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. Author manuscript; available in PMC: 2022 Nov 3.
Published in final edited form as: Pers Individ Dif. 2021 Nov 3;186(Pt B):111365. doi: 10.1016/j.paid.2021.111365

Testing Bidirectional Within-Person Associations between Mindful Attention and Sleep in Adolescence

Rachel G Lucas-Thompson b,a, Megan Moran b, Tori L Crain c
PMCID: PMC8656266  NIHMSID: NIHMS1756130  PMID: 34898775

Abstract

Developments during adolescence increase risk for sleep problems. Research in adults suggests mindfulness and sleep are associated, with two different theoretical explanations for direction of effects. Our goal was to directly test these competing theoretical models at the daily level in adolescents using objective and self-reported measurements of sleep. Adolescents (N=138; 14–21yrs) reported mindful attention and sleep for a week, while wearing an actigraph. Results indicated that, within-person, poor sleep at night predicted less mindful attention the next day; however, mindful attention during the day did not predict sleep that night. These findings provide support for the developmental model of sleep and regulation and suggest poor sleep may impair regulatory abilities the following day.

1. Introduction

Adequate sleep during adolescence is critical for development (Short et al., 2013), but adolescent sleep problems run rampant (Gradisar et al., 2011). Theoretical models highlight the importance for sleep of mindfulness, an attentional pattern that is non-judgmental and present-focused. However, these models frame mindfulness both as a meta-cognitive process that benefits sleep (Garland et al., 2015) and as a regulatory process challenged by poor sleep (Dahl, 1996; Palmer & Alfano, 2017). Tests of these pathways have relied on examining between-person associations between mindfulness and self-reported sleep in adults. However, mindful attention (MA) varies meaningfully within person (Lucas-Thompson, Miller, et al., 2021). Because effects at between-person levels often do not translate within-person (Bliese & Jex, 2002), it is necessary to empirically test associations at the within-person level (Chen et al., 2005). This study is the first to directly test competing pathways based on within-person associations of MA with both self-reported and objectively-measured sleep during adolescence, using intensive repeated measurements.

Adolescence (i.e., 10–25yrs; Steinberg, 2015) is characterized by cognitive and biological changes that relate to both MA and sleep, including reorganization of brain systems (Andersen, 2003) responsible for modulating the interactions between complex regulatory processes (Dahl, 1996) and executive functions such as attention allocation (Keating, 2004; Steinberg, 2015). As these executive functions underlie mindfulness (Jankowski & Holas, 2014), the cognitive capacities to support MA are present but still developing during adolescence. Also, a delayed sleep-wake pattern typically emerges during adolescence, creating critical sleep shortages (Gradisar et al., 2011).

The meta-cognitive model of sleep posits that MA improves sleep through reductions in negative cognitions about sleep difficulties and emotional responses to thoughts about sleep (Garland et al., 2015; Ong et al., 2012). In contrast, the developmental model of regulation and sleep (Dahl, 1996; Palmer & Alfano, 2017) argues that insufficient sleep produces emotional, neurobiological, and cognitive regulatory deficits, particularly for adolescents (Palmer & Alfano, 2017). In this case, as MA is a regulatory process, it is likely challenged by poor sleep.

Experimental/intervention work in adults indicates both that mindfulness-based interventions can improve sleep (Ong et al., 2012) and that individuals randomly assigned to sleep deprivation have lower levels of mindfulness than those in a control condition (Campbell et al., 2018). Observational research consistently indicates that those who report being more mindful also report better sleep (Bogusch et al., 2016; Brisbon & Lachman, 2017; Howell et al., 2010; Howell et al., 2008). However, the majority of this work examined average differences in sleep between people who tend to be more or less mindful and relied on self-reports of sleep, which can be biased (Girschik et al., 2012). For adults, mindfulness and sleep are related at the between-person, but not the within-person, level (Hulsheger et al., 2013). The few existing studies on adolescents have also focused on cross-sectional associations, and indicate that greater mindfulness predicts higher reported sleep quality (Howell et al., 2008; Liu et al., 2018; Murphy et al., 2012); in contrast, on average, mindfulness is not related to objectively-measured sleep (Lucas-Thompson, Seiter, et al., 2021). This study tests two competing theoretical propositions (MA as a predictor of sleep; sleep as a predictor of MA) about links between mindfulness and sleep in adolescence using intensive repeated measurements to examine directionality of effects (Lee et al., 2017) and both objectively-measured and self-reported sleep.

2. Method

2.1. Participants

Participants were 150 adolescents (14–21 years, M=17.86, SD=2.14; 59% female) recruited from a large university in Colorado (64%; from psychology and human development courses) and the surrounding community (36%; recruited through flyers, school/social media advertisements, and booths at community events). The sample was primarily non-Hispanic White (72%) (see supplemental Table 1).

2.2. Procedure

All procedures were approved by the Colorado State University Institutional Review Board. Parents/participants ≥ 18 and participants ≤ 18 provided informed consent and assent, respectively. For seven days, adolescents wore an Actiwatch Spectrum Plus Device (Philips-Respironics) on their nondominant wrist and completed daily diaries online. Every evening, an email/text link to complete the diary was sent.

2.3. Measures

2.3.1. Daily MA

Daily MA was measured using the 5-item Mindful Attention Awareness Scale (Brown & Ryan, 2003), used in past research to measure within-person variations in mindfulness including with adolescents (Brown & Ryan, 2003; Lucas-Thompson, Miller, et al., 2021). Participants rated statements about what they were currently experiencing (e.g., “I am doing something without paying attention”; 1=not at all to 6=very much. Items were reverse-worded, such that higher scores indicate lower MA (α=.86; Ωwithin=.68; Ωbetween=.92).

2.3.2. Objective sleep measurements.

Across days, averages of total sleep in minutes per night, wake after sleep onset (WASO; minutes awake during sleeping periods), and sleep efficiency (time sleeping relative to time in bed) were derived using the standard Philips-Respironics Actiware algorithm. See (Lucas-Thompson, Seiter, Miller, & Crain, 2021) for details of cleaning/calculating procedures.

2.3.3. Self-reported sleep.

Nighttime sleep duration in minutes (computed from bed and wake time reports), minutes to fall asleep, WASO, and 1-item measuring sleep quality were gathered each night.

2.4. Analyses

Multi-level models were conducted in Stata 15 to examine between-person and within-person associations between MA and sleep, controlling for demographics. Recent simulations indicate that these models were adequately powered (Arend & Schafer, 2019).

3. Results

Of the 150 adolescents who participated in the larger study, 138 contributed diaries, with 851 and 875 days of self-reported and objectively-measured data points, respectively (M=6.2 days/participant). Means, adjusting for nesting, were: MA, M=2.59; SD=1.29; objectively-measured total sleep, M=413.63; SD=82.39, WASO, M=40.01; SD=18.61, and sleep efficiency, M=83.42; SD=7.15; as well as self-reported sleep duration, M=459.60; SD=90.91), minutes to fall asleep (M=1.71; SD=.88), WASO (M=.33; SD=.47), and sleep quality (M=3.13; SD=.04).

First, we examined MA during the day as a predictor of sleep that night. MA did not predict objectively-measured sleep (bs<8.35, ps>.05; supplemental Table 2). However, adolescents who reported higher scores on the MAAS (i.e., lower levels of MA), on average, also reported greater time to fall asleep (b=.19, SE=.06, p<.01) and lower sleep quality (b=−.15, SE=.03, p<.01); supplemental Table 3). Within person, MA during the day did not predict sleep.

Second, we examined sleep at night as a predictor of MA the next day. Objectively-measured sleep did not significantly predict next-day MA (bs<.02, ps>.05; supplemental Table 4). However, self-reported sleep did predict next-day MA, between and within person (supplemental Table 4). On average, adolescents who reported a shorter time to fall asleep (b=−.31, SE=.15, p<.01) and lower sleep quality (b=−.79, SE=.24, p<.05 also reported higher scores on the MAAS (i.e., lower MA); at trend levels, more total sleep was related to greater MA (b= −.03, SE=.01, p<.10. Within person, individuals who reported more total sleep (b=−.0008, SE=.0003, p<.05) as well as greater sleep quality (b=−.10, SE=.05, p<.05) relative to their own average also reported significantly greater MA the next day; at trend levels, taking longer to fall asleep predicted lower MA the next day (b=.08, SE=.04, p<.10).

4. Discussion

We tested two competing directional pathways linking MA and sleep in adolescence using intensive repeated measurements. Results of within-person associations suggested that poor sleep at night predicted MA the next day; in contrast, MA during the day did not predict sleep that night. These results provide indirect support for the developmental model of sleep and regulation (Dahl, 1996; Palmer & Alfano, 2017), suggesting that poor sleep may reduce regulatory competence in ways that make maintaining MA very challenging the next day. Because mindfulness is associated with better mental and physical health in adolescence (Cortazar & Calvete, 2019; Lucas-Thompson et al., 2019), understanding factors that contribute to mindfulness has important implications for adolescent wellbeing. We did not find within-person evidence to support the meta-cognitive model of sleep that greater mindfulness promotes better sleep (Ong et al., 2012). Interestingly, most within-person associations were evident with self-reported and not objectively-measured sleep, in line with past research that has relied solely on these self-reports (e.g., Howell et al., 2008; Liu et al., 2018; Murphy et al., 2012). Although mindfulness and objectively-measured sleep were not related, subjective sleep quality, including in adolescence, is important for psychological well-being (Fuligni & Hardway, 2006).

Future research should directly test the proposed mechanisms that link mindfulness and sleep. The meta-cognitive model posits that MA improves sleep by reducing negative cognitive and emotional responses to sleep difficulties (Ong et al., 2012); while the cognitive capacities to support mindfulness are still developing, adolescents may need explicit training in mindfulness of thoughts and emotions, as they receive in a mindfulness-based intervention, to effectively use MA to support sleep. Future tests of these pathways should happen in the context of a mindfulness-based intervention for adolescents, and over longer periods of time. Our sample also was racially/ethnically homogenous, and subsequent studies should improve generalizability. Also, future research should consider important elements of mindfulness beyond MA such as self-compassion (Baer et al., 2006). However, our study provides an important test of theoretical explanations linking sleep and mindfulness and suggest that, in adolescence, poor sleep is a risk factor for reduced mindfulness. Given that mindfulness contributes to adolescent psychological health (e.g., Cortazar & Calvete, 2019), it is important to identify lifestyle factors that may bolster or thwart mindfulness.

Supplementary Material

1

Grant support:

Funding for this project was provided by Award Number K01AT009592-01 from the National Center for Complementary and Integrative Health (PI, Lucas-Thompson). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Complementary and Integrative Health.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Credit Author Statement

Lucas-Thompson: conceptualization, methodology, analysis, writing – original draft, writing – review & editing, and funding acquisition; Moran: writing- original draft, writing – review & editing; Crain: methodology, software, resources, writing – review & editing.

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NIHMS1756130-supplement-1.docx (18.2KB, docx)

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