the identical response at each visit. For the Specific Wish for Treatment scale, significant variations in test-retest correlations existed (ie, ρ=0.32-0.78, between time points 1 and 2); however within scenario, correlations did not significantly vary between time points. Temporal stability was lower in the Specific Wish for Treatment scale compared with General Wishes (average ρ=0.59, between time points 1 and 2; and ρ=0.75, between time points 2 and 3). Conclusions ADs generated by an online decision aid demonstrate good temporal stability, with highest stability for General Wishes and moderate stability for Specific Wish for Treatment regarding medical treatments in specific clinical scenarios. Internal consistency for wish for treatment across all time points and scenarios was high (Cronbach α>0.90).

Original languageEnglish (US)
Pages (from-to)67-72
Number of pages6
JournalBMJ Supportive and Palliative Care
Volume7
Issue number1
DOIs
StatePublished - Mar 1 2017

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Advance Directives
Software
Decision Support Techniques

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Oncology(nursing)
  • Medical–Surgical

Cite this

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title = "Assessing the internal consistency and temporal stability of advance directives generated by an interactive, online computer program",
abstract = "Objective Evaluate the internal consistency and temporal stability of advance directives (ADs) generated by an interactive, online computer program. Methods 33 participants completed the program at three visits, 2 weeks apart. Agreement rates were calculated for the General Wishes component of the AD. The test-retest method was used to examine the temporal stability of the Specific Wish for Treatment component which contains five clinical scenarios. Results General Wishes remained stable with 94{\%} selecting the identical response at each visit. For the Specific Wish for Treatment scale, significant variations in test-retest correlations existed (ie, ρ=0.32-0.78, between time points 1 and 2); however within scenario, correlations did not significantly vary between time points. Temporal stability was lower in the Specific Wish for Treatment scale compared with General Wishes (average ρ=0.59, between time points 1 and 2; and ρ=0.75, between time points 2 and 3). Conclusions ADs generated by an online decision aid demonstrate good temporal stability, with highest stability for General Wishes and moderate stability for Specific Wish for Treatment regarding medical treatments in specific clinical scenarios. Internal consistency for wish for treatment across all time points and scenarios was high (Cronbach α>0.90).",
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AU - Green, Michael

AU - Rush, Kimberly A.

AU - Levi, Benjamin

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N2 - Objective Evaluate the internal consistency and temporal stability of advance directives (ADs) generated by an interactive, online computer program. Methods 33 participants completed the program at three visits, 2 weeks apart. Agreement rates were calculated for the General Wishes component of the AD. The test-retest method was used to examine the temporal stability of the Specific Wish for Treatment component which contains five clinical scenarios. Results General Wishes remained stable with 94% selecting the identical response at each visit. For the Specific Wish for Treatment scale, significant variations in test-retest correlations existed (ie, ρ=0.32-0.78, between time points 1 and 2); however within scenario, correlations did not significantly vary between time points. Temporal stability was lower in the Specific Wish for Treatment scale compared with General Wishes (average ρ=0.59, between time points 1 and 2; and ρ=0.75, between time points 2 and 3). Conclusions ADs generated by an online decision aid demonstrate good temporal stability, with highest stability for General Wishes and moderate stability for Specific Wish for Treatment regarding medical treatments in specific clinical scenarios. Internal consistency for wish for treatment across all time points and scenarios was high (Cronbach α>0.90).

AB - Objective Evaluate the internal consistency and temporal stability of advance directives (ADs) generated by an interactive, online computer program. Methods 33 participants completed the program at three visits, 2 weeks apart. Agreement rates were calculated for the General Wishes component of the AD. The test-retest method was used to examine the temporal stability of the Specific Wish for Treatment component which contains five clinical scenarios. Results General Wishes remained stable with 94% selecting the identical response at each visit. For the Specific Wish for Treatment scale, significant variations in test-retest correlations existed (ie, ρ=0.32-0.78, between time points 1 and 2); however within scenario, correlations did not significantly vary between time points. Temporal stability was lower in the Specific Wish for Treatment scale compared with General Wishes (average ρ=0.59, between time points 1 and 2; and ρ=0.75, between time points 2 and 3). Conclusions ADs generated by an online decision aid demonstrate good temporal stability, with highest stability for General Wishes and moderate stability for Specific Wish for Treatment regarding medical treatments in specific clinical scenarios. Internal consistency for wish for treatment across all time points and scenarios was high (Cronbach α>0.90).

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