Data_Sheet_1_Negative affect instability predicts elevated depressive and generalized anxiety disorder symptoms even when negative affect intensity is controlled for: an ecological momentary assessment study.PDF

IntroductionMood and anxiety disorders are characterized by abnormal levels of positive affect (PA), negative affect (NA) and changes in how emotions unfold over time. To better prevent and treat those disorders, it is crucial to determine which kind of indices of emotion dynamics best predict elevated depressive and generalized anxiety symptoms.Methods221 individuals (60 men; mean age = 46 years, SD = 15 years) completed a 7-day ecological momentary assessment study, where their positive and negative affective experience was assessed 5 times a day. For each participant, the intensity, instability, inertia, and differentiation of PA and NA were calculated. The Estonian Emotional State Questionnaire was used to assess depressive and generalized anxiety disorder (GAD) symptoms.ResultsWe found that NA and PA intensity, and NA instability predicted elevated depressive and GAD symptoms. Models including NA instability alongside PA and NA intensity showed the best fit for both depression and generalized anxiety, as NA instability alongside other variables significantly increased the odds of having elevated depressive and GAD symptoms. Affective inertia, differentiation, and PA instability were not associated with depressive and GAD symptoms.DiscussionIn addition to the mean levels of affect, it is important to study other emotion dynamic indices such as NA instability, as these offer a more nuanced view of underlying emotion dysregulation processes. This could, in the long-term, help tailor more specific prevention and intervention methods for mood and anxiety disorders.</p

Correlations between accelerometer and self-reported PA in 13-14-years-old boys.

<p>Correlations between accelerometer and self-reported PA in 13-14-years-old boys.</p

Multiple regression models for predicting MVPA from IPAQ-SF variable.

<p>Multiple regression models for predicting MVPA from IPAQ-SF variable.</p

Comparison of IPAQ-SF and Two Other Physical Activity Questionnaires with Accelerometer in Adolescent Boys

<div><p>Self-report measures of physical activity (PA) are easy to use and popular but their reliability is often questioned. Therefore, the general aim of the present study was to investigate the association of PA questionnaires with accelerometer derived PA, in a sample of adolescent boys. In total, 191 pubertal boys (mean age 14.0 years) completed three self-report questionnaires and wore an accelerometer (ActiGraph GT1M) for 7 consecutive days. The PA questionnaires were: International Physical Activity Questionnaire-Short Form (IPAQ-SF), Tartu Physical Activity Questionnaire (TPAQ), and the Inactivity subscale from Domain-Specific Impulsivity (DSI) scale. All three questionnaires were significantly correlated with accelerometer derived MVPA: the correlations were 0.31 for the IPAQ-SF MVPA, 0.34 for the TPAQ MVPA and -0.29 for the DSI Inactivity scale. Nevertheless, none of the questionnaires can be used as a reliable individual-level estimate of MVPA in male adolescents. The boys underreported their MVPA in IPAQ-SF as compared to accelerometer-derived MVPA (respective averages 43 and 56 minutes); underreporting was more marked in active boys with average daily MVPA at least 60 minutes, and was not significant in less active boys. Conversely, MVPA index from TPAQ overestimated the MVPA in less active boys but underestimated it in more active boys. The sedentary time reported in IPAQ-SF was an underestimate as compared to accelerometer-derived sedentary time (averages 519 and 545 minutes, respectively).</p></div

Descriptive statistics of the subjects (N = 191).

<p>Descriptive statistics of the subjects (N = 191).</p

Predicting BRF criteria from S5 and XS5 domain scales (German sample, Study 1).

<p>Predicting BRF criteria from S5 and XS5 domain scales (German sample, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182714#sec005" target="_blank">Study 1</a>).</p

Bland and Altman plots with difference in mean time spent in MVPA for the IPAQ-SF and accelerometer GT1M ActiGraph.

<p>In the Bland and Altman plot, difference between two measurements is plotted against their mean. Mean and 95% confidence intervals of the difference are shown with blue lines. If there is no bias (in this case, over- or underestimating), then mean error should be close to zero. In addition, most measurement points should ideally be within the 95% confidence limits of the mean error (that is, within the lower and the upper blue line). International Physical Activity Questionnaire (IPAQ); moderate to vigorous physical activity (MVPA).</p

Self-peer correlations on five-factor domain scales: S5 (black circles) and XS5 (triangles).

<p>Gray lines indicate the correlations after controlling for acquiescence ("s" = subtracting, "p" = partialling). Numeric data are shown in Table L in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182714#pone.0182714.s002" target="_blank">S1 File</a>.</p

Cronbach alphas and congruence coefficients for two Finnish samples (student sample; representative internet sample).

<p>„p” = after partialling acquiescence; „s” = after subtracting acquiescence. Numeric data are presented in Tables G (student sample) and M (representative sample) in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182714#pone.0182714.s002" target="_blank">S1 File</a>.</p

Predicting emotional experience from N and E: S5 contrasted with XS5 (Estonian sample, Study 1).

<p>Predicting emotional experience from N and E: S5 contrasted with XS5 (Estonian sample, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182714#sec005" target="_blank">Study 1</a>).</p