Journal of Depression and Anxiety

Journal of Depression and Anxiety
Open Access

ISSN: 2167-1044

+44 1223 790975

Research Article - (2016) Volume 5, Issue 1

Coping Style as a Moderator of Chronic Loneliness and Substance Use in Emerging Adults

MacNeill LP, DiTommaso E and Brunelle C*
University of New Brunswick, Saint John, Canada, E-mail: macneill@unb.ca
*Corresponding Author: Dr. Brunelle C, Department of Psychology, University of New Brunswick, Saint John, Canada, Tel: 1 506 648 5797 Email:

Abstract

Primary affective bonds are integral to forming successful close adult relationships and an inadequate sense of belongingness can lead to loneliness. Loneliness and insecure attachment have been consistently related to negative behavioural outcomes, such as substance use which is often used as a means to cope with negative emotions The goal of this study was to examine whether coping may moderate the relationship between attachment security, loneliness, and substance use. Two hundred and nine (209) young adults (18-30 years of age) completed self-report questionnaires measuring attachment security, loneliness, coping style, and level of substance use. In the current sample, 60.3% of participants met the criteria for alcohol misuse and 48.3% met the criteria for drug misuse. Results showed that higher levels of chronic social loneliness predicted higher levels of substance use (p =. 029), but coping did not moderate this relationship. Higher attachment avoidance predicted higher levels of substance use (p < .001), while adaptive coping moderated this relationship (p = .001). Since adaptive coping skills may buffer avoidant individuals against substance misuse, it may be useful for substance use interventions to be tailored, such that avoidant individuals are taught coping skills that promote greater awareness of internal states and lessen feelings of interpersonal distress.

Keywords: Coping style; Chronic loneliness; Distress

Introduction

Loneliness is often the result of a discrepancy between one’s desired interpersonal relationships and one’s perceived current relationships [1,2]. Loneliness has been conceptualized as a multidimensional construct comprised of different types of loneliness based on the source of distress [3,4]. Weiss described social loneliness as a result of inadequate social interaction and unsatisfactory social relationships, whereas, emotional loneliness results from unsatisfactory emotional attachments. Research has shown that emotional and social loneliness are distinct constructs that can have different antecedents and behavioural outcomes [3-6].

Loneliness can be influenced by quantitative characteristics of relationships, such as number of social contacts or frequency of social interaction, but loneliness is more often defined by qualitative characteristics of relationships, such as subjective sense of belonging [7-10]. Our sense of belonging and the quality of interpersonal relationships are often rooted deeply in the initial relationships we have with parents and caregivers [11-13]. Attachment theory suggests that, as infants and children, individuals form internal working models of themselves and others which are largely based on their relationship with caregivers [12-14]. These working models result in either secure or insecure attachment. A secure attachment is built in a loving and supportive environment, where the child has a secure base from which to explore their environment [12-14]. Attachment security has been shown to be relatively stable and persist throughout adulthood [15]. Attachment can be conceptualized as a dimensional construct based on attachment related anxiety and attachment related avoidance [16,17].

The transition into adulthood requires both a striving for independence and a reliance on attachment figures [18,19]. Young adulthood is generally a time when the focus on attachment figures shifts from primary caregivers to peers and romantic partners [15] therefore, if secure attachments are not formed early in life, this transition may be challenging. Loneliness is one outcome that can arise during this transition, and research has shown that attachment style is significantly related to loneliness [18]. Research suggests that many young adults experience significant levels of loneliness, particularly during the initial transition to university/college [20-23]. Past research on loneliness has revealed that a large portion of the young adult population is frequently lonely [24,25], and more recent prevalence rates for loneliness range from 20% to 30% [26,27]. Individuals manage feelings of loneliness in different ways, and these coping strategies can have a significant influence on behavioural outcomes.

Coping is commonly defined as a process which includes cognitive and behavioural efforts to manage external or internal stimuli that are appraised as demanding or beyond the resources of the individual [28-30]. Researchers generally categorize coping strategies based on the function of coping efforts. Zuckerman and Gagne [31] proposed a 5-factor model of coping, where adaptive coping is represented by self-help, approach, and accommodation; while maladaptive coping is represented by avoidance and self-punishment [31]. Individuals develop characteristic coping strategies early in childhood and it is suggested that attachment patterns may help explain individual differences in coping strategies. Insecure attachment has been consistently related to maladaptive coping strategies such as withdrawal, avoidance, emotionminimizing, repression, and diversion [32,33]. Adaptive coping strategies have been linked to fewer externalizing problems in adults, while maladaptive coping efforts have been linked to both emotional and behavioural problems [34,35].

Research has reported a significant increase in substance use in young adults during the 21st century [36-38]. Alcohol is a particularly popular drug for young adults and is often perceived as part of university/college campus culture [39-46]. Exposure to alcohol and peer pressure makes time spent in university a window of vulnerability for alcohol use and abuse [39]. Alcohol is often used to facilitate intimacy [47], closeness, [48] and support [39]; therefore, alcohol use in young adults has been viewed by some researchers as a socially normative behaviour that can have beneficial outcomes for social development [42]. Although an abundance of research addresses alcohol use in emerging adults, use and abuse of substances other than alcohol is also a significant concern for this population, which may result in negative outcomes such as academic/occupation failure, as well as, unsuccessful social and interpersonal relationships [49-51].

The current study

The current study aims to examine loneliness and attachment orientation as predictors of substance use, and the potential role of coping style in moderating these relationships. The research discussed above has shown that attachment, loneliness, coping, and substance use are related [52-55], but it is not entirely clear how coping intervenes between stressors, such as loneliness, and negative behavioral outcomes, such as substance use. Two moderation models are hypothesized in the current study. First, the relationship between loneliness and substance use is hypothesized to be dependent on differences among individual coping styles; with coping style influencing the direction and/or strength of the aforementioned relationship. Specifically, in the current study, it is predicted that adaptive coping styles will buffer individuals who report high levels of loneliness against increased substance use behavior. Second, the relationship between attachment orientation and substance use is hypothesized to be dependent on differences among individual coping styles; with coping style influencing the direction and/or strength of this relationship. Specifically, it is predicted that adaptive coping styles will buffer insecurely attached individuals against increased substance use behavior. Given that research has found substance use is correlated with several variables related to personality and mental health [52-54,56-58], the current study will control variables related to personality, anxiety, and depression.

Methods

Participants

A total of 299 participants took part in the current study; however, after data screening 246 cases remained, due to incomplete survey data and data screening procedures. For the purpose of the current study, only participants who were 30 years of age or younger were retained for analysis, given the present interest in an emergent adult population. The sample consisted of 149 females (71.3%) and the majority (83.7%) of the sample identified as Caucasian. Age ranged from 18 to 30 years (M=21.29, SD=3.44), and 87.6% of participants indicated that they were university or college students.

Measures

Demographics and substance use survey (self-developed): This 15-item self-report questionnaire was adapted from University of Washington’s University Life and Substance Use Survey [59]. The questionnaire contains basic demographic questions related to age, gender, ethnicity, and education. The substance use section contains items pertaining to past and current drug and alcohol use, as well as, perceptions of peer substance use.

Social and emotional loneliness scale for adults- short version (SELSA-S) [60]): The SELSA-S is a 15-item questionnaire that measures loneliness as a multidimensional construct. The SELSA-S has three, 5-item subscales: Romantic loneliness, family loneliness, and social loneliness. Each item is rated on a 7-point Likert scale that ranges from 1(strongly disagree) to 7(strongly agree). The SELSA-S divides emotional loneliness into romantic and family loneliness, which have been shown to be independent constructs [3,60]. The SELSA can be used to assess both transient (the last two weeks) and chronic (the past year) loneliness. The current study focused on levels of chronic loneliness. The SELSA-S has been shown to be a reliable and valid measure of adult loneliness [60,61]. For the current study, reliability coefficients for chronic loneliness were 0.88, 0.84, and 0.86 for social, family, and romantic, loneliness respectively.

Experiences in close relationships scale (ECR) [16]: This is a 36- item self-report questionnaire designed to measure adult attachment style. The ECR has two subscales which assess attachment related anxiety and attachment related avoidance. Each item is rated on a 7-point Likert scale that ranges from 1(disagree strongly) to 7 (agree strongly). Higher scores on the two subscales indicate greater attachment related anxiety and attachment related avoidance, respectively. The ECR subscales have shown to be reliable and valid [16,33]. In the current study, the reliability coefficients were 0.85 and 0.91 for the avoidance and anxiety subscales, respectively.

The alcohol use disorder identification test (AUDIT) [62,63]: This is a 10-item self-report questionnaire that measures three different aspects of drinking: alcohol use, dependence, and problems resulting from drinking. The first 8 items are scored on a 5-point Likert scale that ranges from 0 to 4 and the last two questions are scored on a 3-point scale with values of 0, 2, and 4. A score of 8 is the generally accepted cut-off to indicate alcohol misuse and a score of 20 suggests alcohol dependence [63]. The AUDIT has been shown to be a reliable and valid instrument for measuring alcohol misuse [63-66]. In the current study, the AUDIT showed good internal consistency with a reliability coefficient of 0.89.

The drug use disorder identification test (DUDIT) [67]: This is an 11-item self-report questionnaire that measures the use of drugs other than alcohol. Nine of the questions are scored on a 5-point scale ranging from 0 to 4, and two are scored on a 3-point scale with values of 0, 2, and 4. Recommended cut-off scores to indicate drug abuse vary. Voluse, Gioia, Sobell, Dum, Sobell, and Simco [68] suggested a cut-off score of 8, with adequate sensitivity and specificity scores (0.90 and 0.85 respectively). The DUDIT has been shown to be a reliable and valid instrument for measuring drug misuse [67-69]. In the current study, the DUDIT had a Cronbach’s alpha coefficient of 0.95.

The revised COPE Scale (R-COPE) [31]: This is a 40-item self-report questionnaire that assesses a 5-factor model of coping strategies. The five factors include: self-help, approach, accommodation, avoidance, and selfpunishment. Each item is rated on a 4-point Likert scale, indicating how often the participant engages in each statement, ranging from 1(I usually don’t do this at all) to 4(I normally do this a lot). Composite scores can be computed for one adaptive subscale and one maladaptive subscale. The R-COPE has been shown to be a reliable and valid instrument for measuring coping styles [31]. In the current study the reliability coefficients were 0.90, 0.89, 0.90, 0.84, and 0.92, for self-help, approach, accommodation, avoidance, and self-punishment, respectively. The reliability coefficient was 0.93 for the adaptive subscale and 0.90 for the maladaptive subscale, indicating that these scales were reliable.

Generalized anxiety disorder-7 scale (GAD-7) [70]: This is a 7-item self-report questionnaire for screening individuals for and measuring the severity of generalized anxiety disorder symptoms. Each of the items is rated on a 4-point Likert scale ranging from 0 to 3, with responses: “not at all,” “several days,” “more than half the days,” and “nearly every day”. The GAD-7 has been shown to be a reliable and valid instrument for measuring levels of generalized anxiety [71-73]. In the current sample, the reliability coefficient was 0.94.

Patient health questionnaire (PHQ-9) [74]: This is a 9-item self-report questionnaire for screening individuals for and measuring the severity of depressive symptoms. Each item is rated on a 4-point Likert scale ranging from 0 to 3, with responses: “not at all,” “several days,” “more than half the days,” and “nearly every day.” The PHQ-9 has demonstrated adequate reliability and validity [74,75] and in the current sample the reliability coefficient was 0.93.

Big Five Inventory (BFI) [76]: This is a 44-item self- report questionnaire that measures the Big Five Factor theory of personality. The five subscales are: extraversion, neuroticism, openness to experience, agreeableness, and conscientiousness. In previous research, the subscales have shown high reliability and strong convergent and divergent validity with longer Big Five measures [77,78]. In the current sample, reliability coefficients for neuroticism, extraversion, and openness were 0.72, 0.67, and 0.73, respectively. Reliability coefficients for the subscales agreeableness and conscientiousness were very low: 0.55 and 0.43, respectively, and were not included in analyses.

Procedure

The current study was advertised on the campus of an Atlantic Canadian post-secondary institution and through social media outlets. Participants completed the current study either as a paper and pencil survey or as an electronic survey via the data collection software Qualtrics. Participants completed the set of self-report questionnaires in small groups or individually and an informed consent form was presented first to each participant. Participants received one bonus point towards their grade if they were enrolled in an Introductory Psychology course. Students who were not enrolled in an Introductory Psychology course, or who completed the survey electronically, had the option to be entered in a raffle for one of three prizes: a $10, $20, or $30 gift card to a local restaurant, in appreciation for their participation in the current study.

Results

Power analysis and data screening

A priori power analysis was conducted to determine adequate sample size, using an online sample size calculator [79], as well as the program G*Power [80]. Both programs recommended a minimum sample size of N=122 to conduct the moderation regression analysis. This was based on 11 predictors, a medium effect size estimate of f2=0.15, and alpha level of p=0.05. Prior to statistical analyses, the data was screened for accuracy and model assumptions.

Descriptive analyses

After controlling for age, 209 cases were retained for analysis. Eightyeight point five percent (88.5%) of participants reported consuming alcohol at least once, and 61.1% of participants indicated using an illicit drug at least once. Based on the cut-off s for AUDIT scores [63], 58.4% of participants met the criteria for alcohol misuse, and 3.8% of participants met the criteria for alcohol dependence. Based on the cutoff for DUDIT scores [68], 49.8% of participants met the criteria for drug misuse. The most commonly used drug was marijuana or hashish (26.3%), and was followed by cigarettes, cigars, or pipe tobacco (17.7%). All other drug categories had very low rates of use (<4.3%; Table 1). Descriptive statistics for other study variables are presented in Table 2.

  Never use Less than once a month About once a month Two or three times a month Once a week or more
Cigarettes, Cigars 82.3 7.2 1.9 1.4 6.7
Smokeless tobacco 97.1 2.4 0 0 0.5
Marijuana, Hashish 73.7 13.9 1.4 3.8 7.1
Cocaine 97.1 1.9 1.0 0 0
Stimulants 96.2 2.9 1.0 0 0
Sedatives 98.6 1.4 0 0 0
Hallucinogens 96.7 1.9 0 0 0
Opiates, Narcotics 97.6 1.0 0.5 1.0 0
Inhalants 99.5 0.5 0 0 0
Steroids 98.5 0.5 0.05 0 0.5
Club drugs 98.0 2.0 0 0 0
Designer drugs 96.6 2.4 1.0 0 0

Note: The last column consists of the categories once or twice a week, three or four times a week, nearly every day, and once a day or more. Given the small n, they were collapsed into a single category.

Table 1: Frequency statistics for reported current drug use (%).

  M SD MIN MAX
SELSA Social 12.69 6.53 0 32
SELSA Family 12.33 7.04 0 35
SELSA Romantic 16.11 8.79 0 35
AUDIT 9.37 6.33 0 26
DUDIT 6.54 6.15 0 25
ECR Avoidance 69.35 16.24 18 111
ECR Anxiety 66.89 19.65 24 116
RCOPE Adaptive 69.86 12.85 24 96
RCOPE Maladaptive 35.12 9.07 16 55
GAD-7 12.16 6.62 0 28
PHQ-9 12.43 7.97 0 34
DASS-S 22.14 12.39 0 56
BFI Neuroticism 18.98 3.86 10 30
BFI Extraversion 22.28 4.42 10 31
BFI Openness 26.97 4.81 15 40

Table 2: Descriptive statistics for variables included in analyses.

Loneliness and substance use

Given that no significant differences were found between chronic and transient loneliness for any of the loneliness domains (social, family, romantic), chronic loneliness scores were used in the following analyses, as research suggests that chronic loneliness is related to greater levels of distress and other pathological issues [57]. A series of hierarchical multiple linear regression analyses were performed to assess whether chronic loneliness predicted level of substance use over and above personality, anxiety, and depression. AUDIT scores were entered as the criterion variable and the overall model was statistically significant, R2=0.27, F(8, 200)=9.35, p<0.001. After controlling for personality, anxiety, and depression, chronic social loneliness was the only unique predictor of AUDIT scores, t(245)=-2.19, p=0.029. In a second regression analysis, DUDIT scores were entered as the criterion variable and the overall model was statistically significant, R2=0.38, F(8, 200)=15.17, p<0.001. After controlling for personality, anxiety, and depression, chronic loneliness scores did not account for any unique variance in DUDIT scores (Table 3).

  AUDIT DUDIT
  r β r β
Step 1
Extraversion -0.102 0.017 -0.314  -0.174*
Neuroticism 0.004   -0.316** 0.114   -0.298**
Openness -0.035 0.013 0.040 0.131*
GAD_Scores 0.312 0.156 0.451 0.185
PHQ_Scores 0.396 0.471** 0.512 0.471**
    R2=0.25**   R2=0.37**
Step 2
Extraversion -0.102 -0.001 -0.314  -0.159*
Neuroticism 0.004   -0.292** 0.114   -0.313**
Openness -0.035 -0.005 0.040 0.129*
GAD_Scores 0.312 0.152 0.451 0.181**
PHQ_Scores 0.396 0.496** 0.512 0.467
Social Loneliness -0.006  -0.167* 0.168 -0.029
Family Loneliness 0.118 0.054 0.242 0.076
Romantic Loneliness 0.012 -0.004 -0.086 -0.084
    ΔR2=0.02   ΔR2=0.01

Note: * p<0.05, **p<0.01

Table 3: Summary of hierarchical regression analyses for loneliness predicting AUDIT scores and DUDIT scores.

Attachment and substance use

Two hierarchical multiple regression analyses were performed to assess whether attachment style predicted level of substance use over and above personality, anxiety, and depression. First, AUDIT scores were entered as the criterion variable and the model was statistically significant, R2=0.32, F(7, 201)=13.46, p<0.001. After controlling for personality, anxiety, and depression, only attachment avoidance accounted for unique variance in AUDIT scores, t(208)=-4.38, p<0.001. In the second regression analysis, DUDIT scores were entered as the criterion variable and the model was statistically significant, R2=0.46, F(7, 201)=24.59, p<0.001. After controlling for personality, anxiety, and depression, only attachment avoidance accounted for unique variance in DUDIT scores, t(208)=-45.32, p<0.001 (Table 4).

  AUDIT DUDIT
r β r β
Step 1
Extraversion -0.102 0.017 -0.314  -0.174*
Neuroticism 0.004   -0.316** 0.114   -0.298**
Openness -0.035 0.013 0.040 0.131*
GAD_Scores 0.312 0.156 0.451 0.185
PHQ_Scores 0.396 0.471** 0.512 0.471**
    R2=0.25**   R2=0.37**
Step 2
Extraversion -0.102 -0.016 -0.314  -0.198*
Neuroticism 0.004   -0.258** 0.114  -0.180*
Openness -0.035 -0.004 0.040 0.099
GAD_Scores 0.312 0.075 0.451 0.121
PHQ_Scores 0.396 0.483** 0.512 0.505**
Attachment Avoidance -0.231   -0.280** -0.272   -0.302**
Attachment Anxiety 0.109 0.087 0.036 -0.061
    ΔR2=0.07**   ΔR2=0.09**
Note: *p<0.05, **p<0.01

Table 4: Summary of hierarchical regression analyses for attachment predicting AUDIT scores and DUDIT score.

Moderation models

In the first moderation model, it was hypothesized that the nature of the relationship between loneliness and substance use would differ depending on scores on the coping measure. The interaction between chronic loneliness and coping style was assessed with a hierarchical regression analyses, and was only tested for alcohol use (AUDIT) since loneliness scores did not uniquely predict drug use (DUDIT). Two subscales were computed from the R-COPE for use in this analysis: adaptive coping and maladaptive coping. AUDIT scores were entered as the criterion variable, and the predictor variables included the three chronic SELSA-S scales, two R-COPE subscale (adaptive and maladaptive), and 6 interaction variables (SELSA-S by R-COPE scores). There were no significant interactions between loneliness scores and coping scores.

In the second moderation model, it was hypothesized that the nature of the relationship between attachment style and substance use would differ depending on scores on the coping measure. The interaction between loneliness and coping style was assessed through hierarchical regression, separately for alcohol (AUDIT) and drug use (DUDIT). First, AUDIT scores were entered as the criterion variable, and the predictor variables included the two ECR scale scores, two R-COPE subscale scores (adaptive and maladaptive), and four interaction variables. The overall model was statistically significant, R2=0.19, F(8, 197)=5.91, p<0.001. There was a significant interaction between attachment avoidance and adaptive coping, b=-.007, t(197)=- 3.24, p=0.00, which indicates that higher levels of attachment avoidance predict higher levels of alcohol use in individuals who are low on adaptive coping, but higher levels of attachment avoidance predict lower levels of alcohol use in individuals who are high on adaptive coping. There was also a significant interaction between attachment anxiety and maladaptive coping, b=-.005, t(197)=-2.20, p=0.029, which indicates that higher levels of attachment anxiety predict higher levels of drug use in individuals low on maladaptive coping, but higher levels of attachment anxiety predict lower levels of use use in individuals who are high on maladaptive coping (Table 5, Figures 1 and 2).

  AUDIT DUDIT
  r β r β
Step 1        
Attachment Avoidance -0.229     -0.307** -0.270  -0.328*
Attachment Anxiety 0.122 0.235* 0.044 0.150
Adaptive Coping 0.132 0.065 0.124 0.040
Maladaptive Coping 0.023 -0.022 0.027 0.022
    R2=0.12**   R2=0.11**
Step 2        
Attachment Avoidance -0.229  -0.207* -0.270  -0.235*
Attachment Anxiety 0.122 0.178* 0.044 0.084
Adaptive Coping 0.132 0.130 0.124 0.108
Maladaptive Coping 0.023 -0.023 0.027 0.023
Avoidance x Adaptive -0.214  -0.277* -0.234  -0.272*
Avoidance x Maladaptive 0.087 0.043 0.089 0.032
Anxiety x Adaptive 0.044 0.077 -0.001 0.005
Anxiety x Maladaptive -0.149  -0.160* -0.173  -0.208*
    ΔR2=0.08*   ΔR2=0.09**

Note: * p<0.05, ** p<0.01

Table 5: Summary of hierarchical regression analyses for the moderation of attachment style and Audit scores and Dudit scores.

depression-anxiety-Interaction-avoidance-adaptive

Figure 1: Interaction between attachment avoidance and adaptive coping in the prediction of alcohol use.

depression-anxiety-anxiety-maladaptive-coping

Figure 2: Interaction between attachment anxiety and maladaptive coping in the prediction of alcohol use.

Next, DUDIT scores were entered as the criterion variable, and the predictor variables included the two ECR scale scores, two R-COPE subscale scores (adaptive and maladaptive), and four interaction variables. The overall model was statistically significant, R2=0.19, F(8, 197)=6.06, p<0.001. There was a significant interaction between attachment avoidance and adaptive coping, b=-.007, t(197)=-3.19, p=0.002, which indicates that higher levels of attachment avoidance predict higher levels of substance use in individuals who are low on adaptive coping, but higher levels of attachment avoidance predict lower levels of substance use in individuals who are high on adaptive coping. There was also a significant interaction between attachment anxiety and maladaptive coping, b=-.007, t(197)=-2.87, p=0.005, which indicates that higher levels of attachment anxiety predict higher levels of substance use in individuals low on maladaptive coping, but higher levels of attachment anxiety predict lower levels of substance use in individuals who are high on maladaptive coping (Table 5, Figure 3 and 4).

depression-anxiety-avoidance-prediction-drug

Figure 3: Interaction between attachment avoidance and adaptive coping in the prediction of drug use.

depression-anxiety-anxiety-maladaptive-drug

Figure 4: Interaction between attachment anxiety and maladaptive coping in the prediction of drug use.

Discussion

Level of substance use was a primary concern in the present study. The high rate of alcohol use found in the current study is consistent with previous literature, which posits that alcohol use is a normative behaviour in young adults [6,36,39,81]. Furthermore, 58.4% of participants met the criteria for alcohol misuse, which is in line with findings from the National Institute of Alcohol Abuse and Alcoholism (2012), which reports that 50% of young adults engage in binge drinking, a form of alcohol misuse. Alcohol consumption may be a normative behaviour in emerging adults, although quantity and frequency of use are still a concern given the physical, psychological, and emotional impairments associated with excessive substance use [6,39].

Cannabis was the most frequently reported substance of use, which is consistent with previous literature. In the current study, 49.8% of participants met the criteria for drug misuse, which seems disproportionate given that only 61.1% of participants reported using a drug other than alcohol at least once. This would indicate that almost all individuals who have tried drugs misuse them. Results from United States national surveys suggest that university students are at greater risk of drug misuse than their non-attending peers. The Monitoring the Future Survey (2011) reported that college students had higher levels of inhalant, hallucinogen, amphetamine, and steroid use than their nonattending peers [82]. Furthermore, The Core Alcohol and Drug Survey 2011 indicated that college students reported more frequent use of marijuana, cocaine, hallucinogens, and designer drugs than their nonattending peers [83].

The current study examined the association between attachment, chronic loneliness, and substance use, as well as the moderating effect of coping style within these associations. Overall, the relationship between loneliness and substance use was weak. It is important to note that mean loneliness scores in the current study corresponded to other studies examining loneliness in young adults [60]. Therefore, it is unlikely that the current findings resulted from uncharacteristically low scores on the loneliness scales. The present data, nevertheless, supported the idea that level of chronic social loneliness predicts level of alcohol use over and above personality, anxiety, and depression. This suggests that social loneliness could be a small, but distinct, risk factor for increased alcohol use in emerging adults. This could be because during emerging adulthood, forming social bonds tends to take precedence over other relationships [8,84-86]. Individuals in this age group may be more sensitive to the lack of, or perceived lack of, social relationships, and this distress may lead to increased alcohol use. Individuals who are socially lonely may engage in more recreational alcohol use in an attempt to forge new social bonds, and may drink in social settings as a means to increase their positive emotions [87,88].

The current study supported the idea that attachment avoidance predicts level of alcohol and drug use over and above personality, anxiety, and depression. An emerging body of research has investigated substance use within the context of adult attachment, and the nature of this relationship has been explored in the literature [89-91]. Early researchers suggested that there is a direct relationship between insecure attachment and substance use. Kohut [92] suggested that addiction can result when individuals have not formed, or failed to internalize, working models of attachment security. Walant [93] suggested that individuals who are predisposed to substance misuse have experienced a neglect of their attachment needs and subsequently use substances to compensate for a lack of closeness.

The first moderation model was not supported, indicating that coping style does not moderate the relationship between level of chronic loneliness and substance use. Research suggests that social drinking can have some benefits and can create opportunities for social bonding [94]. Therefore, increased alcohol use may not be reflective of maladaptive coping strategies in emerging adults, as this population may be using alcohol as a social activity, rather than as a means for dealing with perceived social isolation. Although this is the first study to investigate the moderating effect of coping styles on the level of substance use, research has highlighted the effect of motivation on substance use, particularly the effect of drinking to cope [87,88]. Cooper et al., [88] found that negative affect and alcohol use are linked by drinking to cope motives, and that adaptive coping strategies buffer against the negative effects of stress on drinking behaviour, reducing alcohol use [95,96]. Given that the current sample may not be engaging in alcohol use to manage negative affect, adaptive coping efforts would do little to decrease consumption. It would be of interest to investigate drinking motives in individuals both high and low in social loneliness, as they could be drinking for different reasons. Cooper [97] suggested four motives for drinking: drinking to cope, conformity, enhancement, and social. While individuals low in social loneliness could be drinking for social and enhancement purposes, individuals high in social loneliness could be drinking for conformity reasons, which could be detrimental, as coping and conformity motives have been associated with greater drinking problems [98-101].

The second moderation model was partially confirmed, indicating that coping style moderates the relationship between attachment style and substance use. There were significant interactions between attachment avoidance and level of adaptive coping in the prediction of both alcohol and other drug use, such that higher levels of adaptive coping buffered avoidant individuals from increased substance use. The relationship between substance use and attachment security has received more attention in the literature than substance use and loneliness; however, research generally focuses on motivation rather than specific coping styles. McNally, et al. [91] found that drinking to cope mediated the relationship between attachment security and alcohol use, suggesting that insecurely attached individuals use alcohol to cope with emotional distress. The authors proposed that insecure attachment is a risk factor for the adoption of less adaptive coping strategies (such as drinking to cope), as a means of regulating negative emotions. In the current study, individuals higher in attachment avoidance did report higher levels of substance use when they used lower levels of adaptive coping, however higher levels of adaptive coping were associated with lower levels of alcohol use. Therefore, insecure attachment may not necessarily lead to maladaptive coping styles, as individuals higher in attachment avoidance may learn more adaptive coping strategies which could protect against substance use as a means of coping.

The interaction between attachment anxiety and maladaptive coping appears more counterintuitive. In the current study, lower levels of maladaptive coping actually led to higher levels of substance use in anxiously attached individuals. One explanation is that individuals who are higher in attachment anxiety may seek out social forms of coping, such as social support, due to their perceived lack of closeness. Social forms of coping may actually lead to more substance use, if alcohol and drugs are used recreationally to fit in, or to feel closer to others. Alternatively, anxiously attached individuals may engage in increased substance use as a replacement for their lack of closeness to others, but once this void is filled, they may feel able to engage in more adaptive coping strategies. This particular finding is counter to the majority of literature regarding attachment and substance use [32,102]. It is, therefore, important to investigate this relationship further to discern whether this finding is replicable or anomalous.

The above discussion must be considered in light of certain limitations. The current study used self-report measures, and this may have influenced the quality of data. Furthermore, this study was crosssectional; therefore causal relationships cannot be assumed. The misuse of alcohol and other drugs can affect the quality of social relationships, which in turn, may increase loneliness and use of substances. In the future, longitudinal research should be conducted to assess the causal links among attachment, loneliness, and substance use. Finally, the current sample was composed primarily of undergraduate students; which limits generalizability. Future studies should consider the current research questions within community and/or clinical samples, in order to better address the generalizability of the current findings.

An abundance of research has demonstrated that substance use has become a major public health concern in North America [103]. The current findings have important implications for individuals in treatment for substance misuse and for those who use substances to cope with interpersonal dissatisfaction. Prevention and intervention of substance use could be tailored, for example, to an individual’s attachment pattern, such that individuals who are high in attachment avoidance can learn coping skills that promote greater awareness of internal states, and may lessen feelings of interpersonal distress.

References

  1. Cacioppo JT, Ernst JM, Burleson MH, McClintock MK, Malarkey WB, et al. (2000). Lonely traits and concomitant physiological processes: The MacArthur social neuroscience studies. Int J Psychophysio35: 143-154.
  2. Peplau LA, Perlman D (1982). Perspectives on loneliness, Loneliness: A sourcebook of current theoryresearch and therapy.Wiley, New York, USA.
  3. DiTommaso E, Spinner B (1993) The Development and Initial Validation of the Social and Emotional Loneliness Scale for Adults (SELSA). Personality and Individual Differences14: 127-134.
  4. Weiss RS (1973) The experience of emotional and social isolation. Cambridge: MIT Press.
  5. DiTommaso 0E, Spinner B (1997) Social and emotional loneliness: A re-examination of Weiss’ typology of loneliness. Personality and individual Differences22: 417-427.
  6. Rubenstein C, Shaver P (1982) The experience of loneliness, Loneliness: A sourcebook of current theoryresearch and therapy. Wiley, New York, USA206-223.
  7. Asher SR,Paquette JA (2003) Loneliness and peer relations in childhood. Current Directions in Psychological Science12:75-78.
  8. Cutrona CE (1982). Transition to college: Loneliness and the process of social adjustment, Loneliness: A sourcebook of current theory research and therapy.Wiley: New York, USA.
  9. Jones WH (1982) Loneliness and social behaviour, Loneliness: A sourcebook of current theoryresearch and therapy. Wiley, New York, USA.
  10. Wheeler L, Reis H, Nezlek J (1983) Loneliness, social interaction, and sex roles.J Pers Soc Psychol 45: 943-953.
  11. Bartholomew K, Horowitz LM (1991) Attachment styles among young adults: a test of a four-category model. J Pers Soc Psychol 61: 226-244
  12. Bowlby J (1969) Attachment and loss: Attachment, Basic Books: New York, USA.
  13. Bowlby J (1973)Attachment and loss: Separationanxiety and anger. Hogarth Press, London.
  14. AinsworthMS,BleharMC,WatersE, WallS (1978) Patterns of attachment: A psychological study of the Strange Situation. Erlbaum, Hillsdale NJ, USA.
  15. HazanC, ZeifmanD (1999) Pair bonds as attachments: Evaluating the evidence, Handbook of attachment: Theoryresearch and clinical applications.Guilford Press, New York, USA.
  16. BrennanKA, ClarkCL, ShaverPR (1998) Self-report measurement of adult romantic attachment: An integrative overview. Attachment theory and close relationships. Guilford Press, New York, USA.
  17. BrennanKA,ShaverPR,TobeyAE (1991) Attachment stylesgenderand parental problem drinking. Journal of Social and Personal Relationships8:451-466.
  18. DiTommasoE,Brannen-McNultyC,RossL,BurgessM (2003) Attachment stylessocial skills and loneliness in young adults. Personality and Individual Differences35:303-312.
  19. KennyME, RiceKG(1995) Attachment to parents and adjustment in late adolescent college students: Current statusapplicationsand future considerations. The Counselling Psychologist23: 433-456.
  20. Berman WH, Sperling MB (1991) Parental attachment and emotional distress in the transition to college. J Youth Adolesc 20: 427-440.
  21. HelsenM,VolleberghW, MeeusW (2000) Social support from parents and friends and emotional problems in adolescence. Journal of Youth and Adolescence 29:319-335.
  22. RokachA (2005) Drug withdrawal and coping with loneliness. Social Indicators Research73:71-85.
  23. WisemanH,MayselessO, SharabanyR (2006) Why are they lonely? Perceived quality of early relationships with parentsattachmentpersonality predispositions and loneliness in first-year university students. Personality and Individual Differences40: 237-248.
  24. RokachA, BrockH (1998) Coping with Loneliness. Journal of Psychology132: 107-127.
  25. FloodM (2005) Mapping loneliness in Australia.The Australia Institute, Canberra Australia.
  26. FranklinA, TranterB (2008) Loneliness in Australia. Research Paper 13Housing and Community Research Unit. University of Tasmania, Hobart Tasmania.
  27. LazarusRS (1993) Coping theory and research: Pastpresentand future. Psychometric Medicine55:234-247.
  28. LazarusRS, FolkmanS (1984) Stressappraisaland coping. Springer, New York, USA.
  29. ZuckermanM,GagneM (2003) The COPE revised: Proposing a 5-factor model of coping strategies. Journal of Research in Personality37:169-204.
  30. DawsonAE,AllenJP,MarstonEG,HafenCA,SchadMM (2014) Adolescent insecure attachment as a predictor of maladaptive coping and externalizing behaviors in emerging adulthood. Attachment & Human Development16: 462-478.
  31. MikulincerM, FlorianV (1995) Appraisal and coping with a real life stressful situation: The contribution of attachment styles. Personality and Social Psychology Bulletin 21: 406-414.
  32. CompasBE,Conor-SmithJK,SaltzmanH,ThomsenAH,WadsworthME (2001) Coping with stress during childhood and adolescence: Problemsprogressand potential in theory and research. Psychological Bulletin127:87-127.
  33. Liu X, Tein JY, Zhao Z (2004) Coping strategies and behavioral/emotional problems among Chinese adolescents. See comment in PubMed Commons below Psychiatry Res 126: 275-285.
  34. Akerlind I, Hörnquist JO (1992) Loneliness and alcohol abuse: a review of evidences of an interplay. See comment in PubMed Commons below Soc Sci Med 34: 405-414.
  35. GoldbergT (1999). Demystifying Drugs: A Psychosocial Perspective. St. Martin’s PressNew York, USA.
  36. MacNeilG,StewartJC,KaufmanAV (2000) Social support as a potential moderator of adolescent delinquent behaviour. Child and Adolescent Social Work Journal 17:361-379.
  37. Borsari B, Carey KB (2006) How the quality of peer relationships influences college alcohol use. See comment in PubMed Commons below Drug Alcohol Rev 25: 361-370.
  38. Gill JS (2002) Reported levels of alcohol consumption and binge drinking within the UK undergraduate student population over the last 25 years. See comment in PubMed Commons below Alcohol Alcohol 37: 109-120.
  39. Kypri K, Langley JD, McGee R, Saunders JB, Williams S (2002) High prevalence, persistent hazardous drinking among New Zealand tertiary students. See comment in PubMed Commons below Alcohol Alcohol 37: 457-464.
  40. TanASL (2012) Through the drinking glass: an analysis of the cultural meanings of college drinking. Journal of Youth Studies15: 119-142.
  41. RabowJ, Duncan-SchillM (1995) Drinking among college students. Journal of alcohol & drug education40: 52-64.
  42. TreiseD,WolburgJM, OtnesCC (1999) Understanding the ‘social gifts’ of drinking rituals: an alternative framework for PSA developers. Journal of advertising28: 17-31.
  43. Workman TA (2001) Finding the meanings of college drinking: an analysis of fraternity drinking stories. Health Commun 13: 427-447.
  44. AlversonH (2005) Students’ social life at Dartmouth College: reflections in their looking glass. HanoverNew Hampshire, USA.
  45. Nezlek JB, Pilkington CJ, Bilbro KG (1994) Moderation in excess: binge drinking and social interaction among college students. See comment in PubMed Commons below J Stud Alcohol 55: 342-351.
  46. BradleyRH, CorwynRF (2004) Life satisfaction among European AmericanAfrican and AmericanChinese AmericanMexican American and Dominican American adolescents. International Journal of Behavioral Development28:385-400.
  47. Javier SJ, Belgrave FZ, Hill KE, Richardson JT (2013) Ethnic and gender differences in normative perceptions of substance use and actual use among college students. See comment in PubMed Commons below J Ethn Subst Abuse 12: 228-241.
  48. NewcombMD (1994) Drug use and intimate relationships among women and men: Separating specific from general effects in prospective data using structural equations models. Journal of Consulting and Clinical Psychology62:463-476.
  49. NewcombMD, BentlerPM (1988) Consequences of Adolescent Drug Use: Impact on the Lives of Young Adults. SageBeverly HillsCA, USA.
  50. BrittonPC (2004) The relation of coping strategies to alcohol consumption and alcohol related consequences in a college sample. Addiction Research & Theory12:103-114.
  51. CorbinWR, FarmerNM,Nolen-HoekesmaS (2013) Relations among stresscoping strategiescoping motivesalcohol consumption and related problems: A mediated moderation model. Addictive Behaviors38:1912-1919.
  52. RafnssonFD,JonssonFH, WindleM (2006) Coping strategiesstressful life eventsproblem behaviorsand depressed affect. AnxietyStress& Coping: An International Journal19241-257.
  53. SadavaSW, PakAW (1994)Problem drinking and close relationships during the third decade of life. Psychology of Addictive Behaviors8:251-258.
  54. http://www.collegedrinkingprevention.gov/SupportingResearch/Journal/goldman.aspx
  55. HeinrichLM, GulloneE (2006) The clinical significance of loneliness: A literature review. Clinical Psychology Review26:695-718.
  56. HingsonR,HeerenT,ZakocsR,KopsteinA, WeschlerH (2002) Magnitude of Alcohol-Related Mortality and Morbidity among U.S. College Students Ages 18-24. Journal of Studies on Alcohol63:136-144.
  57. McGheeD, LemireST (2006) University Life and Substance Use Survey2005, SeattleWA: University of Washington Office of Educational AssessmentReport 06-04.
  58. DiTommasoE,BrannenC, BestLA (2004) Measurement and Validity Characteristics of the Short Version of the Social and Emotional Loneliness Scale for Adults. Educational and Psychological Measurement64: 99-119.
  59. RussellD (1996)UCLA Loneliness scale (Version 3): Reliabilityvalidityand factor structure. Journal of Personality Assessment6620-40.
  60. BaborTF,de la FuenteJR,SaundersJ, GrantM (1992) AUDIT: The Alcohol Use Disorders Identification Test. Guidelines for use in primary health care. Geneva: World Health Organization.
  61. Babor TF,Higgins-Biddle JC,Saunders JB,Monteiro MG (2001) AUDIT: The alcohol use disorders identification test—Guidelines for use in primary care, Geneva: World Health Organization.
  62. KokotailoPK,EganJ,GangonR,BrownD,MundtM, et al. (2004) Validity of the Alcohol Use Disorders Identification Test in College Students. Alcoholic Clinical and Experimental Research 28: 914-920.
  63. ReinertDF, AllenJP (2002) The Alcohol Use Disorders Identification Test (AUDIT): A review of recent research. Alcohol Clin Exp Res 26: 272-279.
  64. SaundersJB, AaslandOG, BaborTF,de la FuenteJR, GrantM (1993) Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption: II. Addiction88: 791-804.
  65. BermanAH,BergmanH,PalmstiernaT, SchlyterF (2005) Evaluation of the Drug Use Disorders Identification Test (DUDIT) in criminal justice and detoxification settings in a Swedish population sample. European Addiction Research11: 22-31.
  66. VoluseAC,GioiaCJ,SobellLC,DumM,SobellMB, et al. (2012) Psychometric properties of the Drug Use Disorders Identification Test (DUDIT) with substance abusers in outpatient and residential treatment. Addictive Behaviors37:36-41.
  67. DurbeejN,BermanAH,GumpertCH,PalmstiernaT,KristianssonM,et al. (2010) Journal of Substance Abuse Treatment39(4)364-377.
  68. SpitzerRL,KroenkeK,WilliamsJBW, LoweB (2006) A brief measure for assessing generalized anxiety disorder. Archives of Internal Medicine166:1092-1097.
  69. ClarkDA,SteerRA, BeckAT (1994) Common and specific dimensions of self-reported anxiety and depression: implications for the cognitive and tripartite models. Journal of Abnormal Psychology103:645-654.
  70. LöweB,DeckerO,MüllerS,BrählerE,SchellbergD,et al. (2008) Validation and standardization of the Generalized Anxiety Disorder Screener (GAD-7) in the general population. Medical Care46: 266-274.
  71. PastoreDR,FisherM, FriedmanSB (1996) Abnormalities in weight statuseating attitudesand eating behaviors among urban high school students: correlations with self-esteem and anxiety. Journal of Adolescent Health18:312-319
  72. Pinto-Meza A, Serrano-Blanco A, Peñarrubia MT, Blanco E, Haro JM (2005) Assessing depression in primary care with the PHQ-9: can it be carried out over the telephone? J Gen Intern Med 20: 738-742.
  73. Cameron IM, Crawford JR, Lawton K, Reid IC (2008) Psychometric comparison of PHQ-9 and HADS for measuring depression severity in primary care. Br J Gen Pract 58: 32-36
  74. JohnOP,DonahueEM, KentleRL (1991) The Big Five Inventory Versions 4a and 5a. University of CaliforniaBerkeleyInstitute of Personality and Social Research, CA, USA.
  75. JohnOP,NaumannLP, SotoCJ (2008) Paradigm shift to the integrative Big Five trait taxonomy: Historymeasurementand conceptual issues, Handbook of personality: Theory and research.Guilford, New York NY, USA.
  76. SotoCJ,JohnOP,GoslingSD, PotterJ (2008) The developmental psychometrics of Big Five self-reports: Acquiescencefactor structurecoherenceand differentiation from ages 10 to 20. Journal of Personality and Social Psychology94:718-737.
  77. FaulF,ErdfelderE,LangAG, BuchnerA (2007) GPower 3: A flexible statistical power analysis program for the socialbehavioraland biomedical sciences. Behavior Research Methods39:175-191.
  78. WeiderH, KaplanEH (1975) Drug use in adolescents: Psychodynamic meaning and pharmacogenic effect,The Psychology of Adolescence.International Universities Press, New York, USA.
  79. JohnstonLD,O’MalleyPM,BachmanJG, SchulenbergJE (2007) Monitoring the future: National survey results on drug use1975-2006: Volume IIcollege students and adults ages. National Institute on Drug Abuse, Bethesda MD.
  80. BernardonS,BabbKA,Hakim-LarsonJ, GraggM (2011) Lonelinessattachmentand the perception and use of social support in university students. Canadian Journal of Behavioural Science43: 40-51.
  81. EshbaughEM (2010) Friend and family support as moderators of the effects of low romantic partner support on loneliness among college women. Individual Differences Research8: 8-16.
  82. PierceGR,SarasonIG, SarasonBR (1991) General and relationship-based perceptions of social support: Are two constructs better than one? Journal of Personality and Social Psychology58:1028-1039.
  83. CatanzaroSJ, LaurentJ (2004) Perceived family supportnegative mood regulation expectanciescopingand adolescent alcohol use: Evidence of mediation and moderation effects. Addictive Behaviors29: 1779-1797.
  84. CooperML,FroneMR,RussellM, MudarP (1995) Drinking to regulate positive and negative emotions: A motivational model of alcohol use. Journal of Personality and Social Psychology69: 990-1005.
  85. CaspersKM,CadoretRJ,LangbehnD,YucuisR, TroutmanB (2005) Contributions of attachment style and perceived social support to lifetime use of illicit substances. Addictive Behaviors30:1007-1011.
  86. Kassel JD, Wardle M, Roberts JE (2007) Adult attachment security and college student substance use. Addictive Behaviors32:1164-1176.
  87. McNally AM, Palfai TP,Levine RV, Moore BM (2003) Attachment dimensions and drinking related problems among young adults: The mediational role of coping motives. Addictive Behaviors28:1115-1127.
  88. Walant KB (1995) Creating the capacity for attachment: Treating addictions and the alienated self. Jason Aronson, Northvale NJ, USA.
  89. Grant AM,BrownB, MorenoMA (2013) The disparity between social drinking motives and social outcomes: A new perspective on college student drinking. College Student Journal47: 96- 101.
  90. Hussong AM (2003) Further refining the stress-coping model of alcohol involvement. Addictive Behaviors28:1515-1522.
  91. Walker R, StephensRS (2014) Protective behavioral strategies mediate problem-focused coping and alcohol use in college students. Addictive Behaviors39:1033-1037.
  92. Cooper ML (1994) Motivations for Alcohol Use Among Adolescents: Development and Validation of a Four-Factor Model. Psychological Assessment6: 117-128.
  93. Bradizza CM, Reifman A, BarnesG (1999) Social and coping reasons for drinking: predicting alcohol misuse in adolescents. Journal of Studies on Alcohol60:491-499.
  94. Carey KB, Correia DJ (1997) Drinking motives predict alcohol-related problems in college students. Journal of Studies on Alcohol58:100-105.
  95. Comeau N, Stewart SH, Loba P (2001)The relations of trait anxietysensitivityand sensation seeking to adolescents’ motivations for alcoholcigaretteand marijuana use. Addictive Behaviors26:803-825.
  96. Cooper ML, Russell M, Skinner JB, Windle M (1992) Development and validation of a three-dimensional measure of drinking motives. Psychological Assessment4:123-132.
  97. Brennan KA, Shaver PR (1995) Dimensions of adult attachmentaffect regulationand romantic relationship functioning. Personality and Social Psychology Bulletin21:267-283.
  98. Fletcher K,Nutton J, Brend D (2015) Attachmenta matter of substance: The potential of attachment theory in the treatment of addictions. Clinical and Social Work Journal4:109-117.
Citation: © 2016 MacNeill LP, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Copyright: MacNeill LP, DiTommaso E, Brunelle C (2016) Coping Style as a Moderator of Chronic Loneliness and Substance Use in Emerging Adults. J Depress Anxiety 5:215.
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