PHLT 8032 Week 9 APA Results Tables Example

Results Tables in APA Style for a Composite County Survey: Respondent Characteristics by Insurance Status and a Summary of the Course's Two Comparisons, With the Prose That Introduces Each Table

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Walden University

PHLT 8032: SPSS Revealed

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Results Tables in APA Style for a Composite County Survey: Respondent Characteristics by Insurance Status and a Summary of the Course's Two Comparisons, With the Prose That Introduces Each Table

Purpose of This Section

This section presents the respondents and the course's two main comparisons in two tables formatted to APA Style, with the text a results section would carry around them. Table 1 describes respondents by insurance status, the grouping used in the Week 7 comparison. Table 2 brings together the Mann-Whitney comparison of poor mental health days and the association between income and self-rated health from Week 8. Both tables were rebuilt in the word processor from SPSS output rather than pasted from the Viewer, since exported tables carry default titles, footnote markers and gridlines that APA Style does not use (American Psychological Association [APA], 2020). The figures are unweighted and come from the cleaned composite extract.

Introducing Table 1

Table 1 compares the 1,622 insured and 213 uninsured respondents on age group, sex, district, smoking status, income and weekly physical activity. Ten respondents who did not report insurance status are omitted from the table but remain in the analytic file. The comparison matters because any difference between the groups in Week 7 could reflect these characteristics rather than insurance itself. The uninsured group is younger: 62.4% are under 50, compared with 41.7% of insured respondents, and only 9.9% are 65 or older, which fits the near-universal Medicare coverage at that age. Smoking among the uninsured runs at about double the insured rate, and the share with household income under $25,000 is well over double. Their median weekly activity is lower, although the interquartile ranges overlap widely. District shares are similar in the two groups.

Table 1

Characteristics of Respondents by Health Insurance Status

Note. Figures are unweighted counts with valid percentages unless stated. Percentages for smoking and income use respondents with a valid answer (smoking: 1,616 insured, 212 uninsured; income: 1,485 insured, 188 uninsured). Mdn = median; IQR = interquartile range. Ten respondents missing insurance status are excluded. Source: composite teaching survey.

Introducing Table 2

Table 2 summarizes the two comparisons carried out earlier in the course, one row each, with the test, the number of respondents, the statistic, the p-value and an effect size. The first row shows a small but clear tendency for the uninsured to count more bad mental health days. Higher income brackets went with more favorable self-rated health, a modest association. Neither result is adjusted for the differences shown in Table 1, a limit discussed below.

Table 2

Summary of Comparisons

Note. Unweighted. Self-rated health is coded 1 (excellent) to 5 (poor), so the negative coefficient indicates more favorable ratings at higher income. For the Mann-Whitney test, r is |z| divided by the square root of N.

Formatting Choices

Both tables follow the APA layout. The table number appears in bold above an italic title in title case. Only horizontal rules are used: one above and one below the column headings and one at the foot, with no vertical lines and no shading. Statistical symbols such as U, z, N and r are italic, while abbreviations that are not symbols, such as IQR, are not. Percentages carry one decimal place and are given in parentheses after counts so that the reader sees both. Each category row names its variable and its statistic, so a reader scanning one line never has to look upward for context. In SPSS output, the corresponding figures come from three procedures, Crosstabs, Explore and the Legacy Dialogs nonparametric test, each with its own layout; rebuilding the tables brings them into one consistent form.

Choices About Content

Table 1 describes rather than tests. Some sections ask for a column of p-values comparing insured and uninsured respondents on each row; this table omits one because a characteristics table is meant to describe who the groups are, and the STROBE guidance for observational studies recommends descriptive characteristics without significance tests for this purpose (von Elm et al., 2007). The prose identifies the differences that matter for interpreting Table 2. Table 2 reports exact p-values except where they fall below .001, following APA guidance, and gives effect sizes because a p-value alone says nothing about magnitude in a sample of this size (Fritz et al., 2012).

Two tables were chosen deliberately. A separate table for each procedure would fragment the results, while one table holding both characteristics and tests would mix description with inference and become hard to read. Each table answers one question a reader would ask: who are these respondents, and what did the comparisons find.

What the Tables Mean Together

Read together, the tables suggest caution in interpreting the Week 7 comparison. Uninsured respondents differ from insured respondents in age, smoking and income, and each of those characteristics is associated with mental health in published surveillance. The difference in poor mental health days may reflect those characteristics as much as insurance status. Table 2's income result also bears on this, since income is associated with self-rated health and the uninsured are concentrated in the lowest bracket. Adjusted analyses are outside the scope of this course, and the final report's limits section will say so explicitly.

References

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: Current use, calculations, and interpretation. Journal of Experimental Psychology: General, 141(1), 2-18. https://doi.org/10.1037/a0024338

von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gotzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. The Lancet, 370(9596), 1453-1457. https://doi.org/10.1016/S0140-6736(07)61602-X