The effect of chronotypes on follow-up outcomes of patients with substance use disorder

Abstract

Substance use disorder (SUD) can have circadian characteristics and individuals with evening chronotype are more prone to addiction. In this study, the effect of chronotypes on the treatment outcomes of SUD was investigated. The study included 66 patients who were diagnosed with SUD according to DSM-5. Two clinical interviews were conducted at 6-month intervals, and remission/relapse status was evaluated at the second interview. The Structured Clinical Interview Form for DSM-IV Axis I Disorders (SCID-I), Addiction Profile Index Practitioner Form, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Pittsburg Sleep Quality Index and Morningness-Eveningness Questionnaire (MEQ) were applied to the patients. MEQ scores of relapsed patients were found to be different in terms of eveningness than those in remission (45.62 ± 8.70 versus 49.75 ± 7.60, p = 0.045). As the craving and addiction profile index total scores (addiction severity) increased, eveningness chronotype scores also increased (r = − 0.387 and r = − 0.286, respectively). The mean scores of craving and BDI were higher in relapsed patients compared to those in remission (p = 0.003 and p = 0.015, respectively). Our results suggest that patients with SUD had a lower morningness chronotype than the general population; additionally, more relapsed patients had an eveningness chronotype. Thus, chronotypes may play a role in the onset, prevention, and treatment outcome of SUD.

Introduction

Numerous biological, physiological, hormonal, behavioral, and psychological events in living organisms occur in accordance with a certain rhythm. In humans, the sleep–wake cycle, body temperature, and hormone levels, along with some cognitive functions have a daily rhythm called the circadian rhythm [1]. Advancement, delay or disruption in the circadian rhythm is strongly linked to psychiatric illnesses.

Disruptions in the function of the circadian clock, which are involved in the timing of many important functions such as metabolism, sleep/wake cycle, and body temperature regulation, were shown to be associated with many disorders, including substance abuse and addiction [2]. Reward-related behaviors are guided by the mesolimbic dopaminergic pathway, medial prefrontal cortex, amygdala, and hippocampus projecting from the midbrain ventral tegmental area into the nucleus accumbens [3]. Substance use can lead to molecular and neural changes in the mesocorticolimbic regions that contribute to the development of addiction [4]. Substance use can also affect the expression of circadian rhythm genes in the mesocorticolimbic structures [5].

Some circadian clock genes (e.g., PER1, PER2, PER3, and CLOCK genes), which regulate functions such as sleep/wake activity, cognition, and attention, can also regulate dopaminergic activity in the reward areas and were shown to be involved in susceptibility to addiction [6].

Regarding the morningness and eveningness chronotypes, individuals with the eveningness chronotypes were shown to smoke more cigarettes, consume more caffeine and alcohol [7, 8] along with a greater incidence of substances use [9]. Data from these studies support the hypothesis of a link between chronotype and substance use; moreover, eveningness chronotype may be a risk factor for substance use or behaviors that can cause addiction. The reason why individuals with eveningness chronotype use more substances can be interpreted as the extra effort needed to adapt to social jetlag and adjust their daily arousal according to environmental conditions. The use of stimulants may help these individuals to cope with daytime sleepiness, while the use of sedatives can help them sleep earlier at night. For these reasons, eveningness chronotype can be considered as an individual risk factor for addiction [10–12].

Studies have shown that upon substance withdrawal, individuals may be more prone to relapse at certain times of the day. For example, with cigarette withdrawal, the daily rhythm was determined as moderate with an increase in craving in the early morning hours, while heroin withdrawal was associated with a peak in the morning and evening hours and was lowest in the middle of the day [13, 14]. The use of melatonin, which is effective on the circadian rhythm and sleep, was reported to decrease relapse tendencies in individuals with substance use disorder (SUD), and may be effective in reducing seeking behavior, tolerance, and addiction in animals [15–17].

Treatment of SUD is a difficult process that can be affected by many factors, and have short remission periods with a high rate of relapse. Among many other relevant factors, the effect of the circadian system on SUD has been investigated in various studies. However, to our knowledge no study in the literature has investigated the remission/relapse status of patients according to morningness/eveningness characteristics. In the current study, we aimed to evaluate the effect of chronotype preferences on the course of treatment in patients with SUD. We also hypothesized that having the eveningness chronotype may be associated with a low remission rate with substance use.

Materials and methods

This study was conducted on patients with SUD at the Alcohol and Drug Addicts Treatment and Research Center of the Faculty of Medicine, Sakarya University, between June 2018 and September 2018. Ethical approval for the study was obtained from the Ethics Committee of Faculty of Medicine of Sakarya University. Completed voluntary informed consent forms were obtained from the patients prior to the start of the study.

Participants

During the 4-month study period, 586 outpatients applied to the Alcohol and Drug Addicts Treatment and Research Center where the research was conducted. Of these, 246 patients had re-applied for consultations due to relapse and were excluded. Of the remaining 340 patients, 86 patients who were diagnosed with substance use disorder according to DSM-5 and agreed to participate in the study, were included in the study. All participants were at least primary school graduates and were aged between 18–65 years. Patients with psychotic disorder, a history of known neurological/metabolic disease, mental retardation, affected by substance toxicity or withdrawal at a level affecting the quality of the interview, and patients carrying out shift work in the last one month were excluded from the study.

Procedure

The patients were informed about the study details. Informed written consent was obtained from the patients who met the inclusion criteria. All participants were evaluated according to structured clinical interview for DSM-IV (SCID-I) and patients who were included in the study met the criteria for SUD according to DSM-5. Two clinical interviews were held with the patients at a 6-month interval. The first clinical interview was carried out after applying the Addiction Profile Index, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Morningness-Eveningness Questionnaire (MEQ) and Pittsburgh Sleep Quality Index (PSQI) by the same psychiatrist (XX) who is trained both theoretically and practically on the application of these tests. The first interview was conducted with 86 patients, each for approximately 45 min, in a quiet room. Six months after the initial evaluation, clinical interviews were again held to evaluate the treatment process. Relapse and remission were evaluated at the second clinical interview. This interview was carried out over the phone, and after briefly providing some information, a detailed assessment was made of the patient's substance use status. Fifteen out of the initial 86 patients could not be reached at the second interview. Additionally, 4 patients were incarcerated at a controlled environment (prison) and one had died. The second clinical interview evaluating remission was therefore carried out with 66 patients. Patients who did not use any substance for six months or had slipped only once were defined to be in remission. Substance users who experienced partial or complete relapses were accepted as relapsed patients [18].

Data collection tools

Structured Clinical Interview Form for DSM IV Axis I Disorders (SCID-I)

SCID-1 was developed as a semi-structured clinical diagnostic tool by Spitzer et al. in 1983. SCID-1 allows the application of a personal interview to investigate whether a patient had any first axis diagnosis in the last 1 month and/or in the past, according to the DSM diagnostic criteria. The validity and reliability studies for the Turkish form were conducted by Çorapcıoğlu et al. [19].

Addiction Profile Index Practitioner Form

The addiction profile index (API) was developed by Ögel et al. to evaluate different dimensions of addiction and the severity of addiction and consists of 37 questions and 5 subscales [20]. The five subscales include: (1) Substance use characteristics, (2) Addiction diagnostic criteria, (3) The effect of substance use on a person's life, 4) Strength of craving for substance use, (5) Motivation to quit substance use. Each subscale is scored within itself and the score of each subscale determines the total score of the Addiction Profile Index with equal weight. The reason for this is the assumption that each subscale affects the severity of addiction differently. There are different forms that are filled by the patient or by the practitioner. The Addiction Profile Index practitioner form was used in the current study.

Beck Depression Inventory (BDI)

The BDI is a Likert-type self-assessment scale developed by Beck to determine the risk of depression and measure the severity of depressive symptoms. It can be applied to both healthy and psychiatric patient groups. The BDI contains a total of 21 questions. Each item is scored between 0–3 and the total score is obtained by summing the score of each item. The total score varies between 0 and 63. The Turkish validity and reliability study for this scale, conducted by Hisli, indicated that the acceptable cut-off score was 17 [21].

Beck Anxiety Inventory (BAI)

The BAI is a 21-item scale developed by Beck et al., that measures the severity of anxiety symptoms experienced by individuals. It is a four-point Likert-type self-rating scale and the total score varies between 0 and 63. The anxiety levels of the patients according to the scores obtained are as follows: a score of 0–7 is classified as minimal, 8–15 as mild, 16–25 as moderate, and 26 and above as severe level of anxiety. The higher the total scores obtained on the scale, the more severe is the anxiety experienced by the individual. The Turkish validity and reliability studies of the scale were conducted by Ulusoy et al. [22].

Pittsburg Sleep Quality Index (PSQI)

The PSQI was adapted to the Turkish by Agargün et al. [23] PSQI is a 19-item self-report scale that evaluates sleep quality and sleep disorder in the past month. It consists of 24 questions; 19 questions are self-report questions while 5 questions are answered by a spouse or roommate. The 18 questions that are scored consist of 7 components that include Subjective Sleep Quality, Sleep Latency, Sleep Time, Conventional Sleep Efficacy, Sleep Disorder, Sleep Drug Use and Daytime Dysfunction. Each component is evaluated with a score of 0–3 points. The combined scores of the 7 components give the total score of the scale, which ranges from 0–21. A total score of greater than 5 indicates "poor sleep quality".

Morningness-Eveningness Questionnaire (MEQ)

MEQ is a self-report scale developed by Horne and Ostberg in 1976, consisting of 19 questions that classify people into “morning type”, “evening type” and “intermediate type” according to the values obtained in terms of lifestyle, sleep–wake patterns and time of their performances. The answers to this Likert-type scale questions are marked on a ruler. A high score (between 59 and 86) obtained from the scale classifies the person as a morning type and low score (between 16 and 41) as an evening type. A score of 42–58 suggests 'Intermediate type'. MEQ is one of the most widely used scales to investigate chronobiological features in both patient and healthy groups and has been translated into many different languages. The reliability and validity study of the Turkish form was carried out by Agargün et al. [24].

Statistical analysis

The data were recorded and statistically analyzed with SPSS (Statistical Package for Social Sciences) Windows 22.0 program. The suitability of the quantitative data for normal distribution was tested with the Kolmogorov–Smirnov test, and appropriate tests were selected according to the outcomes of this test. Logarithmic transformation was applied where necessary. Student t test and Pearson’s correlation analysis were used in the statistical analysis of quantitative data with a normal distribution. Mann–Whitney U test and Spearman correlation analysis tests were used for the analysis of quantitative data that did not show a normal distribution. Chi-square test was used for the comparison of categorical variables. Categorical variables are shown as frequency and percentage values, numerical variables as mean ± standard deviation or median and interquartile width values. Logistic regression analysis was used to examine the factors affecting relapse rate. Results were evaluated at 95% confidence interval and significance level of p ≤ 0.05.

Results

Sociodemographic data

Evaluation of the remission status of 66 patients after 6 months indicated that 40 (60.6%) patients were in early remission while 26 (39.4%) had relapsed. The characteristics of the patients are shown in Table 1. Briefly, three of the patients in the remission group were female and thirty-seven were male, while one patient in the relapse group was female and twenty-five were male. The patients in the relapse group were on average 4 years younger, but the difference was not statistically significant. No statistically significant relationship was identified between different chronotypes and the reasons for initiating substance use such as reduction of stress, curiosity, pleasure, encouragement from peers or being deceived (p = 0.371).

Table 1.

Comparison of sociodemographic features of remission and relapse groups

	Group		t/X2	p
	Remission (n = 40)	Relapse (n = 26)
Age (mean ± SD)	34 ± 10.8	29.4 ± 8.4	1.868	0.066
Gender
Female	3 (75%)	1 (25%)	0.370	0.543
Male	37 (59.7%)	25 (40.3%)
Education level
Primary	4 (50%)	4 (50%)	0.998	0.802
Middle	23 (59%)	16 (41%)
High	10 (66.7%)	5 (33.5%)
University	3 (75%)	1 (25%)
Marital status
Single	13 (54.2%)	11 (45.8%)	2.586	0.276
Married	18 (58.1%)	13 (41.9%)
Divorced	9 (81.8%)	2 (18.2%)
Occupational status
Employed	26 (65%)	14 (35%)	0.821	0.365
Unemployed	14 (53.8%)	12 (46.2%)
Residential area
Urban	34 (60.7%)	22 (39.3%)	0.002	0.966
Rural	6 (60%)	4 (40%)
Living with
Family	36 (60%)	24 (40%)	0.655	0.418
Friends	1 (50%)	1 (50%)
Alone	3 (75%)	1 (25%)

Chi-square and Student’s t-tests were used

SD standard deviation

Substance use pattern of the participants

The most preferred drug was cannabinoid or synthetic cannabinoid. The relapse rate of those who preferred heroin as a priority was statistically significantly lower than the others (p = 0.017). Additionally, the relapse rate was significantly lower in patients with Opioid Use Disorder compared to patients with other substance use disorders (p = 0.002) (Table 2).

Table 2.

Comparison of the clinical data and the chronotype of remission and relapse groups

	Group		t/u	p
	Remission (n = 40)	Relapse (n = 26)
Age of initial substance use (median IQR)	17.50 (15–20)	16 (15–20)	− 0.937	0.349
Maximum abstinence (months) (median IQR)	11 (3–24)	8.5 (3–14)	− 1.291	0.197
Drug preference
Cannabinoids and SCs	15 (46.9%)	17 (53.1%)	8.191	0.017
Opioid	20 (83.3%)	4 (16.7%)
Stimulants (amphetamine, ecstasy, cocaine or crack)	5 (50%)	5 (50%)
DSM-V diagnosis
Cannabis use disorder	15 (46.9%)	17 (53.1%)	15.121	0.002
Opioid use disorder	24 (85.7%)	4 (14.3%)
Multiple substance use disorder	1 (25%)	3 (75%)
Stimulant use disorder	0 (0%)	2 (100%)
BDI (mean ± SD)	19.75 ± 13.14	27.77 ± 11.9	− 2.513	0.015
BAI (mean ± SD)	16.75 ± 11.78	23.65 ± 15.14	− 1.500	0.139
MEQ (mean ± SD)	49.75 ± 7.6	45.62 ± 8.7	2.040	0.045
API Total (addiction severity) (mean ± SD)	5.49 ± 0.9	5.86 ± 0.91	− 1.639	0.106
API substance use characteristics (median IQR)	1.1 (0.2–1.7)	1.2 (0.3–1.3)	542	0.765
API diagnosis (median IQR)	10 (9–11)	10.5 (9–11)	538	0.811
API effects on life (median IQR)	17 (14–19)	17 (15–18)	521.5	0.984
API craving (median IQR)	3 (2–5)	5 (4–7)	743.5	0.003
API motivation (median IQR)	6 (6–6)	6 (6–6)	516	0.909
Chronotype
Morningness	3 (100%)	0 (0%)	2.141	0.343
Intermediate	31 (59.6%)	21 (40.4%)
Eveningness	6 (54.5)	5 (45.5%)

Chi-square, Student’s t and Mann–Whitney U tests were performed

SD standard deviation, SCs synthetic cannabinoids, IQR interquartile range, BDI Beck depression inventory, BAI Beck anxiety inventory, MEQ morningness/eveningness questionnaire, API addiction profile index

Bold means p ≤ 0.05

Relationship between relapse or remission and other factors

The average BDI score of the relapsed patients was significantly higher than the patients who underwent remission (p = 0.015). No statistically significant difference was identified in the BAI and API total score (addiction severity) between patients who underwent remission or had relapsed. The mean morningness/eveningness score for the relapsed patients was statistically significantly lower (low score is evaluated in the direction of eveningness) than the patients who underwent remission (p = 0.045) (Table 2). The API total and sub-parameter scores indicated that craving was statistically significantly higher in the relapsed patients (p = 0.003). No significant difference could be identified in any of the other sub-parameters (Table 2). Additionally, no statistically significant difference in morningness, intermediate and eveningness chronotype features could be identified between the remission and relapsed patients. No relapse was observed in three patients with morningness chronotype, while 40.4% of the intermediate types and 45.5% of the eveningness type underwent relapse (Table 2).

Relationship Between Relapse or Remission and Sleep Quality

A comparison of the PSQI total and subscale scores of the remission and relapse groups is shown in Table 3. No statistically significant difference was found in the PSQI subscale scores, excluding daytime dysfunction, between the two groups. Daytime functionality was significantly more impaired in the relapse group compared to the remission group (p = 0.020). Evaluation of accompanying sleep disorders indicated that the frequency of episodes of disorientation or confusion during sleep was higher in the relapse group (p = 0.006).

Table 3.

Comparison of the PSQI total and subscale scores of remission and relapse groups

	Remission (n = 40)	Relapse (n = 26)	X2/t	p
PSQI—subjective sleep quality	Very good = 3 (7.5%) Fairly good = 15 (37.5%) Fairly bad = 13 (32.5%) Very bad = 9 (22.5%)	Very good = 2 (7.7%) Fairly good = 7 (26.9%) Fairly bad = 10 (38.5%) Very bad = 7 (26.9%)	0.817	0.845
PSQI—sleep latency	0 score = 4 (10.0%) < 1 scores = 11 (27.5%) 1–2 scores = 16 (40.0%) > 3 scores = 9 (22.5%)	0 score = 3 (11..5%) < 1 scores = 10 (38.5%) 1–2 scores = 8 (30.8%) > 3 scores = 5 (19.2%)	1.079	0.782
PSQI—sleep duration (hours)	> 7 h = 14 (35.0%) 6–7 h = 14 (35.0%) 5–6 h = 8 (20.0%) < 5 h = 4 (10.0%)	> 7 h = 8 (30.8%) 6–7 h = 7 (26.9%) 5–6 h = 10 (38.5%)  < 5 h = 1 (3.8%)	3.165	0.367
PSQI—habitual sleep efficiency	> 85% = 23 (57.5%) 75–84% = 3 (7.5%) 65–74% = 8 (20.0%)  < 65% = 6 (15.0%)	> 85% = 15 (57.7%) 75–84% = 3 (11.5%) 65–74% = 3 (11.5%) < 65% = 5 (19.2%)	1.129	0.770
PSQI—sleep disturbances	0 score = 2 (5.0%) 1–9 points = 13 (32.5%) 10–18 points = 19 (47.5%) 19–27 points = 6 (15.0%)	0 score = 0(0%) 1–9 points = 4 (15.4%) 10–18 points = 12(46.2%) 19–27 points = 10 (38.5%)	6.676	0.083
PSQI—use of sleeping medication	Not during past month = 21 (52.5%) Less than once a week = 2 (5.0%) Ones or twice a week = 3 (7.5%) Three or more times a week = 14 (35.0%)	Not during past month = 13 (50.0%) Less than once a week = 2 (7.7%) Ones or twice a week = 2 (7.7%) Three or more times a week = 9 (34.6%)	0.209	0.976
PSQI—daytime dysfunction	0 score = 11 (27.5%) 1–2 scores = 16 (40.0%) 3–4 scores = 11 (27.5%) 5–6 scores = 2 (5.0%)	0 score = 1 (3.8%) 1–2 scores = 8 (30.8%) 3–4 scores = 12 (46.2%) 5–6 scores = 5 (19.2%)	9.800	0.020
PSQI—sleep quality	Good = 6 (15.0%) Poor = 34 (85.0%)	Good = 1 (3.8%) Poor = 25 (96.2%)	2.068	0.231
Global PSQI SCORE	8.47 ± 3.72	10.03 ± 3.35	− 1.647	0.100
Sleep problems reported by bed partner or roommate
Loud snoring	Not during past month = 20 (55.6%) Less than once a week = 4 (11.1%) Ones or twice a week = 5 (13.9%) Three or more times a week = 7 (19.4%)	Not during past month = 12 (54.5%) Less than once a week = 1 (4.5%) Ones or twice a week = 5 (22.7%) Three or more times a week = 4 (18.2%)	1.316	0.725
Long pauses between breaths while asleep	Not during past month = 20 (55.6%) Less than once a week = 4 (11.1%) Ones or twice a week = 3 (8.3%) Three or more times a week = 9 (25.0%)	Not during past month = 13 (59.1%) Less than once a week = 2 (9.1%) Ones or twice a week = 3 (13.6%) Three or more times a week = 4 (18.2%)	0.738	0.864
Legs twitching or jerking while you sleep	Not during past month = 14 (38.9%) Less than once a week = 6 (16.7%) Ones or twice a week = 8 (22.2%) Three or more times a week = 8 (22.2%)	Not during past month = 5 (22.7%) Less than once a week = 5 (22.7%) Ones or twice a week = 8 (36.4%) Three or more times a week = 4 (18.2%)	2.451	0.484
Episodes of disorientation or confusion during sleep	Not during past month = 22 (61.1%) Less than once a week = 4 (11.1%) Ones or twice a week = 4 (11.1%) Three or more times a week = 6 (16.7%)	Not during past month = 5 (22.7%) Less than once a week = 9 (40.9%) Ones or twice a week = 6 (27.3%) Three or more times a week = 2 (9.1%)	12.368	0.006
Other restlessness while you sleep, please describe	Not during past month = 21 (58.3%) Less than once a week = 3 (8.3%) Ones or twice a week = 5 (13.9%) Three or more times a week = 7 (19.4%)	Not during past month = 9 (40.9%) Less than once a week = 4 (18.2%) Ones or twice a week = 4 (18.2%) Three or more times a week = 5 (22.7%)	2.132	0.545

Chi-square, Student’s t tests were performed

SD standard deviation, IQR interquartile range, PSQI Pittsburg sleep quality ındex

Bold means p ≤ 0.05

The patients were also divided into 2 groups according to whether they went to bed before/after midnight. We observed that the craving scores of late sleepers were significantly higher than the early sleepers (p = 0.003). No significant difference was found in the age of initial substance use, episode of maximum abstinence, drug preference, DSM-5 diagnosis, BDI, BAI, MEQ, PSQI global score, API total and subscale score and remission rate between late sleepers and early sleepers. A comparison of the clinical data of the late and early sleepers is shown in Table 4.

Table 4.

Comparison of the clinical data of the groups according to bedtime

	Group		t/u	p
	I. Group (n = 41)	II. Group (n = 45)
Age of initial substance use (median IQR)	18 (15–22)	16 (15–18)	− 1.884	0.060
Maximum abstinence (months) (median IQR)	9 (3–16.50)	8 (3–15.50)	− 0.438	0.661
Drug preference
Cannabinoids and SCs	21 (51.2%)	24 (53.3%)	0.049	0.976
Opioid	14 (34.1%)	15 (33.3%)
Stimulants (amphetamine, ecstasy, cocaine or crack)	6 (14.6%)	6 (13.3%)
DSM-V diagnosis
Cannabis use disorder	22 (53.7%)	20 (44.4%)	2.564	0.633
Opioid use disorder	16 (39.0%)	17 (37.8%)
Multiple substance use disorder	2 (4.9%)	5 (11.1%)
Stimulant use disorder	1 (2.4%)	2 (4.4%)
BDI (mean ± SD)	22.90 ± 13.66	25.73 ± 13.89	− 0.951	0.344
BAI** (mean ± SD)	18.56 ± 14.37	22.02 ± 13.61	− 1.147	0.255
MEQ (mean ± SD)	48.73 ± 8.51	45.73 ± 8.16	1.667	0.099
API total (addiction severity) (mean ± SD)	5.55 ± 1.01	5.89 ± 0.96	− 1.619	0.109
API substance use characteristics (median IQR)	1.18 (0.18–2.2)	1.1 (0.27–1.3)	− 0.096	0.765
API diagnosis (median IQR)	10.5 (8.5–12)	10 (8.7–11)	− 1.057	0.811
API effects on life (median IQR)	17 (14.5–19)	17 (13.5–18)	− 0.431	0.984
API craving (median IQR)	4 (2–6)	5 (3–7)	− 2.197	0.003
API Motivation (median IQR)	6 (6–6)	6 (6–6)	− 0.999	0.909
PSQI total score	8.24 ± 3.97	9.40 ± 3.49	− 1.435	0.155
Remission status
Remission	18 (60%)	22 (61.1%)	0.008	0.927
Relapse	12 (40%)	14 (38.9%)

Chi-square, Student’s t and Mann–Whitney U tests were performed

I. Group group going to bed before midnight, II. Group group going to bed after midnight, SD standard deviation, SCs synthetic cannabinoids, IQR interquartile range, BDI Beck depression inventory, BAI Beck anxiety inventory, MEQ morningness/eveningness questionnaire, API addiction profile index, PSQI Pittsburg sleep quality index

Bold means p ≤ 0.05

Evaluation of the relationship between chronotype and other scales

The correlations between MEQ scores and depression, anxiety levels, and addiction profile scores are shown in Table 5. A negative correlation was identified between craving and API total scores (p = 0.001) as well as between craving and MEQ scores (p = 0.020). Increases in the craving and API total score were associated with a stronger eveningness chronotype. No statistically significant correlation could be identified between the other sub-parameters.

Table 5.

Correlations between MEQ scores and depression, anxiety levels and addiction profile scores

	MEQ scores
	r	p
BDI	− 0.276	0.025
BAI	− 0.259	0.036
API substance use characteristics	− 0.005	0.968
API diagnosis	0.013	0.915
API effects on life	− 0.123	0.324
API craving	− 0.387	0.001
API motivation	0.106	0.398
API total (addiction severity)	− 0.286	0.020

Pearson and Spearman correlation test was performed where appropriate

BDI Beck depression inventory, BAI Beck anxiety inventory, MEQ morningness/eveningness questionnaire, API addiction profile index

Bold means p ≤ 0.05

A negative correlation was found between BDI and MEQ scores (p = 0.025) as well as between BAI and MEQ scores (p = 0.036) scores. Patients tended to have more eveningness chronotype as the depression and anxiety scores increased (Table 5). Logistic regression analyses revealed that having a lower MEQ score, which means being in the eveningness chronotype, could significantly predict the relapse rate among substance users (p = 0.046, 95.0% C1 0.851–0.999) (Table 6). However, a long duration of abstinence from substance use could reduce relapses (p = 0.029, 95.0% C1 0.884–0.994).

Table 6.

Examination of the factors affecting relapse by logistic regression analysis

Predictor	Presence of relapse
	B	S.E.	EXP(B)	95.0% CI for EXP	p
Constant	6.810	3.508	906		0.052
MEQ score	− 0.082	0.041	0.489	0.851–0.999	0.046
Age of initial substance use	− 0.050	0.073	0.951	0.825–1.096	0.951
Maximum abstinence (months)	− 0.065	0.030	0.937	0.884–0.994	0.029
Employment status (0 = employed, 1 = unemployed)	1.001	0.648	2.720	0.764–9,682	0.122
Co-habitants (0 = others, 1 = with family)	− 0.103	0.907	0.902	0.153–5.332	0.909
Regular physical activity (0 = no, 1 = yes)	− 0.948	0.884	0.283	0.069–2.190	0.283
Types of family structures (0 = nuclear family 1 = extended family)	− 1.187	0.681	0.305	0.080–1.161	0.082

The following values verify that the created model of logistic regression analysis fits the observed data well: the value of Cox and Snell R square is 0.223, the value of Nagelkerke’s R square is 0.302. the p value of logistic regression model is statistically significant (p = 0.020), and the value of Hosmer–Lemeshow test is 0.585

MEQ morningness/eveningness questionnaire

Bold means p ≤ 0.05

Discussion

SUD is an important and universal problem that continues to threaten public health. Although various aspects of SUD have been investigated, research on the effect of chronotype is still scarce. To our knowledge, none of the available studies have evaluated the effect of chronotype characteristics in the remission/relapse process of SUD patients. The findings of the current study indicate that patients with SUD who have high craving, more eveningness characteristics, and more depressive complaints have a higher tendency to relapse.

Re-evaluation of 66 patients with SUD 6 months later revealed that 40 (60.6%) of the patients were in early remission while 26 (39.4%) had relapsed. Early remission and continuous remission are both indicated in SUD according to DSM-5. Early remission is defined as a lack of meeting p any diagnostic criteria for at least 3 months, less than 12 months after meeting the substance use criteria completely. Failure to meet the substance use criteria for 12 months or more is defined as continuous remission [25]. The incidence of patients remaining in remission may differ according to the sample characteristics, methods used, and the follow-up periods in different studies. The current study showed an approximately 60% remission rate, which is higher than the findings of previous studies after SUD treatment [26, 27].

Previous studies have reported relapse rates of 66–86% while a review article reported a remission rate of 35–54.4% after an average of 17 years of follow-up [26–28]. The difference in remission rates reported previously and observed in the current study may be attributed to the use of buprenorphine by opioid use disorder patients. This drug had a relatively short follow-up period in the current study. Additionally, relapse rates were not determined by toxicological analysis in all patients in the current study, which may also have contributed to the differences in remission rates.

We observed a significantly lower relapse rate in patients with opioid use (such as heroin) disorder, compared to patients with other substance use disorders. A Cochrane meta-analysis that included 31 randomized studies reported that buprenorphine was an effective drug in opioid use disorder [29]. We believe that the widespread prevalence (85.71%) of patients under maintenance therapy with a combination of buprenorphine/naloxone in our clinic could have contributed to a lower relapse rate among patients who used heroin or other opioids compared to the other patients.

We observed no significant difference in substance use characteristics, diagnosis, effects on life and motivation sub-parameters, and API total scores between patients who underwent remission or relapse. The craving sub-parameter score was found to be significantly higher in patients with relapse, and this was consistent with findings from previous studies, showing that craving is one of the important variables for relapse in patients with SUD [30, 31].

We did not observe any significant effect of social factors such as employment status, co-habitants, regular physical activity and type of family structure on relapse. A negative relationship was identified between relapse rates and living with the family, living in an extended family and exercising regularly. Unemployment and economic distress are well-established chronic stressors that act as risk factors for relapse [32, 33]. In addition, marriage is known to have a protective effect on SUD [34, 35]. Family support was found to be an important motivating factor in quitting alcohol and was shown to contribute to remission [36]. However, it should be kept in mind that the level of interpersonal relationships in each family may differ. Family dynamics, commitment between family members, distribution of family responsibilities and expectations may differ widely. Therefore, detrimental family circumstances may exacerbate the risk for relapse in this group of patients who have difficulties in solving problems and therefore have a tendency for substance abuse [37, 38]. However, further in-depth studies are needed to firmly establish this. Physical activity is thought to induce psychotropic effects such as happiness, euphoria, and tranquility that are also elicited by Δ9-THC, the active ingredient in cannabis; endocannabinoids may also mediate the peripheral and central effects of exercise [39, 40]. Although limited data are available on the relationship between physical activity and SUD, a positive effect of physical activity on depression and anxiety as well as coping with abstinence is already known. This suggests that engaging in physical activities can have a positive role in the treatment of SUD [41]. This relationship did not reach statistical significance in the present study, most likely due to the relatively small sample size.

Correlation analyses between the API and MEQ scores revealed the presence of a negative correlation between craving and API total scores as well as between craving and MEQ scores. The API total score indicates the severity of addiction. Patients with a stronger eveningness chronotype tended to show an increase in addiction severity and craving. Previous reports suggest that individuals who are eveningness type use more substances than the morningness type; therefore, having the eveningness chronotype may be a risk factor for behaviors that can cause addiction [9]. The effort to adapt to the needs of daily activities and social environment can be attributed to the relationship between chronotype and substance use [42]. Additionally, eveningness-type individuals may seek novelty or excitement and their high impulsivity may increase the tendency towards substance use [43, 44].

Circadian genes are thought to be an important biological factor, in addiction susceptibility to SUD, as patients with SUD have an impaired daily rhythm and abnormal circadian functioning. Addictive substances can change the molecular and behavioral rhythms by changing the clock in the limbic regions independently of the suprachiasmatic nucleus. In addition, substances can alter circadian gene expression in reward-related centers of the brain, and reward sensitivity for some substances may be affected by the knockdown of certain circadian genes [2]. Reward-related behaviors in humans are known to possess a circadian regulation. Studies conducted on inpatients indicated that nicotine craving after quitting smoking was low in the morning and gradually increased during the day, suggesting that it may have a daily rhythm [13, 45]. A daily rhythm for heroin withdrawal has also been reported in the form of low cravings at noon and peaking in the morning and evening [14]. In addition, it is thought that circadian clock genes may change in reward-related mechanisms; thus, relapse may occur at certain times of the day in individuals undergoing withdrawal [46]. Overall, individuals with an eveningness chronotype may experience more craving and are more prone to relapse, but not for the risk of addiction.

A comparison of the clinical data of remission and relapse groups in the current study showed that the mean BDI score in relapsed patients with SUD was statistically significantly higher than those who underwent remission (Table 2). A meta-analysis including eighteen studies carried out with the general population using questionnaires indicated the presence of a strong association between major depression and substance use [45, 47]. Treatment compliance is difficult in the presence of comorbid conditions accompanying SUD. In this case, the severity of both disorders increase, and more frequent and rapid slips may be experienced [48].

A negative correlation was identified between depression and anxiety scores as well as depression and MEQ scores. As the depression and anxiety scores of the patients increased, the tendency to have a more eveningness chronotype increased. Individuals with the eveningness chronotype were reported to have more frequent and severe depressive symptoms and were diagnosed with major depressive disorder more often [49–54]. The data on anxiety are contradictory. Although there are studies showing that anxious symptoms are more common in evening types and the presence of an anxious temperament is generally more common [54–57], there are also studies showing that anxiety disorders are not related to an evening chronotype [49]. A significant relationship between eveningness chronotype and high anxiety scores was identified in the current study.

Around 40% of the general adult population is thought to have a morningness or eveningness chronotype (20% with morningness and 20% with eveningness) while 60% have an intermediate chronotype. Among patients with SUD in the current study, this distribution was quite different, with only three patients (4.5%) identified as morningness, 16.7% as eveningness, and the remainder (78.8%) as intermediate type. Chronotype can change according to age; nonetheless, the morning chronotype is said to be more permanent than the evening type; the latter is more likely to change to another chronotype [58]. The distribution of chronotypes in an addicted group with an average age of 40 years was reported as 20% morningness, 32% eveningness and 48% intermediate type. Thus, the incidence of morningness was similar to the general population, while the incidence of evening type was slightly higher [12]. Another study carried out in a cohort of non-dependent individuals with an average age of 51.2 years reported that 28% of participants were the morning type, and 20% were the evening type [59]. Students aged 21–30 years were reported to be 20% morning and 20% evening type [7]. Yet another study in which the participants had a mean age of 37.8 years, 19% were the morning type and 14% evening type [60]. The average age of patients included in the current study was 32.1 years. Comparing the distribution of chronotypes of the cohort of the current study with similar age groups in the literature indicated that the morningness chronotype was significantly lower in the current cohort than in the general population. This skewed balance of the chronotype among the SUD patients in the current study may have caused a shift in the rhythm of the patients towards eveningness and intermediate type in parallel with the substance and pleasure-seeking behavior. An alternative interpretation may be that the morningness chronotype is protective for the development of SUD, which should be investigated in larger samples. This remarkable difference in chronotypes also suggests that better remission may be achieved by returning the patient to their previous rhythms (such as morningness) with the application of social rhythm therapy in the treatment of SUD.

The primary research question of the current study was whether remission or relapse rates can vary according to the chronotype. We found that the mean MEQ score was significantly lower in relapsed patients than in patients under remission. The fact that only 3 morningness patients were detected in our study while the majority were of the intermediate type made it difficult to group the results of the study according to chronotypes. Therefore, we preferred to interpret the relationship between the mean MEQ scores of the patients with relapse and remission; we observed that relapsed patients had a stronger eveningness chronotype.

Despite the limited amount of data from previous studies, it has been suggested that chronic exposure to circadian changes can lead to an increase in alcohol intake. This has been particularly reported among nurses, individuals who travel frequently and experience jet lag, and those who work night shifts. In addition, nurses working in the night shift were found to smoke more. However, none of the studies have addressed the relationship between remission or relapse and the circadian rhythm or chronotype after SUD treatment [61, 62]. The relationship between the mesolimbic system and circadian clock proteins has been shown. Certain times of the day are preferred for substance intake, and craving shows a daily rhythm [5]. In addition, an in vivo rodent study showed that relapse could be prevented by administering casein kinase 1δ, a posttranslational modulator of the circadian genes, to rats consuming alcohol for a long time [63]. Overall, these studies suggest that the circadian system and chronotype can be important in the relapse process in SUD. More research is needed to test the hypothesis that chronotherapeutics and social rhythm therapy can contribute to the treatment of SUD.

Animal studies suggest that the motivation to seek and use substances can change throughout the day; human studies also indicate that craving and mesolimbic activity can change during the day, highlighting the importance of the time of the day for relapse [5]. Although the number of patients with the morningness chronotype in the current study was very low (n = 3) none of these patients underwent a relapse. Rather, more relapses were observed in patients with an eveningness chronotype; moreover, the relapsed patients displayed the eveningness chronotype more strongly. These data provide an indication, albeit limited, of the relationship between chronobiology and remission from SUD suggesting that having an eveningness chronotype could carry a stronger risk for relapse. Our data also supports the presence of a relationship between relapse and the circadian system in SUD. In addition, individuals with an evening chronotype may carry a higher risk of relapse, although studies with larger samples are needed to establish this better.

Since the Fall of 2016, the local time in Turkey is assigned as UTC + 03:00 throughout the year and is called Turkey Time (TRT). Although the concept of daylight-saving time (DST) was designed to save energy and to enable people to benefit more from the available daylight, its effect on health has not been clearly determined. With the transition to DST or exit from DST, nighttime sleep quality may deteriorate and sleep efficiency may decrease. Forcing chronotype features to adapt to this phase shift may lead to alterations in mood and behavior. Evening types generally have more difficulty in adapting to DST. In addition, forcing evening-type individuals to get up earlier in the morning for work or school with DST may increase the level of social jetlag [64, 65]. Therefore, avoiding DST and maintaining a standard time throughout the year may prevent a difficult phase shift and may reduce the level of social jetlag.

The current study has some limitations including a relatively small number of patients, the majority of the patients being male, and the inability to reach 20 patients during the second interview. Another limitation of the study is that the relapse rates were not determined by toxicological analysis. Additionally, assuming that many patients with substance use disorder also abuse alcohol, the fact that alcohol use was not questioned in our study can also be considered as a limitation.

Conclusion

The severity of depression, high craving, and having an eveningness chronotype among patients with SUD were found to be associated with relapse. Studies with larger samples are needed to firmly establish this relationship with chronotype and incorporate chronotherapeutics and social rhythm therapy in the treatment of SUD patients.

Author contributions

Conceptualization: OAC, ASC; Methodology: OAC, ABY, HB, ŞG; Formal analysis and investigation: OAC, ASC, ABY; Writing—original draft preparation: OAC, ASC; Writing—review and editing: ABY, HB, ŞG; Resources: OAC, ASC; Supervision: ABY, HB, ŞG.

Declarations

Conflict of interest

None of the authors report any conflict of interest for this article.

Ethical approval

Ethical approval for the study was obtained from the Ethics Committee of Faculty of Medicine of Sakarya University. Completed voluntary informed consent forms were obtained from the patients prior to the start of the study.