Low-Income Mothers' Nighttime and Weekend Work: Daily Associations With Child Behavior, Mother-Child Interactions, and Mood

In diary studies, people provide frequent reports on the events and experiences of their daily lives. These reports capture the particulars of experience in a way that is not possible using traditional designs. We review the types of research questions that diary methods are best equipped to answer, the main designs that can be used, current technology for obtaining diary reports, and appropriate data analysis strategies. Major recent developments include the use of electronic forms of data collection and multilevel models in data analysis. We identify several areas of research opportunities: 1. in technology, combining electronic diary reports with collateral measures such as ambulatory heart rate; 2. in measurement, switching from measures based on between-person differences to those based on within-person changes; and 3. in research questions, using diaries to (a) explain why people differ in variability rather than mean level, (b) study change processes during major events and transitions, and (c) study interpersonal processes using dyadic and group diary methods.

The recent growth in diary and experience sampling research has increased research attention on how people change over time in natural settings. Often however, the measures in these studies were originally developed for studying between-person differences, and their sensitivity to within-person changes is usually unknown. Using a Generalizability Theory framework, the authors illustrate a procedure for developing reliable measures of change using a version of the Profile of Mood States (POMS; McNair, Lorr, & Droppleman, 1992) shortened for diary studies. Analyzing two data sets, one composed of 35 daily reports from 68 persons experiencing a stressful examination and another composed of daily reports from 164 persons over a typical 28-day period, we demonstrate that three-item measures of anxious mood, depressed mood, anger, fatigue, and vigor have appropriate reliability to detect within-person change processes.

Intelligence scores of children in a longitudinal study were assessed at 4 and 13 years and related to social and family risk factors. A multiple environmental risk score was calculated for each child by counting the number of high-risk conditions from 10 risk factors: mother's behavior, mother's developmental beliefs, mother's anxiety, mother's mental health, mother's educational attainment, family social support, family size, major stressful life events, occupation of head of household, and disadvantaged minority status. Multiple risk scores explained one-third to one-half of IQ variance at 4 and 13 years. The stability between 4- and 13-year environmental risk scores (r = .77) was not less than the stability between between 4- and 13-year IQ scores (r = .72). Effects remained after SES and race, or maternal IQ, were partialled; multiple risk was important in longitudinal prediction, even after prior measurement of child IQ was accounted for; the pattern of risk was less important than the total amount of risk present in the child's context.