{
  "original_study": {
    "claim": {
      "hypothesis": "For hypertensive adults in good general health, education will not significantly reduce the probability of being under-diagnosed with hypertension.",
      "hypothesis_location": "Section 2. Theoretical framework (page 3), where the authors state that they expect 'significantly smaller (possibly zero or even negative) effects of education for generally healthy people than for unhealthy people'.",
      "statement": "The study finds that among hypertensive adults who report good general health, years of education have a small and statistically nonsignificant association with the probability of being under-diagnosed, indicating that education does not meaningfully reduce under-diagnosis in this group.",
      "statement_location": "Section 4. Disease detection results (page 5), where the authors note that for individuals in good health 'the education level does not matter at all,' and Table 2 (page 5), column 'Respondents in good health', row 'Years of Education' (marginal effect = 0.00295, standard error = 0.00206, no significance stars).",
      "study_type": "Observational"
    },

    "data": {
      "source": "Indonesian Family Life Survey (IFLS).",
      "wave_or_subset": "IFLS Wave 4 (2007-2008), restricted to adults over age 45 who were hypertensive based on survey blood pressure measurements.",
      "sample_size": "4,209 hypertensive adults (1,793 men and 2,416 women); disease-detection probit subsamples of 3,145 respondents in good general health and 1,064 respondents in poor general health.",
      "unit_of_analysis": "Individual respondent.",
      "access_details": "The IFLS is described as a publicly available dataset that has received IRB approval at RAND and in Indonesia.",
      "notes": "Hypertension status is based on nurse-measured blood pressure (average of the second and third readings), using WHO cutoffs (systolic ≥140 or diastolic ≥90). Under-diagnosed respondents are those found hypertensive in the IFLS measurements who reported never having been diagnosed with hypertension by a doctor. General health status (GHS) is self-rated on a 1-4 scale and used to split the sample into 'good' (very healthy or somewhat healthy) and 'poor' (unhealthy or somewhat unhealthy) general health groups."
    },

    "method": {
      "description": "The authors estimate probit models of hypertension under-diagnosis using IFLS data, examining how education and individual time preferences relate to the probability of being under-diagnosed, separately for respondents in good versus poor general health.",
      "steps": [
        "Identify adults (over age 45) in IFLS Wave 4 who are hypertensive based on nurse-measured blood pressure following WHO cutoffs.",
        "Classify respondents as 'under-diagnosed' if they are hypertensive in the survey measurements but report never having been diagnosed with hypertension by a doctor.",
        "Obtain self-rated general health status (GHS) and split the hypertensive sample into two groups: respondents in good general health (very healthy or somewhat healthy) and respondents in poor general health (unhealthy or somewhat unhealthy).",
        "Construct explanatory variables including years of education, household per capita expenditures, time preference, risk preference, distance to the nearest health center, age, age squared, and sex.",
        "Estimate probit models of the probability of being under-diagnosed for the full sample and separately for the good-health and poor-health subsamples, and report marginal effects.",
        "Interpret the marginal effect of years of education on under-diagnosis within the good-health subsample to assess whether education significantly affects disease detection for generally healthy hypertensive adults."
      ],
      "models": "Probit regression models of the probability of being under-diagnosed with hypertension, reporting marginal effects for the full sample and for subsamples defined by general health status.",
      "outcome_variable": "Indicator variable equal to 1 if a respondent is hypertensive based on IFLS blood pressure measurements but has not previously been diagnosed with hypertension by a doctor (i.e., under-diagnosed), conditional on being in good general health.",
      "independent_variables": "Years of formal education completed by the respondent.",
      "control_variables": "Household per capita expenditures (log PCE); time preference category; risk preference category; distance to the closest health center; age; age squared; and a female dummy indicator.",
      "tools_software": "not stated"
    },

    "results": {
      "summary": "In the subsample of hypertensive adults who report good general health, years of education have statistically nonsignificant marginal effect on the probability of being under-diagnosed.",
      "numerical_results": [
        {
          "outcome_name": "Probability of being under-diagnosed with hypertension (good general health subsample, effect of years of education)",
          "value": 0.00295,
          "unit": "marginal effect on probability of being under-diagnosed per additional year of education",
          "effect_size": "probit marginal effect = 0.00295",
          "confidence_interval": {
            "lower": "not stated",
            "upper": "not stated",
            "level": "not stated"
          },
          "p_value": "not stated (no significance stars are reported for this coefficient in Table 2, indicating nonsignificance at conventional levels).",
          "statistical_significance": 0,
          "direction": "0"
        }
      ]
    },

    "metadata": {
      "original_paper_id": "10.1016/j.socscimed.2015.11.051",
      "original_paper_title": "Education, individual time preferences, and asymptomatic disease detection",
      "original_paper_code": "not stated",
      "original_paper_data": "not stated"
    }
  }
}