2.1.1 Participants
The study included 205 participants recruited via Amazon Mechanical Turk (MTurk). Participants received $2.00 as compensation and one participant was excluded because of patterned responses to the survey. Of the remaining 204 participants, 112 were male and 92 were female (no participant selected “Other”). Participants ranged in age from 18 to 71 (Mage = 31.96,
SD = 8.58). Of these participants, 20 had a high school diploma or GED equivalent, 20 had an
Associate degree, 53 completed some college, 81 had a Bachelor’s degree, and 30 had a Master’s or Doctoral degree. See Table 1 for a breakdown of ethnicity.
Table 1. Racial and Ethnic Background of Participants
Ethnicity n Percentage
White 163 79.90%
Black or African American 17 8.30%
Asian 9 4.40%
Hispanic or Latino 11 5.40%
Native American or Alaska Native 2 1% Native Hawaiian or Pacific Islander 0 0%
Other 2 1%
2.1.2 Measures
Participants completed three measures, the reader-based standards of coherence measure, need for cognition questionnaire (Cacioppo, Petty, & Kao, 1984; Appendix A), and a shorted version of a reading habits questionnaire (Finucci, Isaacs, Whitehouse & Childs, 1982; Finucci,
Whitehouse, Isaacs & Childs, 1984; Lefly & Pennington, 2000; Parault & Williams, 2009; Appendix B).
2.1.2.1 Need for Cognition
The need for cognition questionnaire consisted of 18 items. This questionnaire related to preferences for problem solving, including complex and abstract problems. Nine items were reverse scaled. Participants rated whether they agreed that a statement is characteristic of them on a Likert scale ranging from strongly disagree (1) to strongly agree (7). The score range of this test is -72 to 72.
2.1.2.2 Adult Reading History Questionnaire (ARHQ)
As a measure of participants’ reading habits, participants also completed a subset of items from the Adult Reading History Questionnaire (ARHQ; Finucci et al.., 1982, 1984; Lefly & Pennington, 2000) and one question from the Reading Activity Questionnaire (Parault & Williams, 2009). The questions targeted readers’ reading frequency, time spent reading, and types of reading materials (Appendix B). Scores for this subset of the ARHQ ranged from 0 – 23 (excluding the question about reading materials). The question regarding types of reading materials stemmed from the Reading Activity Questionnaire and consisted of three broad categories: 1) magazines (online and in print), 2) newspapers (online and in print), and 3) books (non-fiction and fiction). The “Books” category included non-fiction books (self-help, autobiography, biography, history, nature, and sports) and fiction books (romance, mystery/adventure, fantasy/science fiction, and literature). The survey also had an “other” category in which participants could type out additional genres they read. Participants could select multiple types of reading materials.
2.1.2.3 Reader-based Standards of Coherence Questionnaire
After deciding on the three categories for the standards of coherence measure (typical reading goals, desire to understand, and comprehension monitoring), exemplar items were created. The measure also included 6 items adapted from the AMRS (Schutte & Mauloff, 2007). Finally, open-ended responses from 11 undergraduate students, graduate students, and post-doctoral researchers on the following three questions were used to create additional items: 1) Why do you generally read?, 2) What motivates you to understand a text?, and 3) What reading strategies do you use to understand a text, and in what situation? The reader-based standards of coherence measure included 87 items across three hypothesized categories: typical reading goals (30 items), desire to understand (30 items), and comprehension monitoring (27 items). Of the 87 items, 24 were reverse scaled. Similar to the need for cognition questionnaire, participants rated whether they agreed that a statement was characteristic of them on a Likert scale ranging from strongly disagree (1) to strongly agree (7). Please see Appendix C for a full list of the 87 items.
2.1.3 Procedure
Participants completed the reader-based standards of coherence measure, the subset of the adult reading history questionnaire, and the need for cognition questionnaire. All questionnaires were administered via Qualtrics and took approximately 15 minutes to complete.
2.1.4 Analysis Procedure
The analyses were carried out in two steps. First, a principal axis factor (PAF) analysis, a type of EFA, was conducted to extract the items that significantly loaded onto the factors identified
from a parallel analysis. A parallel analysis estimated the number of factors identified from a randomly sampled set of the data and a randomly generated set of data. The number of factors to retain should be fewer than the number identified by the parallel analysis. A PAF analysis was chosen because it is useful for non-normal data (Bartholomew, 1980; Fabrigar, Wegener, MacCallum, & Strahan; 1999), which was the case in the present study. For the PAF analysis, factor loadings greater than .5 were considered significant. Multiple fit indices assessed model fit. Non-significant χ2 values indicate good fit. The root mean square error of approximation (RMSEA) and Tucker-Lewis Index (TLI) were also included to assess model fit. TLI values > .90 indicate acceptable fit and values > .95 indicate good model fit (Hu & Bentler, 1999). RMSEA values < .08 and < .05 indicate acceptable and good fit, respectively (Hu & Bentler).
After the first step, the second step used hierarchical regressions with the finalized version of the reader-based standards of coherence measure to determine whether it accounted for variance in people’s reading habits (ARHQ) when controlling for need for cognition. Analyses for need for cognition and reader-based standards of coherence were conducted separately, then both were entered into a single model. If the change in variance accounted for is significant when the reader- based standards of coherence measure is entered into the model second, it would indicate that reader-based standards of coherence accounts for additional variance not explained by need for cognition. Furthermore, if there is a non-significant change in variance when need for cognition is entered second, it would suggest that the new reader-based standards of coherence measure is a more fine-grain predictor of reading habits than need for cognition.