Sleep quality is associated with emotion experience and adaptive regulation of positive emotion: An experience sampling study

Poor sleep patterns have been strongly linked to disrupted emotional experiences. Emotion regulation, defined as the capacity to manage one's own emotional responses, comprises strategies to increase, maintain, or decrease the intensity, duration, and trajectory of positive and negative emotions. Poor sleep has been identified as a risk factor for emotional dysregulation, but most of the focus has been on negative emotion regulation. We therefore asked whether natural variations in sleep are associated with the experience and regulation of both positive and negative emotion. Young adults, aged between 18–24 years (N = 101), completed 7 days of ecological momentary assessments using a smartphone application. Duration and quality of the previous night's sleep was reported each morning. Levels of positive and negative emotions, and strategies used to regulate emotions, were measured at pseudorandom timepoints four times a day. Multilevel modelling indicated that higher self‐reported sleep quality was significantly associated with increased intensity and duration of positive emotion, and decreased intensity of negative emotion. There were no statistically significant associations between sleep duration and emotion intensity or duration. Sleep quality, and not sleep duration, was also associated with the reported use of positive emotion regulation strategies. For negative emotion regulation strategy use, we found no associations with sleep quality or duration. Naturally occurring fluctuations in daily sleep quality may be important for the experience and regulation of positive emotion in young adults. These findings emphasise the need to examine both positive and negative emotion, and emotion regulation to understand the links between sleep and mood.

tion, and trajectory of positive and negative emotions. Poor sleep has been identified as a risk factor for emotional dysregulation, but most of the focus has been on negative emotion regulation. We therefore asked whether natural variations in sleep are associated with the experience and regulation of both positive and negative emotion.
Young adults, aged between 18-24 years (N = 101), completed 7 days of ecological momentary assessments using a smartphone application. Duration and quality of the previous night's sleep was reported each morning. Levels of positive and negative emotions, and strategies used to regulate emotions, were measured at pseudorandom timepoints four times a day. Multilevel modelling indicated that higher self-reported sleep quality was significantly associated with increased intensity and duration of positive emotion, and decreased intensity of negative emotion. There were no statistically significant associations between sleep duration and emotion intensity or duration. Sleep quality, and not sleep duration, was also associated with the reported use of positive emotion regulation strategies. For negative emotion regulation strategy use, we found no associations with sleep quality or duration. Naturally occurring fluctuations in daily sleep quality may be important for the experience and regulation of positive emotion in young adults. These findings emphasise the need to examine both positive and negative emotion, and emotion regulation to understand the links between sleep and mood.

| INTRODUC TI ON
Sleep loss and poor sleep quality disrupt how the brain processes emotions (Walker & van der Helm, 2009). Much of the evidence on the impact of sleep loss on emotion, be it the processing of emotions, the recognition of emotional stimuli, or the capacity to regulate emotion, is derived from studies of full or partial sleep restriction (for review, see Beattie et al., 2015). Experimentally reducing sleep to a maximum of 2 h total has been associated with decreased positive affect, measured using the Positive and Negative Affect Schedule (PANAS), in adolescents and adults (Talbot et al., 2010). Even partial sleep restriction, such as reducing sleep by 2 h per night for 3 nights, has been associated with linear reductions in positive affect across study days (Saksvik-Lehouillier et al., 2020). Recent meta-analytic evidence from seven unique studies suggests that experimentally induced sleep loss has a modest, but significant, negative effect on emotion ratings (Hedge's g = −0.11). Combining studies in which participants were presented with positive and negative emotion stimuli (e.g., videoclips, or IAPS images), the authors reported no moderating effects of stimulus emotion (Tomaso et al., 2021).
While experimentally limiting sleep has disruptive effects on self-reported mood and emotion ratings (e.g., Haack & Mullington, 2005), less is known about the affective experiences associated with natural fluctuations in sleep patterns, particularly in young people. In adult samples (18-61 years), poorer self-reported sleep, both duration and quality, has been associated with reduced positive and increased negative self-reported emotion (de Wild-Hartmann et al., 2013b), and there is some evidence for similar effects in 13to 16-year-olds (van Zundert et al., 2015). A 14-day diary study of 30 adults aged between 20 and 59 found that self-reported sleep quality was a small, but significant predictor of more positive nextday mood. Sleep quality was, in fact, the best predictor of mood from a range of additional sleep variables (e.g., awakenings, timing; Totterdell et al., 1994). However, as noted in a recent systematic review assessing the association between positive affect and sleep, the majority of studies have been cross-sectional, and have methodological challenges such as inadequate measurement of negative affect, or small heterogenous sample sizes (Ong et al., 2017).

| What about emotion regulation?
Another issue in the burgeoning field of emotion-based sleep research is that most studies have focused on the experience of affect that occurs after sleep loss, rather than on the regulatory processes that may alter emotional experiences . Emotion regulation impairments are central to clinical models of anxiety and depression pathogenesis (Hofmann et al., 2012), and the role of disrupted negative emotion regulation is especially em- Emotion regulation strategies can be broadly categorised as "adaptive", when associated with long-term beneficial outcomes for mental wellbeing, or "maladaptive", when associated with long-term negative outcomes (Schäfer et al., 2017). The habitual use of negative emotion regulation strategies has been associated with the likelihood of developing psychopathology in several meta-analyses. Among commonly assessed strategies for negative emotions, reappraisal can be considered an "adaptive" strategy (associated with reduced likelihood of psychopathology), whereas suppression is considered a "maladaptive" strategy (associated with increased likelihood of psychopathology; Aldao et al., 2010;Schäfer et al., 2017). Although investigated less, discussions of positive emotion regulation differentiate between strategies that either "enhance" or "dampen" positive emotions (Gilbert, 2012;Young et al., 2019), which are considered adaptive and maladaptive, respectively (Feldman et al., 2008). One recent study restricting sleep to 3 h in young adults found reduced self-reported emotion regulation success, specifically cognitive reappraisal, to negative stimuli (Tamm et al., 2019). In a study of partial sleep reduction to 6.5 h over 5 nights, Baum et al. (2014) reported emotion reaction difficulties in adolescents, as indicated by self-reported "easily upset" and unprovoked or disproportionate emotional reactions (interpreted as emotion regulation difficulties), relative to after 5 nights of typical sleep. Again, with a focus on negative emotion, an analysis of university students reported that more self-reported sleep difficulties at baseline were associated with reduced self-reported regulation effectiveness one year later (Tavernier & Willoughby, 2015). However, emotion regulation is not only dependent on the ability to manage responses to negative emotions, or negative feelings. Being able to notice, savour and reflect on positive emotions, is also important for affective functioning and mood, and may plausibly be disrupted with poor sleep, as for positive mood.
In the present study, we aimed to address the gaps in knowledge around the role of sleep in positive emotion regulation, while simultaneously recording negative affect and negative emotion regulation. We focused on young adults (aged 18-24 years) because late adolescence to early adulthood is a developmental period where there are changes in emotion regulation capacities (Young et al., 2019), and striking shifts in sleep patterns (Roenneberg et al., 2004).
Young adults are estimated to have a greater sleep need compared with older adults (Short et al., 2018), and from the onset of puberty, show a preference for a delayed sleep onset timing, leading to the characteristic "owl"-like behaviour of adolescents that persists into the early 20s (Skeldon et al., 2016). Furthermore, younger adults face different daily affective challenges compared with adults, such as the pursuit of autonomy (Weinstein & Mermelstein, 2007), and the neural architecture to support emotion regulation is still maturing in this period (Blakemore & Choudhury, 2006;Guyer et al., 2016).
Finally, adolescence and young adulthood is the developmental window where mood disorders most typically emerge, underscoring the importance of this period for understanding sleep and emotion regulation (Paus et al., 2008).
We used experience sampling to obtain more frequent measurements of young adults' emotional experiences and regulation strategies than afforded by traditional questionnaire measures. Experience sampling also allowed us to measure naturally occurring fluctuations in participants' sleep in their normal environments. We expected that higher ratings of sleep quality and longer sleep duration would be associated with increased levels of positive affect, and decreased negative affect, consistent with previous studies (de Wild-Hartmann et al., 2013b;Reddy et al., 2017). We also expected that higher ratings of sleep quality and longer sleep would be associated with increased use of adaptive regulation of positive and negative emotions and decreased use of maladaptive strategies, in line with previous studies of negative emotion regulation (Mauss et al., 2013;Palmer et al., 2018).

| Participants
Participants were recruited using a research volunteer system at the Institute of Psychiatry, Psychology and Neuroscience, King's College London, which includes both university students and volunteers signing up to the database who are not university students. We also used additional convenience sampling methods, via internal departmental webpages, and social media. Inclusion criteria for participation were: aged 18-24 years, access to an internet-enabled smartphone, Participants gave informed consent online via Qualtrics (Qualtrics International Inc.) prior to completing the baseline assessment.
We aimed to collect data from at least 100 participants, based on the sample size reported in a previous daily diary study (N = 98), taking measures of emotion intensity and duration over the course of 1 week (Verduyn & Brans, 2012). One hundred and forty individuals completed the baseline questionnaire, of whom 15 were excluded for not meeting the eligibility criteria (wrong age, n = 10; incorrect email, n = 2; not resident in the UK, n = 3). Of the remaining 125 participants at baseline, 115 individuals registered for the EMA component of the study. Eight of these participants were later excluded because their residence was subsequently reported as outside the UK, and six participants provided insufficient data, resulting in a final sample of 101 individuals.

| Baseline measures
At baseline, participants completed sleep and emotion-related measures via Qualtrics (see Table 1 for psychometric properties of each scale). Demographic data were also obtained at baseline (gender, age, and education level).

| Sleep
The Insomnia Severity Index (ISI; Morin et al., 2011) is a 7-item instrument, widely used to measure the severity of sleep difficulties and to assess the impact these have on an individual's everyday functioning. Participants responded to seven questions using a 5point Likert scale (0 = no issues, 4 = very severe issues).

| EMA measures
Questionnaire items administered during the daily EMA surveys were: (i) one item on sleep quality from the Consensus Sleep Diary (Carney et al., 2012), a widely used self-report instrument designed for daily sleep recording, and two items asking about sleep schedule (sleep time, awakening time); (ii) five items assessing positive emotion regulation adapted from the RPA and one novel item ("I have been thinking that I deserve these feelings"); and (iii) six items assessing negative emotion regulation, including four items adapted from the ERQ, assessing cognitive reappraisal (2 items) and suppression (2 items) and two additional items to measure distraction ("I have been trying to feel less negative by doing something unrelated"; "I have been trying to feel less negative by thinking about something unrelated"), where the first item measured activity-related distraction, derived from Stone et al. (2019), and the second item measured thought-related distraction (see Figure 2, Table S1). The RPA and ERQ items were modified so that the present perfect tense was used instead of the present tense or the imperative. Participants could therefore answer the instruction, "think about your experiences in the last few hours or since the last survey" (see Table S1 for all the items). However, this modification, along with the other minor language simplifications detailed in Table   S1 should be considered as non-validated changes.

| Sleep parameters
Measures of sleep quality and duration were obtained each morning (10 am-12 pm) with the items (i) "How would you rate the quality of your sleep?" (5-point Likert scale, 1 = very poor, 5 = very good) and (ii) "What time did you go to sleep?" and "What time did you wake up?", with duration calculated from the participant-estimated sleep and wake times.

| Emotion and emotion regulation
Positive and negative emotion intensity were assessed using the two ratings: "How positive have you been feeling?" and "How negative have you been feeling?" on a sliding scale between 0-100. Positive  and negative emotion duration were assessed using the item "How long has this feeling been going on?", on a sliding scale ranging from "Seconds" to "Hours", for ease of participant interpretability. We then converted duration-based responding (seconds-hours) to a score between 0-100, noting that this mapping is conceptually imperfect. The order of the positive and negative items was the same across days and participants. Regardless of the answer provided to the emotion intensity or duration question, the use of regulation strategies was then assessed using the question, "What types of thoughts have you been having about these feelings?" for each emotion type. Participants were able to select as many strategies as applicable (see Figure 2).

| Procedure
After completion of the initial baseline measures, the participants were contacted by a researcher by email and familiarised with the EMA procedures. After registration within the MetricWire application, participants received four questionnaires each day for 7 consecutive days (28 questionnaires in total, see Figure 1). A notification for the first survey of each day was sent to participants at a random timepoint between 10 am and 12 pm, while notifications for the following three surveys were sent at pseudo-random times (at least 2 h apart) between 1 pm and 10 pm. Links to surveys expired after 20 min and were recorded as missed if not returned within this period. A threshold of 20% of completed surveys was required in order for data to be incorporated into subsequent analyses, as per recommendations for EMA procedures to ensure sufficient power (Edwards et al., 2016). Finally, to encourage engagement over the duration of the experiment, participants whose responses dropped below 40% by the third day of surveys were contacted by email and reminded of the participation bonus.

| Statistical analysis
Data processing and analysis was carried out in RStudio version 4.0.2 (The R Development Core Team, 2020). Data collected within the EMA portion of the study were nested in three levels: observations (i.e., surveys), within days (note sleep parameters were measured just once per day), within participants. Multilevel modelling was used because it can accommodate the hierarchical structure of EMA data. All R code is available from: https://osf.io/urjsf/.
For each of the outcomes (EMA measures of emotion intensity, emotion duration, and emotion regulation strategies), three-level, random-intercept models were created, with each of the day-level sleep parameters (sleep duration, sleep quality) added as predictors (10 models in total, 4 for emotion intensity and duration, 6 for regulation strategies). We used baseline participant-level ISI scores, RPA scores, and ERQ scores as covariates. "Participant" and "Days within participant" were added as random intercepts to account for betweenperson and between-day differences, respectively, throughout these analyses, as per previous three-level EMA procedures (Geyer et al., 2018). For multilevel models, we used the lme4 package within R, and an optimisation by quadratic approximation (BOBYQA) with a set maximum of 20,000 iterations. Missing data were handled using listwise deletion for individual assessments (i.e., a missing item on a single ESM questionnaire resulted in removal of that assessment point for that individual, see Table S2 for details on rates of missing data).
We first tested whether the daily EMA measures of sleep (duration and quality) were associated with emotion intensity (positive or negative; 0-100 scales) and emotion duration (positive or negative; 0-100 scales). Next, we tested whether sleep (duration, quality) was associated with emotion regulation (use of strategies coded as binary variables: 0 = not used, 1 = used either/both).
Unlike models with continuous outcomes, which represent expected effects at both the participant and sample level, the results of multilevel models with binary outcome variables are participantspecific only (Hox et al., 2010). Therefore, sample-level trends were calculated in the form of predicted probabilities as per recommendations for logistic models (Persoskie & Ferrer, 2017). All analyses were conducted using maximum likelihood estimates (McCulloch, 2003).
All predictors were centred, with time-varying predictors centred using the individual's mean and time-invariant predictors using the grand mean (Snijders & Bosker, 2012). Sleep duration was assessed as a linear predictor in all models, consistent with previous EMA designs (e.g., Littlewood et al., 2019).
Outliers were calculated by generating weighted averages (using the number of surveys returned by each participant) for each variable. Outliers were defined as where the participant's average exceeded IQR +1.5 or fell below IQR −1.5. We repeated analyses with and without outliers and found similar patterns of significant effects (see Tables S3 and S4). We also conducted sensitivity analyses removing participants with ISI scores in the moderate to severe range (>14), to test whether the effects were driven by these highersymptom individuals (n = 19). As for analyses removing outliers, we found largely comparable patterns of results when excluding these 19 individuals (see Tables S5 and S6).  Figure 3.

| Participant characteristics
For positive regulation strategies, the most frequently used was emotion-focused strategies (57.69% of all reports). Self-focused emotion regulation (19.94%) and dampening (11.66%) were less frequently used. For negative emotion regulation, the frequency of reported use was similar for all three regulation strategies (reappraisal: 29.32%, suppression: 23.66%, distraction: 39.08%). Further descriptive statistics for the experience sampling emotion regulation ratings are presented in Table 2. Within and between-person standard deviations indicate that strategy use varied at least as much within individuals as between individuals. Intra-class correlations show that 12%-47% of the variance within each individual strategy was accounted for by between-person variation.

| Effects of sleep on positive and negative emotion intensity and duration
Four multilevel models examined the effect of daily variation in selfreported sleep quality and duration on daily levels of: (i) positive emotion intensity, (ii) positive emotion duration, (iii) negative emotion intensity, and (iv) negative emotion duration.

| Positive emotion: experience and duration
For positive emotion intensity, there was a small, but statistically significant effect of prior night's sleep quality. Higher quality sleep was associated with higher daily ratings of positive emotion intensity (Table 3; Table S2 for results of models including outliers). In this model, the ISI and two subscales of the RPA (emotion-focused and self-focused positive emotion regulation) were also statistically significant with small effect sizes: lower levels of insomnia symptoms and greater trait use of both emotion-focused and self-focused regulation were associated with higher positive emotion. There was no statistically significant effect of sleep duration or the RPA dampening subscale.
For positive emotion duration, higher ratings of prior night's sleep quality were associated with small increases in the duration of positive emotions, but ratings of prior night's sleep duration were not statistically significant. In this model, greater use of emotion-focused regulation was also associated with small increases in positive emotion duration. The ISI and other two RPA subscales were not.

| Negative emotion: experience and duration
For negative emotion intensity, there was a small, but significant, effect of prior night's sleep quality. Lower quality sleep was associated with higher ratings of negative emotion intensity (Table 4; Table S3 for results of models including outliers). In this model, the ISI and the ERQ cognitive reappraisal subscale were also significant with small effect sizes: higher levels of insomnia symptoms and less trait-level use of cognitive reappraisal were associated with higher negative emotion intensity. Neither prior night's sleep duration nor the ERQ expressive suppression subscale were statistically significant.
For negative emotion duration, there were no statistically significant effects of prior night's sleep quality, or duration. In this model, the ISI and ERQ subscales were also not statistically significantly associated with negative emotion duration.

F I G U R E 3 Mean ratings of reported emotion intensity and duration (a) and regulation strategy use (b and c). Error bars indicate
mean ± standard deviation, "+" in panel (a) denotes outlier values. Note that individuals were able to select more than one regulation strategy at each EMA prompt (therefore total across strategy usage >100%) [Colour figure can be viewed at wileyonlinelibrary.com]

| Effects of sleep on emotion regulation strategy use
Six multilevel models examined the effect of daily variation in sleep quality and duration on daily levels of emotion regulation strategy use (3 positive regulation strategies, 3 negative regulation strategies).

| Positive emotion regulation strategies
For emotion-focused regulation, higher prior night's sleep quality was associated with greater daily use of emotion-focused regulation ( Figure 5, Table 3; Table S2 for results of models including outliers). There were no statistically significant effects of insomnia symptoms or the other subscales of the RPA. In sum, for positive emotion regulation, we found that sleep quality was associated with more use of an adaptive emotion regulation strategy (emotion-focused), and less use of a maladaptive strategy (dampening).

| Negative emotion regulation strategies
For cognitive reappraisal, there were no statistically significant effects of prior night's sleep quality or duration ( Figure 5, Table 4; Table S3 for results of models including outliers). However, base-  Table S3), but otherwise there were no differences between the models including or excluding outliers.
For distraction, there were no statistically significant effects of prior night's sleep quality or duration. There were also no statistically significant effects of insomnia symptoms or either subscale of the ERQ on daily levels of distraction use. In sum, in contrast to that seen for positive emotion, there were no statistically significant associations between sleep quality and emotion regulation strategy use for negative emotion.

| DISCUSS ION
Using experience sampling in young adults, we found that naturally occurring variations in at home sleep patterns, reported each morning for 7 days, were associated with the daily experience of positive emotion. Prior night's sleep quality was associated with the experience of positive emotion, its intensity and duration, and also with reported engagement in strategies to regulate it. Young TA B L E 3 Results from multilevel models examining positive emotions and positive emotion regulation (outliers removed) Note: Effect sizes (ES) are marginal Cohen's f 2 for intensity and duration variables and odds ratios for binary emotion regulation variables.
adults with higher ratings of sleep quality tended to report greater engagement in an adaptive regulation strategy, taking an emotionfocused approach (e.g., appreciating the moment), and less engagement in a maladaptive regulation strategy, dampening (e.g., thinking the positive feelings will go away). Longer sleep duration was not associated with intensity or duration of daily emotion experience, nor with engagement in any of the tested regulation strategies. Our significant effects were small in magnitude, consistent with recent meta-analytic estimates of the impact of experimental sleep reduction on components of emotion processing and experience (Tomaso et al., 2021).
For negative emotion, and negative emotion regulation, sleep pattern associations were apparent only for the measure of emotion intensity. Higher sleep quality, but not longer sleep duration, was associated with reporting of less intense daily negative emotion. The association between better perceived sleep quality and less negative emotion intensity is in line with what might be predicted from neural studies of emotion processing after sleep, whereby sleep deprivation (approx. 35 h) has been associated with an amplified, hyperlimbic response in the amygdala to negative emotional stimuli (Yoo et al., 2007). However, against our initial predictions, participants' reports of three negative emotion regulation strategies, cognitive reappraisal, suppression, and distraction, were not statistically significantly associated with sleep quality or duration.
While a large body of studies have illustrated links between sleep and general mood, or sleep and PANAS-measured affect (Ben Simon et al., 2020), we show that sleep is also associated with reported use of positive emotion regulation strategies. We measured young TA B L E 4 Results from multilevel models examining negative emotions and negative emotion regulation (outliers removed) adults' reported daily tendencies to engage in regulation strategies that can influence the experience of positive emotion, multiple times per day over the course of a week, controlling for trait regulation abilities measured at baseline (ERQ, RPA) and sleep difficulties (ISI).
Our focus on emotion regulation is of importance, because poor regulation is a transdiagnostic risk factor for psychopathology (Aldao et al., 2010), and effective regulation of positive emotion is associated with life satisfaction (Quoidbach et al., 2010).
As has been recommended , we measured both positive and negative emotion experiences, as well as a range of well-defined emotion regulation strategies. Moving beyond cross-sectional measurements of a single regulation strategy, our use of EMA allowed us to capture day-to-day variations in strategy use in a sample of young adults. For positive emotion, we tested two adaptive positive regulation strategies: emotion-focused and self-focused (e.g., taking pride), and one maladaptive strategy (dampening). Self-focus was not significantly associated with sleep quality, whereas the effects for the other two strategies were small to moderate. We found no statistically significant effects for negative emotion regulation strategies, in contrast to work restricting sleep in young adults, which reported reduced cognitive reappraisal success after less sleep (Tamm et al., 2019). We speculate that, because our participants broadly fell within the healthy 7-9-h sleep range

| Blunting or a negative bias? And what might these findings mean?
Our findings suggest that poorer self-reported sleep quality is associated with a move towards the negative: reducing positive emotion intensity and duration of experience but increasing negative emotion intensity. This is distinct from an overall "blunting" of emotion, whereby negative emotion would also be dampened, along with positive emotion (colloquially a "meh" reaction, see Beattie et al., 2015).
It is an open question as to why only positive emotion regulation was related to our participants' previous night's sleep quality, and not negative regulation also. We can speculate that the capacity to observe, savour, and reflect Night-to-night sleep variability is common in the general population (e.g., Dillon et al., 2015;Knutson et al., 2007)

| Comparing trait and daily measures of emotion regulation
We obtained baseline indices of emotion regulation, using two wellestablished questionnaire instruments the ERQ and the RPA, with reasonable psychometric properties (test-retest reliability for RPA subscales from 0.51-0.65; for both ERQ subscales: 0.69, internal consistency for RPA subscales from 0.62-0.80, and for the ERQ from 0.73 to 0.79 (Gross & John, 2003;Raes et al., 2012)). We found that the participants' responses on the ERQ and RPA subscales were significantly correlated with the related EMA measures: for example, trait "suppression" (ERQ) correlated with EMA-measured suppression. Effect sizes were in the small to medium range (Figure 4), as might be anticipated for trait to daily measure correlations. We interpret these correlations as indicating that our EMA measures are reasonably related to the constructs measured in the two standardised questionnaire instruments.

| Limitations and future directions
Our study was observational and complementary to the controlled experimental studies that have directly manipulated sleep (e.g., Baum et al., 2014;Tamm et al., 2019). We assessed prior nights' sleep, preceding next day experiences of emotion and emotion regulation, and we did not address effects in the opposite direction (daily emotion predicting next night of sleep). Future studies might consider approaches such as autoregressive models to examine within-person temporal dynamics (Bulteel et al., 2016). Within our experience sampling measures, we used the same questions and question anchors every day, whereas variation in scale formats, item order, and the avoidance of repeated use of the same anchor points would be useful to address common method variance a priori (Hirschmann & Swoboda, 2017). We treated sleep duration as a linear variable, consistent with previous EMA studies (Littlewood et al., 2019;Short et al., 2017). However, both undersleeping (<5 h) and oversleeping (e.g., over 9 h) have been associated with health outcome impairments (Itani et al., 2017;Jike et al., 2018). Future work might sample participants falling outside the 7-9 h range, which is typically characterised as healthy, along with focused analyses of chronotype differences and sleep pattern regularity (Bauducco et al., 2020). Given the well-established differences between the measures of objective and subjective sleep (Smith et al., 2018), further work would benefit from including additional measurements of sleep quality and sleep time from, for example, actigraphy.
Our participants were asked at each EMA prompt to record their emotions, and how they were regulating these emotions, but were not required to describe the context of emotional experiences themselves. The appropriateness of a regulation strategy is likely to differ depending on the context, so consideration of environmental conditions will be important in future work. To give an example, although dampening is generally defined as maladaptive to positive emotions, if an individual was in a serious situation at the time of the survey prompt, reducing the expression of their positive emotions may have been socially appropriate or culturally expected (John & Gross, 2004). Our measure of regulation strategy use can be characterised as an assessment of participants' tendencies, or reported use of strategies, as distinct from an assessment of their emotion regulation ability (e.g., using measures of efficacy of a strategy to upregulate or downregulate an emotion, see for example Reddy et al. (2017)). While our assessments of trait-level emotion regulation at baseline comprised questionnaires, it would also be possible to combine laboratory measures of regulation with EMA methodology in future work.

| CON CLUS ION
Positive and negative emotion intensity were associated with selfreported sleep quality but not duration, as predicted from previous studies . Sleep quality was also associated with daily adaptive use of positive emotion regulation strategies, as measured in young adults using EMA. Sleep quality was therefore linked with both emotion intensity and regulation of emotion. These findings add to the body of studies, which emphasise the importance of sleep quality over sleep duration in overall emotion experience (e.g., Shen et al., 2018). Our findings emphasise the link between sleep and positive emotion, and are broadly consistent with studies suggesting that poor sleep quality is more robustly associated with impaired positive relative to negative mood (e.g., Bower et al., 2010;de Wild-Hartmann et al., 2013a). We suggest that emotion regulation strategy use may be a candidate mechanism linking poor sleep quality and disrupted positive mood, which could be investigated further in experimental designs.