２，３歳児におけるみたて行動の展開 : 保育園児を対象にした観察研究

departmental bulletin pape

Production of Prompt Charmonia in e+e- Annihilation at sqrt[s] ≈ 10.6 GeV

journal articl

Table_1_Unique Predictors of Sleep Quality in Junior Athletes: The Protective Function of Mental Resilience, and the Detrimental Impact of Sex, Worry and Perceived Stress.docx

Since athletic development and functioning are heavily dependent on sufficient recuperation, sleep in athletes is becoming a topic of increasing interest. Still, existing scientific evidence points to inadequate sleep in athletes, especially in females. This may be due to the fact that sleep is vulnerable to disturbances caused by stress and cognitive and emotional reactions to stress, such as worry and negative affect, which may exacerbate and prolong the stress response. Such disturbing factors are frequently experienced by junior athletes aiming for performance development and rise in the rankings, but may be damaging to athletic progression. Based on limited research in non-athletic samples, mental resilience may protect individuals against the detrimental effects of stress on sleep. Therefore, the present study aimed to investigate the extent to which sex, mental resilience, emotional (negative affect) and cognitive (worry) reactions to stress, and perceived stress, uniquely contributed to sleep quality in a cross-sectional study including 632 junior athletes. A multiple hierarchical linear regression showed that females had poorer sleep quality than males, while the mental resilience sub-components Social Resources and Structured Style were positively associated with sleep quality, providing a protective function and thus preventing sleep quality from deteriorating. Simultaneously, worry, as well as perceived stress, were negatively associated with sleep quality. Together, the independent variables explained 28% of the variance in sleep quality. A dominance analysis showed that perceived stress had the largest relative relationship with sleep quality. Based on these results, close attention should be paid to athletes’ abilities to manage worry and perceived stress, and the potential of mental resilience as a protective factor that could prevent sleep from deteriorating. The latter might be especially relevant for female athletes. Since performance margins are progressively becoming smaller and smaller, every improvement that adequate sleep can provide will be beneficial in terms of improved functioning and athletic performance.</p

Sample characteristics.

Differences in the distribution of DIMS, pubertal status, family economy and mental health scores between children with poor academic performance and children with average-to-good academic performance.</p

Output for Model 1 logistic regression analyses.

AimTo investigate whether pain, sleep duration, insomnia, sleepiness, work-related factors, anxiety, and depression associate with excessive fatigue in nurses.BackgroundFatigue among nurses is a problem in the context of ongoing nursing shortages. While myriad factors are associated with fatigue not all relationships are understood. Prior studies have not examined excessive fatigue in the context of pain, sleep, mental health, and work factors in a working population to determine if associations between excessive fatigue and each of these factors remain when adjusting for each other.MethodsA cross-sectional questionnaire study among 1,335 Norwegian nurses. The questionnaire included measures for fatigue (Chalder Fatigue Questionnaire, score ≥4 categorized as excessive fatigue), pain, sleep duration, insomnia (Bergen Insomnia Scale), daytime sleepiness (Epworth Sleepiness Scale), anxiety and depression (Hospital Anxiety and Depression Scale), and work-related factors. Associations between the exposure variables and excessive fatigue were analyzed using chi-square tests and logistic regression analyses.ResultsIn the fully adjusted model, significant associations were found between excessive fatigue and pain severity scores for arms/wrists/hands (adjusted OR (aOR) = 1.09, CI = 1.02–1.17), hips/legs/knees/feet (aOR = 1.11, CI = 1.05–1.18), and headaches/migraines (aOR = 1.16, CI = 1.07–1.27), sleep duration of ConclusionExcessive fatigue was associated with pain, sleep- and mental health-factors in a fully adjusted model.</div

Histograms and linearity checks using stata.

AimTo investigate whether pain, sleep duration, insomnia, sleepiness, work-related factors, anxiety, and depression associate with excessive fatigue in nurses.BackgroundFatigue among nurses is a problem in the context of ongoing nursing shortages. While myriad factors are associated with fatigue not all relationships are understood. Prior studies have not examined excessive fatigue in the context of pain, sleep, mental health, and work factors in a working population to determine if associations between excessive fatigue and each of these factors remain when adjusting for each other.MethodsA cross-sectional questionnaire study among 1,335 Norwegian nurses. The questionnaire included measures for fatigue (Chalder Fatigue Questionnaire, score ≥4 categorized as excessive fatigue), pain, sleep duration, insomnia (Bergen Insomnia Scale), daytime sleepiness (Epworth Sleepiness Scale), anxiety and depression (Hospital Anxiety and Depression Scale), and work-related factors. Associations between the exposure variables and excessive fatigue were analyzed using chi-square tests and logistic regression analyses.ResultsIn the fully adjusted model, significant associations were found between excessive fatigue and pain severity scores for arms/wrists/hands (adjusted OR (aOR) = 1.09, CI = 1.02–1.17), hips/legs/knees/feet (aOR = 1.11, CI = 1.05–1.18), and headaches/migraines (aOR = 1.16, CI = 1.07–1.27), sleep duration of ConclusionExcessive fatigue was associated with pain, sleep- and mental health-factors in a fully adjusted model.</div

sj-pdf-1-sgo-10.1177_21582440231219538 – Supplemental material for Smartphone Addiction and Subjective Withdrawal Effects: A Three-Day Experimental Study

Supplemental material, sj-pdf-1-sgo-10.1177_21582440231219538 for Smartphone Addiction and Subjective Withdrawal Effects: A Three-Day Experimental Study by Sarah Helene Aarestad, Tine Almenning Flaa, Mark D. Griffiths and Ståle Pallesen in SAGE Open</p

Excessive fatigue depending on demographics, sleep, work-related variables and health issues among 1335 Norwegian nurses participating in the survey of shift work, sleep and health, wave 10 (2018).

Excessive fatigue depending on demographics, sleep, work-related variables and health issues among 1335 Norwegian nurses participating in the survey of shift work, sleep and health, wave 10 (2018).</p

Output for Table 3.

AimTo investigate whether pain, sleep duration, insomnia, sleepiness, work-related factors, anxiety, and depression associate with excessive fatigue in nurses.BackgroundFatigue among nurses is a problem in the context of ongoing nursing shortages. While myriad factors are associated with fatigue not all relationships are understood. Prior studies have not examined excessive fatigue in the context of pain, sleep, mental health, and work factors in a working population to determine if associations between excessive fatigue and each of these factors remain when adjusting for each other.MethodsA cross-sectional questionnaire study among 1,335 Norwegian nurses. The questionnaire included measures for fatigue (Chalder Fatigue Questionnaire, score ≥4 categorized as excessive fatigue), pain, sleep duration, insomnia (Bergen Insomnia Scale), daytime sleepiness (Epworth Sleepiness Scale), anxiety and depression (Hospital Anxiety and Depression Scale), and work-related factors. Associations between the exposure variables and excessive fatigue were analyzed using chi-square tests and logistic regression analyses.ResultsIn the fully adjusted model, significant associations were found between excessive fatigue and pain severity scores for arms/wrists/hands (adjusted OR (aOR) = 1.09, CI = 1.02–1.17), hips/legs/knees/feet (aOR = 1.11, CI = 1.05–1.18), and headaches/migraines (aOR = 1.16, CI = 1.07–1.27), sleep duration of ConclusionExcessive fatigue was associated with pain, sleep- and mental health-factors in a fully adjusted model.</div

Concentration of gambling spending by product type: analysis of gambling accounts records in Norway

Most previous studies on the distribution of gambling losses were based on self-reported data. In this study, we employed tracking data (i.e. electronic betting records) to examine the concentration of gambling losses and whether concentration varies by product type. Tracking data were provided by the Norwegian gambling monopolist, Norsk Tipping (NT). Data comprised of 14 different games for a random draw of 2% (N = 39 995) of all NT’s customers in 2019. We applied three measures of concentration of gambling losses: the mean to median ratio, the Gini coefficient, and the proportion of total losses accounted for by the upper 1%, 5% or 10% of those who gamble. Across the 14 games, the mean/median ratio was 2.22, ranging from 1.37 to 17.48 for the different games, whereas the overall Gini coefficient was 0.65, ranging from 0.55 to 0.90. The upper 1%, 5% and 10% of those who gamble accounted for 17.9% (range = 5.6 − 3 8.3%), 39.5% (range = 23.6 − 74.3%), and 52.2% (range = 37.9 − 86.9%) of the losses, respectively. High concentration of losses was especially pronounced for one type of lottery (Keno), two online casino games (KongKasino and Bingoria), and for two sports betting games (Oddsen and Tipping). These findings were consistent across measures. Overall, the results lend strong support to the notion that a disproportionately large fraction of gambling losses are accounted for by a relatively small minority of people and that concentration of losses varies by product type.</p