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. Author manuscript; available in PMC: 2025 May 1.
Published in final edited form as: J Subst Use Addict Treat. 2024 Jan 26;160:209297. doi: 10.1016/j.josat.2024.209297

Age Moderates the Association of Optimism on Craving during Substance Use Disorder Treatment

Martin Hochheimer a, Justin C Strickland a, Jennifer D Ellis a, Jill A Rabinowitz b, JGregory Hobelmann c, Maggie Ford a, Andrew S Huhn a
PMCID: PMC11060931  NIHMSID: NIHMS1963312  PMID: 38281707

Abstract

Background:

Optimism, characterized by a positive expectancy towards future outcomes, has garnered attention for its potential role in influencing well-being and may be a protective factor in substance use disorder (SUD) treatment. This study evaluated the relationship of optimism and craving among those in substance use disorder SUD treatment.

Methods:

Drawing from a cohort of 4,201 individuals in residential SUD treatment programs, this study used both cross-sectional and longitudinal assessment to examine tonic (steady-state) and cue-induced (phasic) cravings across individuals primarily using eight classes of substances. Previous research established that optimism increases during adulthood and peaks during an individual’s 50s. This study sought to establish if the association between optimism and craving is moderated by age during the first week of treatment and if that relationship changes over the course of treatment both within and between-person.

Results:

This study found a negative correlation between optimism and craving intensity. Elevated optimism scores correlated with substantially reduced levels of both tonic (β = −0.31, p < 0.001) and cue-induced (β = −0.29, p < 0.001) cravings. Age was a significant moderator of the relationship between optimism and craving such that as individuals age, the potency of optimism in mitigating cravings gradually attenuates (interaction for tonic craving: β = 0.06, p < 0.001; interaction for cue-induced craving: β = 0.05, p < 0.001). Reflected in the fact that in older individuals’ cravings tended to converge toward lower or moderate levels, regardless of their optimism scores.

Conclusions:

By delineating the contemporaneous association between high optimism and lower cravings, the study suggests that interventions aimed at fostering optimism may represent an avenue to improve the effectiveness of SUD treatment, especially in emerging adults.

Keywords: Optimism, Craving, Substance use disorder, Treatment outcomes, Age moderation

1. Introduction:

Optimism refers to the tendency to believe that good rather than bad things will happen (Scheier & Carver, 1985). Numerous studies have linked having greater levels of trait optimism to greater career success, better social relations, better physical health (Carver & Scheier, 2014; Scheier & Carver, 2018), positive affect (Steptoe et al., 2009), and lower psychosocial stress (Biber et al., 2022; Na et al., 2021). Dispositional optimism may also protect against the development of, and aid in, recovery (broadly defined) from substance use disorders (SUD); for example, higher levels of optimism have been associated with higher rates of treatment completion among individuals with alcohol use disorder (AUD) (Strack et al., 1987) and heroin use disorder (Zaidi, 2014).

Some evidence indicates that higher optimism is associated with approach rather than avoidant coping styles, and more likely use of problem-focused coping, such as planning or seeking practical support, than emotional coping (Nes & Segerstrom, 2006). In contrast, people who have low optimism believe that the stressful present will not change and engage avoidant coping strategies that are typically emotion-focused, such as denial or wishful thinking (Büyükaşik-Çolak et al., 2012; Nes & Segerstrom, 2006). Previous research has also found that levels of optimism can be increased using a variety of interventions (Froh et al., 2008; Littman-Ovadia & Nir, 2014; Mohammadi et al., 2018; Peters et al., 2010; Peters et al., 2013; Seligman et al., 2006; Seligman et al., 2005; Shapira & Mongrain, 2010), making increasing optimism a potential target SUD treatment.

Drug craving, which has been defined as an irresistible or overpowering desire to use a substance (Flannery et al., 2001; Kleykamp et al., 2019) is one of the hallmarks of SUD (American Psychiatric Association, 2013) and has been associated with negative SUD treatment outcomes including treatment attrition (Panlilio et al., 2019) and return to use (Breese et al., 2005; Cavicchioli et al., 2020; A. S. Huhn et al., 2019; Serre et al., 2018; Serre et al., 2015; Sliedrecht et al., 2019; Stohs et al., 2019; Vafaie & Kober, 2022). For individuals in SUD treatment, craving may be a distressing symptom that presents a periodic or constant challenge in abstaining from drugs and/or alcohol (Kavanagh et al., 2013; Merikle, 1999). Two primary types of craving have been identified in the context of addiction (Shiffman, 2000), (1) baseline or tonic craving is a consistently elevated desire to use substances, and (2) phasic or cue-induced cravings, which refers to bouts of intense desire to use substances, often as the result of exposure to stimuli associated with substance use.

The elaborated intrusion-theory posits that cravings arise as either spontaneous thoughts (i.e. reflected in a baseline or tonic state) or are caused by interacting with a triggering stimulus (i.e., phasic or cue-induced) and that cravings can easily be ignored but one of the hallmarks of SUD is that individuals will perseverate and increase the importance of the thought (i.e., elaborate on the thought) until it becomes an overwhelming urge (May et al., 2015). We hypothesize that those with higher optimism will be more likely to be future focused or use problem-centered coping which will prevent the elaboration of cravings creating a milder experience.

Previous research has found that psychosocial stress and negative affect are significant predictors of heightened craving (Darharaj et al., 2023; Koob & Le Moal, 2008; Sayette, 2016) and that greater optimism is associated with higher positive affect and lower stress, possibly due to coping strategies. While optimism is conceptually described as ‘dispositional’ – implying a level of stability – there is evidence that fluctuations in optimism occur over the course of the lifecycle, with optimism typically peaking when people are in their mid-50s (Chopik et al., 2020; Furnham & Robinson, 2023; Oh et al., 2022; Scheier & Carver, 2018; Schwaba et al., 2019).

Moreover, older age has been shown to be a protective factor against both tonic and cue-induced craving (Epstein et al., 2020; Hintzen et al., 2011; Hochheimer et al., 2023) and it is possible that optimism partially explains the relationship between older age and lower craving. Importantly, at least one study has found that the effect of higher optimism on depression decreases as individuals age (Wrosch et al., 2017) This suggests that there is a change in the relationship between optimism and various factors that contribute to psychological well-being (Oh et al., 2022). Age may moderate the effect of optimism because the nature of optimism may change. In older individuals, optimism may be related to accumulating experiences which show that worst-case scenarios are rare, while optimism in youth may be more closely related to using approach focused coping, which will increase psychological well-being and possibly reduce craving. Understanding how age impacts these relationships is particularly relevant given the recent rise in treatment admissions among older adults (Andrew S. Huhn et al., 2019; Huhn et al., 2018).

This study sought to understand if the positive association of optimism and SUD treatment completion (Strack et al., 1987; Zaidi, 2014) is also reflected in higher optimism being associated with reductions in tonic and/or cue induced cravings. The first week in SUD treatment is a time of transition, when additional interventions could be implemented to promote optimism, which may have downstream effects on the experience of craving (Center for Substance Abuse Treatment, 2005). The current study first investigated if the association between optimism and craving was moderated by age during the first week of treatment. Secondarily, this study evaluated how the relationship between optimism and craving (modified by age) may change over the course of treatment. We sought to explore these associations both within and between-persons, that is to say: does an individual being more optimistic than their personal average indicate that they will also have lower craving (within-person) and do individuals who are more optimistic on average have lower tonic and cue-induced craving than those who are on average less optimistic (between-person)?

2. Method

2.1. Sample/Demographic

The sample consisted of individuals who presented for admission to 59 residential SUD treatment programs in the United States in 2021. All participants were in residential treatment, although they were not in medically managed withdrawal at the time of data collection. The study delivered weekly assessments to patients electronically (e.g., on a computer or tablet) and collected data through a third-party treatment outcomes provider (Trac9). A data transfer agreement provided de-identified data,, and the Johns Hopkins School of Medicine Institutional Review Board acknowledged the study..

During the first week of treatment each participant reported which substance they considered their primary substance from eight possibilities (alcohol, benzodiazepine, cocaine, heroin/fentanyl, marijuana, methamphetamine, prescription opioids, or prescription stimulants). Similarly, patients provided basic demographic information at this time, including race, gender, and age (in years).

2.2. Variables

2.2.1. Optimism

The study measured optimism using the Revised Life Orientation Test (LOT-R) (Scheier & Carver, 1985; Scheier et al., 1994), a 10-item scale that asks individuals the degree to which they agree or disagree with 10 statements on a 5-point Likert scale ranging from “strongly disagree” to “strongly agree.” The instrument includes three items that measure dispositional optimism (e.g., in uncertain times, I usually expect the best). There are three items that assess pessimism and were reverse coded (e.g., if something can go wrong for me, it will), and four items that measure temperament; these are described as filler and were not included in the scoring (Scheier & Carver, 1985; Scheier et al., 1994). Higher scores indicate greater optimism. Previous research foundthis scale to be reliable [α <0.74 (Gustems-Carnicer et al., 2017)]. In this sample, the scale was also reliable with α > 0.86 for each of the primary substances.

2.2. Tonic Craving

The study asked patients to complete a survey (approximately weekly) about their mental health and craving, during which they completed a measure of tonic craving that was specific to their primary substance. Those who endorsed having a primary substance of cocaine, methamphetamine, or benzodiazepines completed the items of the Cocaine Craving Questionnaire (CCQ) (Heinz et al., 2006) with the language modified so that benzodiazepine and methamphetamine replaced cocaine in the questionnaire to accommodate those whose primary substance was not cocaine. In a similar fashion, those who endorsed primary heroin/fentanyl, prescription opioids or prescription stimulants were given the Heroin Craving Questionnaire (HCQ) (Heinz et al., 2006), or a modified version of the HCQ. Those who endorsed primary alcohol use completed the Alcohol Urge Questionnaire (AUQ) (Bohn et al., 1995), and those who endorsed primary marijuana use completed the Marijuana Craving Questionnaire (MCQ) (Heishman et al., 2009).

All four of the instruments ask patients to rate on a 7-point Likert scale (ranging from 1 to 7) how strongly they agreed or disagreed with statements about craving such as: ‘I want my preferred substance so bad I can almost taste it’. The AUQ has 8-items, the CCQ has 10-items, the MCQ has 12-items and the HCQ has 14-items. Since these scales measure the level of craving in the moment, they were always completed prior to showing the visual cues.

The scores were the sum of all the items, and we included only those who responded to every item on a questionnaire. Then we converted the scores to a percent of total possible points and multiplied by 100; this created scores between 0–100 and allowed for comparisons between the four different scales (Hochheimer et al., 2023). We also preformed post-hoc sensitivity analysis using the substance class as a moderator to ensure that the scales are comparable (see Supplemental material). The tonic craving scales have been shown to have good reliability and validity for heroin, cocaine, alcohol, and marijuana (Bohn et al., 1995; Heinz et al., 2006; Heishman et al., 2009; Sussner et al., 2006). In this sample, the reliability for these scales was also high (α range = 0.89 to 0.93).

2.3. Cue-Induced Phasic craving

The study showed participants five images of their primary substance (e.g., a glass of beer or shot of whisky for alcohol). After each image, patients rated the severity of craving they experienced at that moment, using visual analog scale with 7 levels anchored with 0 = no craving and 6 = very high craving. We summed the score for each cue resulting in a total score ranging from 0–30. The reliability of this scale was consistently high in this sample across the range of substances examined (α ≥ 0.9 for each substance).

2.4. Covariates

We adjusted for primary substance given that previous research has shown it may play a role in craving severity (Fatseas et al., 2015; Serre et al., 2018). Similarly, since some previous studies found that craving differs based on race, and gender (Epstein et al., 2020; Hintzen et al., 2011) we included them as covariates. Additionally, we adjusted for days in treatment since cravings diminish over time, once substance use is discontinued (Ekhtiari et al., 2020; Ray & Roche, 2018).

2.5. Analysis

The study evaluated differences between groups based on primary substance using ANOVA followed by Tukey post hoc test. We compared categorical variables with χ2 tests. We evaluated the relationship between craving and optimism cross-sectionally at intake using two multivariate linear regressions: one with tonic craving as the dependent variable, and the other with cue-induced craving as the dependent variable. Optimism was the variable of interest as was the interaction between age and optimism. We also included as covariates days in treatment, primary substance, gender, and race, which were included with the largest group being used as the reference e.g., alcohol, male, and White, respectively. Since few patients endorsed some of the demographic categories presented in Table 1, those who endorsed ‘other’ as their gender (n=13) were included with the reference group, and those who endorsed their race as Asian (n=35), native American (n=46), native Hawaiian/Pacific Islander (n=18) were included in the ‘other’ race category (n=249).

Table 1.

Demographic Characteristics of the Sample

Alcohol (N=1,902, 45.3%) Benzodiazapine (N=98, 2.3%) Cocaine (N=439, 10.4%) Heroin/Fenta nyl (N=367, 8.7%) Marijuana (N=171, 4.1%) Methampheta mine (N=744, 17.7%) Prescription Opioids (N=403,9.6%) Prescription Stimulants (N=77, 1.8%) Overall (N=4,201)
Gender
 Female 530 (27.9%) 39 (39.8%) 111 (25.3%) 127 (34.6%) 40 (23.4%) 271 (36.4%) 114 (28.3%) 32 (41.6%) 1264 (30.1%)
 Male 1367 (71.9%) 58 (59.2%) 328 (74.7%) 239 (65.1%) 128 (74.9%) 470 (63.2%) 289 (71.7%) 45 (58.4%) 2924 (69.6%)
 Other 5 (0.3%) 1 (1.0%) 0 (0%) 1 (0.3%) 3 (1.8%) 3 (0.4%) 0 (0%) 0 (0%) 13 (0.3%)
Race
 African American/Black 175 (9.2%) 4 (4.1%) 184 (41.9%) 30 (8.2%) 29 (17.0%) 47 (6.3%) 36 (8.9%) 12 (15.6%) 517 (12.3%)
 Asian 12 (0.6%) 6 (6.1%) 4 (0.9%) 1 (0.3%) 4 (2.3%) 2 (0.3%) 4 (1.0%) 2 (2.6%) 35 (0.8%)
 Native American 17 (0.9%) 1 (1.0%) 6 (1.4%) 4 (1.1%) 6 (3.5%) 6 (0.8%) 4 (1.0%) 2 (2.6%) 46 (1.1%)
 Native Hawaiian/ Pacific Islander 8 (0.4%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 9 (1.2%) 1 (0.2%) 0 (0%) 18 (0.4%)
 Other 96 (5.0%) 4 (4.1%) 30 (6.8%) 23 (6.3%) 16 (9.4%) 39 (5.2%) 36 (8.9%) 5 (6.5%) 249 (5.9%)
 White 1594 (83.8%) 83 (84.7%) 215 (49.0%) 309 (84.2%) 116 (67.8%) 641 (86.2%) 322 (79.9%) 56 (72.7%) 3336 (79.4%)
Age
 Mean (SD) 43.0 (12.6) 33.3 (13.0)a 43.4 (13.5)b 33.7 (9.38)ac 31.3 (11.6)ac 35.0 (9.63)ace 32.9 (10.4)ac 33.8 (9.27)ac 39.0 (12.6)
 Median [Min, Max] 42.0 [18.0, 77.0] 29.0 [18.0, 71.0] 43.0 [18.0, 72.0] 32.0 [19.0, 69.0] 28.0 [18.0, 70.0] 34.0 [18.0, 65.0] 32.0 [18.0, 77.0] 33.0 [18.0, 63.0] 37.0 [18.0, 77.0]
Days in Treatment
 Mean (SD) 25.9 (18.0) 27.8 (23.0) 21.8 (14.8)ab 20.8 (17.0)ab 23.5 (19.0) 19.6 (19.0)ab 20.0 (17.6)ab 20.4 (13.7) 23.2 (18.1)
 Median [Min, Max] 25.0 [0, 126] 24.0 [0, 128] 22.0 [0, 94.0] 21.0 [0, 107] 21.0 [0, 128] 18.0 [0, 123] 19.0 [0, 128] 22.0 [0, 56.0] 22.0 [0, 128]
AMA
 Discharge AMA 170 (8.9%) 10 (10.2%) 66 (15.0%) 78 (21.3%) 31 (18.1%) 197 (26.5%) 76 (18.9%) 12 (15.6%) 640 (15.2%)
Life Orientation Test
 Mean (SD) 12.3 (5.9) 12.1 (5.2) 12.8 (5.5) 11.7 (4.9) 12.2 (5.3) 11.2 (5.5)ac 11.8 (5.6) 11.3 (5.8) 12.3 (5.7)
 Median(IQR) 13 (9,17) 11.5 (9, 16) 13 (9,14) 12 (9, 14) 12 (9, 16) 12 (8, 15.8) 12 (8, 15) 11.5 (7.8, 15)
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Significant group differences

a

different than alcohol group,

b

different than benzodiazepine group,

c

different than cocaine group,

d

different than heroin/fentanyl,

e

different than marijuana group

Multilevel mixed models evaluate the relationship between optimism and craving moderated by age both within and between-person longitudinally, with the individual being the only random effect. To accomplish this, we used the method described by Kleiman (2017) and Wang and Maxwell (2015) which is to separate the predictor of interest, in this case the LOT-R score into two separate variables. The first is the person-mean which we included as a second level predictor and acts to evaluate the between person difference in optimism. In addition, we created a first level predictor variable by mean centering each observation of the LOT-R by subtracting the person-mean and this variable describes the within person variance of the LOT-R. We conducted all analyses in R (R Core Team, 2022), and considered significant results below an α of 0.05.

3. Results

3.1. Sample

The sample included 4,201 individuals in residential treatment for substance use disorder given weekly assessments 75% of whom completed four or fewer surveys with 1% answering between 15 and 19 surveys; dispersion and density of data are visualized in the supplemental material. Of the 4,201 individuals in the original sample, 4,088 provided any information about the outcome variables of interest, one of which did not complete their first survey within the first seven days of treatment and was not included in the cross-sectional analysis. The participants endorsed one of eight substances (see Table 1 for full descriptive statistics) and the largest portion of the sample indicated that alcohol was their primary substance (45.3%, n=1902) followed by those who endorsed methamphetamine (17.7%, n = 744) and the smallest group endorsed prescription stimulants (1.8%, n = 77). The sample was mostly men (69.6%, n= 2,924); however, there was a larger proportion of women who endorsed primary benzodiazepine or prescription stimulant use (almost 40%). The sample was primarily White (79.4%, n =3,336) and the second largest group included individuals who identified as Black/African American (12.3%, n = 517). In terms of age, there were two distinct patterns; those who endorsed alcohol (M=43.0, SD = 12.6) or cocaine (M=43.4, SD = 13.5) as their primary substance were older than those who endorsed other substances by about eight years. There were small but significant differences in length of stay with the overall mean length of stay 23.2 days (SD = 18.1), though those who endorsed benzodiazepine as their primary substance was longer at 27.8 days (SD=23.0) and those who endorsed methamphetamine as their primary substance were in treatment shorter at 19.6 days (SD=19.0).

3.2. Cross-sectional Analysis

Higher optimism was significantly associated with lower tonic craving (β= −0.31, p<0.001) and cue-induced craving (β =−0.29, p<0.001), with a medium effect size using Cohen’s guidelines (Cohen, 2013; Nieminen, 2022). As expected, older age was associated with lower tonic (β =−0.10, p<0.001) and cue-induced craving (β =−0.09, p<0.001). The interaction between age and optimism was also significant in both the tonic (β =0.06, p<0.001) and cue-induced craving (β =0.05, p<0.001) such that as age increased, the association of optimism on cravings was reduced as illustrated in Figure 1a. and 2a.

Figure 1.

Figure 1.

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Tonic Craving as an Interaction Between of Age and Optimism

Note: Y-Axis scale is truncated and repeated in all figures

Figure 2.

Figure 2.

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Cue-induced Craving as an Interaction Between of Age and Optimism

Note: Y-Axis scale truncated and repeated in all figures.

When compared to primary alcohol use, all other substances were significantly associated with higher tonic craving (see Table 2.) with standardized coefficients from smallest to largest: cocaine (β= 0.12, p=0.013), methamphetamine (β=0.17, p<0.001), benzodiazepine (β= 0.41, p=0.001), heroin/fentanyl (β=0.59, p<0.001), prescription opioids (β=0.70, p<0.001), prescription stimulants (β=0.70, p<0.001), and marijuana (β=0.95, p<0.001). Aside from prescription stimulants, all other classes of substances were associated with higher cue-induced craving (see Table 2.) with standardized coefficients from smallest to largest: benzodiazepine (β= 0.21, p=0.031), prescription opioids (β=0.24, p<0.001), methamphetamine (β=0.33, p<0.001), cocaine (β=0.38, p<0.001), heroin/fentanyl (β= 0.52, p<0.001) and marijuana (β= 0.59, p<0.001). There was no significant association of gender with craving but compared to those who were White, Black/African-Americans had lower cue-induced craving (β = −0.13, p=0.005).

Table 2.

Results of the Cross-sectional Regression Analysis

Predictors Verbal craving, converted score (0–100) Visual craving, total score (0–30)
Estimates CI p Estimates CI p
Life Orientation Test - Revised −2.05 (−0.31) −2.42 – −1.68 (−0.34 – −0.28) <0.001 −0.69 (−0.29) −0.83 – −0.54 (−0.32 – −0.26) <0.001
Age −0.43 (−0.10) −0.55 – −0.30 (−0.13 – −0.07) <0.001 −0.14 (−0.09) −0.19 – −0.09 (−0.13 – −0.06) <0.001
Age * Life Orientation Test - Revised 0.02 (0.06) 0.01 – 0.03 (0.03 – 0.09) <0.001 0.01 (0.05) 0.00 – 0.01 (0.02 – 0.08) <0.001
Primary Substance Alcohol Ref. Ref.
Benzodiazepine 9.59 (0.41) 5.34 – 13.83 (0.23 – 0.60) <0.001 1.82 (0.21) 0.16 – 3.48 (0.02 – 0.40) 0.031
Cocaine 2.83 (0.12) 0.59 – 5.07 (0.03 – 0.22) 0.013 3.26 (0.38) 2.39 – 4.14 (0.28 – 0.48) <0.001
Heroin/Fentanyl 13.57 (0.59) 11.19 – 15.95 (0.48 – 0.69) <0.001 4.47 (0.52) 3.54 – 5.40 (0.41 – 0.62) <0.001
Marijuana 22.07 (0.95) 18.77 – 25.37 (0.81 – 1.09) <0.001 5.09 (0.59) 3.80 – 6.38 (0.44 – 0.74) <0.001
Methamphetamine 3.96 (0.17) 2.15 – 5.77 (0.09 – 0.25) <0.001 2.90 (0.33) 2.19 – 3.60 (0.25 – 0.41) <0.001
Prescription Opioids 16.21 (0.70) 13.92 – 18.51 (0.60 – 0.80) <0.001 2.10 (0.24) 1.20 – 2.99 (0.14 – 0.34) <0.001
Prescription Stimulants 16.30 (0.70) 11.60 – 21.00 (0.50 – 0.91) <0.001 0.62 (0.07) −1.21 – 2.46 (−0.14 – 0.28) 0.506
Gender Male Ref. Ref.
Female 0.77 (0.03) −0.61 – 2.15 (−0.03 – 0.09) 0.273 0.23 (0.03) −0.31 – 0.77 (−0.04 – 0.09) 0.402
Race White Ref
African American −1.53 (−0.07) −3.56 – 0.51 (−0.15 – 0.02) 0.142 −1.15 (−0.13) −1.95 – −0.36 (−0.22 – −0.04) 0.005
Other 0.11 (0.00) −2.19 – 2.41 (−0.09 – 0.10) 0.924 −0.68 (−0.08) −1.58 – 0.21 (−0.18 – 0.02) 0.135
Observations 4087 4087
R2 / R2 adjusted 0.233 / 0.231 0.165 / 0.163
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3.3. Longitudinal Analysis

As at intake, there was a significant inverse relationship between optimism and both tonic and cue-induced craving. There was a moderate effect size when assessed as between-person differences using the person-mean LOT-R score (tonic β=−0.33, p<0.001; cue-induced β= −0.30, p<0.001) but with a small effect when examining within-person differences using the personcentered LOT-R score (tonic β = −0.19, p<0.001, cue-induced β = −0.19, p<0.001) using Cohen’s guidelines (Cohen, 2013; Nieminen, 2022). Older age was also significantly related to reduced tonic (β = −0.45, p=<0.001) and cue-induced (β = −0.12, p<0.001) craving. The interactions between age and optimism scores were also significant (p<0.001) for both tonic (Figure 1b. and Figure 1c.) and cue-induced craving, both within-person and between person, indicating that as a person ages, the relationship between optimism and cravings are reduced (see Figure 2b. and Figure 2c.).

Longer time in treatment was also significantly related to lower tonic (β =−0.16, p<0.001) and cue-induced (β = −0.21, p<0.001) craving (see Table 3.). When compared to primary alcohol use, all other primary substances were associated with significantly higher tonic craving, except cocaine, with standardized coefficients from smallest to largest: methamphetamine (β = 0.10, p=0.002), benzodiazepine (β = 0.26, p=0.001), heroin/fentanyl (β = 0.66, p=<0.006), prescription opioids (β=0.71, p<0.001) prescription stimulants (β = 0.74, p<0.001), and marijuana (β = 0.88, p<0.001). Similarly, all substances were associated with higher cue-induced craving when compared with alcohol, except prescription stimulants, and the standardized coefficients from smallest to largest were as follows: prescription opioids (β= 0.21, p<0.001), cocaine (β=0.21, p<0.001), benzodiazepine (β =0.21, p = 0.01), methamphetamine (β = 0.27, p < 0.001), marijuana (β = 0.41, p<0.001) and heroin/fentanyl (β = 0.44, p<0.001). Neither gender nor race was significantly associated with a difference in either tonic or cue-induced craving.

Table 3.

Results of Longitudinal Regression Analysis

Tonic craving, converted score (0–100) Visual craving, total score (0–30)
Predictors Estimates (std. Beta) 95% CI (std. CI) p-value Estimates (std. Beta) 95% CI (std. CI) p-value
LOT-R person mean −2.22 (−0.33) −2.52 – −1.93 (−0.35 – −0.31) <0.001 −0.68 (−0.30) −0.80 – −0.56 (−0.32 – −0.27) <0.001
LOT-R person mean centered −1.82 (−0.19) −2.00 – −1.65 (−0.20 – −0.18) <0.001 −0.65 (−0.18) −0.71 – −0.58 (−0.19 – −0.17) <0.001
Age −0.45 (−0.07) −0.56 – −0.34 (−0.09 – −0.04) <0.001 −0.12 (−0.05) −0.17 – −0.08 (−0.08 – −0.03) <0.001
Age * LOT-R person mean 0.02 (0.07) 0.02 – 0.03 (0.05 – 0.10) <0.001 0.01 (0.05) 0.00 – 0.01 (0.03 – 0.08) <0.001
Age * LOT-R person mean centered 0.02 (0.04) 0.01 – 0.02 (0.03 – 0.04) <0.001 0.01 (0.04) 0.00 – 0.01 (0.03 – 0.04) <0.001
Days in treatment −0.16 (−0.16) −0.17 – −0.15 (−0.17 – −0.15) <0.001 −0.08 (−0.21) −0.08 – −0.07 (−0.22 – −0.20) <0.001
Primary Substance Alcohol Ref. Ref.
Benzodiazepine 5.15 (0.26) 2.23 – 8.08 (0.11 – 0.40) 0.001 1.57 (0.21) 0.38 – 2.76 (0.05 – 0.37) 0.010
Cocaine 1.26 (0.06) −0.30 – 2.83 (−0.02 – 0.14) 0.114 1.56 (0.21) 0.93 – 2.19 (0.13 – 0.30) <0.001
Heroin/Fentanyl 13.33 (0.66) 11.66 – 15.00 (0.58 – 0.75) <0.001 3.26 (0.44) 2.59 – 3.94 (0.35 – 0.54) <0.001
Marijuana 17.72 (0.88) 15.42 – 20.03 (0.77 – 1.00) <0.001 3.02 (0.41) 2.09 – 3.95 (0.28 – 0.54) <0.001
Methamphetamine 2.02 (0.10) 0.74 – 3.29 (0.04 – 0.16) 0.002 1.96 (0.27) 1.44 – 2.47 (0.20 – 0.34) <0.001
Prescription Opioids 14.14 (0.71) 12.53 – 15.76 (0.62 – 0.79) <0.001 1.55 (0.21) 0.89 – 2.20 (0.12 – 0.30) <0.001
Prescription Stimulants 14.77 (0.74) 11.45 – 18.08 (0.57 – 0.90) <0.001 0.34 (0.05) −1.00 – 1.68 (−0.14 – 0.23) 0.622
Gender Male Ref. Ref.
Female 0.17 0.01 −0.80 – 1.14 (−0.04 – 0.06) 0.729 0.37 (0.05) −0.02 – 0.76 (−0.00 – 0.10) 0.065
Race White Ref. Ref.
African American 0.01 0.00 −1.40 – 1.43 (−0.07 – 0.07) 0.984 −0.50 (−0.07) −1.07 – 0.08 (−0.15 – 0.01) 0.089
Other 0.80 0.04 −0.81 – 2.40 (−0.04 – 0.12) 0.332 −0.20 (−0.03) −0.85 – 0.45 (−0.12 – 0.06) 0.552
Random Effects
 σ2 140.27 19.31
 τ00 156.66 26.72
 ICC 0.53 0.58
 N 4088 4088
 Observations 17840 17840
 Marginal R2 / Conditional R2 0.302 / 0.670 0.222 / 0.674
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4. Discussion

4.1. Summary

This study sought to evaluate if optimism may act as a protective factor in substance use recovery by evaluating the association of optimism with tonic and/or cue-induced craving among those in treatment for SUD, and if this protective quality changes as a function of age. The results of the cross-sectional analysis indicated that during the first week in residential treatment individuals with higher optimism also report lower craving, but that the relationship between optimism and craving becomes weaker in older individuals. These associations were also found in the longitudinal analysis which also indicated that individuals with higher average optimism generally have lower tonic and cue-induced craving. Additionally, individuals with higher optimism than is typical for them at the time of assessment also had lower craving compared to their personal baseline. These finding were not only statistically significant but also clinically relevant since an individual who is able to increase their baseline (i.e., mean) optimism by five points on the LOT-R which is less than one standard deviation will also lower both their tonic and cue-induced by over 10% of the scale (11.1/100 for tonic craving and 3.4/30 for cue-induced craving).

This study extends previous research has found that optimism is associated with higher levels of treatment completion for individuals in treatment for AUD and HUD (Strack et al., 1987; Zaidi, 2014), by examining tonic and cue-induced cravings which are also measures that are associated with positive treatment outcomes. These findings continue to expand the interrelationships between optimism, positive affect, and coping styles. Optimism is associated with positive affect (Steptoe et al., 2009), which is in turn associated with lower cravings (Carrico et al., 2018; Lydon-Staley et al., 2017; Schlauch et al., 2013) and conversely that low optimism is associated with negative affect which is in turn associated with higher craving (Cyr et al., 2022; Hogarth, 2020; Hogarth et al., 2019). Optimism is also associated with lower psychosocial stress (Biber et al., 2022; Na et al., 2021), which is a correlate of lower craving (Ruisoto & Contador, 2019) and finally, optimism is associated with self-efficacy (Görgülü, 2019; Majer et al., 2004) which is also a correlate of lower cravings.

At the heart of these associations may be that individuals who believe that generally good rather than bad things will happen fear failure less and believe that they are likely to find a solution to whatever difficult situation they are in. They therefore discount the possibility of failure and are more willing to employ approach-oriented and usually problem-focused coping styles (Büyükaşik-Çolak et al., 2012; Carver & Scheier, 2014; Carver & Scheier, 2017; Nes & Segerstrom, 2006; Scheier & Carver, 1985), which may lead to higher self-efficacy and positive affect. Additionally, believing that good things will happen and that stressful situations are challenges that can be addressed may allow individuals with higher optimism to more effectively cope with stressful situations in the moment than those with lower optimism. They may similarly rate their experience of craving lower than those with lower optimism. In addition, the fact that the relationship between optimism and craving attenuates as people age may be due to the higher prevalence of adaptive coping styles in older adults (Meléndez et al., 2012), which allow an individual not to be distressed by their experience of craving.

4.2. Strengths/Limitations

This study has several strengths that lend support to its findings. This study used a large sample drawn from different communities across the US that consisted of individuals in treatment for eight substance classes, providing a representative picture of the relationship between optimism and craving across the lifespan in a sample that can be generalized to the population of SUD treatment seekers. The study also employed a longitudinal design, which allowed for the examination of changes in the association between optimism and craving over time and used a method to disaggregate the between-person and within-person effects.

The strengths of this study design are tempered by several limitations including using self-report subjective measures of either tonic or cue-induced craving (instead of objective measures e.g., neurophysiology), and the rescaling of different measures of similar constructs for comparison purposes. Additionally, we limited the sample to individuals in residential treatment settings to better compare individuals within the same setting, which increases internal validity but limits generalizability. Given that we followed a single cohort, it may be difficult to disentangle effects of aging vs. age groups, however, previous research that has followed several cohorts with one study following a cohort of adults aged 16–70 over the course of 25 years and consistently found that optimism increases with age and peaking when individuals are in their mid 50s (Chopik et al., 2020; Furnham & Robinson, 2023; Oh et al., 2022; Schwaba et al., 2019).

4.3. Implications

While our findings suggest a potential link between optimism and craving reduction, it is important to recognize the constraints of this observational study and the modest effect of increased optimism directly on cravings. These data suggest that promoting optimism may be a useful strategy for reducing craving and improving treatment outcomes. While further research is needed before drawing definitive conclusions, this study supports the suggestion of a 2017 review (Malouff & Schutte, 2017), that many interventions that have been shown to increase optimism to moderate or large effect and can easily be incorporated into standard SUD treatment including self-compassion training (Smeets et al., 2014), a cognitive behavioral therapy curriculum (Antoni et al., 2001), training to develop an adaptive coping strategy (Chesney et al., 2003), and the Best Possible Self intervention (Meevissen et al., 2011), which involves visualization of life after everything has gone well and personal goals have been achieved. Moreover, the discernment that age nuances the optimism-craving interconnection creates the possibility that research into tailoring treatment modalities to different age brackets combined with levels of optimism, may be worthwhile, especially given the escalating number of older adults seeking SUD treatment (Andrew S. Huhn et al., 2019; Huhn et al., 2018).

Supplementary Material

1
NIHMS1963312-supplement-1.docx (1,001.7KB, docx)

  • Optimism significantly reduces both tonic and cue-induced cravings in SUD treatment.

  • Age moderates the relationship between optimism and craving so that as individuals age the effect of optimism is less.

  • Interventions that improve optimism should be incorporated into substance use treatment.

Funding:

This study was supported by the National Institute on Drug Abuse T32 DA007209 (Strain, Weerts) and UH3 DA048734 (Huhn).

Footnotes

Conflict of Interest

The authors have no conflicts of interest to report

CREDIT

Martin Hochheimer – conceptualized the study, conducted the analysis, wrote the original draft and reviewd and edited the draft

Justin Strickland – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript.

Jennifer Ellis – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript.

Jill Rabinowitz – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript.

J. Gregory Hobelmann – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript.

Maggie Ford – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript.

Andrew Huhn – assisted with developing the method of analysis, made significant contributions to the rewriting, and editing of the manuscript, supervised and administered the study.

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