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Psychiatry Research 321 (2023) 115066

Available online 26 January 2023 0165-1781/© 2023 Elsevier B.V. All rights reserved.

Effectiveness of one-week internet-delivered cognitive behavioral therapy for insomnia to prevent progression from acute to chronic insomnia: A two-arm, multi-center, randomized controlled trial

Lulu Yang a,b, Jihui Zhang c, Xian Luo a,b, Yuan Yang a,b, Yuhan Zhao a,b, Fei Feng d, Shuai Liu a,b,e, Chenxi Zhang a,b, Zhe Li f, Chao Wang g, Wei Wang h, Fan Jiang i, Yunshu Zhang j, Yuanyuan Hu k, Changjun Su l, Huijuan Wu m, Huan Yu n, Shirley Xin Li o, Yun Kwok Wing p, Ying Luo q, Bin Zhang a,b,*

a Department of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou, China b Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, China c Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China d Shenzhen Kangning Hospital, Shenzhen, China e The Third People’s Hospital of Qinghai Province, Xining, China f Department of Sleep Medicine, Suzhou Guangji Hospital, Suzhou, China g Department of Sleep Medicine, Henan Mental Hospital, Henan, China h Department of Psychiatry, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China i Outpatient Department, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China j Department of Sleep Medicine, Hebei Mental Health Center, Hebei, China k Department of Sleep Medicine, Zhongshan Third People’s Hospital, Zhongshan, China l Department of Neurology, Tangdu Hospital, Air Force Military Medical University, Xi’an, China m Department of Neurology, Second Affiliated Hospital of Naval Medical University, Shanghai, China n Sleep and Wake disorders’ center of Fudan University, Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China o Department of Psychology, The University of Hong Kong, Hong Kong SAR, China p Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China q The Second People’s Hospital of Guiyang, Guizhou, China

A R T I C L E I N F O

Keywords: Psychotherapy Acute insomnia Mental health Digital health

A B S T R A C T

Acute insomnia is common and a substantial proportion of people with acute insomnia (i.e. 3 days to 3 months) transit into chronic insomnia (i.e. 3 months or longer). Therefore, early intervention for acute insomnia is vital to prevent chronicity. Previous trials with small sample sizes have shown that brief versions of both individual and group-based face-to-face cognitive behavioral therapy for insomnia (CBT-I) can improve insomnia symptoms among those with acute insomnia. However, it is unknown whether one-week internet-delivered cognitive behavioral therapy for insomnia (CBT-I) is effective in treating acute insomnia. This was a randomized controlled trial and 192 participants were randomly assigned to the CBT-I group (n = 95) or control group (n = 97). The primary outcome was the incidence of chronic insomnia, determined via a structured diagnostic questionnaire for insomnia disorders according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Secondary outcomes were Insomnia Severity Index (ISI), Dysfunctional Beliefs and Attitudes about Sleep (DBAS), Epworth Sleepiness Scale (ESS), Pre-sleep Arousal Scale (PSAS), Ford Insomnia Response to Stress Test (FIRST), Sleep Hygiene and Practices Scale (SHPS), Hospital Anxiety and Depression Scale (HADS), and Short-Form 12- Item Health Survey version 2 (SF-12v2). At week 12, the incidence of chronic insomnia was significantly lower in the CBT-I group compared with control group (33.3% [27/81] vs. 65.8% [52/79]). Participants in the CBT-I group achieved significantly more improvements in ISI, ESS, PSAS, FIRST, SHPS, HADS-Depression, and the mental component summary and physical component summary of SF-12v2 than control group, but not DBAS and HADS-Anxiety. This one-week internet-delivered CBT-I program is an effective tool to prevent the chronicity of acute insomnia.

* Correspondence author at: Department of Psychiatry, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.

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Psychiatry Research

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https://doi.org/10.1016/j.psychres.2023.115066 Received 27 June 2022; Received in revised form 19 January 2023; Accepted 22 January 2023

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1. Introduction

Acute insomnia is characterized by the presence of difficulties in sleep initiation or maintenance that occurs at least three times per week for less than three months according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (American Psychi- atric Association, 2013). Acute insomnia is common and most people have experienced it, especially in response to situational stress or rapid changes in circadian rhythms. Notably, acute insomnia is at risk of evolving into chronic insomnia, which is defined by meeting DSM-5 criteria for insomnia disorder and symptoms lasting three months or longer (American Psychiatric Association, 2013).

Two prospective studies conducted by Ellis et al. reported that the annual incidence of acute insomnia is 36.6%, and 40% of those with acute insomnia develop chronic insomnia (Ellis et al., 2014, 2012). These findings suggest that acute insomnia is very common in the gen- eral population and a substantial proportion of people experiencing acute insomnia transit into chronic insomnia. It indicates that acute insomnia is a key transitional stage of chronic insomnia. Therefore, early intervention for acute insomnia may prevent chronicity. However, there are currently no guidelines for the treatment of acute insomnia, although cognitive behavioral therapy for insomnia (CBT-I) has been recommended as the first-line treatment for chronic insomnia (Qaseem et al., 2016).

In the past, short-term use of hypnotics was considered to relieve symptoms of acute insomnia (Sahoo, 2012; Chervin, 2014), whereas adverse effects are common, such as headache, nausea, tiredness, and drowsiness. Among non-pharmacological treatments, two trials con- ducted by Ellis et al. showed that brief versions of both individual CBT-I and group-based CBT-I effectively treat acute insomnia (Ellis et al., 2015; Boullin et al., 2016). These studies suggest that acute insomnia can be well managed by brief versions of CBT-I. Nonetheless, face-to-face CBT-I is limited in the real world due to high cost, the perceived inconvenience of traveling to face-to-face sessions, and a shortage of trained therapists as well as a large population with acute insomnia. Internet-delivered CBT-I can reduce such barriers but to date, it is still unclear whether internet-delivered CBT-I, a more accessible and low-cost one, is effective in treating acute insomnia, though many studies have proven excellent efficacy and feasibility of internet-delivered CBT-I for management of chronic insomnia (Cheng and Dizon, 2012; Espie et al., 2019; Ritterband et al., 2017).

Insomnia, especially when it becomes chronic, is associated with problems in the general population such as unhelpful sleep beliefs, daytime sleepiness, more pre-sleep arousal and sleep reactivity, and improper sleep hygiene, which may potentially maintain or exacerbate insomnia (Ellis et al., 2021). Previous studies show that CBT-I improves those problems among different populations (Chan et al., 2021; Redeker et al., 2022; Yang and Jun, 2022), and therefore we also aimed to assess the impact of the internet-delivered CBT-I on these problems among population with acute insomnia. Furthermore, evidence also shows insomnia is bidirectionally related to anxiety and depression and those emotional symptoms in the treatment of insomnia should also be con- cerned (Alvaro et al., 2013). Additionally, patients with insomnia tend to have impaired quality of life, which has become an important construct in contemporary medicine and health care (Kyle et al., 2010). Therefore, in this study, we aimed to 1) examine the effectiveness of a one-week internet-delivered CBT-I program to prevent the progression from acute to chronic insomnia; 2) investigate whether this one-week internet-delivered CBT-I program could improve insomnia symptoms, dysfunctional beliefs and attitudes about sleep, daytime sleepiness, pre-sleep arousal, sleep reactivity, sleep hygiene and practices, depres- sive and anxiety symptoms, and quality of life in patients with acute insomnia recruited from sleep clinics.

2. Methods

2.1. Study design and participants

This study was a two-arm, multi-center, randomized controlled trial. Participants were recruited between November 2017 and June 2019 in sleep clinics at 31 public hospitals in China. The researchers and clini- cians in these 31 sleep clinics were trained to understand the study design and study protocol and to conduct screening procedures via video conference with an experienced sleep medicine specialist from the Nanfang Hospital of Southern Medical University, and two experts in cognitive behavioral therapy, from the Department of Psychiatry of the Chinese University of Hong Kong and the Department of Psychology of the University of Hong Kong, respectively. Ethical approval for the study was obtained from the Ethics Committee of Southern Medical University (reference number: NFEC-2017–131). The trial has been registered at https://clinicaltrials.gov/(ID: NCT03302455). The protocol has been published (Yang et al., 2019). The study followed the CONSORT (Consolidated Standards of Reporting Trials) guideline (Eysenbach et al., 2011).

The screening procedure was as follows: 1) patients with acute insomnia symptoms were introduced the study protocol and invited by doctors in local sleep clinics to participate in this study. An electronic informed consent was signed if they agreed to participate; 2) psychia- trists in local sleep clinics conducted face-to-face interviews with pa- tients and screened potentially eligible participants according to inclusion and exclusion criteria; and 3) potentially eligible participants referred by local doctors were further assessed by researchers in the Southern Hospital of Southern Medical University to confirm the in- clusion and exclusion criteria. Inclusion criteria were as follows: (1) meeting diagnostic criteria for acute insomnia according to the DSM-5; (2) aged eighteen years or older; (3) being able to comply with the intervention; (4) being able to provide informed consent; and (5) own- ing a smart device (such as smartphone or tablet). Exclusion criteria were as follows: (1) the presence of a significant untreated mental or medical illness (e.g., consciousness disturbances, mania, acute phase of schizophrenia, major depressive disorder); (2) receiving any kind of psychotherapy for insomnia in the past 6 months; and (3) being shift workers or frequent flyers who cross time zones (e.g., international flight crews). To allow for greater generalizability, this study did not exclude patients with medical diseases and/or mental disorders (e.g., depression in remission) whose conditions were stable, or individuals receiving pharmacological treatments (e.g., antihypertensive drugs, antidepres- sants, benzodiazepines). The usual care that participants had been receiving via their medical advisers, including medical prescriptions, continued in both groups.

2.2. Interventions

2.2.1. CBT-I group Participants in the CBT-I group received the one-week internet-

delivered CBT-I intervention which was delivered using WeChat Mini Program (WMP). Participants could access the program and all tools using the WeChat app of any smartphone. This program was designed to deliver core materials 7 times with each session daily which lasted approximately 15 mins and was presented with text, pictures, and audio. The core contents were designed based on CBT-I (Perlis et al., 2008; Espie et al., 2001). Information about sleeping pills was also appended as supplementary material to the program. Seven sessions are as follows: sleep hygiene education, individualized sleep restriction, stimulus con- trol, relaxation audios (muscle relaxation, breathing exercise, guided imagery, and mindfulness), cognitive components, information about sleeping pills, and a brief overview. Individualized sleep restriction was provided according to their sleep pattern in the past 2 weeks prior to the treatment session, and meanwhile, participants were informed that time in bed (TIB) should not be less than 5 h. Participants in the CBT-I group

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were told to follow this prescribed schedule for one week and afterward adjust it according to principles of titration by themselves when the 7-day intervention ended. Sleep restriction titration was conducted as follows: 15-min reduction in TIB when sleep efficiency was <85%, no change in TIB when between sleep efficiency was 85–90%, and 15-min increase in TIB when sleep efficiency was >90%. The upward titration was continued as long as sleep efficiency met more than 90% for the previous week. Participants could access the relaxation audio on the first day of the intervention and be reminded to practice with audio every day. Participants received reminders on WeChat if they did not access core materials on time. If they did not log on the program for more than one day, they would get a reminder phone call from a research assistant. The program was kept accessible to the CBT-I group until week 12.

2.2.2. Control group Some participants in this study had been receiving medication for

acute insomnia or medical diseases before participation and were permitted to continue treatment as usual. Other than this, participants did not receive any intervention for insomnia from this trial. They were only asked to complete assessments on time.

Given that very few adverse effects of CBT-I were reported in many trials (Seyffert et al., 2016), we did not especially record adverse events in the study. However, participants were told to feel free to contact us when needed and they were also allowed to receive their usual follow-up in the clinic. All participants in the two groups were offered standard treatment (pharmacological treatment or non-pharmacological treat- ment) after follow-up at week 12.

2.3. Measurements

Demographics and clinical data were collected at baseline. Assess- ments were conducted at week 0, week 2, and week 12. Participants received a WeChat notification to complete the self-reported question- naires online. If participants did not complete the questionnaires within two days, they would receive a reminder or phone call.

2.3.1. Primary outcome Incidence of chronic insomnia: the diagnosis of chronic insomnia was

determined via a structured diagnostic questionnaire for insomnia dis- order through self-evaluation according to the DSM-5 at week 12, which mainly includes a predominant complaint of difficulty initiating or maintaining sleep or early morning awakening for at least three nights per week despite adequate opportunity for sleep, related daytime symptoms, and whether these symptoms had lasted for at least 3 months.

2.3.2. Secondary outcome

(1) Insomnia symptoms severity

Severity of insomnia symptoms was measured by the Insomnia Severity Index (ISI) (Badiee Aval Baghyahi et al., 2013), which has adequate psychometric properties and is sensitive to treatment response (Bastien et al., 2001). The sum score of the ISI ranges from 0 to 28 and higher scores indicate worse insomnia. This outcome was collected at baseline, week 2, and week 12 in both groups.

(1) Other sleep-related questionnaires

The Epworth Sleepiness Scale (ESS, scale 0–3; range 0–24; higher scores indicate increased severity of daytime sleepiness) was used to assess daytime sleepiness (Chen et al., 2002). The Pre-Sleep Arousal Scale (PSAS, scale 1–5; range 16–80; higher scores indicate a higher level of pre-sleep arousal) was used to assess pre-sleep arousal (Nicassio et al., 1985; Jan et al., 2009). The Ford Insomnia Response to Stress Test (FIRST, scale 1–4; range 9–36; higher scores indicate a higher proba- bility of stress-induced sleep disturbances) is a self-report measure to

assess sleep reactivity (Gao et al., 2014). The Sleep Hygiene Practice Scale (SHPS, scale 1–6; range 30–180; higher scores indicate a higher frequency of inappropriate sleep hygiene behaviors) was used to mea- sure general sleep hygiene practices (Yang et al., 2010). The 30-item Dysfunctional Beliefs and Attitudes about Sleep (DBAS, scale 1–5; range 30–150; higher scores indicate fewer dysfunctional beliefs and attitudes) was used to measure sleep-related beliefs, potential treat- ments, expectations, and attitudes towards causes, whose items are sensitive to changes with cognitive therapy (Espie et al., 2000). These outcomes were collected at baseline and week 12 in both groups.

(1) Mood symptoms and quality of life

The Hospital Anxiety and Depression Scale (HADS, scale 0–3; range 0–42; higher scores indicate worse depression or anxiety) (Zigmond and Snaith, 1983) was used to measure depressive and anxiety symptoms and consists of 14 items: seven items related to anxiety (HADS-Anxiety, scale 0–3; range 0–21; higher scores indicate worse anxiety) and seven related to depression (HADS-Depression, scale 0–3; range 0–21; higher scores indicate worse depression). The depression subscale score of 9 or higher indicates the presence of depression, and the anxiety subscale score of 6 or higher indicates the presence of anxiety (Leung et al., 1999). This outcome was collected at baseline, week 2, and week 12 in both groups.

Short-Form 12-Item Health Survey version 2 (SF-12v2, higher scores indicate better quality of life) is a generic measure of perceived health status (Lam et al., 2013). This questionnaire consists of 12 items, and physical component summary (PCS) and mental component summary (MCS) scores were calculated. This outcome was collected at baseline and week 12 in both groups. A modified Chinese Simplified version of SF-12v2 was used in the study; permission was obtained from Quality- Metric Inc (License agreement # SO042221/QM051672).

(1) Treatment adherence and perceived helpfulness

At week 2, participants in the CBT-I group were required to complete a self-report scale, Treatment Component Adherence Scale (TCAS), to assess treatment adherence to and perceived helpfulness of each thera- peutic element (Manber et al., 2011).

Adherence to each therapeutic element was rated on a 0 to 3 scale as follows: (0) followed rarely or not at all; (1) followed occasionally; (2) followed most of the time; (3) followed consistently. Perceived help- fulness of each therapeutic element was rated as (0) not helpful at all; (1) slightly helpful; (2) moderately helpful; (3) very helpful; (4) never attempted.

2.4. Randomization and masking

Participants fulfilling the study criteria were randomly allocated to either the CBT-I group or control group using simple randomization (computer-generated random numbers). An independent researcher from the IT department implemented randomization and treatment allocation through an automated online system. The research team was not able to influence randomization and had no access to allocations.

An independent researcher from the IT department, who carried out the randomization and allocation procedure, was masked to the study protocol. Participants were not masked to treatment allocation as par- ticipants in the control group did not receive any intervention from our study. The research team had limited contact with participants to avoid bias derived from study allocation or self-reported assessments. Statis- tical analysis was carried out by an independent researcher from Southern Medical University who was not involved with the randomi- zation and assessment procedures.

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2.5. Statistical analysis

Main analyses were on an intent-to-treat (ITT) basis, with all ran- domized participants included in the analysis and analyzed according to the original group assignment regardless of adherence to treatment assignment. Per protocol (PP) analysis was used for the consistency test. The PP group refers to all ITT participants who completed the internet- delivered CBT-I program and assessments at baseline, week 2, and week 12, which was no longer an unbiased sample from this randomized trial. In ITT analysis, the last observation carried forward (LOCF) method was used to impute any missing data. The results were presented as mean with standard deviation (x ± s) for continuous variables and frequencies with percentages for categorical variables.

Baseline demographic characteristics were compared by t-test for continuous variables and chi-square test for categorical variables. Repeated measures analysis of variance (RM-ANOVA) was used to analyze outcomes of all self-reported questionnaires between the two groups, and results were presented with 2-sided P values for ISI, DBAS, ESS, PSAS, FIRST, SHPS, HADS, and SF-12v2. The chi-square test was

used to compare differences in the incidence of chronic insomnia at week 12 between the two groups. All analyses were two-tailed with an alpha level set at P <0.05 and were conducted using SPSS 26.0.

3. Results

As Fig. 1 shows, after the clinical screening, a total of 231 potentially eligible participants were referred from sleep clinics between November 2017 and June 2019, of whom 39 were excluded. Among 192 partici- pants, 95 and 97 were randomized to the CBT-I group and control group, respectively. In the CBT-I group, 89 participants (93.7%) completed 5–7 sessions, 4 (4.2%) completed 1–4 sessions, and 2 (2.1%) did not start the program (reasons unknown).

The mean (SD) age of 192 participants was 35.3 (10.9) years old, and 61.5% (118/192) were female. A total of 153 participants [CBT-I group: 81 (85.3%), control group: 72 (74.2%)] at week 2 and 147 [CBT-I group: 77 (81.1%), control group: 70 (72.2%)] at week 12 completed assess- ments. There were no significant differences in dropout rates and sleep- related medication use between the CBT-I group and control group at

Fig. 1. CONSORT Diagram of Study Enrollment Flow.

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week 2 and 12. Additionally, 160 participants [CBT-I group: 81 (85.3%), control group: 79 (81.4%)] completed the self-evaluation of chronic insomnia at week 12. Finally, 95 participants in the CBT-I group and 97 participants in the control group were included in ITT analysis. In addition, 77 participants in the CBT-I group and 70 participants in the control group were included in PP analysis.

Table 1 compares sample characteristics between groups. No sig- nificant differences were found in age, gender, body mass index, marital status, educational level, employment status, income level, lifestyle factors, physical disease, nap habits, sleep latency, and sleep-related medication between the CBT-I group and control group, suggesting the sample characteristics were similar between groups.

3.1. Primary outcomes

Analyses addressing the treatment effect on the primary outcome measures showed significant differences between the two groups. There were 27 out of 81 in the CBT-I group and 52 out of 79 in control group meeting the diagnostic criteria for chronic insomnia. There was a significantly higher incidence of chronic insomnia in the control group than the CBT-I group (65.8% [52/79] vs. 33.3% [27/81], P <0.001).

3.2. Secondary outcomes

As shown in Table 2, the ISI total score significantly decreased in the CBT-I group from 16.9 (5.2) at baseline, to 10.6 (8.5) at week 2, to 8.7 (7.7) at week 12, but decreased only slightly in the control group. RM- ANOVA revealed significant time main effect, group main effect, and time-by-group interaction between the two groups (Overall P ≤ 0.001). In the PP analysis, similar outcomes were observed [see Supplementary Table 1].

Table 2 showed that there were significant group main effects in ESS,

PSAS, FIRST, and SHPS scores (Overall P < 0.001). In addition, signif- icant time-by-group interactions in ESS, PSAS, FIRST, and SHPS scores were also observed (Overall P < 0.001), suggesting that the improve- ments in daytime sleepiness, pre-sleep arousal, sleep reactivity, and sleep hygiene and practices were more evident in the CBT-I group over time. For DBAS scores, analyses demonstrated dysfunctional beliefs and attitudes about sleep increased over time and there was a significant time main effect (P < 0.001). However, no group main effect and time- by-group interaction were found. Similar outcomes were observed in the PP analysis [see Supplementary Table 1].

Table 2 showed significant group main effect and time-by-group interaction were seen in HADS-Depression, SF-12v2, PCS, and MCS scores (P ≤ 0.003), while no significant differences in group main effect and time by the group were found in HADS-Anxiety scores. This was consistent with the results from the PP analysis [see Supplementary Table 1].

In terms of adherence to individual treatment components [see Supplementary Table 2], more than 60% of participants reported that they followed most items well. However, two items, “Getting out of bed when I cannot sleep” and “Returning only when feeling sleepy after leaving the bed and bedroom” were followed rarely or not at all by more than 40% of participants.

Considering perceived helpfulness [see Supplementary Table 3], most items were reported to be moderately or very helpful. However, more than 27% of participants considered “Getting out of bed when I cannot sleep” and “Do some pastime when I cannot sleep” unhelpful.

4. Discussion

This randomized controlled trial showed that a one-week internet- delivered CBT-I intervention is effective in preventing the progression of acute insomnia to chronic insomnia. In addition, this one-week internet- delivered CBT-I program improved insomnia symptoms, sleep-related symptoms, depressive symptoms, and quality of life among patients with acute insomnia. Unexpectedly, no significant improvement in either dysfunctional beliefs and attitudes about sleep or anxiety symp- toms was observed after the intervention. The excellent compliance rate of 93.7% indicates that this one-week program was well accepted by patients with acute insomnia.

Our findings provide strong support for the hypothesis that one-week internet-delivered CBT-I can prevent the transition into chronic from acute insomnia. This is in line with a randomized trial conducted by Ellis et al. that documented the efficacy of single 60- to 70-min sessions of face-to-face CBT-I with an accompanying self-help pamphlet to treat acute insomnia (Ellis et al., 2015). The current study extended our un- derstanding of CBT-I utility in at least three ways. First, this one-week CBT-I delivered over the internet is likely to be more accessible and less expensive but provides comparable effectiveness. Second, internet-delivered CBT-I also improved other sleep-related symptoms, depressive symptoms, and quality of life in patients with acute insomnia. Third, excellent compliance suggests high acceptability to patients. Notably, some participants (33.3%) in the CBT-I group still developed chronic insomnia at the follow-up despite the intervention, and there- fore, more research is warranted to further enhance the effectiveness of internet-delivered CBT-I intervention among the population with acute insomnia.

Consistent with previous trials (Espie et al., 2019; Blake et al., 2017; Fornal-Pawlowska and Szelenberger, 2013; Kloss et al., 2016) targeting chronic insomnia, participants with acute insomnia in this trial achieved great improvement in daytime sleepiness, pre-sleep arousal, sleep reactivity, and sleep hygiene and practices after internet-delivered CBT-I intervention. Concerning the DBAS, there was a significant improve- ment over time in the CBT-I group in dysfunctional beliefs and attitudes about sleep assessed by DBAS but no statistically significant differences were observed between CBT-group and control group. An internet CBT-I program (SHUTi), consisting of 6 online sessions designed to be

Table 1 General characteristics of participants in two groups.

Characteristic CBT-I Group (N = 95)

Control Group (N = 97)

P value

Gender, female, No. (%) 55 (57.9) 63 (64.9) 0.32 Age, mean (SD), y 35.6 (11.2) 35.0 (10.6) 0.72 BMI, mean (SD), kg/m2 21.3 (2.8) 20.9 (2.9) 0.37 Married, No. (%) 60 (63.2) 68 (70.1) 0.31 Full-time employed, No. (%) 60 (63.2) 60 (61.9) 0.85 Education level (College or

higher), No. (%) 57 (60.0) 62 (63.9) 0.58

Income level (≥ 5000RMB/ month), No. (%)

53 (55.8) 42 (43.3) 0.083

Lifestyle Tea consumption, No. (%) 0.78 Usually/Sometimes 45 (47.4) 44 (45.4) Seldom/Never 50 (52.6) 53 (54.6)

Caffeine consumption, No. (%) 0.94 Usually/Sometimes 20 (21.1) 20 (20.6) Seldom/Never 75 (78.9) 77 (79.4)

Alcohol consumption, No. (%) 0.94 Usually/Sometimes 25 (26.3) 26 (26.8) Seldom/Never 70 (73.7) 71 (73.2)

Smoking, No. (%) 0.63 Usually/Sometimes 7 (7.4) 9 (9.3) Seldom/Never 88 (92.6) 88 (90.7)

Physical disease, No. (%) 40 (42.1) 32 (33.0) 0.19 Nap habit, No. (%) 54 (56.8) 55 (56.7) 0.98 Sleep latency (> 30mins), No.

(%) 59 (62.1) 60 (61.9) 0.97

Average sleep time, mean (SD), h 5.6 (1.9) 5.7 (2.0) 0.82 Subjective sleep time required,

mean (SD), h 7.8 (0.9) 7.8 (0.9) 0.69

Sleep problem duration, mean (SD), mo.

1.3 (0.6) 1.3 (0.6) 0.55

Sleep-related medication, No. (%)

12 (12.6) 16 (16.5) 0.45

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completed weekly during 9 weeks, has been confirmed to improve maladaptive sleep- and insomnia-related cognition compared with dig- ital patient education (Vedaa et al., 2019). Furthermore, a review (Thakral et al., 2020) discussing changes in dysfunctional beliefs about sleep after CBT-I indicated that most randomized controlled trials delivering CBT-I over 6 weeks achieved positive outcomes with mod- erate to large effects on beliefs and attitudes about sleep. Given these findings, the differences between our study and others might be explained in that a single session for cognitive reconstruction in our program is too short to significantly change maladaptive beliefs compared with the control group, which indicates that a brief internet-delivered CBT-I program may include intensive cognitive therapy. In addition, it is notable that insomnia symptoms were signif- icantly improved among the CBT-I group in our study. Therefore, how and to what extent changes in dysfunctional beliefs are associated with improvement in insomnia and related symptoms warrant future inves- tigation. On the other hand, we noticed that control group also achieved improvement, and we speculate that two factors might contribute to this. First, participants in the control group sought information about insomnia and they learned and practiced since they didn’t get any additional inventions from the trial. A similar situation also appeared in another study (Zetterqvist et al., 2003). Second, two scales including the sleep hygiene practice scale and dysfunctional beliefs and attitudes about sleep may serve as a potential education about sleep and insomnia. Further studies are warranted to explore the possible associations.

In our study, the findings revealed that the one-week internet- delivered CBT-I also significantly improved depressive symptoms compared with the control group, which is in line with two randomized controlled trials investigating the effectiveness of SHUTi (Christensen et al., 2016) or Sleepio (Felder et al., 2020). The internet-delivered CBT-I, which targets insomnia, might be one promising strategy to prevent depression in people at risk, based on evidence that insomnia is a strong risk factor for the development of depression, commonly pre- ceding its development (Batterham et al., 2012). In addition, an insomnia intervention would be more acceptable to the public, given that people frequently seek help from family doctors for insomnia (Aikens and Rouse, 2005). A 9-w randomized controlled trial with 6- and 12-mo follow-up, examined the effectiveness of CBT-I versus depression CBT, both delivered by the internet, in 43 adults in whom comorbid insomnia and depression were diagnosed, and the results demonstrated that CBT-I was more effective than depression CBT in reducing

depression symptoms (Blom et al., 2015). Nevertheless, despite these findings, the mechanisms by which insomnia intervention might improve depression remain unclear, warranting further studies. Con- cerning the anxiety symptoms, contrary to the significant improvement found in those studies (Christensen et al., 2016; Felder et al., 2020), we found that there was no significant improvement in anxiety symptoms after the internet-delivered CBT-I intervention. We speculate that two factors may contribute to the inconsistent findings. First, the one-week relaxation training is relatively short to achieve significant improve- ment compared with other online CBT-I programs (Christensen et al., 2016; Felder et al., 2020). Second, only four kinds of relaxation audios were included in the program, while individual preferences and differ- ences in characteristics might influence the effects (Klainin-Yobas et al., 2015; Kwekkeboom and Gretarsdottir, 2006). Besides, the relaxation training was presented via text and audio in the program, which might be not as understandable as animated video (McCarthy, 2015).

The current study had a significantly higher compliance rate than standard online CBT-I with 6 weekly sessions (Christensen et al., 2016; Espie et al., 2019), which indicates that one-week internet-delivered CBT-I is easy for participants to follow. However, two items, “Getting out of bed when I cannot sleep” and “returning only when feeling sleepy after leaving the bed and bedroom”, generated poor adherence and had little perceived helpfulness, which is consistent with group CBT-I (Manber et al., 2011). Therefore, when initiating behavioral therapy, adequate communication and education on these items should be provided.

Several limitations should be considered in the current study. First, we did not collect details about participants’ medication such as types, dose, and compliance. However, rates of medication treatment were comparable between groups at baseline, week 2, and week 12. Second, similar to most randomized controlled trials of CBT-I (Espie et al., 2019; Rajabi Majd et al., 2020; Ritterband et al., 2017), we could not fully implement a double-blinded study design. Third, all measurements were self-reported, which may have led to reporting bias. Notably, the diag- nosis of chronic insomnia, as the primary outcome, was determined via a structured diagnostic questionnaire for insomnia disorder through self-evaluation according to the DSM-5 in our study, and therefore, further clinical trials with more reliable measurements are warranted to confirm the effectiveness of internet-delivered CBT-I among the popu- lation with acute insomnia. Fourth, the information on whether the acute insomnia was a first episode or a recurrent episode at baseline was not collected. Besides, we did not screen for other co-morbid sleep

Table 2 Outcomes of Sleep, depressive and anxiety symptoms and quality of life at Baseline, Week 2 and Week 12 (In intention-to-treatment population).

CBT-I Group Control Group Repeated Measures ANOVA Variables Baseline▴

(N = 95) Week 2▴

(N = 95) Week 12▴

(N = 95) Baseline▴

(N = 97) Week 2▴

(N = 97) Week12▴

(N = 97) P value (between groups)

P value (time)

η2 (time × group)

P value (time × group)

ISI 16.9 (5.2) 10.6 (8.5)

8.7 (7.7) 16.6 (6.0) 12.9 (4.8)

14.2 (4.5) <0.001 <0.001 0.06 0.001

DBAS 94.9 (15.2)

NA 108.7 (19.2)

94.1 (11.5)

NA 106.0 (17.7)

0.42 <0.001 0.003 0.48

ESS 6.7 (3.8) NA 4.7 (4.0) 6.7 (4.4) NA 8.8 (5.8) <0.001 0.91 0.13 <0.001 PSAS 34.8 (7.9) NA 32.2 (9.7) 38.0 (9.1) NA 44.0 (12.9) <0.001 0.046 0.15 <0.001 FIRST 21.4 (4.3) NA 15.7 (4.8) 22.2 (4.3) NA 20.0 (5.6) <0.001 <0.001 0.08 <0.001 SHPS 80.0

(16.6) NA 68.9

(21.7) 77.4 (14.4)

NA 95.3 (21.2) <0.001 0.045 0.31 <0.001

HADS Depression 6.5 (3.8) 5.9 (3.7) 5.6 (3.2) 6.8 (3.6) 7.4 (3.0) 8.6 (4.4) <0.001 0.10 0.08 <0.001 Anxiety 7.0 (3.8) 7.2 (4.1) 8.2 (3.9) 7.3 (3.9) 7.5 (3.2) 9.4 (4.3) 0.20 <0.001 0.01 0.16

SF-12v2 PCS 48.1 (7.0) NA 51.9 (7.6) 48.0 (6.2) NA 45.4 (7.1) <0.001 0.26 0.18 <0.001 MCS 39.6 (8.8) NA 45.5

(11.6) 39.9 (10.0)

NA 36.8 (11.2) 0.003 0.13 0.14 <0.001

Abbreviations: ISI, Insomnia Severity Index; DBAS, Dysfunctional Beliefs and Attitudes about Sleep; ESS, Epworth Sleepiness Scale; PSAS, Pre-sleep Arousal Scale; FIRST, Ford Insomnia Response to Stress Test; SHPS, Sleep Hygiene and Practices Scale; HADS, Hospital Anxiety and Depression Scale; SF-12v2, Short-Form 12-Item Health Survey version 2; PCS, Physical Component Summary; MCS, Mental Component Summary.

▴ Mean values (standard deviation).

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disorders. However, participants with insomnia caused by other sleep disorders could not be better explained by other sleep disorders and did not occur exclusively during the course of those disorders according to the DSM-5, which was used as one inclusion criterion in our study. In addition, this program did not target specific triggers of acute insomnia, and more personalized programs may improve efficacy. Fifth, only participants from sleep clinics were recruited in our study. Therefore, our results may not be generalizable to populations with acute insomnia in other settings, such as community-dwelling populations. Finally, we did not especially record adverse events in the study. Thus, further studies are warranted to comprehensively and systematically investigate the adverse effects of CBT-I in different delivery formats and populations.

In conclusion, the one-week internet-delivered CBT-I program can effectively prevent the progression from acute to chronic insomnia with excellent compliance. In addition, it can improve insomnia symptoms, sleep-related symptoms, depressive symptoms, and quality of life among patients with acute insomnia. One-week internet-delivered CBT-I is inexpensive and has great promise as a treatment strategy for acute insomnia.

Role of funding sources

This work was supported by the National Natural Science Foundation of China (82071488, B. Zhang), the Science and Technology Planning Project of Guangdong Province (B. Zhang), the President Foundation of Nanfang Hospital, Southern Medical University (B. Zhang), and the National Natural Science Foundation of China (81901348, S. Liu). The funders had no role in study design, data collection or analysis, manu- script preparation, or the decision to submit for publication.

CRediT authorship contribution statement

Lulu Yang: Methodology, Formal analysis, Investigation, Data curation, Software, Visualization, Writing – original draft, Writing – review & editing. Jihui Zhang: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data curation, Validation, Writing – review & editing. Xian Luo: Methodology, Resources, Data curation, Project administration. Yuan Yang: Methodology, Resources, Data curation. Yuhan Zhao: Methodology, Resources, Data curation. Fei Feng: Resources, Data curation. Shuai Liu: Methodology, Re- sources, Data curation, Funding acquisition. Chenxi Zhang: Method- ology, Resources, Data curation. Zhe Li: Resources, Data curation. Chao Wang: Resources, Data curation. Wei Wang: Resources, Data curation. Fan Jiang: Resources, Data curation. Yunshu Zhang: Resources, Data curation. Yuanyuan Hu: Resources, Data curation. Changjun Su: Re- sources, Data curation. Huijuan Wu: Resources, Data curation. Huan Yu: Resources, Data curation. Shirley Xin Li: Conceptualization. Yun Kwok Wing: Conceptualization, Supervision, Writing – review & edit- ing. Ying Luo: Resources, Data curation. Bin Zhang: Conceptualization, Data curation, Investigation, Methodology, Project administration, Funding acquisition, Supervision, Writing – review & editing.

Declaration of Competing Interest

The authors have declared that there are no conflicts of interest in relation to the subject of this study.

Acknowledgments

We thank the following hospitals for helping in recruiting partici- pants: Chaohu Hospital of Anhui Medical University, Second People’s Hospital of Yuxi City, Xuanwu Hospital Capital Medical University, Ningbo First Hospital, Longyan Mental Health Center, Third People’s Hospital of Ganzhou, Yueyang Hospital of Integrated Traditional Chi- nese and Western Medicine, Shanghai University of Traditional Chinese

Medicine, Shanghai Mental Health Center, The First Affiliated Hospital of Wenzhou Medical University, Ningbo Kangning Hospital, Shunde Hospital of Southern Medical University, Xiamen Xian Yue Hospital, The Second Affiliated Hospital of Nanchang University, Shandong Mental Health Center, JiangXi Mental Hospital, Hebei General Hospital, Peo- ple’s Hospital of Xinjiang Uygur Autonomous Region.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psychres.2023.115066.

References

Aikens, J.E., Rouse, M.E., 2005. Help-seeking for insomnia among adult patients in primary care. J. Am. Board Fam. Pract. 18 (4), 257–261. https://doi.org/10.3122/ jabfm.18.4.257.

American Psychiatric Association, 2013. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). American Psychiatric Publising, Washington, DC.

Alvaro, P.K., Roberts, R.M., Harris, J.K., 2013. A Systematic Review Assessing Bidirectionality between Sleep Disturbances, Anxiety, and Depression. Sleep. 36 (7), 1059–1068. https://doi.org/10.5665/sleep.2810.

Badiee Aval Baghyahi, S., Gao, Y., Bahrami Taghanaki, H.R., Badiee Aval, M., 2013. 2738 – Reliability and validity of the chinese translation of insomnia severity index (C-ISI) in chinese patients with insomnia. Eur. Psychiat. 28 (1), 1. https://doi.org/10.1016/ S0924-9338(13)77338-3.

Bastien, C.H., Vallières, A., Morin, C.M., 2001. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2 (4), 297–307. https:// doi.org/10.1016/s1389-9457(00)00065-4.

Batterham, P.J., Glozier, N., Christensen, H., 2012. Sleep disturbance, personality and the onset of depression and anxiety: prospective cohort study. Aust. N. Z. J. Psychiatry 46 (11), 1089–1098. https://doi.org/10.1177/0004867412457997.

Blake, M., Schwartz, O., Waloszek, J.M., Raniti, M., Simmons, J.G., Murray, G., Blake, L., Dahl, R.E., Bootzin, R., McMakin, D.L., Dudgeon, P., Trinder, J., Allen, N.B., 2017. The SENSE study: treatment mechanisms of a cognitive behavioral and mindfulness- based group sleep improvement intervention for at-risk adolescents. Sleep 40 (6). https://doi.org/10.1093/sleep/zsx061.

Blom, K., Jernelöv, S., Kraepelien, M., Bergdahl, M.O., Jungmarker, K., Ankartjärn, L., Lindefors, N., Kaldo, V., 2015. Internet treatment addressing either insomnia or depression, for patients with both diagnoses: a randomized trial. Sleep 38 (2), 267–277. https://doi.org/10.5665/sleep.4412.

Boullin, P., Ellwood, C., Ellis, J.G., 2016. Group vs. individual treatment for acute insomnia: a pilot study evaluating a "one-shot" treatment strategy. Brain Sci. 7 (1), 1. https://doi.org/10.3390/brainsci7010001.

Chan, N.Y., Li, S.X., Zhang, J., Lam, S.P., Kwok, A.P.L., Yu, M.W.M., Chan, J.W.Y., Li, A. M., Morin, C.M., Wing, Y.K., 2021. A prevention program for insomnia in at-risk adolescents: a randomized controlled study. Pediatrics 147 (3), e2020006833. https://doi.org/10.1542/peds.2020-006833.

Chen, N.H., Johns, M.W., Li, H.Y., Chu, C.C., Liang, S.C., Shu, Y.H., Chuang, M.L., Wang, P.C., 2002. Validation of a Chinese version of the Epworth sleepiness scale. Qual. Life Res. 11 (8), 817–821. https://doi.org/10.1023/a:1020818417949.

Cheng, S.K., Dizon, J., 2012. Computerised cognitive behavioural therapy for insomnia: a systematic review and meta-analysis. Psychother. Psychosom. 81 (4), 206–216. https://doi.org/10.1159/000335379.

Chervin, R.D., 2014. Common Pitfalls in Sleep Medicine: Case-Based Learning. Cambridge University Press.

Christensen, H., Batterham, P.J., Gosling, J.A., Ritterband, L.M., Griffiths, K.M., Thorndike, F.P., Glozier, N., O’Dea, B., Hickie, I.B., Mackinnon, A.J., 2016. Effectiveness of an online insomnia program (SHUTi) for prevention of depressive episodes (the GoodNight Study): a randomised controlled trial. Lancet Psychiat. 3 (4), 333–341. https://doi.org/10.1016/S2215-0366(15)00536-2.

Ellis, J.G., Cushing, T., Germain, A., 2015. Treating acute insomnia: a randomized controlled trial of a "single-shot" of cognitive behavioral therapy for insomnia. Sleep 38 (6), 971–978. https://doi.org/10.5665/sleep.4752.

Ellis, J.G., Perlis, M.L., Bastien, C.H., Gardani, M., Espie, C.A., 2014. The natural history of insomnia: acute insomnia and first-onset depression. Sleep 37 (1), 97–106. https://doi.org/10.5665/sleep.3316.

Ellis, J.G., Perlis, M.L., Espie, C.A., Grandner, M.A., Bastien, C.H., Barclay, N.L., Altena, E., Gardani, M., 2021. The natural history of insomnia: predisposing, precipitating, coping, and perpetuating factors over the early developmental course of insomnia. Sleep 44 (9), zsab095. https://doi.org/10.1093/sleep/zsab095.

Ellis, J.G., Perlis, M.L., Neale, L.F., Espie, C.A., Bastien, C.H., 2012. The natural history of insomnia: focus on prevalence and incidence of acute insomnia. J. Psychiatr. Res. 46 (10), 1278–1285. https://doi.org/10.1016/j.jpsychires.2012.07.001.

Espie, C.A., Emsley, R., Kyle, S.D., Gordon, C., Drake, C.L., Siriwardena, A.N., Cape, J., Ong, J.C., Sheaves, B., Foster, R., Freeman, D., Costa-Font, J., Marsden, A., Luik, A.I., 2019. Effect of digital cognitive behavioral therapy for insomnia on health, psychological well-being, and sleep-related quality of life: a randomized clinical trial. JAMA Psychiat. 76 (1), 21–30. https://doi.org/10.1001/ jamapsychiatry.2018.2745.

Espie, C.A., Inglis, S.J., Harvey, L., Tessier, S., 2000. Insomniacs’ attributions. psychometric properties of the dysfunctional beliefs and attitudes about sleep scale

L. Yang et al.

Psychiatry Research 321 (2023) 115066

8

and the sleep disturbance questionnaire. J. Psychosom. Res. 48 (2), 141–148. https://doi.org/10.1016/s0022-3999(99)00090-2.

Espie, C.A., Inglis, S.J., Tessier, S., Harvey, L., 2001. The clinical effectiveness of cognitive behaviour therapy for chronic insomnia: implementation and evaluation of a sleep clinic in general medical practice. Behav. Res. Ther. 39 (1), 45–60. https:// doi.org/10.1016/s0005-7967(99)00157-6.

Eysenbach, G., CONSORT-EHEALTH Group, 2011. CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J. Med. Internet Res. 13 (4), e126. https://doi.org/10.2196/jmir.1923.

Felder, J.N., Epel, E.S., Neuhaus, J., Krystal, A.D., Prather, A.A., 2020. Efficacy of digital cognitive behavioral therapy for the treatment of insomnia symptoms among pregnant women: a randomized clinical trial. JAMA Psychiat. 77 (5), 484–492. https://doi.org/10.1001/jamapsychiatry.2019.4491.

Fornal-Pawlowska, M., Szelenberger, W., 2013. [Cognitive behavioral therapy for chronic insomnia]. Psychiatr. Pol. 47 (2), 269–279.

Gao, C.Y., Gan, J.L., Zhao, L.M., Zhu, X.Q., Liang, X.J., Chen, T., 2014. Initial application of Chinese version of Ford insomnia response to stress test scale. J Clin Psychiat 24 (5), 305–307. https://doi.org/10.3969/j.issn.1005-3220.2014.05.008.

Jan, Y.W., Chen, C.W., Yang, C.M., Lin, S.C., 2009. Validation of the Chinese Version of the Pre-Sleep Arousal Scale (PSAS). Archiv. Clin. Psychol. 4 (1), 51–58.

Kloss, J.D., Nash, C.O., Walsh, C.M., Culnan, E., Horsey, S., Sexton-Radek, K., 2016. A "Sleep 101" program for college students improves sleep hygiene knowledge and reduces maladaptive beliefs about sleep. Behav. Med. 42 (1), 48–56. https://doi.org/ 10.1080/08964289.2014.969186.

Kwekkeboom, K.L., Gretarsdottir, E., 2006. Systematic review of relaxation interventions for pain. J. Nurs. Scholarsh. 38 (3), 269–277. https://doi.org/10.1111/j.1547- 5069.2006.00113.x.

Klainin-Yobas, P., Oo, W.N., Suzanne Yew, P.Y., Lau, Y., 2015. Effects of relaxation interventions on depression and anxiety among older adults: a systematic review. Aging Ment. Health 19 (12), 1043–1055. https://doi.org/10.1080/ 13607863.2014.997191.

Kyle, S.D., Morgan, K., Espie, C.A., 2010. Insomnia and health-related quality of life. Sleep Med. Rev. 14 (1), 69–82. https://doi.org/10.1016/j.smrv.2009.07.004.

Lam, E.T., Lam, C.L., Fong, D.Y., Huang, W.W., 2013. Is the SF-12 version 2 Health Survey a valid and equivalent substitute for the SF-36 version 2 Health Survey for the Chinese? J. Eval. Clin. Pract. 19 (1), 200–208. https://doi.org/10.1111/j.1365- 2753.2011.01800.x.

Leung, C.M., Wing, Y.K., Kwong, P.K., Lo, A., Shum, K., 1999. Validation of the Chinese- Cantonese version of the hospital anxiety and depression scale and comparison with the Hamilton Rating Scale of Depression. Acta Psychiatr. Scand. 100 (6), 456–461. https://doi.org/10.1111/j.1600-0447.1999.tb10897.x.

Manber, R., Bernert, R.A., Suh, S., Nowakowski, S., Siebern, A.T., Ong, J.C., 2011. CBT for insomnia in patients with high and low depressive symptom severity: adherence and clinical outcomes. J. Clin. Sleep Med. 7 (6), 645–652. https://doi.org/10.5664/ jcsm.1472.

McCarthy, J., 2015. Evaluating written, audio and video feedback in higher education summative assessment tasks. Issues Educ. Res. 25 (2), 153–169.

Nicassio, P.M., Mendlowitz, D.R., Fussell, J.J., Petras, L., 1985. The phenomenology of the pre-sleep state: the development of the pre-sleep arousal scale. Behav. Res. Ther. 23 (3), 263–271. https://doi.org/10.1016/0005-7967(85)90004-x.

Perlis, M.L., Jungquist, C., Smith, M.T., Posner, D., 2008. Cognitive Behavioral Treatment of Insomnia: A Session-By-Session Guide. Springer, New York.

Qaseem, A., Kansagara, D., Forciea, M.A., Cooke, M., Denberg, T.D., Clinical Guidelines Committee of the American College of Physicians, 2016. Management of chronic insomnia disorder in adults: a clinical practice guideline from the American College of Physicians. Ann. Intern. Med. 165 (2), 125–133. https://doi.org/10.7326/M15- 2175.

Rajabi Majd, N., Broström, A., Ulander, M., Lin, C.Y., Griffiths, M.D., Imani, V., Ahorsu, D.K., Ohayon, M.M., Pakpour, A.H., 2020. Efficacy of a theory-based cognitive behavioral technique app-based intervention for patients with insomnia: randomized controlled trial. J. Med. Internet Res. 22 (4), e15841. https://doi.org/ 10.2196/15841.

Redeker, N.S., Yaggi, H.K., Jacoby, D., Hollenbeak, C.S., Breazeale, S., Conley, S., Hwang, Y., Iennaco, J., Linsky, S., Nwanaji-Enwerem, U., O’Connell, M., Jeon, S., 2022. Cognitive behavioral therapy for insomnia has sustained effects on insomnia, fatigue, and function among people with chronic heart failure and insomnia: the HeartSleep Study. Sleep 45 (1), zsab252. https://doi.org/10.1093/sleep/zsab252.

Ritterband, L.M., Thorndike, F.P., Ingersoll, K.S., Lord, H.R., Gonder-Frederick, L., Frederick, C., Quigg, M.S., Cohn, W.F., Morin, C.M., 2017. Effect of a web-based cognitive behavior therapy for insomnia intervention with 1-year follow-up: a randomized clinical trial. JAMA Psychiat. 74 (1), 68–75. https://doi.org/10.1001/ jamapsychiatry.2016.3249.

Sahoo, S., 2012. Can’t Sleep? Issues of Being an Insomniac. IntechOpen. Seyffert, M., Lagisetty, P., Landgraf, J., Chopra, V., Pfeiffer, P.N., Conte, M.L., Rogers, M.

A., 2016. Internet-delivered cognitive behavioral therapy to treat insomnia: a systematic review and meta-analysis. PLoS One 11 (2), e0149139. https://doi.org/ 10.1371/journal.pone.0149139.

Thakral, M., Von Korff, M., McCurry, S.M., Morin, C.M., Vitiello, M.V., 2020. Changes in dysfunctional beliefs about sleep after cognitive behavioral therapy for insomnia: a systematic literature review and meta-analysis. Sleep Med. Rev. 49, 101230 https:// doi.org/10.1016/j.smrv.2019.101230.

Vedaa, Ø., Hagatun, S., Kallestad, H., Pallesen, S., Smith, O.R.F., Thorndike, F.P., Ritterband, L.M., Sivertsen, B., 2019. Long-term effects of an unguided online cognitive behavioral therapy for chronic insomnia. J Clin Sleep Med 15 (1), 101–110. https://doi.org/10.5664/jcsm.7580.

Yang, C.M., Lin, S.C., Hsu, S.C., Cheng, C.P., 2010. Maladaptive sleep hygiene practices in good sleepers and patients with insomnia. J. Health Psychol. 15 (1), 147–155. https://doi.org/10.1177/1359105309346342.

Yang, Y., Luo, X., Paudel, D., Zhang, J., Li, S.X., Zhang, B., 2019. Effects of e-aid cognitive behavioural therapy for insomnia (eCBT-I) to prevent the transition from episodic insomnia to persistent insomnia: study protocol for a randomised controlled trial. BMJ Open 9 (11), e033457. https://doi.org/10.1136/bmjopen-2019-033457.

Yang, Y.Y., Jun, S., 2022. The effects of cognitive behavioral therapy for insomnia among college students with irritable bowel syndrome: a randomized controlled trial. Int. J. Environ. Res. Public Health 19 (21), 14174. https://doi.org/10.3390/ ijerph192114174.

Zetterqvist, K., Maanmies, J., Ström, L., Andersson, G., 2003. Randomized controlled trial of internet-based stress management. Cogn. Behav. Ther. 32 (3), 151–160. https://doi.org/10.1080/16506070302316.

Zigmond, A.S., Snaith, R.P., 1983. The hospital anxiety and depression scale. Acta Psychiat Scand 67 (6), 361–370. https://doi.org/10.1111/j.1600-0447.1983. tb09716.x.

L. Yang et al.