Validation of Psychosocial Measures Assessing American Indian Parental Beliefs Related to Control over Their Children’s Oral Health

Objectives: To validate questionnaire items assessing American Indian (AI) parental beliefs regarding control over their children&rsquo
s oral health within the context of psychosocial measures and children&rsquo
s oral health status. Methods: Baseline questionnaire data were collected as part of a randomized controlled trial (n = 1016) addressing early childhood caries. Participants were AI parents with preschool-age children in the Navajo Nation Head Start program. Questionnaire items assessed parental oral health locus of control (OHLOC) and agreement with beliefs indicating that they were in control of their children&rsquo
s oral health (internal), the dentist was in control (external powerful others), or children&rsquo
s oral health was a matter of chance (external chance). Exploratory factor analysis was conducted, and convergent validity was assessed using linear regression. Results: Parents with more education (p &lt
0.0001) and income (p = 0.001) had higher scores for internal OHLOC. Higher internal OHLOC scores were associated with higher scores on knowledge (p &lt
0.0001), perceived seriousness and benefits (p &lt
0.0001), higher self-efficacy, importance, sense of coherence (p &lt
0.0001 for all), and lower scores for perceived barriers (p &lt
0.0001) and distress (p = 0.01). Higher scores for both types of external OHLOC were associated with lower scores on knowledge (p &lt
0.0001), perceived seriousness (p &lt
0.0001), and higher scores on perceived susceptibility (p = 0.01 external chance
&lt
0.0001 powerful others) and barriers (&lt
0.0001). Higher scores for external powerful others were associated with lower scores for importance (p = 0.04) and sense of coherence (p = 0.03). Significant associations were not found for OHLOC beliefs and children&rsquo
s oral health status. Conclusions: Questionnaire items addressing OHLOC functioned in accordance with the theoretical framework in AI participants.