Participants and Procedure

Data were collected as part of a larger study58. Participants were required to be native Swedish speakers, healthy, and to not have any psychiatric or neurological diagnoses. Forty-seven nonpaid participants volunteered for the study. After signing the informed consent, they filled in an online well-being questionnaire. Then, during the subsequent three weeks (i.e., 21 days), participants logged onto and filled in an online home dream diary every morning upon awakening in which they reported all their dreams and rated their affective experiences in those dreams. Three participants (1 man, 2 women) were excluded from the analyses because they provided less than five dream reports. Thus, the final sample consisted of 44 participants (16 men, 28 women, M age = 26.93, SD age = 5.09, range = 19–40 years). The study was performed in accordance with the Declaration of Helsinki and was approved by the Regional Ethical Review Board in Gothenburg, Sweden.

Well-Being Questionnaire

The online well-being questionnaire included scales measuring all the different components of well-being, symptoms of ill-being, and sociodemographic questions. All the scales were administered in Swedish. Scales that were not available in Swedish, were translated from English to Swedish using the back-translation method84. One bilingual translator translated the scales into Swedish and another independent bilingual translator back-translated the scales into English. The back-translated versions of the scales were compared to the original ones by the first author of the study to ensure conceptual equivalence. Table 1 summarizes all the scales included in the well-being questionnaire and provides data about their reliability in the current sample.

Life satisfaction

The Satisfaction With Life Scale (SWLS)85 was used to measure how participants evaluate their life on the whole. The scale consists of five items (e.g., “I am satisfied with my life”) that are rated on a scale from 1 (strongly disagree) to 7 (strongly agree). The total score is calculated by summing up all the five items with higher scores indicating higher satisfaction with life. This scale was used because it is the most widely used scale for measuring life satisfaction and displays good psychometric properties with Cronbach’s alpha (α) ranging from 0.79 to 0.8986,87. A psychometric evaluation of the Swedish version of the scale in a nationwide sample of university students showed good reliability (α = 0.88) and provided support for the unidimensional model88.

Domain satisfaction

The Brunnsviken Brief Quality of Life Scale (BBQ)89 was used to measure how satisfied participants are with different domains of life. The scale consists of 12 items covering six life domains (leisure time, view on life, creativity, learning, friends and friendship, view of self). Participants rate the importance (e.g., “My leisure time is important for my quality of life”) and satisfaction (e.g., “I am satisfied with my leisure time: I have the opportunity to do what I want in order to relax and enjoy myself”) with each domain on a scale from 0 (do not agree at all) to 4 (agree completely). To obtain a total score, the satisfaction and importance rating for each domain are first multiplied and then the six products are summed up. This scale was used because it is a brief, open access scale validated in both clinical and non-clinical samples and has demonstrated good psychometric properties in a Swedish sample (α = 0.76)89.

Positive and Negative Affect

The two affective components of HWB were measured with three different scales. The Positive and Negative Affect Schedule (PANAS)90 was used because this is one of the most well-validated and frequently used scales to measure affect in psychological science with adequate psychometric properties91. It consists of 20 items with 10 items measuring positive affect (e.g., interested, proud, inspired) and 10 items measuring negative affect (e.g., distressed, hostile, ashamed). Participants were asked to rate to what extent they experienced each of the feelings during the past 24 hours on a scale from 1 (very slightly or not at all) to 5 (extremely). The positive and negative affect items were summed up to obtain the positive affect subscale (PANAS_PA) and the negative affect subscale (PANAS_NA), respectively. The Swedish versions of the subscales have shown good reliability (α PA ranging from 0.82 to 0.87 and α NE ranging from 0.85 to 0.86)92,93.

The modified Differential Emotions Scale (mDES)55 was included to measure a broader range of affect. The scale consists of 20 affect categories, 10 for measuring positive affect (e.g., amusement, gratitude, love) and 10 for measuring negative affect (e.g., scorn, disgust, hate). Each category is described by three adjectives (e.g., grateful, appreciative, or thankful) and participants rated the greatest amount they experienced each of those during the past 24 hours on a scale from 0 (“I did not experience any of these feelings at all”) to 4 (“I experienced one or more of these feelings extremely much”). The positive affect subscale (mDES_PA) and the negative affect subscale (mDES_NA) were obtained by calculating the mean score of the 10 positive affect categories and of the 10 negative affect categories, respectively. In previous studies the scales have demonstrated good reliability (α PA ranging from 0.93 to 0.94 and for α NA ranging from 0.85 to 0.86)94,95.

Similarly to Lee et al.17, additional items were added to ensure that both high-and low-arousal (positive and negative) affect were measured and to enable investigation of correlations between low-arousal positive affect and PoMS. Therefore, items from the 12-Point Affect Circumplex Scales (12-PAC)96 were included to represent the four different quadrants of the affect circumplex: high-arousal positive affect (12-PAC_HPA; excited, enthusiastic, energetic, elated), low-arousal positive affect 12-PAC_LPA; (calm, tranquil, serene, relaxed), high-arousal negative affect (12-PAC_HNA; nervous, fearful, upset, anxious), and low-arousal negative affect (12-PAC_LNA; sad, down, drowsy, tired). Participants rated to what extent they experienced each of these feelings during the past 24 h on a scale from 1 (not at all) to 5 (extremely). Mean scores for each subscale were calculated. In Lee et al.17 similar subscales demonstrated acceptable reliability (α HPA = 0.80, α LPA = 0.80, α HNA = 0.85, α LNA = 0.67).

Eudaimonic Well-Being

Of the several existing scales measuring EWB, the Flourishing Scale (FS)78 was used because rather than addressing a specific conceptualization of EWB, it combines different conceptualizations and was specifically created to complement SWB. The scale consists of 8 items and measures important facets of optimal functioning considered central to EWB, including purpose and meaning (e.g., “I lead a purposeful and meaningful life”). Participants rate to what extent they agree with each item on a scale from 1 (strongly disagree) to 7 (strongly agree). The total score is calculated by adding up the responses to each item with higher scores indicating more optimal functioning. The scale has been shown to be unidimensional and display good psychometric properties (α ranging from 0.87 to 0.89)97. Good reliability of the Swedish version of the scale has also been demonstrated (α = 0.87)98.

Peace of Mind

The Peace of Mind Scale (PoMS)17 was used to measure how often participants experience inner peace and harmony in their daily life. The original scale consists of 7 items (e.g., “I have peace and harmony in my mind”) of which two items are reverse-scored (e.g., “It is difficult for me to feel settled”). The items are rated on a scale from 1 (not at all) to 5 (all of the time) and the mean of the item scores reflects an overall measure of peace of mind. Although PoMS was originally developed to measure well-being in the Chinese culture, Lee et al.17 demonstrated it to be a valid and reliable measure also in a Western sample (European Americans). However, because in the US sample the two reverse-coded items loaded on a separate factor, the authors excluded these two items and used the five-item PoMS instead (α = 0.90). We assessed the factor structure of the Swedish version of the scale in a pilot sample of 140 Swedish university students (54 men, 86 women; M age = 25.30, SD age = 6.72, range = 19–59 years). Confirmatory factor analysis (using the lavaan function in R99) indicated the two-factor solution to be a better fit (χ2 = 21.70, df = 13, p = 0.060, RMSEA = 0.07, CFI = 0.98, SRMR = 0.03, AIC = 2505.24) than the one-factor solution (χ2 = 27.57, df = 14, p = 0.016, RMSEA = 0.08, CFI = 0.97, SRMR = 0.04, AIC = 2509.15). Therefore, we used the five-item PoMS in subsequent analyses. However, to enable comparison with Lee et al.17, we present the reliability, descriptive statistics, and correlations with other well-being measures for both the five- and seven-item PoMS. We also repeated the multilevel analyses using the seven-item PoMS and the results were essentially the same as those obtained using the five-item PoMS.

Depression

The depression module of the Patient Health Questionnaire (PHQ-9)100 was used to measure symptoms of depression. The brief 9-item scale is based on the diagnostic criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM-5)101 and used in both research and clinical practice. Participants rate how often, over the last two weeks, each of the symptoms (e.g., “Little interest or pleasure in doing things”) has bothered them on a scale from 0 (not at all) to 3 (nearly every day). The total score is obtained by summing up the ratings for each item and the cut-off scores of 5, 10, 15, and 20 represent mild, moderate, moderately severe and severe depression, respectively. It is a widely used open access depression screening instrument demonstrating good psychometric properties (α = 0.87) in the general (i.e., non-clinical) population102.

Anxiety

The Generalized Anxiety Disorder Scale (GAD-7)103 was used to measure symptoms of anxiety. The 7-item scale is based on the most prominent features of the diagnostic criteria A, B, and C for generalized anxiety disorder from the DSM-5101. Participants rate how often, over the last two weeks, each of the symptoms (e.g., “Worrying too much about different things”) has bothered them on a scale from 0 (not at all) to 3 (nearly every day). The scores for each item are summed to obtain a total score with 5, 10, and 15 representing mild, moderate, and severe anxiety, respectively. The scale has shown good psychometric properties (α = 0.89) in the general (i.e., non-clinical) population104.

Additional measures

In addition to mental well-being, participants also answered questions about their physical well-being, physical ill-being, and subjective sleep quality. Because the current study focused on mental well-being, these data were not included in the analyses.

Home Dream Diary

Participants were asked to write down their dreams every morning upon awakening during a three-week period. To counteract forgetting, participants were instructed to jot down their dreams (using pen and paper) immediately upon awakening, but before getting up. Thereafter, they were to log onto and fill in an online daily dream diary. In this diary participants reported whether they remembered having any dreams that night and, in case they did, provided a detailed description of the dream. Specifically, they were asked to write down the dream in as much detail as they could remember (what happened, where, when, who was present, what they felt and thought). Participants were asked to report their dreams as completely and truthfully as possible, and to not edit, censor, interpret or elaborate the dream reports beyond what they remembered happening. If participants wished to comment on some aspects of the dream, they were asked to add their comments in brackets or at the end of the dream reports so that these would be clearly distinguishable from the actual dream (report). Following Antrobus105, the length or word count of each dream report was calculated by counting together all dream-related words, excluding fillers, repetition, corrections, and waking comments. After reporting the dream, participants rated the feelings they experienced in the dream using the mDES55. If participants remembered several dreams from the same night, they were asked to report the dream and rate the dream affect separately for each dream. In case participants had not logged onto the online dream diary on some day(s), an email reminder was sent.

Self-ratings of dream affect

Self-ratings of dream affect were obtained using the mDES scale. This scale was used to ensure comparability and consistency with our previous study59. Participants were asked to rate the extent to which they experienced each of the 20 affect categories in their dream on a scale from 0 (“I did not experience any of these feelings at all”) to 4 (“I experienced one or more of these feelings extremely much”). Similarly to the waking affect ratings, the mean scores of the 10 positive and 10 negative affect categories were calculated to obtain the positive affect subscale (Dreams_SR_PA) and the negative affect subscale (Dreams_SR_NA), respectively (min = 0; max = 4) (see Supplementary Materials for examples of dream reports and self-ratings of dream affect).

External ratings of dream affect

All dream reports were combined, randomized, and all identifying information removed. Two judges content analysed the reports according to the criteria, procedure, and measures used in Sikka et al.59. First, the judges worked independently and identified each and every occasion when affect was explicitly expressed in the dream report (as experienced by the dream self in the dream), could be unambiguously inferred from the behaviour of the dream self, or both. However, because the interrater percent agreement was low for cases where affect was inferred (53.7%), subsequent analyses included only the 503 cases where affect had been explicitly expressed. The interrater percent agreement for explicitly expressed affect was 84.7% and for cases where affect was both expressed and inferred 73.9%. Then, the judges independently classified these occurrences of affect using the mDES. In addition to the 20 mDES categories an additional “Other” category was used for cases that were difficult to classify into the existing categories (altogether 8.3% occurrences of affect). Interrater reliability using Cohen’s kappa106 indicated almost perfect agreement between the judges’ classification of affect (κ = 0.92). The judges did not rate the intensity of affect because the reliability and validity of such ratings is questionable6. The mDES categories that had at least one occurrence per dream report were counted together to form a positive affect (Dreams_ER_PA) and negative affect (Dreams_ER_NA) subscale (min = 0; max = 10) (see Supplementary Materials for examples of dream reports and external ratings of dream affect). For a more detailed description of the content analysis process and interrater reliability calculations, see Sikka et al.58.

Statistical Analyses

Because measurement occasions (i.e., ratings of daily dream affect, N = 552, M = 12.55, SD = 5.72) were nested within individuals (N = 44), data were analysed using multilevel regression models, also known as mixed model analysis or hierarchical linear modelling107 in the R statistical program (Version 3.4.1 R Development Core Team, 2017). These models allow for dependency across measurement occasions and can deal with unbalanced designs in which different individuals have a different number of measurement occasions. Moreover, these models allow for between- and within-person variation simultaneously, which results in more precise estimation of standard errors of regression coefficients. In addition, the modelling of the within-person variation generalizes the results to the population mean level, in terms of the fixed effects. In the present study, we focused on fixed terms describing the mean response in the population level.

There were four separate outcome variables representing the ratings of dream affect with self- and external ratings: (1) external ratings of positive affect (Dreams_ER_PA); (2) external ratings of negative affect (Dreams_ER_NA); (3) self-ratings of positive affect (Dreams_SR_PA); (4) self-ratings of negative affect (Dreams_SR_NA). The first two outcome variables (1–2) represent count data (i.e., the number of times different categories of affect were rated to occur in the dream report). Count data are often modelled with Poisson regression. However, if the data show more variation than expected, Type-I errors may result. Because preliminary analyses showed a marked overdispersion (i.e., observed variance was larger than the mean) in the outcome variable Dreams_ER_PA, we used generalized linear mixed-effects models for the negative binomial family (glmer.nb function in R108). The outcome variable Dreams_ER_NA was not overdispersed and thus the generalized linear mixed-effects model with poisson distribution and log function was used (glm function in R108). In both of these models there was subject-specific random mean-response included in the model. The other two outcome variables (Dreams_SR_PA and Dreams_SR_NA) represent continuous data (i.e., mean scores of dream affect ratings) and therefore linear mixed-effects models with maximum likelihood estimation (using lmer function in R108) were used. There was a subject-specific random intercept included in the model. Additionally, because the residuals for the model including the outcome variable Dreams_SR_NA were not normally distributed, this outcome variable was square-root transformed before the model was fit.

Thus, a series of two-level regression models were fitted in which the dream affect ratings were Level-1 outcome variables and the scores on well-being scales Level-2 predictor variables. Because the four positive and four negative waking affect scales aimed to measure the same underlying construct and also displayed very high correlations among each other (> 0.8), a composite measure for waking positive affect and negative affect was created. For this, the affect scales were first recoded to be on the same scale (i.e., 1–5) and then a mean of all the four different scales (e.g., mean of PANAS_PA, mDES_PA, 12-PAC_HPA and 12-PAC_LPA) calculated. This was done separately for the positive and negative affect yielding a composite positive affect scale (PA) and a composite negative affect scale (NA). As such, there were in total eight Level-2 predictor variables (SWLS, BBQ, PA, NA, FS, PoMS, PHQ9, GAD7). Multicollinearity — the degree to which the predictors are correlated — was evaluated using multicollinearity diagnostics. The variance inflation factor (VIF) and tolerance are the most commonly used methods for detecting multicollinearity. VIF values exceeding 5 or 10 and tolerance values remaining below 0.1 or 0.2 are usually considered problematic109,110,111. The multicollinearity diagnostics (calculated using the vif function in the usdm package112) showed that for all predictors VIF remained below 4 (except for the FS for which VIF = 4.28) and tolerance above 0.2 which indicates sufficient independence among the predictors. Removing the predictor with the highest VIF (i.e., FS) and repeating all the analyses did not alter the results.

All Level-2 predictor variables were standardized and grand mean centered. In all the analyses we controlled for the length of each dream report to account for the fact that ratings of affect are more likely to occur in longer dream descriptions. Therefore, the length of the dream report (word count) was entered as a Level-1 predictor in the analyses. Additionally, to account for gender differences, gender was controlled for and dummy-coded variables (0 for men; 1 for women) were entered as Level-2 predictors in the analyses. Also, age was controlled by adding the standardized and grand mean centered age as a Level-2 predictor in the models.

Because all the well-being variables were standardized and centered before the analysis, the estimated coefficients indicate a magnitude of change in the outcome variable associated with an increase of one standard deviation in the predictor variable.