Improving Sleep Among Teachers: an Implementation-Intention Intervention

Abstract

Background: Insufficient sleep is common among teachers and is associated with diverse health risks. This study aimed to predict intention and sleep duration by applying the Theory of Planned Behavior (TPB) and to examine the effectiveness of an implementation-intention intervention to improve sleep duration and quality.

Method: Sixty-nine teachers (M = 36.8 years, SD = 10.4) were assigned to an active control group (CG) or intervention group (IG). At baseline, TPB variables were assessed and participants of the IG received instructions to develop implementation intentions to reach the goal of sleeping 8 h on average. During a 3-week intervention period, all participants wore an activity tracker (Fitbit Charge HR) to measure sleep duration and kept diaries to assess sleep quality, physical activity, and stress. After 1 month, a 1-week follow-up, including a booster for the IG, was conducted.

Results: Forty-two percent of variance in sleep duration were explained by control variables, past behavior, perceived behavioral control, and intention. Mixed ANOVAS with baseline covariates found a large main effect with longer sleep duration in the IG. A time x group interaction suggested that only the IG slept significantly longer in the follow-up period compared to the intervention period. For sleep quality, a medium-sized main effect for study group was found and a time x group interaction indicated higher sleep quality in the IG for week 3 and the follow-up.

Conclusion: The TPB was effective in predicting sleep intention and duration. Implementation intentions accompanied by daily monitoring and a booster appear to be promising for improving sleep.

Keywords: Implementation intentions; Self-monitoring; Sleep duration; Sleep quality; Teachers; Theory of planned behavior.

Fig. 1

Participant flow diagram

Fig. 2

Fitbit-measured sleep duration as a function of study group and time after intervention. Mixed ANOVA with baseline scores for perceived behavioral control and intention as covariates; intervention period, weeks 1–3: aggregated fitbit-measured sleep duration from 7 consecutive days; follow-up period (booster week) after a break of 4 weeks: aggregated fitbit-measured sleep duration from 7 consecutive days. Error bars represent one standard deviation. Significant group differences in sleep duration for intervention weeks and follow-up (Welch tests; p < .001); Cohen’s d_{(week 1)} = .84, 95% CI [.35; 1.33]; Cohen’s d_{(week 2)} = .93 [.44; 1.43]; Cohen’s d_{(week 3)} = 1.06 [.56; 1.56]; Cohen’s d_(follow-up) = 1.41 [.89; 1.94]. Mean group differences and CI (in minutes): M_{Diff(week 1)} = 27.1, CI [11.5; 42.6]; M_{Diff(week 2)} = 32.6, CI [15.8; 49.4]; M_{Diff(week 3)} = 41.8 CI [22.9; 60.7]; M_{Diff(week 4)} = 49.6, CI [32.6; 66.7]

Fig. 3

Self-reported sleep quality as a function of study group and time after intervention. Mixed ANOVA with perceived behavioral control as covariate; sleep quality: daily self-report (2 items); from 0 (“very bad”) to 100 (“very good”), α = .86; intervention period, weeks 1–3: aggregated sleep quality from 7 consecutive days; follow-up (booster week) after a break of 4 weeks: aggregated sleep quality from 7 consecutive days. Error bars represent one standard deviation. Significant group differences in sleep quality for intervention week 3 and follow-up week (Welch tests; p < .01); Cohen’s d_{(week 1)} = .29, 95% CI [−.18; .77]; Cohen’s d_{(week 2)} = .27 [−.21; .74]; Cohen’s d_{(week 3)} = .71 [.22; 1.19]; Cohen’s d_(follow-up) = .75 [.26; 1.23]. Mean group differences and CI: M_{Diff(week 1)} = 3.7, CI [−2.4; 9.8]; M_{Diff(week 2)} = 3.7, CI [−2.9; 10.4]; M_{Diff(week 3)} = 9.1, CI [2.9; 15.2]; M_{Diff(week 4)} = 8.6, CI [3.0; 14.1]