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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: Behav Sleep Med. 2022 Apr 1;21(2):142–149. doi: 10.1080/15402002.2022.2057986

Strategies for Controlling Unwanted Intrusive Thoughts and Insomnia Severity in Urban-Residing Young Adult African Americans

Alicia Stokes 1,*, Milan Poindexter 1, Kimberly Bell 3, Thomas A Mellman 2
PMCID: PMC9552939  NIHMSID: NIHMS1821222  PMID: 35362345

Abstract

Introduction:

Poor sleep is common in our society, particularly for African Americans, and is associated with adverse mental and physical health outcomes. Unwanted, intrusive thoughts contribute to sleep disturbances and can be engendered by living in stressful urban environments, which are disproportionately inhabited by African Americans. Studies of other populations have shown that cognitive coping strategies to manage intrusive thoughts vary in their adaptiveness.

Objective:

To examine the relationship between thought control strategies and insomnia severity in urban residing young-adult African Americans.

Method:

Sixty-four young adult African Americans completed a demographic questionnaire, the Thought Control Questionnaire for Insomnia-revised, and the Insomnia Severity Index.

Results:

There were moderate to strong positive correlations of aggressive suppression, worry, behavioral distraction, and social avoidance with ISI scores. Poor sleepers endorsed greater use of worry and aggressive suppression than good sleepers. Results from a multiple linear regression analysis revealed that aggressive suppression, social avoidance, and behavioral distraction significantly predicted insomnia severity, and aggressive suppression was the strongest predictor in the model.

Conclusions:

These results extend findings of aggressive suppression as a correlate of insomnia severity to an urban-residing young adult African American sample. Future research should identify adaptive approaches and the utility of modifying maladaptive strategies.

Keywords: Insomnia, African Americans, Intrusive Thoughts, Sleep Disturbance, Thought Control Strategies

Introduction

Insomnia disorder, which is characterized by chronic difficulties falling asleep, staying asleep and/or nonrestorative sleep that is associated with impairment of daytime functioning, is a prevalent condition in our society with an estimated 6–10% meeting diagnostic criteria for insomnia (Morin et al., 2006 & Ohayon, 2002). Insomnia symptoms, however, affect roughly 30% of American adults, and are also associated with multiple adverse mental and physical health outcomes including anxiety, depression, chronic mental health symptoms hypertension and impaired quality of life (Biddle et al., 2019; Redeker et al., 2010; Roth & Ancoli-Israel, 1999; Taylor et al., 2005). Although, it remains unclear whether African Americans have a higher prevalence of insomnia disorder, it is well established that African Americans take longer to fall asleep, have more fragmented sleep, spend less time in slow-wave sleep and have poorer sleep quality than non-Hispanic Whites (Grandner et al., 2016; Kingsbury et al., 2013; Lauderdale et al., 2006; Mezick et al., 2008; Profant et al., 2002). These disparities are problematic because consequences of poor sleep may disproportionately affect African Americans who are at a higher risk for negative health outcomes. Therefore, it is critical to understand the factors associated with insomnia, particularly in African Americans.

Adverse environmental and psychosocial factors including racial discrimination (Bethea et al., 2020) and stressful neighborhood environments (Hale and Do, 2007) can impact sleep by engendering intrusive thoughts. Intrusive thoughts are defined as “any distinct, identifiable cognitive event that is unwanted, unintended, and recurrent. It interrupts the flow of thought, interferes in task performance, is associated with negative affect, and is difficult to control” (Clark, 2005, p. 4). Researchers have found an association between intrusive thoughts and insomnia. Lichstein and Rosenthal (1980) found that cognitive rather than somatic arousal was endorsed as the major contributor to their insomnia in a sample of 296 individuals with insomnia. In a clinical sample of 14 adults with primary insomnia, those with greater stressful intrusive thoughts had poorer sleep quality (Hall et al., 2000).

Investigators have considered strategies for controlling or suppressing sleep-interfering intrusive thoughts and their relationships with insomnia (Harvey, 2005). In their 2005 study, Ree and colleagues surveyed 191 individuals with primary insomnia, 96 good sleepers, and 98 participants who were identified as having subthreshold insomnia to examine the relationships between subscales of the Thought Control Questionnaire for Insomnia-Revised and insomnia severity. Results of their study revealed that aggressive suppression (e.g., “I get angry at myself for having the thought”), social avoidance (e.g., “I avoid discussing the thought”), behavioral distraction (e.g., “I try to block them out by reading, watching TV, or listening to the radio”), and worry (e.g., “I worry about more minor things”) were associated with poorer sleep. Whereas cognitive distraction (e.g., “I think pleasant thoughts instead”) was associated with good sleep.

Gellis and Park (2013) examined whether nighttime thought control strategies predicted insomnia severity in 460 students from a large private University in the Northeast region of the United States. They found that cognitive distraction was negatively associated, and aggressive suppression was positively associated with insomnia severity, after accounting for anxiety, depression, sleep hygiene, and pain. More recently, Sella and Borella (2020) conducted a study in Italy evaluating strategies for managing intrusive thoughts in 147 good sleeper and poor sleeper groups as assessed by the Pittsburgh Sleep Quality Index. Poor sleepers were more likely to use aggressive suppression, reappraisal and worry as cognitive coping strategies than good sleepers. These findings help characterize the adaptiveness of using certain strategies to cope with intrusive thoughts that occur during the pre-sleep period.

Stressful neighborhood environments in which African Americans disproportionately reside, may engender nocturnal vigilance during the night as a result of sustained exposure to threat and influence the effectiveness of strategies employed to manage intrusive thoughts during the pre-sleep period. To our knowledge, no studies have examined the relationship between thought control strategies and insomnia severity in an urban-residing African American sample. Therefore, we sought to examine this relationship and extend previous findings that suggest that thought control strategies vary in their adaptiveness to our sample. Understanding this relationship will aid in the development and promotion of adaptive coping strategies to manage intrusive thoughts during the pre-sleep period.

Method

Participants and Procedure

Upon approval from the Institutional Review Board at Howard University, participants were recruited from the Washington, DC metropolitan area via flyers and participant referrals. Participants were recruited to participate in a larger study that included home monitoring and longitudinal follow-up. Flyers were posted near the University and in Southeast D.C, so that our participants represented our target demographic. Participants who were interested in the study were scheduled via telephone or email to be evaluated in the clinical research unit (CRU) at the Howard University Hospital. Following the consenting procedures, participants were instructed to complete the questionnaires on a laptop provided by the researchers. Participants were excluded from enrollment if they did not self-identify as Black or African American between the ages of 18–35, live in the D.C. Metropolitan area, have conventional sleep-wake schedules (i.e., not work overnight shifts), and have a BMI <40. Participants were also excluded from the study if they had sleep apnea, were living on a college campus, or reported a medical or psychiatric condition that affects their sleep. Exceptions were made for diagnoses of PTSD, anxiety disorders, phobic disorder, or past major depression that did not require medication to remain in remission.

Measures

Demographic Questionnaire

Participants completed a demographic questionnaire providing information about their age, gender, race/ethnicity, country of birth, home address, highest level of education, occupation, marital status, household income, number of dependents, medical conditions, medications, tobacco, and caffeine use.

Thought Control Questionnaire for Insomnia-Revised (TCQI-R)

The TCQI-R assesses the use of different cognitive control strategies while being kept awake by thoughts (Ree et al., 2005). The TCQI-R is a validated measure and studies have found its subscales internally consistent: Cronbach alpha = 0.64 – 0.83 (Ree et al., 2005), a Cronbach’s alpha = 0.80 was observed for this sample. The TCQI-R contains an introductory question that asks (“How often does thinking too much keep you awake”) that is rated on an 11-point Likert scale ranging from 0 (“never”) to 10 (“every night”). The initial question is then followed up by 35-items that are rated on a 4-point Likert scale ranging from 1 (“almost never”) to 4 (“almost always”). These items capture 6 different thought control strategies: cognitive distraction (e.g., “I think pleasant thoughts instead”); behavioral distraction (e.g., “I try to block them out by reading, watching TV, or listening to the radio”); aggressive suppression (e.g., “I get angry at myself for having the thought”); social avoidance (e.g., “I avoid discussing the thought”); worry (e.g., “I worry about more minor things”); reappraisal (e.g., “I try to reinterpret the thought”).

Insomnia Severity Index (ISI)

The ISI is a 7-item self-report questionnaire that assesses the impact and severity of insomnia symptoms over the last two weeks (Bastien et al., 2001; Morin et al., 2011). The ISI has been found to be a valid and reliable measure of insomnia severity (Cronbach’s alpha = 0.74) (Bastien et al., 2001). Items are rated on a 5-point Likert scale, with items rating from 0 “not at all” to 4 “very much”. The sum of all items yields a total score that ranges from 0 to 28. The total score may be interpreted as (0–7) absence of insomnia, (8–14) subthreshold insomnia, (15–21) moderate insomnia, and (22–28) severe insomnia. Within a non-clinical population, a cutoff score of 10 has been recommended for detecting insomnia (Morin et al., 2011).

Statistical Analysis

All data analyses were conducted with IBM SPSS Statistics, version 26.0 (IBM Corp.). Descriptive statistics for gender, age, education, and income were calculated to characterize the sample. Bivariate correlations to calculate Pearson’s r were conducted to determine relationships between thought control strategies and insomnia severity. Next, independent samples t-tests were conducted to identify differences in thought control strategies between those with low insomnia symptoms (ISI < 10) and insomnia symptoms above the screening threshold (ISI ≥ 10). These analyses were followed by a linear regression model with ISI as the dependent and thought control strategies as the independent variables. Prior to conducting the analysis, the statistical assumptions of linearity, normality, homoscedasticity, and multicollinearity were tested. Each of the assumptions were met except for multicollinearity. Aggressive suppression and worry were highly correlated at r=.69, p<01. Worry had a variance inflation factor of 3.10. Using a conservative cutoff of 2.5 (Allison, 2001; Midi & Bagheri, 2010), worry was removed as a predictor in the model.

Results

Descriptive Statistics

Sixty-eight African Americans were consented to participate in the study. Four participants were disqualified due to meeting one of the exclusion criteria. Leaving the final sample N=64 (M = 25.81, SD = 3.55). 49.3% of participants were female (n = 36); all participants were single with no children. Twenty-six percent of participants had less than a college degree, and 29% had an annual income of less than 25,000 (Table 1). There was a gap in obtaining address information. For the subset with the data available (n = 45), (31%) participants lived in ward 5, (11%) lived in ward 8, and (15.6%) lived in ward 7. The violent crime rates (per 1,000 pop.) for those wards are 13, 16, 15 respectively. The violent crime rate average for our participants is 13.82, compared to the violent crime rate of DC: 10.56 (Urban Institute of Greater DC, 2016).

Table 1.

Demographic Characteristics of the African American Sample (N=62)

n %
Gender
Female 36 49.3%
Male 28 38.4%
Education
Some high school 1 1.4%
High school 5 6.8%
Some college 13 17.8%
College 30 41.1%
Some graduate school 6 8.2%
Graduate school 6 8.2%
Professional school 3 4.1%
Income
$0–24,999 21 28.8%
$25,000–49,999 15 20.5%
$50,000–74,999 18 24.7%
$75,000–99,999 6 8.2%
$100,000–124,999 4 5.5%
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Bivariate Correlations

There were significant positive correlations between aggressive suppression r=.50, p<.01, worry r=.52, p< .01, behavioral distraction r=.41, p<.01, and social avoidance r=.36, p<01 with ISI scores. Cognitive distraction and reappraisal were not significantly correlated with ISI scores. The correlation coefficients are presented in Table 2.

Table 2.

Correlations between Thought Control Strategies and Insomnia Severity

Aggressive Suppression Behavioral Distraction Worry Cognitive Distraction Reappraisal Social Avoidance ISI
Aggressive Suppression 1 .56** .69** .48** .36** .52** .50**
Behavioral Distraction 1 .67** .57** .53** .54** .42**
Worry 1 .33** .53** .61** .52**
Cognitive Distraction 1 .41** .30* .21
Reappraisal 1 .45** .13
Social Avoidance 1 .36**
ISI 1
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*

p<.05

**

p<.01

Mean Differences in Thought Control Strategies

Independent samples t-tests were conducted to compare thought control strategy use between those with low insomnia symptoms (ISI<10) and threshold insomnia symptoms (ISI>10). Those with threshold insomnia symptoms endorsed greater use of worry to manage their sleep-disruptive intrusive thoughts than those with low insomnia symptoms (M=.82, SD=.48 vs. M=.54, SD=.44), t (62) =−2.25, p<.05, 95% CI [−.53, −.03]. Those with threshold insomnia symptoms also endorsed greater use of aggressive suppression as a coping strategy than those with low insomnia symptoms (M=.93, SD=.62) vs. M=.52, SD=.42) t (62) =−3.12, p<.01, 95% CI [−.67, −.15]. Figure 1. summarizes the significant differences in mean scores for aggressive suppression and worry between participants with low insomnia symptoms and insomnia symptoms above the screening threshold.

Figure 1.

Figure 1.

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Mean differences in worry and aggressive suppression between those with low insomnia symptoms and threshold insomnia symptoms

Regression Analysis Examining the Relationship Between Thought Control Strategies and Insomnia Severity

A multiple linear regression analysis was conducted to examine the effect of thought control strategies on insomnia severity (Table 3). Aggressive suppression, behavioral distraction, reappraisal, cognitive distraction, and social avoidance were entered as predictors in the model. The regression model was significant, F (5, 58) = 5.32, p<.001, R2=.32, adjusted R2=.26. This effect was driven by aggressive suppression with β = .407, p = .006, rs =.84. The beta values for behavioral distraction social avoidance were not statistically significant in the model.

Table 3:

Summary of Regression Model Examining the Relationship Between Thought Control strategies and Insomnia Severity

Variable b SE b β t p r s
Aggressive Suppression 3.80 1.34 .41** 2.85 .01 .84
Social Avoidance .78 1.16 .09 .67 .51 .61
Behavioral Distraction 1.89 1.04 .29 1.82 .08 .71
Reappraisal −1.21 .98 −.17 −1.24 .22 .22
Cognitive Distraction −.92 1.17 −.11 −.79 .44 .35
R2 .32
Adjusted R2 .26
F 5.33***
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Note. b = Unstandardized regression coefficient; β = Standardized regression coefficient; rs = structure coefficient

*

p < .05

**

p<.01

***

p<.001

Discussion

In the present study, we extended the previously identified associations between aggressive suppression, worry, behavioral distraction, and social avoidance with insomnia severity (Ree et al., 2005, Gellis & Park., 2013, Schmidt et al., 2010) to an urban residing African American sample. Cognitive distraction, which has previously been associated with better sleep outcomes, was not significantly associated with insomnia severity in our study. The prior studies that found a statistically significant relationship between cognitive distraction and insomnia severity were from predominantly non-Hispanic White or samples where race/ethnicity was not specified (Ree et al., 2005, Gellis & Park., 2013). It is possible that nocturnal vigilance engendered by living in stressful urban environments may not be as easily mitigated by cognitive distraction relative to other forms of intrusive thoughts disrupting sleep. It is also possible that this association would be observed in a larger sample.

In the grouped comparison, participants with insomnia symptoms endorsed using aggressive suppression and worry to cope with their intrusive thoughts during the pre-sleep period more frequently than those with low insomnia symptoms. These findings are consistent with research that suggests that poor sleepers are more likely to endorse aggressive suppression, reappraisal and worry to manage intrusive thoughts than good sleepers (Sella & Borella, 2020). Results of this study did not support the expectation that participants with low insomnia symptoms employed cognitive distraction to cope with their sleep-disruptive intrusive thoughts more than those with insomnia symptoms. Aggressive suppression, social avoidance, cognitive distraction, reappraisal, and behavioral distraction explained a statistically significant amount of the variance in insomnia severity in our sample of urban-residing young adult African Americans.

The results of this study also have potential implications for public health and support education strategies for improving sleep among those residing in stressful/threatening environments. There should also be efforts to design urban environments in a manner that reduces the experience of threat.

Limitations of the study include the modest sample size, cross-sectional design, and homogeneous sample. The cross-sectional design of the study limited our ability to make causal inferences about the relationship between thought control strategies and insomnia severity. Additionally, examining the relationship between thought control strategies and insomnia severity over multiple timepoints would be beneficial because the frequency in which an individual may suffer from intrusive thoughts may change over time. A longitudinal design would also be of interest in an urban-residing African American sample to assess changes in the neighborhood environment and how that affects their coping strategies. Generalizability is also a concern in our study. Our participants are aged 18–35, single, with no children, and mostly college educated and may therefore not optimally represent the population of interest.

Based on the current findings and limitations of the study it would be of interest for future research to examine this relationship within a larger and more heterogeneous sample. It is also of interest to directly examine the impact that living in distressed neighborhood environments has on the thought control strategies that an individual will employ. This knowledge gained from these next steps could be used to inform interventions for promoting more adaptive thought control strategies.

Acknowledgements

This research was supported by the NHLBI grant R01HL136626 to Dr. Thomas A. Mellman. The authors would like to acknowledge Travan Hurst, Ishaan Sandhu, Edward Bauer, and Pewu Lavela for their technical support and assistance with data management.

Footnotes

There are no competing financial interests to disclose.

References

  1. Bastien CH, Vallières A, & Morin CM (2001). Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep medicine, 2(4), 297–307. [DOI] [PubMed] [Google Scholar]
  2. Bethea TN, Zhou ES, Schernhammer ES, Castro-Webb N, Cozier YC, & Rosenberg L (2020). Perceived racial discrimination and risk of insomnia among middle-aged and elderly Black women. Sleep, 43(1), zsz208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Biddle DJ, Hermens DF, Lallukka T, Aji M, & Glozier N (2019). Insomnia symptoms and short sleep duration predict trajectory of mental health symptoms. Sleep medicine, 54, 53–61. [DOI] [PubMed] [Google Scholar]
  4. Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report, 2008 2009. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5842a2.htm (accessed May 10, 2021)
  5. Clark CR, Kawachi I, Ryan L, Ertel K, Fay ME, & Berkman LF (2009). Perceived neighborhood safety and incident mobility disability among elders: the hazards of poverty. BMC public health, 9(1), 1–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Ellis J, & Cropley M (2002). An examination of thought control strategies employed by acute and chronic insomniacs. Sleep Medicine, 3(5), 393–400. [DOI] [PubMed] [Google Scholar]
  7. Grandner MA, Williams NJ, Knutson KL, Roberts D, & Jean-Louis G (2016). Sleep disparity, race/ethnicity, and socioeconomic position. Sleep medicine, 18, 7–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Gellis LA, & Park A (2013). Nighttime thought control strategies and insomnia severity. Cognitive therapy and research, 37(2), 383–389. [Google Scholar]
  9. Gross RT, & Borkovec TD (1982). Effects of a cognitive intrusion manipulation on the sleep-onset latency of good sleepers. Behavior Therapy, 13(1), 112–116. [Google Scholar]
  10. Hale L, & Do DP (2007). Racial differences in self-reports of sleep duration in a population-based study. Sleep, 30(9), 1096–1103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Hall M, Buysse DJ, Nowell PD, Nofzinger EA, Houck P, Reynolds CF III, & Kupfer DJ (2000). Symptoms of stress and depression as correlates of sleep in primary insomnia. Psychosomatic medicine, 62(2), 227–230. [DOI] [PubMed] [Google Scholar]
  12. Harvey AG (2001). I can’t sleep, my mind is racing! An investigation of strategies of thought control in insomnia Allison G. Harvey. Behavioural and Cognitive Psychotherapy, 29(1), 3. [Google Scholar]
  13. Harvey AG (2002). A cognitive model of insomnia. Behaviour Research and Therapy, 40, 869–93. [DOI] [PubMed] [Google Scholar]
  14. Harvey AG (2005). A cognitive theory and therapy for chronic insomnia. Journal of Cognitive Psychotherapy, 19(1), 41–59. [Google Scholar]
  15. Kingsbury JH, Buxton OM, Emmons KM, & Redline S (2013). Sleep and its relationship to racial and ethnic disparities in cardiovascular disease. Current cardiovascular risk reports, 7(5), 387–394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Lauderdale DS, Knutson KL, Yan LL, Rathouz PJ, Hulley SB, Sidney S, & Liu K (2006). Objectively measured sleep characteristics among early-middle-aged adults: the CARDIA study. American journal of epidemiology, 164(1), 5–16. [DOI] [PubMed] [Google Scholar]
  17. Lichstein KL, & Rosenthal TL (1980). Insomniacs’ perceptions of cognitive versus somatic determinants of sleep disturbance. Journal of abnormal psychology, 89(1), 105. [DOI] [PubMed] [Google Scholar]
  18. Mezick EJ, Matthews KA, Hall M, Strollo PJ Jr, Buysse DJ, Kamarck TW, … & Reis SE (2008). Influence of race and socioeconomic status on sleep: Pittsburgh Sleep SCORE project. Psychosomatic medicine, 70(4), 410. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Morin CM, Belleville G, Bélanger L, & Ivers H (2011). The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep, 34(5), 601–608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Morin CM, LeBlanc M, Daley M, Gregoire JP, & Merette C (2006). Epidemiology of insomnia: prevalence, self-help treatments, consultations, and determinants of help-seeking behaviors. Sleep medicine, 7(2), 123–130. [DOI] [PubMed] [Google Scholar]
  21. Ohayon MM (2002). Epidemiology of insomnia: what we know and what we still need to learn. Sleep medicine reviews, 6(2), 97–111. [DOI] [PubMed] [Google Scholar]
  22. Profant J, Ancoli‐Israel S, & Dimsdale JE (2002). Are there ethnic differences in sleep architecture? American Journal of Human Biology: The Official Journal of the Human Biology Association, 14(3), 321–326. [DOI] [PubMed] [Google Scholar]
  23. Redeker NS, Jeon S, Muench U, Campbell D, Walsleben J, & Rapoport DM (2010). Insomnia symptoms and daytime function in stable heart failure. Sleep, 33(9), 1210–1216. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Ree MJ, Harvey AG, Blake R, Tang NK, & Shawe-Taylor M (2005). Attempts to control unwanted thoughts in the night: development of the thought control questionnaire-insomnia revised (TCQI-R). Behavior Research and Therapy, 43(8), 985–998. [DOI] [PubMed] [Google Scholar]
  25. Roth T, & Ancoli-Israel S (1999). Daytime consequences and correlates of insomnia in the United States: results of the 1991 National Sleep Foundation Survey. II. Sleep: Journal of Sleep Research & Sleep Medicine [PubMed] [Google Scholar]
  26. Schmidt RE, Gay P, Ghisletta P, & Van der Linden M (2010). Linking impulsivity to dysfunctional thought control and insomnia: a structural equation model. Journal of Sleep Research, 19(1‐Part‐I), 3–11. [DOI] [PubMed] [Google Scholar]
  27. Sella E, & Borella E (2020). Strategies for controlling sleep-related intrusive thoughts, and subjective and objective sleep quality: how self-reported poor and good sleepers differ. Aging & Mental Health, 1–8. [DOI] [PubMed]
  28. Taylor DJ, Lichstein KL, Durrence HH, Reidel BW, & Bush AJ (2005). Epidemiology of insomnia, depression, and anxiety. Sleep, 28(11), 1457–1464. [DOI] [PubMed] [Google Scholar]
  29. Wells A, & Davies MI (1994). The Thought Control Questionnaire: A measure of individual differences in the control of unwanted thoughts. Behaviour research and therapy, 32(8), 871–878. [DOI] [PubMed] [Google Scholar]
  30. Ziglari L (2017). Interpreting multiple regression results: β weights and structure coefficients. General Linear Model Journal, 43(2), 13–22. [Google Scholar]

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