Effect of Metacognitive-Based Training on Sleep Quality Among Persons With Alcohol Use Disorder

Article information

Chronobiol Med. 2026;8(1):50-54
Publication date (electronic) : 2026 March 31
doi : https://doi.org/10.33069/cim.2026.0002
Saveetha College of Occupational Therapy, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Tamil Nadu, India
Corresponding author: Vinitha Lakshmi Ravichandran, MOT, Saveetha College of Occupational Therapy, Saveetha Institute of Medical and Technical Sciences (SIMATS), No. 3 Brodies Road, 1st Street, Poonamallee, Saveetha Nagar, Chennai 600056, Tamil Nadu, India. Tel: 91-7397405544, E-mail: vinithalakshmi171@gmail.com
Received 2026 January 7; Revised 2026 February 7; Accepted 2026 February 21.

Abstract

Objective

Alcohol use disorder is associated with compulsive drinking and impaired self-control, often leading to poor sleep quality. This study aimed to assess the effect of metacognitive-based training on sleep quality in persons with alcohol use disorder.

Methods

A quasi-experimental design was used with 30 male patients aged 25–45 years with alcohol use disorder and poor sleep quality, recruited from Recovery Home Foundation, Chennai. They were divided into control (conventional occupational therapy) and experimental (metacognitive-based training) groups. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) before and after the 12-week intervention. Data were analyzed using paired and independent t-tests.

Results

The results showed a significant improvement in sleep quality in the experimental group compared to the control group (mean PSQI score: control 8.53 vs. experimental 4.87; p<0.001).

Conclusion

The study concluded that metacognitive-based training was effective in improving sleep quality among male patients with alcohol use disorder.

INTRODUCTION

Among the most common mental illnesses worldwide, particularly in wealthy and upper-middle-class nations, alcohol use disorders are linked to high rates of death and disease burden, primarily due to medical outcomes such as liver cirrhosis or damage [1]. The expression “alcohol problems” refers to a broad spectrum of undesirable events, including health issues, alcohol dependence, and maladaptive, impaired, or hazardous behavior. Alcohol issues can affect those who drink excessively on rare occasions (accidents, violent crimes, poisoning, etc.) as well as those who drink excessively on a regular basis. For instance, there are more records of men than women having alcohol use disorders, heavy drinking, and receiving treatment for alcoholism. The condition has a varied course with high rates of remission and relapse; its manifestation varies in pattern and intensity in response to environmental factors and life events, such as traumas [2].

Moritz and Woodward [3] initially created a series of training modules known as metacognitive training based on theoretical discoveries on cognitive biases and processes. A group intervenCIMtion called “metacognitive training” informs participants about cognitive distortions and raises their awareness of the negative impacts these biases may have on their daily functioning. Previous studies on metacognitive training have reported improvements in depression and quality of life [4]. It also includes metacognitive regulatory functions, such as planning and monitoring task performance, and evaluating the efficacy of these processes. This has led to an increase in the importance of teaching metacognitive skills in various training programs. There are numerous settings and methods in which metacognitive training can be beneficial for a wide range of age groups. Thus, the primary objectives of metacognitive training are to raise metacognitive awareness and gradually teach the individual how to use metacognitive experience and knowledge to question and arrive at more complex conclusions [2].

Sleep is a more complex neurological state whose main purpose is to provide the body with rest and replenish its energy stores. Sleep disruptions that are frequent and persistent have an impact on a person’s health [5]. It has long been recognized that alcohol has a calming effect. However, excessive alcohol consumption impairs sleep quality, and insomnia is a common complaint among people with alcohol use disorders. Sleep difficulties have been linked to a number of chronic illnesses, including obesity, musculoskeletal conditions, depression, anxiety, and restless legs syndrome. Drinking alcohol also has a variety of negative effects on sleep quality. Numerous studies have demonstrated that while drinking temporarily makes people feel drowsier, it eventually leads to numerous nocturnal and early morning awakenings. In an attempt to have a better night’s sleep, people with alcohol use disorders often drink alcohol before bed. If they have insomnia, a lot of moderate drinkers also consume alcohol right before bed [6].

The term “metacognition” describes how people react to their own ideas and beliefs about sleep, which raises their level of hyperarousal in the context of sleep disturbance [7]. According to Sella et al. [8], a person’s metacognitive activity around sleep includes both their employment of thought-control strategies to address any intrusive thoughts about their sleep and their metacognitive beliefs over whether they have difficulty sleeping. Even negative and undesired thoughts may result from it. Consequently, it has been shown that controlling intrusive thoughts metacognitively before bed has a significant effect on sleep quality [9].

This gap underscores the need for empirical evidence to validate the training’s effectiveness in improving sleep quality. This study aims to provide empirical evidence supporting the use of metacognitive-based training in improving sleep quality among persons with alcohol use disorder. Therefore, this study aims to examine the effect of metacognitive-based training to improve sleep quality among persons with alcohol use disorder. It is hypothesized that the intervention group will demonstrate significantly greater improvements compared to the control group.

METHODS

The study was approved by the Institutional Scientific Review Board of Saveetha College of Occupational Therapy (Ref. No. SCOT/ISRB/045/2025) on 12.02.2025. The recruited participants were informed about the objectives of the study, and written informed consent was obtained.

The research was carried out at Recovery Home Foundation, Chennai, among male patients aged 25–45 years with alcohol use disorder and poor sleep quality. A total of 60 participants were assessed for eligibility. Of these, 5 were excluded for not meeting the inclusion criteria, resulting in 55 eligible participants. Among them, 25 declined to participate due to personal reasons and time constraints. Consequently, 30 participants were allocated equally into the control group (n=15) and the experimental group (n=15). All allocated participants completed the intervention and were included in the final analysis (Figure 1).

Figure 1.

Flowchart of participant enrolment and allocation.

Demographic and clinical details, including sleep patterns and sleep quality, were assessed using the Pittsburgh Sleep Quality Index (PSQI) (Supplementary Material) [10]. After baseline data were obtained, the experimental group received metacognitivebased training, whereas the control group received conventional occupational therapy sessions. The intervention for the experiment group was conducted over 12 weeks, with each session lasting approximately 1 hour and 15 minutes (Table 1). A pre-test assessment was conducted before the initiation of the therapy sessions, and a post-test assessment was conducted during the final session. After completion of the 12-week intervention period, the PSQI was administered to both groups to evaluate the effectiveness of metacognitive-based training on sleep quality among persons with alcohol use disorder (Figure 1).

Intervention schedule and activities for the experimental group over 12 weeks

Control group intervention

Participants allocated to the control group received conventional occupational therapy throughout the 12-week intervention period. The sessions primarily focused on sleep education, wherein participants were informed about normal sleep physiology, the effects of alcohol use on sleep, and the importance of maintaining regular sleep–wake routines. In addition, structured sleep hygiene instructions were provided, including guidance on optimizing the sleep environment, reducing stimulating activities before bedtime, and establishing healthy bedtime practices. Basic relaxation techniques were also incorporated to promote physical and mental relaxation prior to sleep. The control intervention was delivered with the same frequency and duration as the experimental group; however, it did not include any metacognitive-based training components.

Experimental group intervention (metacognitive-based training)

Participants in the experimental group received metacognitivebased training delivered over a period of 12 weeks, with sessions conducted three times per week, each lasting approximately 1 hour and 15 minutes. The intervention was designed to enhance metacognitive awareness, monitoring, and regulation of sleeprelated thoughts and beliefs that contribute to poor sleep quality among persons with alcohol use disorder. The training focused on helping participants recognize, reflect upon, and modify maladaptive cognitive and metacognitive processes associated with sleep disturbances.

The intervention incorporated several structured activities. Sleep-related guided imagery was used to promote awareness of intrusive thoughts and mental imagery occurring before sleep, enabling participants to observe these thoughts without engaging with them. This activity emphasized metacognitive monitoring and cognitive distancing. Journaling activities encouraged participants to record their sleep patterns, pre-sleep thoughts, emotional responses, and coping strategies, thereby fostering selfreflection and insight into repetitive thinking patterns and dysfunctional beliefs about sleep. In the gratitude practice, participants were guided to intentionally shift attention from ruminative or negative sleep-related thoughts toward positive experiences, supporting metacognitive control and attentional flexibility. Motivational interviewing techniques were integrated to enhance awareness of thought–behavior relationships, strengthen selfregulation, and promote adaptive coping strategies for managing sleep-related concerns and alcohol-related triggers.

Throughout the intervention, therapists facilitated discussions aimed at helping participants evaluate the usefulness of their thoughts, challenge rigid beliefs about sleep, and develop healthier metacognitive strategies such as acceptance, thought postponement, and adaptive problem-solving. The intervention emphasized the process of “thinking about thinking” rather than directly modifying thought content, thereby enabling participants to gain greater control over sleep-related cognitive and emotional arousal. This structured metacognitive approach was intended to reduce pre-sleep hyperarousal and improve overall sleep quality.

Statistical analysis

Statistical analysis was conducted using SPSS Statistics version 23.0 (IBM Corp.). Descriptive statistics were used to summarize the data and examine the distribution of variables. The measurement parameters included mean, standard deviation, and range (minimum–maximum) for repeated assessments.

The sample consisted of 30 male participants with alcohol use disorder selected using a convenience sampling technique. As the data were normally distributed, parametric tests were applied to evaluate statistical differences between pre-test and post-test scores within and between groups.

A paired t-test was used to analyze within-group differences (pre-test vs. post-test), while an independent t-test was performed to compare post-test scores between the control and experimental groups to determine the statistical significance of the metacognitive-based training intervention.

RESULTS

Sleep quality improved significantly in both the control and experimental groups from pre-test to post-test. In the control group, the mean PSQI score decreased from 9.40±2.13 at pre-test to 8.53±1.69 at post-test (t=2.385, df=14, p=0.032), indicating a statistically significant improvement. Conventional treatment led to a statistically significant improvement in the control group (Table 2).

Statistical analysis of sleep quality scores between pre-test and post-test in the control and experimental groups

In the experimental group, the mean PSQI score decreased from 9.53±1.81 at pre-test to 4.87±0.83 at post-test (t=15.380, df=14, p<0.001), demonstrating a highly significant improvement. Metacognitive-based training, therefore, resulted in a highly significant improvement within the experimental group (Table 2).

Post-test scores differed significantly between the groups (t=7.555, df=28, p<0.001), with the experimental group showing a lower mean score than the control group, indicating greater improvement in sleep quality (Table 3).

Statistical analysis of post-test level sleep quality scores between control and experimental groups

Table 4 presents the clinical interpretability of PSQI scores based on the established cut-off value (>5 indicating poor sleep quality). At baseline, all participants in both the control and experimental groups (100%) had PSQI scores greater than 5, indicating poor sleep quality. Following the intervention, the control group demonstrated a reduction in mean PSQI scores, suggesting statistical improvement; however, all participants (100%) continued to score above the clinical cut-off of 5, indicating that sleep quality remained within the poor range.

Clinical interpretability of PSQI cut-off change (PSQI >5 vs. ≤5)

In contrast, the experimental group showed substantial clinical improvement. Post-intervention, only 4 participants (26.7%) remained above the cut-off, while 11 participants (73.3%) achieved PSQI scores ≤5, reflecting a transition from poor to good sleep quality. These findings indicate that although conventional occupational therapy contributed to some improvement, metacognitive-based training resulted in both statistically significant and clinically meaningful changes in sleep quality.

DISCUSSION

The study was conducted to explore the effect of metacognitive-based training on sleep quality among persons with alcohol use disorder. The research was carried out at Recovery Home Foundation, Chennai, among male patients aged 25–45 years with alcohol use disorder and poor sleep quality.

A total of 30 participants were selected based on the inclusion and exclusion criteria. The participants were divided into two groups using a lottery method, with 15 participants allocated to the control group and 15 to the experimental group. Baseline assessment was conducted using the PSQI for both groups. The control group received conventional occupational therapy, including sleep education, sleep hygiene protocols, and relaxation techniques, whereas the experimental group received metacognitive-based training. Upon completion of the therapy program, a post-test assessment was conducted using the PSQI for both groups.

The post-test comparison between the control and experimental groups revealed a mean score of 8.53 in the control group and 4.87 in the experimental group, indicating a highly statistically significant difference (t=7.555; p<0.001), and the alternate hypothesis was accepted. These findings indicate that metacognitive-based training resulted in significantly greater improvement in sleep quality compared to conventional occupational therapy.

The results are consistent with a previous study conducted by Cheriki et al. [4], which demonstrated the effectiveness of metacognitive-based training in improving sleep quality and reducing insomnia symptoms among nurses. This supports the evidence that metacognitive-based interventions have a greater impact on sleep quality compared to conventional approaches.

Beyond statistical significance, the observed reduction in PSQI scores in the intervention group reflects a clinically meaningful improvement in sleep quality. A global PSQI score >5 is widely used to indicate poor sleep quality. At baseline, the majority of participants in both groups scored above this clinical cut-off, indicating clinically significant sleep disturbance. Following the intervention, mean PSQI scores in the metacognitive-based training group decreased to below the clinical threshold, suggesting a transition from poor to acceptable sleep quality for a substantial proportion of participants. In contrast, post-intervention scores in the control group largely remained above the cut-off, indicating persistent clinically relevant sleep problems. These findings highlight that metacognitive-based training not only produces statistically significant improvements but also yields changes that are likely to be meaningful in real-world clinical practice.

The present study has certain limitations. The sample size was small and included only male participants, which may limit the generalizability of the findings. Gender-based comparisons were not performed, and long-term follow-up was not conducted. Additionally, the study relied on self-reported measures of sleep quality and lacked assessor blinding. Future studies with larger, more diverse samples and longer follow-up periods are recommended.

This study demonstrates the effectiveness of metacognitivebased training in significantly improving sleep quality among persons with alcohol use disorder. Statistical analysis revealed a highly significant improvement in the experimental group compared to the control group following the intervention. These findings suggest that integrating metacognitive-based training can effectively address sleep quality of life in persons with alcohol use disorder. Moving forward, healthcare strategies may consider adopting this approach to enhance outcomes for this population.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.33069/cim.2026.0002.

Notes

The authors have no potential conflicts of interest to disclose.

Availability of Data and Material

The datasets generated or analyzed during the study are not publicly available due to request from their caregivers but are available from the corresponding author on reasonable request.

Author Contributions

Conceptualization: Vinitha Lakshmi Ravichandran. Funding acquisition: Keerthana Perumalsamy. Investigation: Keerthana Perumalsamy. Methodology: Keerthana Perumalsamy. Project administration: Vinitha Lakshmi Ravichandran. Supervision: Vinitha Lakshmi Ravichandran. Validation: Vinitha Lakshmi Ravichandran. Visualization: Keerthana Perumalsamy. Writing—original draft: Keerthana Perumalsamy. Writing—review & editing: Vinitha Lakshmi Ravichandran, Keerthana Perumalsamy.

Funding Statement

None

Acknowledgments

None

References

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Article information Continued

Figure 1.

Flowchart of participant enrolment and allocation.

Table 1.

Intervention schedule and activities for the experimental group over 12 weeks

Week Sessions Activities
Week 1 1–3 - Pre-test using the Pittsburgh Sleep Quality Index for both groups
- Consent form obtained from both groups
- Introduction about the therapist and patients
Week 2 4–6 - Explanation of the intervention to participants
- Ice-breaker activities
- Sleep education and sleep hygiene protocol classes
Week 3 7–9 - Guided imagery
Week 4 10–12 - Journaling
Week 5 13–15 - Gratitude practice
Week 6 16–18 - Motivational interviewing
Week 7 19–21 - Guided imagery
Week 8 22–24 - Journaling
Week 9 25–27 - Gratitude practice
Week 10 28–30 - Motivational interviewing
Week 11 31–33 - Evaluation and feedback sessions
Week 12 34–36 - Post-test using the Pittsburgh Sleep Quality Index for both groups

Table 2.

Statistical analysis of sleep quality scores between pre-test and post-test in the control and experimental groups

PSQI scores (mean±SD)
t df p
Pre-test (n=15) Post-test (n=15)
Control 9.40±2.13 8.53±1.69 2.385 14 0.032*
Experimental 9.53±1.81 4.87±0.83 15.380 14 <0.001***
*

p<0.05;

***

p<0.001 (paired t-test).

SD, standard deviation. PSQI, Pittsburgh Sleep Quality Index.

Table 3.

Statistical analysis of post-test level sleep quality scores between control and experimental groups

Control (n=15) Experimental (n=15) t df p
PSQI score 8.53±1.69 4.87±0.84 7.555 28 <0.001***

Values are presented as mean±standard deviation.

***

p<0.001 (independent t-test).

PSQI, Pittsburgh Sleep Quality Index.

Table 4.

Clinical interpretability of PSQI cut-off change (PSQI >5 vs. ≤5)

Time point Control group (n=15)
Experimental group (n=15)
Poor sleep (PSQI>5) Good sleep (PSQI≤5) Poor sleep (PSQI>5) Good sleep (PSQI≤5)
Pre-intervention 15 (100) 0 (0) 15 (100) 0 (0)
Post-intervention 15 (100) 0 (0) 4 (26.7) 11 (73.3)

Values are presented as n (%). PSQI, Pittsburgh Sleep Quality Index. PSQI >5 indicates poor sleep quality; PSQI ≤5 indicates good sleep quality.