Trends in insomnia research for the next decade: a narrative review

Marques, Daniel Ruivo; Gomes, Ana Allen; Clemente, Vanda; Santos, José Moutinho dos; Serra, Joana; Azevedo, Maria Helena Pinto de

doi:10.1007/s41105-020-00269-7

Cited by 11 publications

(7 citation statements)

References 73 publications

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“…19 To provide targeted interventions and strategies that facilitate prevention and alleviation of clinically significant distress, it is important to understand mechanisms that increase their risk for insomnia with sophisticated methods. A recent review 30 on the trends in insomnia research indicated research using network approach was warranted. To the best of our knowledge, only two studies 31,32 have examined insomnia using network analysis.…”

Section: Introductionmentioning

confidence: 99%

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Bai¹,

Zhao²,

An³

et al. 2021

NSS

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The coronavirus disease 2019 (COVID-19) pandemic is associated with increased risk of insomnia symptoms (insomnia hereafter) in health-care professionals. Network analysis is a novel approach in linking mechanisms at the symptom level. The aim of this study was to characterize the insomnia network structure in mental health professionals during the COVID-19 pandemic. Patients and Methods: A total of 10,516 mental health professionals were recruited from psychiatric hospitals or psychiatric units of general hospitals nationwide between March 15 and March 20, 2020. Insomnia was assessed with the insomnia severity index (ISI). Centrality index (ie, strength) was used to identify symptoms central to the network. The stability of network was examined using a case-dropping bootstrap procedure. The network structures between different genders were also compared. Results:The overall network model showed that the item ISI7 (interference with daytime functioning) was the most central symptom in mental health professionals with the highest strength. The network was robust in stability and accuracy tests. The item ISI4 (sleep dissatisfaction) was connected to the two main clusters of insomnia symptoms (ie, the cluster of nocturnal and daytime symptoms). No significant gender network difference was found. Conclusion: Interference with daytime functioning was the most central symptom, suggesting that it may be an important treatment outcome measure for insomnia. Appropriate treatments, such as stimulus control techniques, cognitive behavioral therapy and relaxation training, could be developed. Moreover, addressing sleep satisfaction in treatment could simultaneously ameliorate daytime and nocturnal symptoms.

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Section: Introductionmentioning

confidence: 99%

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Bai¹,

Zhao²,

An³

et al. 2021

NSS

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“…The first three items measure insomnia severity (difficulties in initiating and maintaining sleep and waking up too early), and the last four items assess sleep satisfaction, noticeability of the sleep problem to others, worry about the sleep problem, and sleep problem's interference with daily functioning. Four severity categories have been identified for the total score: no insomnia (score range 0-7), subthreshold insomnia (score range [8][9][10][11][12][13][14], moderate insomnia (score range [15][16][17][18][19][20][21], and severe insomnia (score range [22][23][24][25][26][27][28], and the original version of the instrument showed acceptable reliability, convergent validity with other subjective and objective sleep measures, and sensitivity to change after treatment. According to Morin et al [37], a cut-off of 10 maximizes sensitivity and specificity and is optimal for detecting insomnia cases in community samples, and thus a total score ≥ 10 was used in this study to select subjects reporting relevant insomnia symptoms.…”

Section: Insomnia Severity Indexmentioning

confidence: 99%

“…Worse health outcomes in the long term and a non-remitting course have been consistently observed in association with the objective short-sleep-duration phenotype [ 7 , 19 ]. However, the identification of insomnia phenotypes is still ongoing and represents a significant trend in contemporary insomnia research [ 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Sleep Quality and Insomnia Severity among Italian University Students: A Latent Profile Analysis

Carpi

Marques

Milanese

et al. 2022

JCM

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Insomnia is a widespread sleep disorder associated with physical and mental health conditions. Although the heterogeneity of insomnia presentations has been acknowledged, research investigating clinically meaningful insomnia subtypes is still ongoing. This study aimed at exploring insomnia subtypes according to widely-used measures of symptoms severity and sleep quality among Italian university students using a latent profile analysis. Data were collected from 490 students reporting relevant insomnia symptoms through an online cross-sectional survey comprising the Insomnia Severity Index, the Pittsburgh Sleep Quality Index, the 21-item Depression Anxiety Stress Scale, and the Short Form-12. Latent profile analysis identified five insomnia subtypes. The severe insomnia (8.8%) group showed the highest insomnia severity, with diverse complaints concerning sleep quality and daytime functioning. Moderate insomnia with sleep duration complaints (8.4%) and moderate insomnia with medication use (15.9%) subgroups were characterized by middle range insomnia severity, with problems of sleep continuity and sleep medication use, respectively. Subthreshold insomnia with sleep latency complaints (20.4%) and subthreshold insomnia (46.5%) groups showed attenuated insomnia symptoms. Higher psychological complaints and worse quality of life were associated with greater sleep complaints. Overall, these findings highlight the relevance of sleep quality domains in identifying insomnia subtypes and might help optimize insomnia treatments.

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“…Insomnia is the most common sleep disorder (Buysse & Harvey, 2017) with a prevalence of 3-22%, varying by the classification system used (Wilson & Attarian, 2017). It is characterized as the difficulty in initiating or maintaining sleep, waking up earlier than desired for three or more nights in a week, for at least 3 months, and causing significant impairment in daily functioning (APA, 2014;American Academy of Sleep Medicine, 2013;Marques et al, 2020). Individuals with insomnia experience fatigue, malaise, difficulty paying attention, concentration or memory difficulties, irritability, mood disturbances, daytime sleepiness, behavioral disorders, among other problems (Ong & Gehrman, 2017).…”

Section: Introductionmentioning

confidence: 99%

The Role of Sleep Effort as a Mediator Between Anxiety and Depression

2023

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Depression, anxiety, and insomnia are all conditions that share a complex bidirectional relationship. Sleep effort is a construct with cognitive and behavioral components that perpetuates insomnia. Although many studies have examined the associations between these three variables, no studies have yet examined sleep effort as a mediating variable between anxiety and depression and vice versa. Online versions of the Hospital Anxiety and Depression Scale and the Glasgow Sleep Effort Scale were administered to a sample of 1927 higher education students aged 18–40 years (75.9% women and 76% from 18 to 23 years old). As part of the survey, participants also completed a sociodemographic questionnaire. Mediation analysis indicated that sleep effort mediates the relationship between depression and anxiety, when the former was the predictor and the latter was the criterion. Moreover, sleep effort also mediated the relationship between anxiety and depression when the former was the predictor and the latter was the criterion, albeit in a lesser extent. Sleep effort appears to play a bidirectional mediational role between depression and anxiety, being a potential target for intervention.

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Trends in insomnia research for the next decade: a narrative review

Cited by 11 publications

References 73 publications

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Sleep Quality and Insomnia Severity among Italian University Students: A Latent Profile Analysis

The Role of Sleep Effort as a Mediator Between Anxiety and Depression

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