Does an offer of individualized alcohol care management from a nurse for up to 12 months—in which patients choose their drinking goals and alcohol-related care—improve drinking outcomes for primary care patients with heavy drinking?
In this randomized clinical trial of 304 participants, patient-centered alcohol care management did not decrease heavy drinking or alcohol-related problems at 12 months even though more patients engaged in alcohol-related care, including medications for alcohol use disorders.
Additional research is needed to develop effective primary care management for patients at high risk for alcohol use disorders.
Experts recommend that alcohol use disorders (AUDs) be managed in primary care, but effective approaches are unclear.
To test whether 12 months of alcohol care management, compared with usual care, improved drinking outcomes among patients with or at high risk for AUDs.
Design, Setting, and Participants
This randomized clinical trial was conducted at 3 Veterans Affairs (VA) primary care clinics. Between October 11, 2011, and September 30, 2014, the study enrolled 304 outpatients who reported heavy drinking (≥4 drinks per day for women and ≥5 drinks per day for men).
Nurse care managers offered outreach and engagement, repeated brief counseling using motivational interviewing and shared decision making about treatment options, and nurse practitioner–prescribed AUD medications (if desired), supported by an interdisciplinary team (CHOICE intervention). The comparison was usual primary care.
Main Outcomes and Measures
Primary outcomes, assessed by blinded telephone interviewers at 12 months, were percentage of heavy drinking days in the prior 28 days measured by timeline follow-back interviews and a binary good drinking outcome, defined as abstinence or drinking below recommended limits in the prior 28 days (according to timeline follow-back interviews) and no alcohol-related symptoms in the past 3 months as measured by the Short Inventory of Problems.
Of 304 participants, 275 (90%) were male, 206 (68%) were white, and the mean (SD) age was 51.4 (13.8) years. At baseline, both the CHOICE intervention (n = 150) and usual care (n = 154) groups reported heavy drinking on 61% of days (95% CI, 56%-66%). During the 12-month intervention, 137 of 150 patients in the intervention group (91%) had at least 1 nurse visit, and 77 of 150 (51%) had at least 6 nurse visits. A greater proportion of patients in the intervention group than in the usual care group received alcohol-related care: 42% (95% CI, 35%-49%; 63 of 150 patients) vs 26% (95% CI, 19%-35%; 40 of 154 patients). Alcohol-related care included more AUD medication use: 32% (95% CI, 26%-39%; 48 of 150 patients in the intervention group) vs 8% (95% CI, 5%-13%; 13 of 154 patients in the usual care group). No significant differences in primary outcomes were observed at 12 months between patients in both groups. The percentages of heavy drinking days were 39% (95% CI, 32%-47%) and 35% (95% CI, 28%-42%), and the percentages of patients with a good drinking outcome were 15% (95% CI, 9%-22%; 18 of 124 patients) and 20% (95 % CI, 14%-28%; 27 of 134 patients), in the intervention and usual care groups, respectively (P = .32-.44). Findings at 3 months were similar.
Conclusions and Relevance
The CHOICE intervention did not decrease heavy drinking or related problems despite increased engagement in alcohol-related care.
clinicaltrials.gov Identifier: NCT01400581
More than 13% of US adults have active alcohol use disorders (AUDs),1,2 and fewer than 1 in 5 receive alcohol treatment.1,3 Even when referred, most people with AUDs do not engage in alcohol treatment.4,5 Moreover, AUDs are often chronic.6-11
Experts have called for new models of primary care (PC) to manage AUDs.6-11 These models focus on engaging patients in patient-centered PC, often with shared decision making, because no one treatment among a number of effective medications and behavioral treatments for AUDs is consistently superior.12-15 As a result, engagement in alcohol-related care has been identified as a key measure of quality of care for AUDs, including in PC.16,17 However, trials testing PC management of AUDs have had varying results.4,18-20
The Choosing Healthier Drinking Options in Primary Care (CHOICE) intervention was designed to improve drinking outcomes by engaging patients at high risk for AUDs in patient-centered, alcohol-related care, including individualized drinking goals.21 The CHOICE trial tested whether the 12-month CHOICE intervention decreased the frequency of heavy drinking and increased the proportion of patients drinking below recommended limits without alcohol-related symptoms.
The CHOICE trial was a randomized encouragement trial22 that offered patients alcohol-related services but did not require that they accept.21 The trial was conducted at 3 Veterans Affairs (VA) PC sites in Washington (1 added after the trial commenced to meet recruitment targets) and was approved with Health Insurance Portability and Accountability Act waivers by VA Puget Sound and Kaiser Permanente Washington institutional review boards. Enrollment coordinators recruited patients and obtained written informed consent. The study had a Certificate of Confidentiality from the National Institutes of Health. The full trial protocol is available in Supplement 1.
Eligibility and Recruitment
Primary care patients were eligible for recruitment if they had positive screening results for AUDs in their VA electronic health records (EHRs) based on Alcohol Use Disorders Identification Test–Consumption (AUDIT-C) scores (≥4 points for women and ≥5 for men).23 The multistep recruitment process included asking PC providers (eg, physicians, nurse practitioners, and physician assistants) to review their patients with positive screening results for appropriateness and to sign study invitation letters if willing; sending patients invitation letters with an opt-out option; telephone screening; and in-person baseline assessments.21 About 25% of men eligible for recruitment were randomly assigned to a no-contact group to allow evaluation of recruitment effects.21
Inclusion criteria,21 designed to identify patients who might benefit from alcohol care management, included receipt of PC in a study clinic, age 21 to 75 years, and heavy drinking (≥4 drinks/occasion for women and ≥5 for men,24 at least twice per week in the past month or once per week if prior alcohol treatment).25 Exclusions were acute medical or psychiatric instability, alcohol treatment in the previous 90 days, cognitive impairment, end-of-life care, current or planned pregnancy, enrollment in another VA trial, plans to leave the VA, employment by the VA, exclusion by PC provider, or inadequate contact information.
Patients were randomized 1:1 to usual VA PC alone or usual care plus the intervention in blocks of 6, 8, and 10, stratified by sex, past-year Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition alcohol dependence, and site using a computer-generated list of random numbers. Treatment assignment was concealed by computer and assigned by a study coordinator after baseline assessments were complete.21 Primary care providers were given a general description of the intervention, and randomization assignments were noted in the EHR.
Two nurses provided alcohol care management over 12 months, consistent with effective approaches for other chronic conditions,26,27 communicating with PC providers via the VA EHR.21 A PC nurse practitioner was available to prescribe US Food and Drug Administration–approved medications for AUDs,14 and an interdisciplinary team supervised nurses weekly. Nurses received 6 to 18 hours of training in motivational interviewing and AUDs, depending on prior experience.21
Nurses initially invited patients to 1 to 2 engagement visits focused on the patients’ life and goals. Subsequently, nurses provided feedback from baseline assessments, using motivational interviewing and shared decision making28 to engage patients in considering options regarding drinking (no change, self-monitoring, decreasing drinking, or abstaining), and asked if patients wanted support for making changes. Support included repeated nurse visits to review patient self-monitoring and/or biomarkers and provide behavioral goal setting and skills development for reducing drinking, AUD medications,14 withdrawal management, mutual help (eg, Alcoholics Anonymous), and referral to and/or support for linkage to VA specialty addictions treatment, per patient preference. The frequency of nurse visits and whether they occurred by telephone or in person were also based on patient preference. However, nurses recommended follow-up every 1 to 2 weeks for 2 months and monthly thereafter, with the next appointment scheduled at the end of each contact.21 Patients who missed appointments were called weekly, then monthly, and sent letters.
All patients received usual care from their VA PC providers. The 3 study sites all offered annual behavioral health screening, integrated mental health services, and access to specialty mental health and addictions clinics.
Baseline assessments included in-person interviews, self-report questionnaires, and laboratory tests. Drinking outcomes were assessed at 3 months and 12 months by independent, blinded telephone interviewers.29 Laboratory biomarkers and self-report questionnaires were also collected at 12 months.21 Data on utilization and medications were obtained from VA databases. Patients were compensated $20, $10, and $30 for baseline, 3-month, and 12-month assessments, respectively.
Two primary outcomes, measured at 12 months, were percentage of heavy drinking days (HDDs)30 and good drinking outcomes (GDOs).31,32 These outcomes were relevant irrespective of whether a patient’s goal was abstinence. Percentage of HDDs was the proportion of nonhospitalized days when the patient reported heavy drinking (defined earlier) on the 28-day timeline follow-back interview.33 Percentage of HDDs is associated with AUD symptoms.30,34 A GDO was defined as abstinence or drinking below recommended limits based on timeline follow-back interviews (0 HDDs and ≤7 or ≤14 drinks per week for women and men, respectively), and no alcohol symptoms (past 3 months) on the Short Inventory of Problems (SIP).35
Process measures of engagement in alcohol-related care relevant to patients in both the intervention and usual care groups were as follows: receipt of AUD medications (naltrexone, acamprosate, or disulfiram); greater than 30 days’ supply of AUD medication(s); VA addictions treatment; patient-reported Alcoholics Anonymous attendance; and a composite of any of these. Measures of participation in the intervention included the number of visits with a CHOICE nurse and receipt of abnormal alcohol biomarker monitoring on 2 or more occasions (gamma glutamyl transferase, mean corpuscular volume, or carbohydrate deficient transferrin). Secondary drinking outcomes, defined a priori, included percentage of HDDs and GDO at 3 months and others measured at 3 and 12 months: no heavy drinking, percentage of days abstinent, abstinence, drinking below weekly limits (based on timeline follow-back interviews), SIP scores (past 3 months),35 and readiness rulers.36 At 12 months, patients also completed the AUDIT (0-40 points),37 including the AUDIT-C (0-12 points),23 and testing for alcohol biomarkers. Measures of health status (1-5 points)38 and hospitalizations were assessed at both follow-ups. Health care utilization and remaining covariates (Table 1)39-42 were obtained from baseline assessments or EHRs. Covariates for main analyses included stratification variables (sex, alcohol dependence, site), baseline age, and baseline value of the outcome.21
A sample size of 150 patients per group was needed to detect a difference of 4 HDDs (out of 28), based on a type I error probability of 0.05 (2-sided), to provide greater than 90% power, assuming attrition of less than 15% and an intraclass correlation coefficient of 0.05 to account for clustering of patients by PC providers, so recruitment continued until 300 patients consented. This sample size provided greater than 80% power to detect a 16% absolute difference in the proportion of patients with GDOs.
Analyses comparing the intervention and usual care groups followed an intent-to-treat approach, with patients included in randomly assigned groups regardless of participation. In accordance with the prespecified analysis plan, differences in primary and secondary outcomes between intervention and usual care groups were evaluated using generalized estimating equations regression models clustered by PC provider, adjusted for covariates described earlier.43 For the binary GDO, eligibility criteria required baseline values of 0, so analyses were adjusted for baseline percentage of HDDs. Analyses used an independent working correlation model and a robust sandwich variance estimator. For the primary outcomes, percentage of HDDs, which was nonnormally distributed (eFigure in Supplement 2), and GDO, binomial regression with a logit link was used to estimate odds ratios. For the secondary outcome percentage of days abstinent and binary outcomes (eg, abstinence), the same approaches were used. For continuous secondary outcomes (eg, laboratory tests), linear regression models were used to estimate mean differences. For count data (eg, number of PC visits), Poisson models with log link were used to estimate relative risks. For health-related quality of life, proportional odds models with a logit link were used to estimate odds ratios. Tests and confidence limits were 2-sided (α = .05).44
To account for missing follow-up data, primary analyses applied multiple imputation using chained equations,45 which assumes data are missing at random,46 based on 30 imputations (eAppendix 1 in Supplement 2). Sensitivity analyses were conducted including only complete cases, as planned a priori.
Recruitment alone could decrease drinking by patients in the usual care group,47-49 biasing the trial to the null. Therefore, the study included a no-contact group to allow evaluation of recruitment effects.21 Scores on the AUDIT-C (0-12 points) documented in the EHR in the 24 months after EHR sampling21 were compared for potentially recruited men and those randomly assigned to the no contact group (Figure), using generalized estimating equations adjusting for baseline EHR AUDIT-C scores and time to follow-up EHR AUDIT-C scores (eAppendix 2 in Supplement 2). Analyses were conducted using the Microsoft R Open software package, version 3.3.1 (Microsoft Corp).
Recruitment and Follow-up
Of 1400 patients who completed telephone screening, 571 were eligible, and 304 (53%) consented and were randomized (Figure). Two hundred seventy-five participants (90%) were male, 206 (68%) were white, and the mean (SD) age was 51.4 (13.8) years. The intervention (n = 150) and usual care (n = 154) groups were comparable at baseline (Table 1), and follow-up was comparable (Figure; eTable 1 in Supplement 2). Two hundred fifty-eight patients (85%) completed interviews at 12 months.
Receipt of the Intervention and Alcohol-Related Care
Among participants randomized to the CHOICE intervention, 137 of 150 (91%) had at least 1 visit with a CHOICE nurse and 77 of 150 (51%) had at least 6 visits (8 [5%] had 1 visit; 52 [35%], 2-5 visits; 32 [21%], 6-9 visits; and 45 [30%], ≥10 visits). While few patients in either group had biomarker monitoring, more in the intervention group had it than in usual care (17 of 150 [11%] vs 3 of 154 [2%]; odds ratio, 6.8; 95% CI, 1.8-25.9; P = .005). More patients in the intervention group than in the usual care group were treated with AUD medications (respective number of patients: oral naltrexone, 39 and 11; acamprosate, 12 and 0; and disulfiram, 4 and 5), but there was no difference in VA addiction treatment at 3 or 12 months (Table 2).
Primary outcomes improved at 12 months but did not differ between the groups. The mean percentage of HDDs decreased from 61% (95% CI, 56%-66%) at baseline to 39% (95% CI, 32%-47%) and 35% (95% CI, 28%-42%) in the intervention and usual care groups at 12 months, respectively (Table 3) (P = .44). The percentages of patients with GDOs were 15% (95% CI, 9%-22% [18 of 124 patients]) and 20% (95% CI, 14%-28% [27 of 134 patients]) in the intervention and usual care groups, respectively (P = .32) (Table 3). Results were unchanged in sensitivity analyses restricted to complete cases (eTable 2 and eTable 3 in Supplement 2).
Secondary drinking outcomes at 3 and 12 months showed no benefit of the intervention (Table 3). Percentage of days abstinent was higher in patients in the usual care group at 3 and 12 months, whereas health status showed greater improvement in patients in the intervention group at 12 months (Table 3). Outpatient utilization did not differ (eTable 4 in Supplement 2) except specialty mental health care utilization was lower for patients in the intervention group at 12 months. The remainder of secondary outcomes, including biomarkers, did not differ between groups (Table 3 and eTable 4 in Supplement 2).
Analyses of the no-contact group suggested that recruitment did not decrease patients’ drinking. Mean adjusted EHR AUDIT-C scores during follow-up did not differ between potentially recruited men and those in the no contact group (mean [SD] score of 4.2 [0.09] in the no-contact group vs 4.3 [0.05] in the potentially recruited group; P = .40) (Table 4).21
The CHOICE trial tested whether offering alcohol care management to PC patients with or at high risk for AUDs improved drinking outcomes. The intervention did not decrease drinking or related symptoms despite increasing engagement in alcohol-related care, including a 4-fold increase in initiation of AUD medications. The intervention was associated with fewer days abstinent than usual care.
Four previous trials of alcohol care management showed increased patient engagement in alcohol-related care, but findings regarding changes in patients’ drinking have been mixed. One VA trial of PC patients4 tested an intervention that included a recommendation to take naltrexone and abstain from drinking, with frequent visits to encourage both; 66% of patients receiving the intervention took naltrexone and the intervention decreased heavy drinking (secondary outcome). Another trial recruited hospitalized VA patients and tested an intervention focused on PC management of alcohol-related medical conditions with a goal of abstinence.18 The intervention improved 3 of 4 drinking outcomes.18 The AHEAD trial recruited individuals with AUDs (77%) and/or drug use disorders (DUDs) (88%) from outside PC (>74% from residential detoxification) and evaluated PC delivered by an interdisciplinary team including a care manager.19 The patient-centered intervention increased AUD medication use from 4% to 16%, but did not improve primary or secondary drinking outcomes. The SUMMIT trial tested care management in PC patients with a high probability of AUDs and/or opioid use disorders. Care coordinators offered referral for brief therapy in PC and/or to PC providers for medications. The intervention did not increase AUD or opioid use disorder medication use (both 13%), but increased abstinence from both alcohol and opioids, the primary outcome: 33% vs 22% were abstinent at follow-up (P = .03).20
Differing results between the 2 alcohol care management trials with negative findings, CHOICE and AHEAD,19 and the other 3 trials that found that care management reduced drinking4,18,20 could reflect several differences across trials. One difference was the study samples. The trials in which care management resulted in decreased drinking were either restricted to patients with AUDs only (ie, no other DUDs) or showed benefit restricted to those with AUDs only.4,18,20,50 Care management interventions might be more effective in patients with uncomplicated AUDs. However, fewer than 1 in 5 patients in CHOICE had a DUD, making it unlikely that this is the sole factor contributing to observed differences in outcomes across trials. Severity of alcohol-related symptoms does not seem to distinguish positive and negative trials. At baseline, mean SIP scores were 9 in CHOICE, 20 to 21 for alcohol in AHEAD, 6 in the VA trial, and 10 to 11 in SUMMIT.4,19,20
Other aspects of trial design could have contributed to differing findings. The CHOICE and AHEAD trials, in which care management failed to reduce drinking, had prespecified primary drinking outcomes and rigorously assessed bias due to missing follow-up data.19 The other 3 trials did not.4,18,20 However, several factors make it unlikely that improved drinking outcomes in the latter trials were spurious findings.4 One trial showed decreased heavy drinking, a single prespecified secondary outcome.4 Another found that 3 of 4 drinking outcomes significantly improved.18 The third had a composite outcome of abstinence from both opioids and alcohol, but secondary analyses showed the benefit was restricted to patients with AUDs alone.20,50 The SUMMIT trial had lower follow-up (66%) that differed somewhat across the groups (62% and 70%) and could have impacted results. The CHOICE and AHEAD trials found results unchanged with multiple imputation and complete case analyses of primary outcomes; however, follow-up rates were much higher.
Specific elements of the alcohol care management interventions seem likely contributors to the different outcomes of alcohol care management trials. The trials that showed decreased drinking in the intervention compared with the control condition were all abstinence oriented. Two of the 3 tested more directive, yet patient-centered, interventions in which patients were presented with a treatment plan with an explicit recommendation to abstain.4,18 The SUMMIT trial did not specify that the intervention was abstinence oriented, but the main outcome was abstinence. The SUMMIT intervention also offered patients a manual-driven behavioral treatment in PC.20 In contrast, CHOICE and AHEAD allowed patients to select their own drinking goals, abstinence or reduction, based on an assumption that engaging patients in alcohol-related care would decrease drinking.19 In sum, the CHOICE trial’s results, when added to existing literature,4,18-20 suggest that to be effective, alcohol care managers might need to recommend abstinence, engage most patients in use of naltrexone,4 and/or offer effective behavioral treatment in PC.20
Two trials of alcohol care management with prespecified primary drinking outcomes—CHOICE and AHEAD19—found that the experimental interventions increased engagement in alcohol-related care without improving drinking outcomes. Current quality measures for AUDs are based on the assumption that engagement in alcohol-related care alone improves outcomes. The National Committee for Quality Assurance (NCQA) Healthcare Effectiveness Data and Information Set (HEDIS) AUD measures are focused on initiation and engagement in alcohol-related care. Any visit with an eligible AUD diagnosis code is considered initiation or engagement, even a PC visit without any evidence of medication or behavioral treatment for AUDs.51 The CHOICE and AHEAD trials suggest that engagement in alcohol-related PC management alone may be insufficient to improve drinking outcomes in patients with or at high risk for AUDs. This finding has implications for future improvements for quality measurement.
The CHOICE trial has important limitations. First, while the intervention was designed to address AUDs, only 73% of participants met criteria for AUDs at baseline. Second, the multistep recruitment could have motivated some patients receiving usual care to change and/or seek care,47-49 and EHR documentation of randomization to the usual care group could have led clinicians caring for patients in the usual care group to refer them for alcohol treatment. More than 25% participated in specialty treatment or Alcoholics Anonymous by 12 months, and patients in the usual care group reported more days abstinent at both follow-ups. Future practical clinical trials should be designed to evaluate PC interventions compared with true usual care without recruitment, screening, and assessment of the comparison group until follow-up.52 Third, CHOICE was an effectiveness trial and did not assess intervention fidelity because of concern that audiotapes would interfere with engagement.21 Despite 2 hours of supervision weekly,21 the CHOICE nurses might not have offered the intervention as intended. Fourth, main measures were based on potentially biased self-report and the intervention could have made patients more comfortable accurately reporting their drinking. However, objective biomarkers did not differ between the groups. Fifth, the CHOICE trial’s main outcomes, commonly used in trials, may not reflect patient goals and those who “fail” on such outcomes could nonetheless have improved functioning.53,54 Future analyses will evaluate mental health symptoms and health status in multiple domains. Finally, only 53% of eligible patients enrolled, and the study sample consisting largely of middle-aged, male US veterans may limit generalizability.
The CHOICE intervention engaged patients in alcohol-related care and increased use of AUD medications. However, the nurse care management intervention did not decrease drinking more than usual care. Patient-centered interventions that recommend a goal of abstinence and engage most patients in medication use and/or offer brief therapy for AUDs appear most effective. Future research should evaluate whether these interventions improve functioning and health outcomes, as well as patient-reported drinking outcomes.
Accepted for Publication: January 20, 2018.
Corresponding Author: Katharine A. Bradley, MD, Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave, Ste 1600, Seattle, WA 98101 (firstname.lastname@example.org).
Published Online: March 26, 2018. doi:10.1001/jamainternmed.2018.0388
Author Contributions: Dr Bradley had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Bradley, Ludman, Saxon, Williams, Hawkins, Achtmeyer, Greenberg, Kivlahan.
Acquisition, analysis, or interpretation of data: Bradley, Bobb, Ludman, Chavez, Saxon, Merrill, Williams, Hawkins, Caldeiro, Achtmeyer, Lapham, Richards, Lee.
Drafting of the manuscript: Bradley, Bobb, Saxon, Williams, Hawkins, Achtmeyer, Lapham, Richards.
Critical revision of the manuscript for important intellectual content: Bobb, Ludman, Chavez, Saxon, Merrill, Williams, Hawkins, Caldeiro, Achtmeyer, Greenberg, Lapham, Lee, Kivlahan.
Statistical analysis: Bobb, Lapham.
Obtained funding: Bradley, Ludman, Williams, Hawkins, Kivlahan.
Administrative, technical, or material support: Ludman, Chavez, Saxon, Hawkins, Achtmeyer, Greenberg, Lapham, Richards, Lee.
Study supervision: Bradley, Ludman, Saxon, Merrill, Caldeiro, Greenberg.
Conflict of Interest Disclosures: None reported.
Funding/Support: The study was funded by the National Institute on Alcohol Abuse and Alcoholism (grant RO1 AA018702). In-kind support was provided by the Center of Excellence in Substance Abuse Treatment and Education, VA Puget Sound Health Care System, Health Services Research and Development Seattle Center of Innovation for Veteran-Centered and Value-Driven Care, and Kaiser Permanente Washington Behavioral Health Support Services. Support for manuscript preparation was provided by National Institute on Alcohol Abuse and Alcoholism grant K24 AA022128 (Dr Bradley) and VA Health Services Research and Development Career Development Award 12-276 (Dr Williams).
Role of the Funder/Sponsor: The funder/sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: Julie Laguire, RN, and Sue Ruedebusch, RN (Veterans Affairs Puget Sound Health Care System), were CHOICE nurses; Chester Pabiniak, MS, and Malia Oliver, BA (Kaiser Permanente Washington Health Research Institute), contributed to database management; Rachel Thomas, MPH (Veterans Affairs Puget Sound Health Care System), oversaw randomization, data collection, quality monitoring, and other study documentation; Chris Bryson, MD, contributed to the original grant and early conduct of the trial; and Thomas Wickizer, PhD (Ohio State University College of Public Health), Paul Cornia, MD (Veterans Affairs Puget Sound Health Care System), and Peter Roy-Byrne, MD (University of Washington School of Medicine), served as our data safety monitoring board. All received compensation from National Institute on Alcohol Abuse and Alcoholism grant RO1 AA018702 with the exception of Dr Bryson.
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