Empathy is a well-defined active ingredient in clinical encounters. To measure empathy, the current gold standard is behavioral coding (i.e., trained coders attribute overall ratings of empathy to ...clinician behaviors within an encounter), which is labor intensive and subject to important reliability challenges. Recently, an alternative measurement has been proposed: capturing empathy as synchrony in vocally encoded arousal, which can be measured as the mean fundamental frequency of the voice (mean F0). This method has received preliminary support by one study (Imel, Barco, et al., 2014). We aimed to replicate this study by using 2 large samples of clinical interactions (alcohol brief motivational interventions with young adults, N = 208; general practice consultations, N = 204). Audio files were segmented to identify respective speakers and mean F0 was measured using speech signal processing software. All sessions were independently rated by behavioral coders using 2 validated empathy scales. Synchrony between clinician and patient F0 was analyzed using multivariate multilevel models and compared with high and low levels of empathy derived from behavioral coding. Findings showed no support for our hypothesis that mean F0 synchrony between clinicians and patients would be higher in high-empathy sessions. This lack of replication was consistent for both clinical samples, both behavioral coding instruments, and using measures of F0 synchrony occurring at both the session-level and minute-level. We considered differences in culture and language, patients' characteristics, and setting as explanations for this failure to replicate. Further replication testing and new developments regarding measurement methods and modeling are needed.
Public Significance Statement
In this study, we replicated the methods of a first analysis that tried to use new technology (automated coding of speech features) to facilitate coding of empathy in clinical interactions. Results were not replicated and showed no support for this new method. The present findings call for new developments to measure empathy, an important active ingredient of clinical encounters and therapy.
The sequential analysis of client and clinician speech in psychotherapy sessions can help to identify and characterize potential mechanisms of treatment and behavior change. Previous studies required ...coding systems that were time-consuming, expensive, and error-prone. Existing software can be expensive and inflexible, and furthermore, no single package allows for pre-parsing, sequential coding, and assignment of global ratings. We developed a free, open-source, and adaptable program to meet these needs: The CASAA Application for Coding Treatment Interactions (CACTI). Without transcripts, CACTI facilitates the real-time sequential coding of behavioral interactions using WAV-format audio files. Most elements of the interface are user-modifiable through a simple XML file, and can be further adapted using Java through the terms of the GNU Public License. Coding with this software yields interrater reliabilities comparable to previous methods, but at greatly reduced time and expense. CACTI is a flexible research tool that can simplify psychotherapy process research, and has the potential to contribute to the improvement of treatment content and delivery.
Background and aims
There is evidence that low‐risk drinking is possible during the course of alcohol treatment and can be maintained following treatment. Our aim was to identify characteristics ...associated with low‐risk drinking during treatment in a large sample of individuals as they received treatment for alcohol dependence.
Design
Integrated analysis of data from the Combined Pharmacotherapies and Behavioral Intervention (COMBINE) study, Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity) and the United Kingdom Alcohol Treatment Trial (UKATT) using repeated‐measures latent class analysis to identify patterns of drinking and predictors of low‐risk drinking patterns during treatment.
Setting
United States and United Kingdom.
Participants
Patients (n = 3589) with alcohol dependence receiving treatment in an alcohol clinical trial were primarily male (73.0%), white (82.0%) and non‐married (41.7%), with an average age of 42.0 (standard deviation = 10.7).
Measurements
Self‐reported weekly alcohol consumption during treatment was assessed using the Form‐90 and validated with biological verification or collateral informants.
Findings
Seven patterns of drinking during treatment were identified: persistent heavy drinking (18.7% of the sample), increasing heavy drinking (9.6%), heavy and low‐risk drinking (6.7%), heavy drinking alternating with abstinence (7.9%), low‐risk drinking (6.8%), increasing low‐risk drinking (10.5%) and abstinence (39.8%). Lower alcohol dependence severity and fewer drinks per day at baseline significantly predicted low‐risk drinking patterns e.g. each additional drink prior to baseline predicted a 27% increase in the odds of expected classification in heavy drinking versus low‐risk drinking patterns; odds ratio = 1.27 (95% confidence interval (CI) = 1.10, 1.47, P = 0.002. Greater negative mood and more heavy drinkers in the social network were significant predictors of expected membership in heavier drinking patterns.
Conclusions
Low‐risk drinking is achievable for some individuals as they undergo treatment for alcohol dependence. Individuals with lower dependence severity, less baseline drinking, fewer negative mood symptoms and fewer heavy drinkers in their social networks have a higher probability of achieving low‐risk drinking during treatment.
•Alcohol use disorder clinical course is dynamic and heterogeneous.•Posttreatment transitions between periods of heavy and nonheavy drinking predict long-term alcohol use and psychosocial ...functioning.•Drinking episode transitions occurring within outpatient treatment have good stability and predict long-term functioning.
The purpose of this study was to examine whether changes in heavy drinking occurring within alcohol treatment predict long-term functioning.
Latent profile analyses were conducted using data from Project MATCH and COMBINE. Observed changes in heavy and nonheavy drinking within consecutive 2-week periods over the respective treatment durations were characterized for each participant and were used to identify latent profiles.
Both data sets revealed 6 profiles: (1) continuous “remission” (nonheavy drinking); (2) transition from heavy drinking (“relapse”) to remission; (3) mostly remission, limited relapse; (4) numerous short transitions between relapse and remission; (5) transition to relapse; and (6) continuous relapse. Profiles 1 and 2 had the best long-term outcomes, Profiles 5 and 6 had the worst, and Profiles 3 and 4 fell between these groups. Within-treatment patterns of heavy drinking and nonheavy drinking were also associated with post-treatment patterns of relapse and remission.
Patterns of transition between episodes that respectively include heavy and nonheavy drinking predict long-term alcohol use and psychosocial outcomes and seem essential for clinicians to discuss with their patients. Relapses during outpatient treatment do not necessarily indicate treatment failure, provided they are relatively brief and/or infrequent. In addition, some individuals can and do change from transition patterns of heavy drinking within treatment that are predictive of poorer long-term functioning to transition patterns that predict better functioning within the first year post-treatment.
Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical ...provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients’ EHRs.
This observational study used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0−11), during routine care 3/1/2015–3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity.
Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p’s<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting ≥2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7–21.6), 16.6% initiated treatment among diagnosed (11.7–21.6), and 24.3% engaged in treatment among initiated (15.8–32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1379).
Despite documented symptoms, CUD was underdiagnosed and undertreated in medical settings.
•Documentation of cannabis use disorder (CUD) diagnosis and treatment was low.•A DSM-5 Symptom Checklist offered to patients could support diagnosis and treatment.•CUD diagnosis and treatment increased with report of symptoms on the checklist.•Gender moderated associations between reported symptoms and diagnosis and treatment.•There were missed opportunities to identify and treat CUD across all subgroups.
Background
Craving and negative affect are distressing and commonly experienced during alcohol use disorder (AUD) treatment. Patients may assume that initiating abstinence will intensify their ...cravings and negative affect despite limited empirical data to support this assumption. This study extends and replicates, under improved methodological conditions, previous work that found reductions in daily craving associated with initiating abstinence.
Methods
Seventy‐eight adults (80.8% male, 57.1% Caucasian) in a clinical trial testing prazosin for AUD provided daily reports of drinking, craving, and negative affect for up to 12 weeks (mean = 64.77 daily reports). Participants were classified into 3 subgroups based on whether and when they initiated 14 days of continuous abstinence, including (i) “abstinence initiators” who quit drinking during treatment (n = 17), (ii) “already abstainers” who were abstinent at the start of treatment (n = 20), and (iii) “continued drinkers” who never initiated abstinence (n = 41). The timing and degree of change in craving and negative affect were compared across these groups using multivariate growth curve modeling.
Results
All participant subgroups reported gradual reductions in craving over the course of treatment, with “abstinence initiators” reporting additional sudden reductions in craving upon initiating abstinence from alcohol. “Continued drinkers” reported higher levels of craving than “already abstainers” throughout the full course of treatment. Negative affect followed a different pattern of change, with “abstinence initiators” experiencing gradual reductions in negative affect after initiating abstinence but no changes prior to or immediately upon initiating abstinence, and with “already abstainers” and “continued drinkers” experiencing no changes in negative affect over time.
Conclusions
Initiating abstinence is associated with immediate reductions in craving, followed by gradual reductions in both craving and negative affect. Results provide insight into the timing and magnitude of changes in theoretically and clinically important variables and may help patients anticipate when to expect improvement in craving and negative effect.
Patients with alcohol use disorder (AUD) may worry that initiating abstinence will intensify their cravings and negative affect. We examined changes in daily craving and negative affect before and after patients initiated abstinence from alcohol during a pharmacotherapy clinical trial. Initiating abstinence was associated with immediate (same‐day) reductions in craving, followed by continued, gradual reductions in craving and negative affect after that. Results provide more precise insight into the timing and magnitude of change in clinically important AUD treatment outcomes.
Depression is the most prevalent mental health problem. The need for effective treatments for depression far outstrips the availability of trained mental health professionals. Smartphones and other ...widely available technologies are increasingly being leveraged to deliver treatments for depression. Whether there are patient characteristics that affect the potency of smartphone interventions for depression is not well understood.
This study aimed to evaluate whether patient characteristics including clinical diagnosis, depression severity, psychosis status, and current use of antidepressant medications impact the effects of an evidence-based smartphone intervention on depressive symptoms.
Data were collected as part of a 2-arm randomized controlled trial comparing a multimodal smartphone intervention called FOCUS with a clinic-based intervention. Here, we report on 82 participants assigned to 12 weeks of FOCUS treatment. We conducted assessments of depressive symptoms using the Beck Depression Inventory-second edition (BDI-II) at baseline, postintervention (3 months), and follow-up (6 months). We tested for differences in the amount of improvement in BDI-II scores from baseline to posttreatment and 6-month follow-up between each of the following patient subgroups using 2 (group) × 2 (time) mixed effects models: diagnosis (ie, schizophrenia spectrum disorder vs bipolar disorder vs major depressive disorder), depression severity (ie, minimal-mild vs moderate-severe depression), psychosis status (ie, presence vs absence of psychotic symptoms), and antidepressant use (ie, taking antidepressants vs not taking antidepressants).
The majority of participants were male (60%, 49/82), African American (65%, 53/82), and middle-aged (mean age 49 years), with a high school education or lower (62%, 51/82). There were no differences in patient demographics across the variables that were used to stratify the analyses. There was a significant group × time interaction for baseline depression severity (F
=5.26, P=.02 posttreatment and F
=6.56, P=.01 6-month follow-up). Participants with moderate or severe depression had significant improvements (t
=3.20, P=.003 posttreatment and t
=4.20, P<.001 6-month follow-up), but participants with minimal or mild depression did not (t
=0.20, P=.84 posttreatment and t
=0.43, P=.67 6-month follow-up). There were no significant group × time interactions for diagnosis, psychosis status, or antidepressant medication use. Participants with minimal or mild depression had negligible nonsignificant improvements (<1 point on the BDI-II). Reduction in depression in all other groups was larger (range 1.7-6.5 points on the BDI-II).
Our results suggest that FOCUS can be deployed to treat moderate to severe depressive symptoms among people with schizophrenia spectrum disorders, bipolar disorder, and major depressive disorder, in concert with antidepressant medications or without them, in both people with and without active psychotic symptoms. The study results are consistent with research on transdiagnostic models in psychotherapy and extend our knowledge about the potential of transdiagnostic mobile health.
ClinicalTrials.gov NCT02421965; http://clinicaltrials.gov/ct2/show/NCT02421965 (Archived by WebCite at http://www.webcitation.org/76pyDlvAS).
Couple‐based treatments for alcohol use disorders (AUDs) produce higher rates of abstinence than individual‐based treatments and posit that active involvement of both identified patients (IPs) and ...significant others (SOs) is partly responsible for these improvements. Separate research on couples’ communication has suggested that pronoun usage can indicate a communal approach to coping with health‐related problems. The present study tested whether communal coping, indicated by use of more first‐person plural pronouns (“we” language), fewer second‐person pronouns (“you” language), and fewer first‐person singular pronouns (“I” language), predicted improvements in abstinence in couple‐based AUD treatment. Pronoun use was measured in first‐ and mid‐treatment sessions for 188 heterosexual couples in four clinical trials of alcohol behavioral couple therapy (ABCT). Percentages of days abstinent were assessed during treatment and over a 6‐month follow‐up period. Greater IP and SO “we” language during both sessions was correlated with greater improvement in abstinent days during treatment. Greater SO “we” language during first‐ and mid‐treatment sessions was correlated with greater improvement in abstinence at follow‐up. Greater use of IP and SO “you” and “I” language had mixed correlations with abstinence, typically being unrelated to or predicting less improvement in abstinence. When all pronoun variables were entered into regression models, only greater IP “we” langue and lower IP “you” language predicted improvements in abstinence during treatment, and only SO “we” language predicted improvements during follow‐up. Most pronoun categories had little or no association with baseline relationship distress. Results suggest that communal coping predicts better abstinence outcomes in couple‐based AUD treatment.
Los tratamientos de pareja para los trastornos relacionados con el abuso de alcohol producen índices más altos de abstinencia que los tratamientos individuales y plantean que la participación activa de ambos pacientes identificados y sus seres queridos es parcialmente responsable de estas mejoras. Distintas investigaciones sobre la comunicación en la pareja han sugerido que el uso de pronombres puede indicar un método comunitario para afrontar problemas relacionados con la salud. El presente estudio evaluó si el afrontamiento comunitario, indicado por el uso de más pronombres de la primera persona del plural (uso de “nosotros”), menos pronombres de la segunda persona del singular (uso de “tú”), y menos pronombres de la primera persona del singular (uso de “yo”), predijeron mejoras en la abstinencia en los tratamientos de pareja para los trastornos por abuso del alcohol. Se evaluó el uso de pronombres de 188 parejas heterosexuales en las primeras sesiones del tratamiento así como en las de la mitad del tratamiento en cuatro ensayos clínicos de una terapia conductual de pareja para el abuso de alcohol. Se evaluaron los porcentajes de los días abstinentes durante el tratamiento y durante un periodo de seis meses de seguimiento. Un mayor uso del pronombre “nosotros” por parte de los pacientes identificados y de los seres queridos durante ambas sesiones estuvo correlacionado con una mayor mejora de los días abstinentes durante el tratamiento. Un mayor uso del pronombre “nosotros” por parte de los seres queridos durante las primeras sesiones y las de la mitad del tratamiento estuvo correlacionado con una mayor mejora en la abstinencia al momento del seguimiento. Un mayor uso de los pronombres “tú” y “yo” por parte de los pacientes identificados y de los seres queridos tuvo correlaciones ambivalentes con la abstinencia. Normalmente dicho uso no estuvo relacionado con la abstinencia o predijo menos mejoras en esta. Cuando todas las variables de los pronombres se ingresaron en modelos de regresión, solo un mayor uso del pronombre “nosotros” por parte de los pacientes identificados y un menor uso del pronombre “tú” por parte de los pacientes identificados predijeron mejoras en la abstinencia durante el tratamiento, y solo el uso del pronombre “nosotros” por parte de los seres queridos predijo mejoras durante el seguimiento. La mayoría de las categorías de pronombres tuvieron escasa o ninguna asociación con los problemas relacionales basales. Los resultados sugieren que el afrontamiento comunitario predice mejores resultados de abstinencia en los tratamientos de pareja para los trastornos relacionados con el abuso del alcohol.
伴侣为基础的酒精滥用障碍治疗比个人为基础的治疗戒酒比例高,并且表明身份确定的患者(IPs)及其重要伴侣(SOs)双方的积极参与对这些进展都有帮助。伴侣沟通的单独研究显示代词的使用表明了从社区角度解决健康相关问题的方法。该项研究测试了由使用更多第一人称复数代词(“我们”语言),更少第二人称代词(“你们”语言)和更少使用第一人称单数代词(“我”语言)表明的社区解决方法是否能够预期伴侣为基础的AUD治疗在戒酒方面的进展。我们在治疗初期和中期对188对异性恋伴侣在四组酒精行为伴侣治疗(ABCT)临床试验过程中代词使用进行度量。我们在治疗期间和6个月后续随访期间对戒酒天数比例进行评估。在两个阶段,更高的 IP和SO“我们”语言使用和治疗期间戒酒更大进展相关。在治疗初期和中期更多的SO“我们”语言使用和后续随访期间更大的戒酒进展有关。更高的IP和SO“你们”语言和“我”语言的使用对戒酒有混合相关性,通常与较少的戒酒进展没有关联或对其有预期。当所有代词变量都被纳入回归模型,只有更高的IP“我们”语言和更低的“你们”语言可以预期治疗期间戒酒进展,而只有SO“我们”语言可以预期后续随访过程的进展。大多数代词范畴与基线关系困扰只有很小关系或没有关系。结果表明社区应对在伴侣为基础的AUD治疗中可以预期更好的戒酒成果。
Structural equation modeling (SEM) is a multivariate data analytic technique used in many domains of addictive behaviors research. SEM results are usually summarized and communicated through ...statistical tables and path diagrams, which emphasize path coefficients and global fit without showing specific quantitative values of data points that underlie the model results. Data visualization methods are often absent in SEM research, which may limit the quality and impact of SEM research by reducing data transparency, obscuring unexpected data anomalies and unmodeled heterogeneity, and inhibiting the communication of SEM research findings to research stakeholders who do not have advanced statistical training in SEM.
In this report, we show how data visualization methods can address these limitations and improve the quality of SEM-based addictive behaviors research. We first introduce SEM and data visualization methodologies and differentiate data visualizations from model visualizations that are commonly used in SEM, such as path diagrams. We then discuss ways researchers may utilize data visualization in SEM research, including by obtaining estimates of latent variables and by visualizing multivariate relations in two-dimensional figures. R syntax is provided to help others generate data visualizations for several types of effects commonly modeled in SEM, including correlation, regression, moderation, and simple mediation.
The techniques outlined here may help spur the use of data visualization in SEM-based addictive behaviors research. Using data visualization in SEM may enhance methodological transparency and improve communication of research findings.
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•Data visualization is rarely used in SEM-based addictive behaviors research.•We discuss challenges, benefits, and approaches for visualizing SEM data.•Visualization may improve research transparency and communication to stakeholders.
Screening for unhealthy alcohol use in primary care may help identify patients at risk for negative health outcomes.
This study examined the associations between 1) screening with the AUDIT-C ...(alcohol consumption) and 2) an Alcohol Symptom Checklist (symptoms of alcohol use disorder) and subsequent-year hospitalizations.
This retrospective cohort study was conducted in 29 primary care clinics in Washington State. Patients were screened in routine care (10/1/2016–2/1/2019) with the AUDIT-C (0−12) and administered the Alcohol Symptom Checklist (0−11) if they had AUDIT-C score ≥ 7. All-cause hospitalizations were measured within 1 year of the AUDIT-C and Alcohol Symptom Checklist. AUDIT-C and Alcohol Symptom Checklist scores were categorized based on previously used cut-points.
Of 305,376 patients with AUDIT-Cs, 5.3% of patients were hospitalized in the following year. AUDIT-C scores had a J-shaped relationship with hospitalizations, with risk for all-cause hospitalizations higher for patients with the AUDIT-C scores 9–12 (12.1%; 95% CI: 10.6–13.7%, relative to a comparison group of those with AUDIT-C scores 1–2 (female)/1–3 (male) (3.7%; 95% CI: 3.6–3.8%), adjusted for socio-demographics. Patients with AUDIT-C ≥ 7 and Alcohol Symptom Checklist scores reflecting severe AUD were at increased risk of hospitalization (14.6%, 95% CI: 11.9–17.9%) relative to those with lower scores.
Higher AUDIT-C scores were associated with higher incidence of hospitalizations except among people with low-level drinking. Among patients with AUDIT-C ≥ 7, the Alcohol Symptom Checklist identified patients at increased risk of hospitalization. This study helps demonstrate the potential clinical utility of the AUDIT-C and Alcohol Symptom Checklist.
•Unhealthy alcohol use increases risk for negative health outcomes.•Brief screening tools can be used to identify unhealthy alcohol use in primary care•Unhealthy alcohol use is associated with greater risk of future hospitalization
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