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. Author manuscript; available in PMC: 2023 Jun 1.
Published in final edited form as: J Behav Cogn Ther. 2022 Mar 19;32(2):136–144. doi: 10.1016/j.jbct.2022.02.004

Open trial of a personalized feedback intervention and substance-free activity supplement for veterans with PTSD and hazardous drinking

Matthew T Luciano a,b,*, Meghan E McDevitt-Murphy a, James G Murphy a, Rebecca J Zakarian a, Cecilia C Olin a
PMCID: PMC9307063  NIHMSID: NIHMS1791266  PMID: 35872748

Abstract

This study reports findings from an open trial of a two-session intervention for veterans with symptoms of PTSD and hazardous drinking. Rooted in behavioral economic theory, this intervention aimed to decrease alcohol use and increase alcohol-free activities through personalized and normative feedback. This trial assessed the feasibility and acceptability of the intervention in a sample of 15 veterans. Participants completed assessments at baseline and post-intervention (1-month and 3-months). Thirteen participants (86.6%) were retained between the baseline assessment and second intervention session. Acceptability data indicated that veterans overwhelmingly viewed the intervention positively with little dropout between the two sessions. Further, participants in our study reduced alcohol consumption from 37.30 (SD = 17.30) drinks per week at baseline to 22.50 (SD = 27.75) drinks per week at the 1-month assessment and then to 14.60 (SD = 18.64) at the 3-months assessment, representing medium to large effects. PTSD severity also decreased from 57.20 (SD = 16.72) at baseline to 48.90 (SD = 18.99) at the 1-month assessment, representing a small effect. Though effect sizes from pilot trials should be interpreted with caution, findings suggest that this intervention was well-received, feasible to deliver, and may have resulted in improvements in intervention targets.

Keywords: Posttraumatic stress disorder, Alcohol use, Brief intervention, Personalized drinking feedback, Behavioral economics

Hazardous alcohol use and posttraumatic stress disorder (PTSD) are common and significant issues among veterans, with one systematic review reporting prevalence rates of alcohol misuse as high as 61.3% among individuals with PTSD (Debell et al., 2014). Additionally, co-occurring PTSD and hazardous drinking is associated with serious functional health consequences (McDevitt-Murphy et al., 2010) and a more severe pattern of symptoms than those with either condition alone (Blanco et al., 2013). To address this pressing clinical issue, it is important to consider explanatory frameworks for this comorbidity that can be translated into behavioral interventions.

One framework that may offer insight into the comorbidity between PTSD and alcohol misuse is behavioral economics (Vuchinich & Tucker, 1988). Behavioral economics integrates concepts and terminology from both operant psychology and microeconomics to better understand human decision-making by considering individual and contextual factors. Contextual factors include the availability and cost (e.g., monetary, time, effort) of engaging in a behavior, as well as the availability and cost of some alternative behavior.

Behavioral economic theory is often applied to hazardous drinking (MacKillop et al., 2010), and suggests that alcohol use is less likely to occur in conditions where substance-free alternatives involve a low response cost and are readily available. This is supported by research from Joyner and colleagues (2016), who found that low reward availability in one’s environment was significantly related to higher levels of alcohol use disorder (AUD) symptoms and alcohol-related problems in a sample of college student drinkers. Further, research suggest that alcohol use is more likely to occur when individuals place a high value on alcohol (i.e., alcohol demand; Martínez-Loredo, González-Roz, Secades-Villa, Fernández-Hermida, & MacKillop, 2020). Collectively, these studies suggest that reward availability and the perceived value of alcohol may be related to harmful alcohol use, and thus, are worthy targets for behavioral interventions (Fazzino, Bjorlie, & Lejuez, 2019).

When considered in the context of PTSD, the reinforcing value of alcohol use and substance-free activities may be influenced by symptoms such as avoidance or anhedonia. For example, a loss of interest or enjoyment from activities that are constructive, social, or relaxing may lead to a shift in preference toward activities that are immediately reinforcing, such as alcohol use. At the same time, PTSD-related avoidance may limit access to substance-free alternatives, which in turn increases the likelihood of alcohol use. In line with this theory, Tripp et al. (2015) found that alcohol demand partially mediated the association between PTSD symptoms and alcohol problems. Further, suppressed environmental reward availability was also shown to mediate the relationship between PTSD severity and alcohol misuse in a sample of young adults (Acuff et al., 2018), implying that higher PTSD severity may lead to reduced access to positive reinforcement in one’s environment, subsequently leading to increased substance use.

Alcohol feedback interventions

One intervention to address harmful alcohol use is personalized and normative feedback (PNF). These interventions are administered with a Motivational Interviewing (MI) counseling style and use printed feedback packets to promote self-awareness of an individual’s drinking behavior as they compare to the drinking behavior of others. According to social norms theory (Miller & Prentice, 1994), individuals who overestimate the prevalence of peer alcohol use increase their risk for drinking. By presenting PNF, however, individuals may learn that these beliefs are incorrect and subsequently change their behavior to match the norm. These interventions have been studied extensively in college student populations, but have recently shown promise in veteran samples (Martens, Cadigan, Rogers, & Osborn, 2015; Pedersen, Parast, Marshall, Schell, & Neighbors, 2017). One such intervention aimed to reduce alcohol use in a sample of veterans in VA primary care by integrating normative feedback about alcohol use with personalized feedback about PTSD symptoms and coping styles. Results suggest that this intervention was effective in reducing alcohol consumption, alcohol-related consequences, and PTSD symptoms over a 6-month follow up interval (McDevitt-Murphy et al., 2014; Luciano et al., 2019). However, effect sizes for these types of interventions are generally small (Riper et al., 2009; Huh et al., 2015) which may suggest a need for augmentation.

Activity intervention supplements

To improve intervention effect, a newer approach has incorporated intervention supplements that are grounded in behavioral economic theory. These supplemental sessions focus on bolstering alcohol-free sources of positive reinforcement and reducing demand for alcohol. In one study, a sample of heavy drinking young adults who received a standard alcohol feedback intervention plus a session on increasing substance-free activities (e.g., joining an academic club, becoming involved in community activities/events) demonstrated greater reductions in alcohol-related problems compared to a group that was randomized to receive standard alcohol feedback plus a relaxation session (Murphy et al., 2012). Results from a follow-up study of this two-session intervention found robust and enduring reductions in alcohol consumption and problems (compared to an assessment condition) up to 16 months later. These changes in drinking were mediated by changes in substance-related reinforcement (Murphy et al., 2019), suggesting that the session content may be beneficial in improving the efficacy of single-session feedback interventions.

The present study reports on an adaptation of this intervention that was tailored for veterans with symptoms of PTSD and hazardous alcohol use. The first session incorporated elements of commonly used brief alcohol feedback interventions. The second session targeted PTSD-related avoidance behavior and anhedonia (Geisner, Neighbors, & Larimer, 2006) in an effort to increase engagement with alcohol-free sources of positive reinforcement using behavioral economic concepts (e.g., increasing value and availability of substance-free reinforcement). In addition to exploring the acceptability and feasibility of this two-session intervention, we also examined effect size estimates for (1) alcohol consumption, (2) alcohol-related consequences, and (3) PTSD severity over the course of three months in an open trial design.

Method

Participants

Fifteen veterans completed the open trial, including 13 cisgender men and 2 cisgender women. The mean age was 38.20 years (SD = 11.85). The majority of participants identified as either Non-Hispanic Black (n = 6; 40.0%), Non-Hispanic White (n = 7; 46.7%), or Other (n = 2; 13.3%). A majority of participants were veterans of the US Army (n = 9; 60%), with others reporting having served in the Marines (n = 3; 20%), Airforce (n = 2; 13.3%), or Navy (n = 1; 16.7%). All participants screened positive for hazardous drinking, reported symptoms of PTSD, and stated that they were not currently in treatment for either PTSD or AUD. In addition to alcohol, participants also reported using other substances at baseline including cannabis (n = 7; 46.7%), stimulants (n = 2; 13.3%), and cocaine (n = 1; 6.7%).

Seven of the intervention completers had full data for both the one-month and the three-month follow up assessments. Three participants completed both intervention sessions but only the one-month follow-up assessment. Three participants completed both intervention sessions and only the three-month follow-up assessment. This resulted in 10 veterans being include in the one-month effect size calculations, and a partially overlapping group of 10 veterans being included in the three-month effect size calculations. Only 2 participants were unable to complete both feedback sessions.

Procedure

Veterans were recruited throughout the community via fliers (e.g., universities, gyms, restaurants), social media advertisements (e.g., Facebook, Craigslist), outreach to Veterans groups (e.g., University-based groups, Vet Center), recontacting participants of prior observational studies (i.e., Project BRAVE), and emails to a university listserv for student veterans. All appointments occurred in Memphis, Tennessee between February 2019 and February 2020. Those who met inclusion criteria were invited to participate in the study and schedule an initial appointment.

At this appointment, Veterans completed an assessment battery that populated responses to an online database in real time. In a separate room, a study intervention used these responses to fill out a PNF packet that could be reviewed with veterans upon completion of the assessment. Responses to this assessment battery were also used to populate the activity-focused feedback session (session 2), which was delivered approximately one week after the alcohol-focused feedback session.

Interventionists on the study were doctoral students in clinical psychology (including the first, fourth, and fifth authors). All interventionists were trained in MI and the delivery of PNF interventions. Interventionists received weekly supervision and consultation by a licensed clinical psychologist (the second author).

The first intervention session focused on alcohol use through use of PNF delivered by an interventionist using MI (Miller & Rollnick, 2013). Feedback elements from this session can be found in Table 1. Norms for feedback elements were derived from a published report of a large national civilian sample and were based on age and gender (Chan, Neighbors, Gilson, Larimer, & Marlatt, 2007). This first appointment, which included the baseline assessment and alcohol-focused feedback intervention session, took approximately 2 hours to complete.

Table 1.

Intervention elements and description of purpose.

Intervention elements Purpose of intervention elements
Alcohol session
 Rapport building and introduction Fosters involvement and collaboration
 Alcohol decisional balance Establishes function and consequence of use
 Feedback on consumption and BAC Increases discrepancy between individual behavior and norms
 Feedback on financial cost, caloric cost, and other consequences of use Makes consequences concrete and sets up a discussion towards change talk
 Feedback on protective behaviors Helps to establish actionable goals
 Goal setting and grand summary Develops goals and reinforces the most salient content from the session
PTSD adapted SFAS session
 Rapport building and introduction Fosters involvement and collaboration
 Feedback on self-reported PTSD symptoms Provides perspective on PTSD symptoms
 Discuss avoided trauma-related situations and activities that are no longer enjoyed Frames avoidance behavior and anhedonia as a cause of mental health decline
 Clinical problem-solving to engage in value-driven activity Provides a specific plan for using approach-oriented behaviors
 Graphing actual time spent across activities vs. how veteran would like to spend time Provides perspective on time devoted to avoidance behavior (including drinking) and clarifies values and promotes engagement
 Personalized referrals for further treatment Provides community and VA resources for those seeking further treatment
 Personalized activity suggestions Presents a list of low- to no-cost activities of interest to veterans within the community
 Episodic future thinking activity (Atance & O’Neill, 2001) Increases future orientation and emphasizes the potential value in distal rewards
 Goal Setting and Grand Summary Develops goals and reinforces salient content
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At the conclusion of the alcohol feedback intervention, participants were scheduled for a second session with the same clinician that would occur one week later. At this second session, participants engaged in a MI counseling session aimed at increasing substance-free activity, with a particular focus on overcoming PTSD-related avoidance. The supplemental intervention was adapted from an existing manual (Substance-Free Activity Session; Murphy et al., 2012, 2019) to be more appropriate for veterans dealing with PTSD symptoms. The feedback supplement was adapted through a process of collaboration among the first three authors, and input from 5 key informant interviews. Key informants were veterans who had PTSD and a history of hazardous drinking. More information about this second session can be found in Table 1. Afterward, participants completed a brief questionnaire assessing intervention acceptability that was created specifically for this study. Participants received $30 for completing the baseline assessment and the two intervention sessions.

Participants were asked to complete two follow-up assessments occurring 1 month and 3 months after the second intervention session. Assessments were either completed in person or remotely via a secure survey link. Each follow-up assessment took approximately 30 to 45 minutes, and participants were compensated with $15 at the end of each assessment.

Measures

Alcohol Use Disorders Identification Test (AUDIT; Saunders, Aasland, Babor, De la Fuente, & Grant, 1993)

The AUDIT is a 10-item instrument that assesses hazardous drinking. Items (rated 0 to 4) are summed to create a total score ranging from 0 to 40. The AUDIT was included as a screening instrument, using the recommended cut score of 8 to identify hazardous drinking. Research has shown that the AUDIT can detect AUDs well among veterans (Crawford et al., 2013). Cronbach’s alpha at baseline for the full sample was .88.

Daily Drinking Questionnaire (DDQ; Collins, Parks, & Marlatt, 1985)

The DDQ assesses respondents’ typical level of alcohol consumption over the past month. The DDQ has demonstrated strong correlations with other measures of alcohol consumption (Kivlahan, Marlatt, Fromme, Coppel, & Williams, 1990) and good test-retest reliability (Neighbors, Dillard, Lewis, Bergstrom, & Neil, 2006). Three variables of interest were calculated from the DDQ including (a) number of drinking days per typical week, (b) number of standard drinks per typical week, and (c) number of binge days per typical week. Binge drinking was defined as 5 or more standard drinks for men or 4 or more standard drinks for women on the same drinking occasion.

Short inventory of problems (SIP; Feinn, Tennen, & Kranzler, 2003)

The SIP measures alcohol-related consequences with 15 items across five domains, although for the present study we used only the full scale. Each item is a statement (“When drinking, I have done impulsive things that I regretted later”) that the respondent is asked to rate on a scale of 0 (Never) to 3 (Daily or almost daily). Psychometric evaluations of the SIP have found it to be a highly reliable and valid instrument in a sample of heavy drinking adults (Alterman, Cacciola, Ivey, Habing, & Lynch, 2009). Given the 3-months time frame assessed in the measure, the SIP was only administered at the baseline appointment and the 3-months follow-up. Cronbach’s alpha at baseline for the total score was .96.

PTSD checklist-5 (PCL-5; Weathers et al., 2013)

The PCL-5 is a 20-item questionnaire used to assess DSM-5 symptoms of PTSD in the past month. Participants rate how much each symptom has bothered them over the past 30 days (0 = Not at all; 4 = Extremely). Items were summed to obtain a severity score (ranging from 0 to 80). The PCL-5 demonstrated strong test-retest reliability, as well as good convergent and discriminant validity in a sample of veterans (Bovin et al., 2015). We employed a standard cut score of 33 or higher as an inclusion criterion for this study. Cronbach’s alpha at baseline was .93.

Acceptability Questionnaire

A 28-item questionnaire assessing intervention acceptability was developed specifically for this study. Statements focused on important aspects of acceptability for both sessions including individual components of the intervention, intervention structure, perception on intervention mechanisms, and global perceptions of the intervention. Participants also evaluated four principles of MI, as described by Miller and Rollnick (2013). Participants rated each statement with one of three descriptive responses to indicate their level of agreement (Yes, Maybe/Sometimes, or No). This measure was administered immediately after the supplemental intervention and assessed the acceptability of both intervention sessions.

Data analysis plan

Analyses were conducted using SPSS version 26. Z-scores were computed for all variables, and outliers (> 3.29 standard deviations above the mean) were adjusted to one unit above the highest value (Tabachnick, Fidell, & Osterlind, 2013). No measures contained missing data. All acceptability data were calculated from those who completed the full intervention. Baseline means and standard deviations were calculated twice (once for those who completed the one-month follow up appointment and a second time for those who completed the three-month follow up appointment).

Analyses also examined changes in alcohol consumption, alcohol-related problems, and PTSD severity. Calculating effect size estimates in pilot studies should be done with caution due to low sample sizes and the high risk of Type I error (Leon, Davis, & Kraemer, 2011), therefore, these estimates should be considered exploratory. Hedges’s g was calculated to assess the magnitude of within subject effects and was chosen as the effect size estimator because it is the preferred metric for samples less than 20 (Ellis, 2010).

Results

Attrition and retention

A CONSORT (Consolidated Standards of Reporting Trials) flow chart describing recruitment and retention is presented in Fig. 1. A total of 129 participants were screened for study eligibility, though a majority of those who completed the screening process were not eligible for the study (n = 104). Of those enrolled (n = 15), two participants did not complete the full intervention, resulting in 13.3% attrition. One completed the alcohol-focused session, but did not return calls to schedule his second intervention. The other participant completed his baseline assessment and planned to return for the alcohol intervention, but was unable to attend due to the start of the COVID-19 outbreak.

Figure 1.

Figure 1

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CONSORT flow chart depicting recruitment, intervention completion, and follow-up rates.

Intervention acceptability

An item-by-item report on intervention acceptability can be found in Table 2. In brief, the elements of the intervention were generally rated positively, with acceptability ratings between 61.5% and 100%.

Table 2.

Acceptability of intervention components.

Yes Maybe/sometimes No
Global ratings of intervention
 I would participate in this intervention again 10 (76.9%) 3 (23.1%) 0 (0%)
 I would suggest this intervention to a friend or family member who is also using alcohol in the aftermath of a past trauma 13 (100%) 0 (0%) 0 (0%)
 I plan on using the information from this intervention to make healthier decisions 13 (100%) 0 (0%) 0 (0%)
 I felt that the intervention was specific to me (e.g., it considered my experiences, race/ethnicity, gender, and where I come from) 13 (100%) 0 (0%) 0 (0%)
MI principles — resisting the righting reflex
 I felt like the interventionist was arguing with me 0 (0%) 0 (0%) 13 (100%)
 I felt like the interventionist was trying to correct me 2 (15.4%) 0 (0%) 11 (84.6%)
MI principles — understand the patient’s motivations
 I felt understood to by the interventionist 12 (92.3%) 1 (7.7%) 0 (0%)
 The interventionist made an effort to see my perspectives on a number of issues 13 (100%) 0 (0%) 0 (0%)
MI principles — listen with empathy
 I felt listened to by the interventionist. 13 (100%) 0 (0%) 0 (0%)
 The interventionist gave me the floor to express my thoughts. 13 (100%) 0 (0%) 0 (0%)
MI principles — empower the patient
 I felt empowered by the interventionist 8 (61.5%) 5 (38.5%) 0 (0%)
 I felt like the interventionist was pressuring me to change my behavior 0 (0%) 0 (0%) 13 (100%)
Intervention structure
 I found today’s feedback packet to be helpful 13 (100%) 0 (0%) 0 (0%)
 I found today’s feedback session to be too long 1 (7.7%) 0 (0%) 12 (92.3%)
 The structure of today’s intervention was doable for me (i.e., meeting with an interventionist twice over two weeks) 11 (84.6%) 0 (0%) 2 (15.4%)
Activity intervention components
 I found today’s goal-setting worksheet to be helpful 11 (84.6%) 0 (0%) 2 (15.4%)
 I found the personalized referrals to be helpful 12 (92.3%) 0 (0%) 1 (7.7%)
 I found the personalized activities to be helpful 13 (100%) 0 (0%) 0 (0%)
 I found the future writing activity to be helpful 9 (69.2%) 0 (0%) 4 (30.8%)
 I found the feedback on how I spend my time to be helpful 13 (100%) 0 (0%) 0 (0%)
 I found the brainstorming session on how to engage in activities to be helpful 12 (92.3%) 0 (0%) 1 (7.7%)
Intervention mechanisms
 Over the last two conversations, I have become more aware of my drinking pattern and the consequences of my drinking 13 (100%) 0 (0%) 0 (0%)
 Over the last two conversations, I have become more aware of how my daily activities influence my mental health 13 (100%) 0 (0%) 0 (0%)
 Today’s session made me think more about my future 13 (100%) 0 (0%) 0 (0%)
 Today’s session has given me activities and resources that will help me grow as a person 13 (100%) 0 (0%) 0 (0%)
 Today’s session has made me want to make changes in how I spend my time 13 (100%) 0 (0%) 0 (0%)
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“Today’s session” refers to the activity session.

Effect size estimates for alcohol and PTSD outcomes

Means and standard deviations for scores derived from the DDQ, SIP, and PCL-5 are presented in Table 3. The average number of standard drinks per typical week decreased from baseline to the 1-month and 3-months assessments. Similar changes were found for binge days per typical week and number of drinking days per typical week. The average score on the SIP also decreased from baseline to the 3-months follow-up. The mean PCL-5 score decreased from the baseline to the 1-month assessment, but showed a slight increase from baseline to the 3-months assessment. Hedges’s g values are presented in Table 3. All Hedges’s g values for the DDQ fell within the medium to large range for both the 1-month and 3-months analyses. Small effects were noted for PCL-5 at the 1-month assessment and for the SIP at the 3-months assessment.

Table 3.

Means, standard deviations, and effect size estimates for outcomes and theorized mechanisms of change among intervention completers (n = 13a).

1-month completers (n = 10) 3-months completers (n = 10)
Baseline 1-month Baseline to 1-month Baseline 3-months Baseline to 3-months
M (SD) M (SD) Hedges’s g M (SD) M (SD) Hedges’s g
DDQ — Number of drinking days per typical week 5.60 (1.43) 2.90 (2.18) 1.46 5.50 (1.84) 3.30 (2.91) .90
DDQ — Drinks per typical week 37.30 (17.30) 22.50 (27.75) .64 34.80 (17.33) 14.60 (18.64) 1.12
DDQ — Binge episodes per typical week 3.70 (2.26) 1.80 (2.20) .85 3.00 (2.00) 1.40 (2.17) .77
SIP Total — — — 12.60 (10.54) 9.70 (10.46) .28
PCL-5 Total 57.20 (16.72) 48.90 (18.99) .46 55.30 (16.37) 57.10 (14.41) .12
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Questions on the SIP were assessed with a three-month timeframe, so were not included in the 1-month calculations. DDQ = Daily Drinking Questionnaire; SIP = Short Inventory of Problems; PCL-5 = PTSD Checklist for DSM-5; Hedges’s g values are considered small (g = 0.2 to 0.49), medium (g = 0.5 to 0.79), or large (g = 0.8 or higher). Thirteen veterans completed the full intervention, however, some completed the 1-month assessment and did not complete the 3-months assessment (and vice versa).

a

13 participants completed follow up data, though missing data occurred at both the 1-month and 3-months timepoints resulting in 10 completed 1-month assessments and 10 completed 3-months assessments.

Discussion

This open trial examined a two-session intervention aimed at reducing hazardous alcohol use and PTSD symptoms in a sample of veterans. A high retention rate and a positive response to the intervention support study feasibility and acceptability. Reductions in alcohol consumption, alcohol-related problems, and PTSD symptom severity were also noted over the course of the study.

Participants reported that a majority of the intervention elements were beneficial. These elements include personalized activity suggestions, a discussion on how to engage with these activities despite avoidance tendencies, and a graphing activity that helps veterans to become aware of how they are spending time. Additionally, participant ratings suggest that the study interventionists were able to foster core MI principles such as listening with empathy and empowering the client. Finally, the structure of the intervention (e.g., meeting over the course of two sessions; the length of each session, etc.) was received positively by veterans.

The strong approval ratings for the activity intervention elements suggests that participants benefited from the conversations and exercises included in this approach. Further, the strong ratings for MI principles suggests that the intervention can be delivered in such a way where participants leave feeling understood and motivated for change. It may also suggests that core MI values are not being sacrificed in exchange for additional intervention elements. Finally, the overall approval of the intervention length is promising for researchers who wish to extend the PNF approach by departing from the traditional one-session feedback intervention model.

This study also demonstrates promising feasibility which was reflected in low patient dropout. The high rate of retention in this trial (and the brevity of the intervention as a whole) suggests that the intervention itself may be feasible to implement on a larger scale. However, recruitment for this study was challenging. Over the course of a year, we screened 129 veterans to recruit 15 participants. This may speak to the feasibility of conducting a larger trial with the community-based recruitment streams we established in this pilot.

With respect to alcohol consumption and frequency, we found moderate to large estimates at both the 1-month and 3-months follow-up assessments. However, only a randomized controlled trial could determine if behavioral economic informed feedback supplements outperform single-session alcohol feedback sessions. Still, promising within-group effect sizes may provide justification to pursue a more stringent test of the hypothesis that a two-session alcohol and activity feedback session can create an effect larger than those seen in single-session alcohol feedback interventions for alcohol-related outcomes.

The changes in alcohol consumption presented here are generally in line with other studies that have employed the SFAS (on which we based the second intervention session in this trial), despite the fact that these prior trials have almost exclusively been conducted with college student samples. For example, Murphy and colleagues (2012, 2019) supplemented a brief drinking feedback intervention with a substance-free activity feedback session in two studies and found similarly sized effects for alcohol consumption and binge frequency. Though concordance between the effects of the present intervention and the effects of similar interventions is promising from a replication standpoint, it is also important to view these findings with caution due to the methodological limitations of an uncontrolled trial and because of inherent differences in the two samples.

Though two-session PNF interventions certainly hold promise, single session feedback interventions have also been shown to be useful in reducing alcohol use behavior for those with PTSD (Monahan et al., 2013; McDevitt-Murphy et al., 2014) and may even be effective in reducing symptoms of PTSD directly (Luciano et al., 2019). In the current study, PTSD symptoms reduced from baseline to the 1-month assessment, although they returned to baseline levels by the 3-months assessment. This may suggest that some aspect of our intervention, such as the reduction in alcohol use or the focus on increasing valued substance-free activities, may have short-term benefits on PTSD symptoms but are not a replacement for more intensive trauma-focused psychotherapies or more intensive behavioral activation therapies focused on increasing mood enhancing and goal-directed activities (Daughters et al., 2018).

Despite these encouraging findings, we must acknowledge several limitations. First, the lack of comparison condition in our open trial design limits our conclusions about study efficacy. In the future, a controlled trial would provide more information about this intervention’s actual effect. Second, effect size estimates should be viewed cautiously in the light of the small sample size. Third, the norms of this study were based on those from a study conducted in 2007, and these statistics may now be out of date. Fourth, because this study was underpowered for inferential statistical tests, it is impossible to know if any of the observed effects would reach the threshold of statistical significance.

Future directions and conclusions

Several future directions may be warranted in light of this study. First, it may be helpful for future studies to recruit from primary care VA settings, since primary care includes veterans who may not be actively seeking mental health treatment but may be experiencing health-related effects of their alcohol use. This could also fit well in VA primary care since regular screening for hazardous drinking and PTSD is already occurring in that setting. Second, the encouraging acceptability/feasibility results from this open trial suggest that a more rigorous test of this intervention may be warranted, such as an appropriately powered randomized controlled trial. Overall, findings of this open trial suggest that additional evaluation of this intervention approach is warranted.

Funding

This work was supported by the National Institute of Health [F31 AA026174 and T32 AA013525]. These funding sources had no involvement other than financial support.

Footnotes

Disclosure of interest

The authors declare that they have no competing interest.

Références

  1. Acuff SF, Luciano MT, Soltis KE, Joyner KJ, McDevitt-Murphy ME, & Murphy JG (2018). Access to environmental reward mediates the relation between posttraumatic stress symptoms and alcohol problems and craving. Experimental and Clinical Psychopharmacology, 26, 177–185. 10.1037/pha0000181 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alterman AI, Cacciola JS, Ivey MA, Habing B, & Lynch KG (2009). Reliability and validity of the alcohol short index of problems and a newly constructed drug short index of problems. Journal of Studies on Alcohol and Drugs, 70, 304–307. 10.15288/jsad.2009.70.304 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Atance CM, & O’Neill DK (2001). Episodic future thinking. Trends in Cognitive Sciences, 5(12), 533–539. 10.1016/S1364-6613(00)01804-0 [DOI] [PubMed] [Google Scholar]
  4. Blanco C, Xu Y, Brady K, Pérez-Fuentes G, Okuda M, & Wang S (2013). Comorbidity of posttraumatic stress disorder with alcohol dependence among US adults: Results from National Epidemiological Survey on Alcohol and Related Conditions. Drug and Alcohol Dependence, 132(3), 630–638. 10.1016/j.drugalcdep.2013.04.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bovin MJ, Marx BP, Weathers FW, Gallagher MW, Rodriguez P, Schnurr PP, & Keane TM (2015). Psychometric properties of the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders — Fifth Edition (PCL-5) in veterans. Psychological Assessment, 28, 1379–1391. 10.1037/pas0000254 [DOI] [PubMed] [Google Scholar]
  6. Chan KK, Neighbors C, Gilson M, Larimer ME, & Marlatt GA (2007). Epidemiological trends in drinking by age and gender: Providing normative feedback to adults. Addictive Behaviors, 32, 967–976. 10.1016/j.addbeh.2006.07.003 [DOI] [PubMed] [Google Scholar]
  7. Collins RL, Parks GA, & Marlatt GA (1985). Social determinants of alcohol consumption: the effects of social interaction and model status on the self-administration of alcohol. Journal of Consulting and Clinical Psychology, 53(2), 189–200. 10.1037//0022-006x.53.2.189 [DOI] [PubMed] [Google Scholar]
  8. Crawford EF, Fulton JJ, Swinkels CM, Beckham JC, Mid-Atlantic VA, VA Mid-Atlantic MIRECC OEF/OIF Registry Workgroup, & Calhoun PS (2013). Diagnostic efficiency of the AUDIT-C in US veterans with military service since September 11, 2001. Drug and Alcohol Dependence, 132(1—2), 101–106. 10.1016/j.drugalcdep.2013.01.012 [DOI] [PubMed] [Google Scholar]
  9. Daughters SB, Magidson JF, Anand D, Seitz-Brown CJ, Chen Y, & Baker S (2018). The effect of a behavioral activation treatment for substance use on post-treatment abstinence: A randomized controlled trial. Addiction, 113(3), 535–544. 10.1111/add.14049 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Debell F, Fear NT, Head M, Batt-Rawden S, Greenberg N, Wessely S, & Goodwin L (2014). A systematic review of the comorbidity between PTSD and alcohol misuse. Social Psychiatry and Psychiatric Epidemiology, 49(9), 1401–1425. 10.1007/s00127-014-0855-7 [DOI] [PubMed] [Google Scholar]
  11. Ellis PD (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press. [Google Scholar]
  12. Fazzino TL, Bjorlie K, & Lejuez CW (2019). A systematic review of reinforcement-based interventions for substance use: Efficacy, mechanisms of action, and moderators of treatment effects. Journal of Substance Abuse Treatment, 104, 83–96. 10.1016/j.jsat.2019.06.016 [DOI] [PubMed] [Google Scholar]
  13. Feinn R, Tennen H, & Kranzler HR (2003). Psychometric properties of the Short Index of Problems as a measure of recent alcohol-related problems. Alcoholism: Clinical and Experimental Research, 27, 1436–1441. 10.1097/01.ALC.0000087582.44674.AF [DOI] [PubMed] [Google Scholar]
  14. Geisner IM, Neighbors C, & Larimer ME (2006). A randomized clinical trial of a brief, mailed intervention for symptoms of depression. Journal of Consulting and Clinical Psychology, 74, 393–399. 10.1037/0022-006X.74.2.393 [DOI] [PubMed] [Google Scholar]
  15. Huh D, Mun EY, Larimer ME, White HR, Ray AE, Rhew IC, Kim SY, Jiao Y, & Atkins DC (2015). Brief motivational interventions for college student drinking may not be as powerful as we think: An individual participant-level data meta-analysis. Alcoholism: Clinical and Experimental Research, 39(5), 919–931. 10.1111/acer.12714 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Joyner KJ, Pickover AM, Soltis KE, Dennhardt AA, Martens MP, & Murphy JG (2016). Deficits in access to reward are associated with college student alcohol use disorder. Alcoholism: Clinical and Experimental Research, 40, 2685–2691. 10.1111/acer.13255 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kivlahan DR, Marlatt GA, Fromme K, Coppel DB, & Williams E (1990). Secondary prevention with college drinkers: Evaluation of an alcohol skills training program. Journal of Consulting and Clinical Psychology, 58(6), 805–810. 10.1037/0022-006X.58.6.805 [DOI] [PubMed] [Google Scholar]
  18. Leon AC, Davis LL, & Kraemer HC (2011). The role and interpretation of pilot studies in clinical research. Journal of Psychiatric Research, 45, 626–629. 10.1016/j.jpsychires.2010.10.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Luciano MT, McDevitt-Murphy ME, Acuff SF, Bellet BW, Tripp JC, & Murphy JG (2019). Posttraumatic stress disorder symptoms improve after an integrated brief alcohol intervention for OEF/OIF/OND veterans. Psychological Trauma: Theory, Research, Practice and Policy, 11(4), 459–465. 10.1037/tra0000378 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. MacKillop J, Miranda R, Monti PM, Ray LA, Murphy JG, Rohsenow DJ, & Gwaltney CJ (2010). Alcohol demand, delayed reward discounting, and craving in relation to drinking and alcohol use disorders. Journal of Abnormal Psychology, 119, 106–114. 10.1037/a0017513 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Martens MP, Cadigan JM, Rogers RE, & Osborn ZH (2015). Personalized drinking feedback intervention for veterans of the wars in Iraq and Afghanistan: A randomized controlled trial. Journal of Studies on Alcohol and Drugs, 76, 355–359. 10.15288/jsad.2015.76.355 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Martínez-Loredo V, González-Roz A, Secades-Villa R, Fernández-Hermida JR, & MacKillop J (2020). Concurrent validity of the Alcohol Purchase Task for measuring the reinforcing efficacy of alcohol: An updated systematic review and meta-analysis. Addiction, 116, 2635–2650. 10.1111/add.15379 [Epub ahead of print. PMID: 33338263] [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. McDevitt-Murphy ME, Murphy JG, Williams JL, Monahan CJ, Bracken-Minor KL, & Fields JA (2014). Randomized controlled trial of two brief alcohol interventions for OEF/OIF veterans. Journal of Consulting and Clinical Psychology, 82, 562–568. 10.1037/a0036714 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. McDevitt-Murphy ME, Williams JL, Bracken KL, Fields JA, Monahan CJ, & Murphy JG (2010). PTSD symptoms, hazardous drinking, and health functioning among U.S. OEF and OIF veterans presenting to primary care. Journal of Traumatic Stress, 23, 108–111. 10.1002/jts.20482 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Miller DT, & Prentice DA (1994). Collective errors and errors about the collective. Personality and Social Psychology, 20(5), 541–550. 10.1177/0146167294205011 [DOI] [Google Scholar]
  26. Miller WR, & Rollnick S (2013). Motivational Interviewing: Helping people change. Guilford press. [Google Scholar]
  27. Monahan CJ, McDevitt-Murphy ME, Dennhardt AA, Skidmore JR, Martens MP, & Murphy JG (2013). The impact of elevated posttraumatic stress on the efficacy of brief alcohol interventions for heavy drinking college students. Addictive Behaviors, 38(3), 1719–1725. 10.1016/j.addbeh.2012.09.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Murphy JG, Dennhardt AA, Martens MP, Borsari B, Witkiewitz K, & Meshesha LZ (2019). A randomized clinical trial evaluating the efficacy of a brief alcohol intervention supplemented with a substance-free activity session or relaxation training. Journal of Consulting and Clinical Psychology, 87, 657–669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Murphy JG, Dennhardt AA, Skidmore JR, Borsari B, Barnett NP, Colby SM, & Martens MP (2012). A randomized controlled trial of a behavioral economic supplement to brief motivational interventions for college drinking. Journal of Consulting and Clinical Psychology, 80, 876–886. 10.1037/a0028763 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Neighbors C, Dillard AJ, Lewis MA, Bergstrom RL, & Neil TA (2006). Normative misperceptions and temporal precedence of perceived norms and drinking. Journal of Studies on Alcohol, 67(2), 290–299. 10.15288/jsa.2006.67.290 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Pedersen ER, Parast L, Marshall GN, Schell TL, & Neighbors C (2017). A randomized controlled trial of a web-based, personalized normative feedback alcohol intervention for young-adult veterans. Journal of Consulting and Clinical Psychology, 85(5), 459–470. 10.1037/ccp0000187 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Riper H, van Straten A, Keuken M, Smit F, Schippers G, & Cuijpers P (2009). Curbing problem drinking with personalized-feedback interventions: A meta-analysis. American Journal of Preventive Medicine, 36, 247–255. 10.1016/j.amepre.2008.10.016 [DOI] [PubMed] [Google Scholar]
  33. Saunders JB, Aasland OG, Babor TF, De la Fuente JR, & Grant M (1993). Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction, 88, 791–804. 10.1111/j.1360-0443.1993.tb02093 [DOI] [PubMed] [Google Scholar]
  34. Tabachnick BG, Fidell LS, & Osterlind SJ (2013). Using multivariate statistics. New York: Harper & Row. [Google Scholar]
  35. Tripp JC, Meshesha LZ, Teeters JB, Pickover AM, McDevitt-Murphy ME, & Murphy JG (2015). Alcohol craving and demand mediate the relation between posttraumatic stress symptoms and alcohol-related consequences. Experimental and Clinical Psychopharmacology, 23, 324–331. 10.1037/pha0000040 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Vuchinich RE, & Tucker JA (1988). Contributions from behavioral theories of choice to an analysis of alcohol abuse. Journal of Abnormal Psychology, 97, 181–195. 10.1037/0021-843X.97.2.181 [DOI] [PubMed] [Google Scholar]
  37. Weathers FW, Litz BT, Keane TM, Palmieri PA, Marx BP, & Schnurr PP (2013). The PTSD Checklist for DSM-5 (PCL-5).. Scale available from the National Center for PTSD at www.ptsd.va.gov [Google Scholar]

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