Secondary Outcomes (end points)
Average number of days missed per month: The average number of days a child has missed per month, calculated for months when they were fully enrolled in the program.
Attendance rate excluding illness-related absences (if possible to calculate): Proportion of scheduled program days the child was marked present, calculated after excluding days for which caregiver-reported illness was recorded as the reason for absence. This outcome is exploratory and will be interpreted cautiously, as self-reported absence reasons may be measured with error and could be influenced by the intervention.
Expulsion rate (if possible to calculate): Proportion of children who were formally expelled during the observation period. Expulsion is a binary outcome defined as one for children who were expelled from the program – usually due to poor attendance – and zero otherwise.
Drop-out rate: Proportion of children who drop out of the program during the observation period, where drop out is a binary outcome coded as one for children who voluntarily left the program, and zero otherwise.
Caregiver knowledge and attitudes related to attendance (survey-based, if fielded):
Perceived acceptable number of absences in a typical month, calculated as the average number of absences indicated in response to the question “In a typical month, about how many days do you think it is OK for a child to miss Head Start?”
Knowledge of whether the program has minimum attendance expectations, calculated as the percentage of caregivers that respond “Yes” to the question “To your knowledge, is there a minimum number of days per month that Head Start expects children to attend?”
Awareness of possible program actions related to low attendance, calculated as the percentage of caregivers who respond “Yes” or “Maybe” to the question “Are you aware of any actions that Head Start might take if a child consistently misses school?”
Beliefs about whether consistent attendance supports child learning and development, measured using the question: “Do you believe that missing two days or more per month at Head Start negatively affects your child’s learning or development?” The primary indicator will be the percentage of caregivers who answer “Yes, a lot.” We will also provide a descriptive comparison across all response options:
Yes, a lot
Yes, a little
Maybe, but it depends on the reason for the absence
Only if it happens frequently
No, not really
I’m not sure
Beliefs about whether children benefit more from daily attendance versus staying home, calculated as the percentage of caregivers who select “A child benefits more from attending Head Start every day.” In response to the question “Which of the following statements best matches your views?”
Satisfaction with the child’s current attendance level, measured as the percentage of caregivers who answered "No" to the question “Did your child attend Head Start as often as you wanted this school year (starting in September)?”
Perceived norms regarding the child’s attendance relative to classmates, described by comparing the percentage of caregivers who believe their child attends a lot more, more, about the same, fewer, or a lot fewer days than other children, or that do not know. We will not be verifying how this corresponds to their child’s attendance. However, higher percentages of caregivers reporting “a lot more” or “more” would indicate a tendency to perceive their child as attending more than peers, highlighting potential overestimation of attendance relative to classmates.
Caregiver-reported barriers to attendance (survey-based, if fielded):
The calculation will be based on caregivers’ report of how often specific factors contributed to their child’s absences from HS/EHS from September through March, using a frequency scale ranging from Never (0 days) to Very often (>15 days). Factors include illness, transportation problems, caregiver availability, child reluctance, family preferences, weather, scheduling confusion, and caregiving arrangements. Outcomes will be summarized as the percentage of caregivers selecting each frequency category for each barrier. We will also calculate the proportion of children affected by each barrier at least once, noting that responses reflect caregiver perceptions rather than verified reasons for absences.