Evaluation of sleep quality in patients diagnosed with bipolar disorder and major depression during remission period

Abstract

BACKGROUND

Sleep disturbances and residual functional impairment are increasingly recognized as important determinants of outcome in mood disorders, even during remission. Persistent disruptions in sleep may reflect underlying pathophysiological mechanisms and contribute to impaired psychosocial recovery. By comparing remitted bipolar disorder (BD) and major depressive disorder (MDD) patients with healthy controls, the present study sought to clarify the extent of these disturbances and their correlates.

AIM

To evaluate differences in sleep quality, psychosocial functioning, and insomnia severity among remitted patients with BD and MDD, in comparison with healthy controls. A secondary aim was to examine the clinical and psychosocial factors influencing sleep quality within these groups.

METHODS

The study included 135 participants: 45 remitted BD patients, 45 remitted MDD patients, and 45 healthy controls. Sleep quality was assessed with the Pittsburgh Sleep Quality Index, psychosocial functioning with the global assessment of functioning, and insomnia severity with the Insomnia Severity Index. Sociodemographic and clinical characteristics were also recorded. Comparative analyses were conducted to evaluate differences between groups, and regression models were used to identify predictors of sleep quality.

RESULTS

Both BD and MDD groups demonstrated significantly poorer sleep quality and higher insomnia severity compared with healthy controls. Poor sleep quality was observed in 75.6% of BD patients and 57.8% of MDD patients. Group differences were most pronounced in Pittsburgh Sleep Quality Index subdomains including sleep latency, sleep duration, and habitual sleep efficiency. Regression analysis identified insomnia severity (β = 0.510) and functional capacity (β = -0.043) as significant correlates of sleep quality, indicating that greater insomnia severity and lower functioning were independently associated with poorer sleep.

CONCLUSION

The findings underscore that even during remission, BD and MDD are accompanied by substantial impairments in sleep quality and psychosocial functioning. These results highlight the importance of addressing residual symptoms, particularly insomnia and functional difficulties, in long-term management strategies. Interventions aimed at improving sleep and enhancing daily functioning should be considered essential components of treatment to promote recovery and quality of life in remitted patients.

Key Words: Bipolar disorder; Major depressive disorder; Sleep quality; Insomnia; Functioning; Remission

Core Tip: Although remission is often equated with clinical recovery in mood disorders, growing evidence highlights the persistence of subthreshold symptoms, particularly those related to sleep and psychosocial functioning. This study investigates sleep quality, insomnia severity, and functional outcomes in euthymic patients with bipolar disorder and major depressive disorder compared to healthy controls. The findings demonstrate that even during remission, both bipolar disorder and major depressive disorder patients exhibit significantly poorer sleep quality and reduced functioning. Notably, insomnia severity was the most robust predictor of impaired sleep, while higher psychosocial functioning correlated with better sleep outcomes. These results underscore the need for clinicians to adopt a dimensional approach to remission, incorporating residual symptoms such as sleep disturbances and functional impairment into long-term treatment planning.

INTRODUCTION

Bipolar disorder (BD) and major depressive disorder (MDD) are two of the most prevalent and debilitating psychiatric conditions, characterized by disruptions in mood, cognition, and physiological functioning[1]. BD is typified by alternating episodes of mania or hypomania and depression, while MDD manifests through persistent and pervasive depressive symptoms[2]. Among the myriad symptoms that define these disorders, sleep disturbances stand out as both a core feature and a significant marker of disease progression. Sleep irregularities, ranging from insomnia to hypersomnia, not only exacerbate clinical symptoms but also compromise functional recovery and quality of life[3]. Moreover, both functional impairment and poor sleep quality are linked to an increased risk of morbidity and mortality in the general population[4]. Given their prevalence and impact, addressing sleep disturbances and functional impairments is crucial, as they may emerge as dominant symptoms in BD and MDD.

The interplay between sleep and mood regulation has been a focal point of psychiatric research, highlighting the bidirectional relationship wherein sleep disturbances can both result from and contribute to mood dysregulation[5]. In BD, sleep disruptions are integral to the clinical picture, with reduced sleep commonly preceding manic episodes and excessive sleep accompanying depressive phases. Similarly, in MDD, insomnia is one of the most prevalent symptoms, often serving as both a diagnostic criterion and a therapeutic target. These findings suggest that sleep dysfunction is not merely a secondary phenomenon but a central component in the pathophysiology of these disorders. Moreover, persistent sleep disturbances have been linked to treatment resistance, increased relapse rates, and poorer long-term outcomes, emphasizing their role as a prognostic indicator[6].

A crucial mechanism underlying these sleep disturbances is the dysregulation of circadian rhythms, which govern sleep-wake cycles and other physiological processes[7]. Both BD and MDD have been associated with circadian rhythm disruptions, driven by genetic, neurobiological, and environmental factors[8-10]. In BD, circadian instability is closely tied to mood episode recurrence, rapid cycling, and functional impairments[11]. In MDD, alterations in circadian rhythms contribute to the chronicity and severity of depressive symptoms[12]. This shared pathophysiological underpinning offers a compelling explanation for the high prevalence of sleep-related issues across these disorders and highlights the therapeutic potential of targeting circadian dysregulation to improve sleep and stabilize mood.

In literature, despite symptom resolution in remission phases, individuals with BD and MDD often report persistent sleep difficulties, suggesting that underlying neurobiological vulnerabilities remain active[13-16]. Research indicates that poor sleep quality during remission is a critical predictor of relapse and functional decline, reinforcing its importance as a treatment focus[6]. Persistent sleep disturbances may serve as a residual marker of the disorder’s pathophysiology, indicating incomplete recovery and necessitating continued monitoring and intervention. Addressing these disruptions in remission is pivotal for enhancing long-term stability and improving overall patient well-being.

This study aims to investigate sleep quality in individuals with BD and MDD during remission phases, contrasting these findings with those from healthy controls. By examining the persistence of sleep disturbances and functional impairments in the absence of acute mood symptoms, the research seeks to elucidate their role as potential residual symptoms during remission. Ultimately, the findings are expected to contribute to a more nuanced understanding of the interrelationship between sleep, circadian rhythms, and mood disorders, informing the development of more effective and comprehensive treatment strategies.

MATERIALS AND METHODS

Study design and participants

This study aims to compare patients diagnosed with BD and MDD according to Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria during their remission phase, with a control group of healthy individuals, and was conducted at Erzurum City Hospital. The study initially included 50 patients diagnosed with BD, 50 patients with MDD, and 50 healthy controls. Of the 150 individuals enrolled, 15 were excluded according to a priori criteria: Withdrawal of consent (n = 3); clinically significant medical or neurological comorbidity (n = 4; e.g., obstructive sleep apnea, severe cardiovascular disease); use of medications known to affect sleep (n = 4; e.g., beta-blockers, sedatives); and missing primary outcome data or quality-control failure (n = 4). The final analytic sample therefore comprised 135 participants: 45 remitted BD, 45 remitted MDD, and 45 healthy controls. All aged 18-65 years, literate, and without psychiatric treatment changes in the last three months. Participants in the BD and MDD groups were diagnosed according to the DSM-5 criteria, confirmed by two senior psychiatrists. Remission in the BD group was defined as scores of ≤ 7 on the 17-item Hamilton Depression Rating Scale (HAM-D) and ≤ 6 on the Young Mania Rating Scale (YMRS), maintained for at least eight weeks. For the MDD group, remission was defined as a score of ≤ 7 on the HAM-D for at least eight weeks. The healthy controls included individuals with no history of psychiatric disorders and no family history of psychiatric conditions.

Participants aged 18-65 were eligible for inclusion if they met the remission criteria for their respective diagnostic groups (BD or MDD). Exclusion criteria for all groups included significant medical or neurological comorbidities (e.g., sleep apnea, severe cardiovascular disease), use of medications known to influence sleep, such as beta-blockers or sedatives, history of alcohol or substance use disorders, or recent (< 8 weeks) clinically significant changes in psychotropic medications for BD or MDD groups.

Procedure

Sociodemographic and clinical data, including height, weight, and other parameters, will be collected using a specifically designed data form. Participants will complete the Pittsburgh Sleep Quality Index (PSQI), Global Assessment of Functioning (GAF) Scale, Insomnia Severity Index (ISI), YMRS, and HAM-D. Written and verbal informed consent will be obtained from all participants. The healthy control group will be age-matched and gender-matched individuals with no psychiatric diagnoses. The study will examine sleep quality and related parameters across the groups. Height and weight measurements were recorded during clinical assessments to calculate body mass index (BMI). For the healthy controls group, eligibility was determined through structured clinical interviews to confirm the absence of psychiatric disorders, medical conditions that could impair sleep quality, or medications affecting sleep.

Instruments and measurements

Structured Clinical Interview for DSM-5 Disorders - Clinician Version: The Structured Clinical Interview for DSM-5 Disorders - Clinician Version is a structured clinical interview administered by trained clinicians to establish DSM-5 diagnoses. It has been validated and adapted for use in Turkish populations[17]. In this study, it will confirm participants’ diagnoses and identify comorbid psychiatric conditions.

PSQI: The PSQI is a self-report questionnaire assessing sleep quality and disturbances over seven domains: Subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each domain is scored between 0 and 3, producing a total score between 0 and 21, with higher scores indicating poorer sleep quality. The PSQI is widely used to evaluate sleep disorders, with demonstrated reliability and validity[18,19].

GAF: The GAF assesses psychological, social, and occupational functioning on a scale from 0 to 100, with higher scores indicating better overall functioning. Although replaced by more contemporary tools such as the World Health Organization Disability Assessment Schedule in DSM-5, GAF remains a practical measure for tracking overall functioning during treatment[20].

ISI: The ISI evaluates the severity of insomnia symptoms through a 7-item self-report questionnaire, covering dimensions such as difficulty falling asleep, maintaining sleep, early awakenings, and satisfaction with sleep patterns. Scores range from 0 to 28, categorized as no clinically significant insomnia (0-7), mild insomnia (8-14), moderate insomnia (15-21), and severe insomnia (22-28). It is widely utilized for assessing treatment outcomes and insomnia severity[21,22].

YMRS: The YMRS is an 11-item clinician-administered scale assessing the severity of manic symptoms. It evaluates mood, increased energy, sexual interest, sleep reduction, verbal activity, thought processes, motor activity, and other indicators. Items are scored from 0 to 4 or 0 to 8, with higher scores indicating more severe manic symptoms. The YMRS is a standard tool for monitoring manic episodes and treatment outcomes in BD[23,24].

HAM-D: The HAM-D is a clinician-administered scale for assessing depression severity. Initially consisting of 17 items, extended versions include up to 21 items. Symptoms such as depressed mood, guilt, insomnia, appetite loss, and decreased libido are rated from 0 to 4. Total scores classify depression as normal (0-7), mild (8-13), moderate (14-18), severe (19-22), or very severe (23+). HAM-D is widely employed for evaluating depression severity and treatment efficacy[25,26].

Statistical analysis

Descriptive statistics were used to summarize sociodemographic and clinical characteristics. Group differences were analyzed using ANOVA for continuous variables and χ² tests for categorical variables. Post hoc comparisons were conducted using the Bonferroni method to identify pairwise differences between groups. For variables where covariates (e.g., age, gender, BMI) could influence the outcomes, analysis of covariance (ANCOVA) was performed to adjust for these factors. Correlation analyses were conducted to examine relationships between sleep quality, sociodemographic, and clinical variables. Stepwise linear regression analysis was performed to identify significant predictors of sleep quality. Variables that showed significant differences between groups (based on ANCOVA or χ² tests) were included in the model, with predictors retained at P < 0.05.

Ethical approval

The research protocol underwent scrutiny and approval from the Scientific Research Ethics Committee of the University of Health Sciences, Erzurum City Hospital (Approval No. 2024/09-176), adhering strictly to the principles outlined in the Helsinki Declaration.

RESULTS

The study included a total of 135 participants divided equally into three groups: BD (n = 45), MDD (n = 45), and healthy controls (n = 45). The groups were comparable in terms of age (F = 0.123, P = 0.884) and gender distribution (χ² = 0.063, P = 0.969). The mean ± SD age of participants was 42.62 ± 10.39 years, with similar values across the groups: 42.77 ± 10.84 for BD, 41.77 ± 9.53 for MDD, and 42.62 ± 10.39 for healthy controls. Female participants constituted 60.0% of the BD group, 62.2% of the MDD group, and 62.2% of the healthy controls group (Table 1).

Table 1 Descriptive and comparative statistics of the study groups, mean ± SD/n (%).

	Total sample (n = 135)
	Bipolar disorder (n = 45)	Major depressive disorder (n = 45)	Healthy controls (n = 45)	χ2/F	P value4	Effect size5	P value6	P value7	P value8
Age1	42.62 ± 10.39	42.77 ± 10.84	41.77 ± 9.53	0.123	0.884
Education (years)1	9.37 ± 4.09	8.86 ± 4.03	9.88 ± 3.43	0.786	0.458
Gender (female)	27 (60.0)	28 (62.2)	28 (62.2)	0.063	0.969
Body mass index2	31.35 ± 5.79	30.22 ± 5.43	27.73 ± 5.33	4.275	0.003	0.070	1.0	0.008	0.116
Unemployed or irregular work	34 (75.6)	20 (44.1)	7 (15.6)	32.718	< 0.001	0.492	BD > MDB, BD > HC, MDB > HC
Single or no partner	15 (33.3)	10 (22.2)	10 (22.2)	1.929	0.381
Smoker (yes)	23 (51.1)	28 (62.2)	28 (62.2)	1.526	0.466
Lifetime AUD/SUD	5 (11.1)	5 (11.1)	1 (2.2)	19.197	0.205
PSQI total3	7.84 ± 3.10	7.22 ± 3.15	4.64 ± 0.82	8.913	< 0.001	0.200	0.891	< 0.001	< 0.001
Subjective sleep quality3	0.82 ± 0.53	0.82 ± 0.49	0.97 ± 0.14	1.684	0.140
Sleep latency	1.84 ± 1.16	1.84 ± 1.12	1.02 ± 0.33	10.790	< 0.001	0.143	1.0	< 0.001	< 0.001
Sleep duration	0.33 ± 0.73	0.20 ± 0.58	0.91 ± 0.35	22.497	< 0.001	0.258	1.0	< 0.001	< 0.001
Habitual sleep efficiency3	0.64 ± 0.74	0.42 ± 0.65	0.04 ± 0.20	10.915	< 0.001	0.145	0.239	< 0.001	0.011
Sleep disturbances	1.35 ± 0.80	1.28 ± 0.78	1.0 ± 0.36	1.435	0.242
Use of sleep medication3	2.06 ± 1.40	1.82 ± 1.45	0.11 ± 0.31	39.128	< 0.001	0.378	0.763	< 0.001	< 0.001
Daytime drowsiness	0.77 ± 1.14	0.82 ± 1.11	0.46 ± 0.50	0.877	0.419
ISI3	4.95 ± 4.26	3.02 ± 2.95	0.60 ± 1.26	19.207	< 0.001	0.229	0.015	< 0.001	0.002
PSQI total cut-off > 5	34 (75.6)	26 (57.8)	4 (8.9)	43.019	< 0.001	0.565	BD > HC, MDD > HC
GAF3	71.66 ± 11.39	78.46 ± 7.76	88.82 ± 3.83	42.681	< 0.001	0.398	< 0.001	< 0.001	< 0.001

¹Post hoc comparisons were conducted using the least significant difference method following a one-way ANOVA.

²Pairwise comparisons are based on ANCOVA using estimated marginal means, adjusted for covariates (age and gender) with the Bonferroni method for multiple comparisons.

³Pairwise comparisons are based on ANCOVA using estimated marginal means, adjusted for covariates (age, body mass index and gender) with the Bonferroni method for multiple comparisons.

⁴Bipolar disorder, major depressive disorder vs healthy control.

⁵Effect sizes were reported as partial eta squared (ANCOVA) and Cramer’s V (χ²).

⁶Bipolar disorder vs major depressive disorder.

⁷Bipolar disorder vs healthy control.

⁸Major depressive disorder vs healthy control.

AUD: Alcohol use disorder; SUD: Non-alcohol substance use disorder; PSQI: Pittsburgh Sleep Quality Index; ISI: Insomnia Severity Index; GAF: Global Assessment of Functioning; BD: Bipolar disorder; MDD: Major depressive disorder; HC: Healthy control.

BMI

Significant differences in BMI were observed among the groups (F = 4.275, P = 0.003, η² = 0.070). Post hoc comparisons revealed that participants in the BD group had significantly higher BMI compared to the healthy controls group (P = 0.008). Regarding employment, the BD group reported the highest rate of unemployment or irregular work (75.6%) compared to both the MDD (44.1%) and healthy controls (15.6%) groups (χ² = 32.718, P < 0.001, V = 0.492). Similarly, the proportion of participants with PSQI scores above the clinical cut-off (> 5) was significantly greater in both BD (75.6%) and MDD (57.8%) groups compared to the healthy controls group (8.9%), χ² = 43.019, P < 0.001, V = 0.565 (Table 1).

Sleep quality

Sleep quality as measured by the PSQI total score differed significantly across groups (F = 8.913, P < 0.001, η² = 0.200). The BD (7.84 ± 3.10) and MDD (7.22 ± 3.15) groups scored higher than the healthy controls group (4.64 ± 0.82, P < 0.001). Additionally, the ISI scores were significantly elevated in the BD (4.95 ± 4.26) and MDD (3.02 ± 2.95) groups compared to healthy controls (0.60 ± 1.26), F = 19.207, P < 0.001, η² = 0.229. Sleep-specific domains such as sleep latency (F = 10.790, P < 0.001, η² = 0.143), sleep duration (F = 22.497, P < 0.001, η² = 0.258), habitual sleep efficiency (F = 10.915, P < 0.001, η² = 0.145), and use of sleep medication (F = 39.128, P < 0.001, η² = 0.378) also showed significant differences, with poorer scores in BD and MDD compared to healthy controls. Other domains such as subjective sleep quality, sleep disturbances, and daytime drowsiness did not differ significantly among groups (Table 1).

GAF score

GAF scores highlighted significant functional impairments in clinical groups. Participants in the BD (71.66 ± 11.39) and MDD (78.46 ± 7.76) groups exhibited lower GAF scores compared to the healthy controls group (88.82 ± 3.83, F = 42.681, P < 0.001). However, no significant differences were found among the groups for smoking habits (P = 0.466) or marital status (P = 0.381; Table 1).

The relationship between PSQI total scores and key clinical variables

Correlation analyses showed strong associations between PSQI total scores and key clinical variables. PSQI was positively correlated with ISI (r = 0.710, P < 0.01) and BMI (r = 0.207, P < 0.05), and negatively correlated with GAF (r = -0.418, P < 0.01) and smoking status (r = -0.249, P < 0.01). ISI scores showed a similar pattern, being negatively correlated with GAF (r = -0.401, P < 0.01) and positively associated with PSQI (r = 0.710, P < 0.01; Table 2).

Table 2 Correlation analysis of sociodemographic data and clinical characteristics.

Correlation coefficient	Age1	Education1	Female2	BMI1	Irregular work2	Smoker2	ISI1	GAF1
PSQI total	0.000	-0.005	0.131	0.2073	0.1903	-0.2494	0.7104	-0.4184
ISI	-0.036	-0.075	0.051	0.1963	0.1863	-0.1923	1	-0.4014
GAF	-0.059	0.075	-0.036	-0.2384	-0.3384	-0.040	-0.4014	1

¹Pearson correlation coefficient.

²Spearman’s rank correlation coefficient.

³The correlation is significant (two-tailed) at the 0.05 Level.

⁴Correlation is significant at the 0.01 Level (two-tailed).

PSQI: Pittsburgh Sleep Quality Index; ISI: Insomnia Severity Index; GAF: Global Assessment of Functioning; BMI: Body mass index.

A forward stepwise multivariate regression analysis was conducted to identify predictors of sleep quality as measured by the PSQI total score. The final model was significant [F (3,132) = 73.179, P < 0.001] and explained 52.6% of the variance in sleep quality (adjusted R² = 0.519). ISI emerged as the strongest predictor [β = 0.535, P < 0.001, Exp(β) = 1.71, 95% confidence interval: 0.428-0.641], followed by global functioning [GAF; β = -0.043, P = 0.017, Exp(β) = 0.96, 95% confidence interval: -0.078 to -0.008]. The variable “gas” was included in the stepwise model, while work status and BMI were excluded due to non-significance. Collinearity diagnostics indicated no problematic multicollinearity among predictors (variance inflation factor ≤ 1.192). These results suggest that higher insomnia severity and lower global functioning are associated with poorer sleep quality in the sample (Table 3).

Table 3 Stepwise multivariate regression analysis of factors affecting sleep quality.

Variable	β	Significance	95%CI (for β)	VIF
Pittsburgh sleep quality index1
Constant	8.454	< 0.001	5.509-11.400	N/A
Insomnia severity index	0.535	< 0.001	0.428-0.641	1.192
Global functioning	-0.043	0.017	-0.078 to -0.008	1.192

¹A forward stepwise linear regression analysis was conducted. The final model achieved F (3,132) = 73.179, P < 0.001, with an R² of 0.526 and an adjusted R² of 0.519, variables excluded from the model include work status and body mass index.

CI: Confidence interval; VIF: Variance inflation factor; N/A: Not applicable.

DISCUSSION

To the best of our knowledge, the present study is the first to explore the relationship between sleep quality, psychosocial functioning, and insomnia severity in patients with BD and MDD during remission. Our findings indicate a clear inverse relationship between sleep quality and psychosocial functioning in individuals diagnosed with BD and MDD, even during remission. Moreover, strikingly, we observed that approximately 75% of BD patients and 58% of MDD patients experienced poor sleep quality despite being in remission. Additionally, a statistically significant difference in sleep quality among the three groups was observed across multiple PSQI subscales, including sleep latency, sleep duration, habitual sleep efficiency, and the use of sleep medication. Notably, insomnia severity showed the strongest correlation with poor sleep quality, highlighting the persistence of sleep disturbances in these clinical populations.

Both BD and MDD have been shown in previous studies to have significant negative effects on the course of the illness, symptom burden, and functionality due to sleep disturbances[3]. In a study by Keskin et al[4], 56.5% of BD patients were reported to have poor sleep quality, which was suggested to adversely affect the overall functioning of the disorder. MDD patients also exhibit similar sleep characteristics to those with BD, with insomnia symptoms often continuing during the remission phase[27,28]. Furthermore, systematic reviews examining the relationship between depression and sleep have reported that 90% of individuals with depression experience poor sleep quality, with sleep disturbances considered an independent risk factor for the development of depression[29,30]. These findings underscore the need to address sleep disturbances not merely as symptoms but as integral components of the disease process that should be incorporated into treatment strategies. Although circadian dysregulation has been implicated in the pathophysiology of both BD and MDD, our study did not include objective circadian markers such as melatonin profiles or dim-light melatonin onset. Future research should integrate circadian assessments to clarify whether misalignment contributes to residual sleep disturbances during remission.

Given the chronic and evolving course of BD, the link between insomnia, the number of episodes, and the duration of illness may stem from the patient’s clinical state and the progressive impact on neural structures as the condition advances[31]. In BD, the prevalence and intensity of symptoms are closely linked to the severity of psychopathology[32]. Sleep disturbances, a hallmark symptom of BD, are similarly influenced by the condition’s severity. Short sleep duration is associated with more pronounced symptoms, while both excessively short and prolonged sleep durations correlate with reduced functioning and diminished quality of life in individuals with BD[31]. In our study, we found that better psychosocial functioning was associated with improved sleep quality. The association between psychosocial functioning and sleep quality is likely to be bidirectional: Impaired sleep may reduce daytime functioning, while functional difficulties, including occupational and social stressors, may further disrupt sleep. Given the cross-sectional design of the present study, we cannot establish the directionality of this relationship, and longitudinal studies are needed to clarify causality.

BD and MDD are well-documented contributors to diminished functioning across occupational, familial, and social domains[2]. Evidence from a review of studies on psychosocial functioning in BD indicates that 30%-60% of individuals fail to regain their pre-illness level of functioning[33]. Similarly, depression-related functional impairments result in profound disruptions to social and occupational activities, including work, education, leisure, family life, and household responsibilities. These impairments not only reduce quality of life but also strain interpersonal relationships[34]. Although symptomatic remission is often associated with some degree of functional improvement, many individuals continue to face significant functional deficits well beyond the resolution of their symptoms. This delay highlights the disconnect between symptomatic relief and full functional recovery, with the latter often lagging behind the former[35,36].

Poor sleep quality is a well-recognized contributor to significant impairments in functioning and a marked decline in quality of life. It is also linked to the onset or worsening of medical, neurological, and psychiatric conditions[37]. In BD, poor sleep quality has been specifically associated with higher relapse rates, treatment resistance, unfavorable prognoses, reduced functionality, and diminished quality of life[6]. Sleep disturbances are notably prevalent among individuals with BD, exerting a detrimental impact on disease progression, quality of life, functional outcomes, symptom burden, and overall treatment success[3]. Various factors, including older age, elevated BMI, medication use, medical and psychiatric comorbidities, and stress, influence sleep quality and contribute to these adverse outcomes[38]. Consistent with previous research, our findings further underscore a link between poor sleep quality and higher BMI, reinforcing the multifactorial nature of sleep disturbances and their pervasive effects on health. In our sample, BMI was significantly higher in BD patients compared to healthy controls, and a weak positive correlation with PSQI scores was observed. This suggests that elevated BMI may be one of several contributing factors to poorer subjective sleep quality. However, given the small effect size, these findings should be interpreted with caution, and future studies using objective sleep measures are warranted to clarify the role of BMI in sleep disturbances during remission. Another factor identified in our sample was employment status, which differed significantly across groups. Higher rates of unemployment or irregular work were observed in the BD group compared to both MDD and healthy controls. Unemployment may contribute to poorer sleep through increased psychosocial stress, disrupted daily routines, and reduced social and financial stability. Conversely, impaired sleep itself can exacerbate functional difficulties, further hindering occupational engagement. While the present study cannot establish causality, the association highlights the importance of considering socioeconomic variables, particularly employment, when addressing sleep quality in remitted mood disorder patients. In addition to socioeconomic factors, disorder-specific characteristics may contribute to the observed differences between BD and MDD patients. BD is associated with greater circadian instability and heightened vulnerability to rhythm disruption, which may exacerbate sleep difficulties even during remission. Furthermore, differences in medication profiles, such as the use of mood stabilizers or atypical antipsychotics in BD vs antidepressants in MDD, may also influence sleep architecture. Together, these factors suggest that poorer sleep quality in BD is not solely attributable to socioeconomic stressors but may also reflect underlying biological and treatment-related distinctions.

Although treatments for BD and MDD are often regarded as achieving full remission, persistent impairments in sleep quality and overall functioning challenge this assumption. Our findings indicate that even in remission, patients frequently struggle with poor sleep and diminished functionality. It should also be noted that the remission thresholds used (HAM-D ≤ 7 and YMRS ≤ 6) may not fully capture subthreshold mood symptoms. Such residual symptoms, although not meeting the clinical criteria for relapse, could contribute to the persistence of sleep disturbances during remission. These results emphasize the need to redefine treatment objectives, shifting from a narrow focus on symptom control to a more comprehensive strategy that prioritizes restoring sleep quality and enhancing psychosocial functioning to support a more complete and sustained recovery.

Clinical recommendations

From a clinical perspective, our findings highlight the need for targeted management of sleep problems during remission. Evidence-based interventions such as cognitive-behavioral therapy for insomnia, sleep hygiene education, and stimulus control techniques may be effective non-pharmacological options. In cases where symptoms persist or are severe, short-term pharmacological treatments could also be considered as adjunctive measures. Incorporating these approaches into routine follow-up may help mitigate the residual burden of sleep disturbances in patients with mood disorders.

Study limitations

This study has several limitations. While the groups were comparable in age and gender, age-related changes in sleep quality were not explicitly examined, which may have influenced the findings. Sleep quality was assessed using validated scales; however, the absence of objective measures such as polysomnography represents a limitation. In addition, the reliance on self-report scales (PSQI and ISI) may introduce recall or reporting bias. Future studies should incorporate objective methods such as actigraphy or polysomnography to more accurately capture sleep disturbances. The sample size, particularly in the clinical groups, may also restrict the generalizability of the findings. Moreover, participants were recruited from a single tertiary hospital in Turkey, which may limit the generalizability of our findings to other healthcare systems and cultural contexts. Additionally, the cross-sectional nature of the study precludes establishing causal relationships. Finally, the lack of comprehensive evaluations of co-occurring medical conditions and detailed histories of prior health factors should be acknowledged as additional limitations.

CONCLUSION

This study highlights the persistent challenges of poor sleep quality and diminished psychosocial functioning in patients with BD and MDD, even during remission. Sleep and functioning are two aspects that are considered to be most severely affected in these disorders, with sleep disturbances often directly contributing to reduced functionality. These findings underscore the limitations of viewing remission solely as symptom resolution, emphasizing the need to address sleep disturbances as integral components of the disease process. By prioritizing interventions aimed at improving sleep quality and psychosocial functioning, treatment strategies can more effectively support sustained recovery and enhance overall quality of life. Future research should focus on developing and implementing targeted approaches to mitigate these enduring impairments and optimize long-term outcomes for patients with BD and MDD.

ACKNOWLEDGEMENTS

The authors would like to thank the patients and healthy controls for their participation in the study.