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Research ArticleOriginal Research

Do Subjective Measures Improve the Ability to Identify Limited Health Literacy in a Clinical Setting?

Melody S. Goodman, Richard T. Griffey, Christopher R. Carpenter, Melvin Blanchard and Kimberly A. Kaphingst
The Journal of the American Board of Family Medicine September 2015, 28 (5) 584-594; DOI: https://doi.org/10.3122/jabfm.2015.05.150037
Melody S. Goodman
From the Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO (MSG); the Division of Emergency Medicine, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO (RTG, CRC); the Department of Medicine, Washington University School of Medicine, St. Louis, MO (MB); and the Department of Communication and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (KAK).
PhD
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Richard T. Griffey
From the Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO (MSG); the Division of Emergency Medicine, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO (RTG, CRC); the Department of Medicine, Washington University School of Medicine, St. Louis, MO (MB); and the Department of Communication and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (KAK).
MD, MPH
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Christopher R. Carpenter
From the Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO (MSG); the Division of Emergency Medicine, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO (RTG, CRC); the Department of Medicine, Washington University School of Medicine, St. Louis, MO (MB); and the Department of Communication and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (KAK).
MD, MSc
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Melvin Blanchard
From the Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO (MSG); the Division of Emergency Medicine, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO (RTG, CRC); the Department of Medicine, Washington University School of Medicine, St. Louis, MO (MB); and the Department of Communication and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (KAK).
MD
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Kimberly A. Kaphingst
From the Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO (MSG); the Division of Emergency Medicine, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO (RTG, CRC); the Department of Medicine, Washington University School of Medicine, St. Louis, MO (MB); and the Department of Communication and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (KAK).
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  • Article
  • Figures & Data
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Article Figures & Data

Tables

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    Table 1. Demographic Characteristics of Participants in the Overall, Estimation, and Validation Samples
    VariablesOverall (N = 911)Estimation (n = 456)Validation (n = 455)P value*
    n%n%n%
    Sex
        Male35338.717438.217939.3.83*
        Female55862.328261.827660.7.79*
    Education
        <High school15617.17817.17817.11.00*
        High school39543.420144.019442.6.78*
         >High school36039.517738.818340.2.79*
    Race
        White30833.815133.115734.5.80*
        Black60366.230566.929865.5.72*
    Difficulty with written information
        Always/often/sometimes25127.615120.410022.0.79*
        Rarely/never66072.430579.635578.0.60*
    Confidence in filling out medical forms
        Not at all/a little bit/somewhat34838.217939.316937.1.67*
        Quite a bit/extremely confident56361.827760.828662.9.61*
    Help reading hospital material
        Always/often/sometimes23325.612327.011024.2.63*
        Rarely/never67874.433373.034575.8.40*
    Rapid Estimation of Adult Literacy in Medicine, Revised
        Limited health literacy41845.920545.021346.8.71*
        Adequate health literacy49354.125155.024253.2.69*
    Newest Vital Sign
        Limited health literacy57863.429264.028662.9.79*
        Adequate health literacy33336.616436.016937.1.83*
    Brief Health Literacy Screen score, mean (SD)12.12.812.12.712.12.8.78†
    Age (years), mean (SD)48.51448.514.048.414.1.88†
    • Data are n (%) unless otherwise indicated.

    • ↵* Two-sample test for proportions.

    • ↵† Two-sample t test.

    • SD, standard deviation.

    • View popup
    Table 2. Logistic Regression Models Estimating Limited Health Literacy against the Rapid Estimate of Adult Literacy in Medicine, Revised
    ModelDemographics OnlySILSBHLS
    Difficulty with Written InformationConfidence Filling out Medical FormsHelp Reading Hospital Materials
    PredictorsOR95% CI*P valueOR95% CI*P valueOR95% CI*P valueOR95% CI*P valueOR95% CI*P value
    Age0.990.981.01.340.990.971.01.210.990.981.01.210.990.981.01.320.990.971.01.19
    Sex (reference = male)
        Female0.450.290.71<.010.450.280.72<.010.450.280.70<.010.470.300.74<.010.450.280.71<.01
    Race (reference = white)
        Black8.254.8913.90<.018.765.1015.06<.018.104.8013.67<.018.254.8714.00<.018.214.8313.96<.01
    Education (reference = high school)
        <High School2.571.364.84<.011.971.023.79<.012.511.334.74<.012.221.174.24.022.181.144.15.02
        >High School0.350.220.56<.010.370.230.61<.010.370.230.59<.010.350.210.56<.010.370.230.60<.01
    Difficulty with written information (SILS) (reference = rarely/never)
        Always/often/Sometimes3.141.755.65<.01
    Confidence filling out medical forms (SILS) (reference = quite a bit/extremely confident)
        Not at all/a little bit/somewhat1.350.872.12.19
    Help reading hospital materials (SILS) (reference = rarely/never)
        Always/often/sometimes1.941.183.18.01
    BHLS0.880.810.96<.01
    Goodness of fit statistics
    R20.3420.3750.3460.3570.361
    AIC505.02491.46505.27500.08498.07
    AUROC0.7940.8120.8000.8030.809
    • ↵* For 95% confidence interval (CI) values, the lower limit is set on the left and the upper limit is on the right.

    • AIC, Akaike information criterion; AUROC, area under the receiver operator characteristics curve; BHLS, Brief Health Literacy Screen; OR, odds ratio; SILS, Single Item Literacy Screener.

    • View popup
    Table 3. Logistic Regression Models Estimating Limited Health Literacy against the Newest Vital Sign
    ModelDemographics OnlySILSBHLS
    Difficulty with Written InformationConfidence Filling out Medical FormsHelp Reading Hospital Materials
    PredictorsOR95% CI*P valueOR95% CI*P valueOR95% CI*P valueOR95% CI*P valueOR95% CI*P value
    Age1.021.011.04<.011.021.011.04.011.021.011.04<.011.021.011.04<.011.021.011.04.01
    Sex (reference = male)
        Female0.930.601.44.750.950.611.48.830.920.601.43.720.960.621.49.850.940.061.46.79
    Race (reference = white)
        Black3.512.275.43<.013.502.255.45<.013.412.205.28<.013.412.205.29<.013.332.145.18<.01
    Education (reference = high school)
        <High school2.061.034.130.041.680.823.44.151.970.983.97.061.840.973.73.061.750.863.57.12
        >High school0.400.250.62<.010.430.270.67<.010.420.270.67<.010.410.260.64<.010.440.280.67<.01
    Difficulty with written information (SILS) (reference = rarely/never)
        Always/often/sometimes2.861.505.46<.01
    Confidence filling out medical forms (SILS) (reference = quite a bit/extremely confident)
        Not at all/a little bit/ somewhat1.611.032.52.04
    Help reading hospital materials (SILS) (reference = rarely/never)
        Always/often/sometimes1.801.083.00.02
    BHLS0.850.78.94<.01
    Goodness of fit statistics
    R20.2030.2320.2140.2160.235
    AIC534.75525.27532.29531.46524.15
    AUROC0.7340.7490.7380.7410.749
    • ↵* For 95% confidence interval (CI) values, the lower limit is set on the left and the upper limit is on the right.

    • AIC, Akaike information criterion; AUROC, area under the receiver operator characteristics curve; BHLS, Brief Health Literacy Screen; OR, odds ratio; SILS, Single Item Literacy Screener.

    • View popup
    Table 4. Comparison of Single-Item Literacy Screener/Brief Health Literacy Screen (SILS/BHLS) Model Identification of Limited Health Literacy With Objective Health Literacy Measures (Rapid Estimate of Adult Literacy in Medicine, Revised, and Newest Vital Sign*)
    Models*Limited Health Literacy n (%)Adequate Health Literacy n (%)Kappa95% CIMisclassified (%)SensitivitySpecificityPositive Likelihood RatioNegative Likelihood Ratio
    Difficulty with written information (SILS) and demographics model*
        REALM-R limited health literacy13262.08138.00.430.35–0.5128.10.620.813.260.47
        REALM-R adequate health literacy4719.419580.6
        NVS limited health literacy23381.55318.50.490.41–0.5723.70.820.682.560.26
        NVS adequate health literacy5532.511467.5
    Brief Health Literacy Screen and demographics model*
        REALM-R limited health literacy17180.34219.70.420.34–0.5029.50.800.622.110.32
        REALM-R adequate health literacy9238.015062.0
        NVS limited health literacy22177.36522.70.480.40–0.5624.80.770.722.750.32
        NVS adequate health literacy4828.412171.6
    • ↵* Models control for age, sex, race, and education.

    • NVS, Newest Vital Sign; REALM-R, Rapid Estimate of Health Literacy in Medicine, Revised.

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The Journal of the American Board of Family     Medicine: 28 (5)
The Journal of the American Board of Family Medicine
Vol. 28, Issue 5
September-October 2015
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Do Subjective Measures Improve the Ability to Identify Limited Health Literacy in a Clinical Setting?
Melody S. Goodman, Richard T. Griffey, Christopher R. Carpenter, Melvin Blanchard, Kimberly A. Kaphingst
The Journal of the American Board of Family Medicine Sep 2015, 28 (5) 584-594; DOI: 10.3122/jabfm.2015.05.150037

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Do Subjective Measures Improve the Ability to Identify Limited Health Literacy in a Clinical Setting?
Melody S. Goodman, Richard T. Griffey, Christopher R. Carpenter, Melvin Blanchard, Kimberly A. Kaphingst
The Journal of the American Board of Family Medicine Sep 2015, 28 (5) 584-594; DOI: 10.3122/jabfm.2015.05.150037
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