Change in Patient Activation and Mental Illness Symptoms After Communication Training: A Multisite Study With a Diverse Patient Sample
Abstract
Objective:
Patient activation involves patients’ ability and motivation to communicate about their health and health care. Research has demonstrated that clinician or patient interventions may improve patient activation. This study explored the degree to which clinician and patient interventions affected both patient activation and symptoms of depression and anxiety in a racially and ethnically diverse clinical sample.
Methods:
Data were from a randomized clinical trial that included 312 patients and 74 clinicians from 13 Massachusetts community- and hospital-based outpatient behavioral health clinics. Patients completed measures of patient activation and depression and anxiety symptoms. Secondary data analyses were conducted to examine the effect of patient and clinician interventions (DECIDE-PA and DECIDE-PC, respectively) on depression and anxiety symptoms and patient activation. A multilevel, mixed-effects simultaneous-equation model was estimated to assess the relationship between the interventions, changes in patients’ symptoms, and patient activation.
Results:
Clinicians’ greater intervention dosage (i.e., more completed DECIDE-PC training sessions) was associated with patients’ decreased anxiety symptoms, but associations with patient activation or depression symptoms were not significant. The effect of clinician training dosage on anxiety symptoms was stronger when patients and clinicians were not of the same race-ethnicity. The reduction in patients’ anxiety symptoms appeared to increase patient activation.
Conclusions:
Clinician interventions designed to boost patient-clinician communication and the therapeutic alliance may serve to lessen patients’ anxiety and may ultimately improve patient activation.
HIGHLIGHTS
•
In a racially and ethnically diverse sample, patients whose clinician had participated in more DECIDE-PC training sessions had greater improvements in anxiety symptoms.
•
The effect of the clinician's training dosage on the patient's anxiety was stronger for clinician-patient pairs that were racially-ethnically discordant than for concordant pairs.
•
Improvements in anxiety symptoms appeared to lead to greater patient activation in a racially and ethnically diverse clinical sample treated mostly by white providers.
Patient activation involves patients’ capacity and motivation to manage their health and health care (1–3). It is pivotal in improving patient-clinician communication and the overall quality of behavioral health care (4, 5) and health outcomes (6–8). Interventions designed to promote patient activation have involved peer specialists (9) and a brief educational program (10) as part of patient care. Patient interventions have been found to improve patients’ self-efficacy (11–13), health management skills (4, 5), and health behaviors (14), with mixed findings regarding the effect on symptoms of mental illness (10, 15). The patient intervention, DECIDE-PA program (Decide the problem; Explore the questions; Closed- or open-ended questions; Identify the who, why, or how of the problem; Direct questions to your health care professional; and Enjoy a shared solution), is the first manual-based patient intervention shown to improve patient activation among behavioral health care patients in a clinical trial (4). This program targets the communication aspects that could influence patient activation, such as patients’ ability to learn information about their illness, communicate their needs, discuss treatment options, and ask questions about their care with health care professionals (16).
The clinician intervention is another important but less discussed approach to improve patient activation. Research involving interventions in community mental health clinics demonstrated that a therapeutic alliance (i.e., patient-clinician agreement on tasks-goals and bonds [17, 18]) is a prerequisite for the prospective development of patient activation (19). Given the well-documented contribution of the therapeutic alliance to mental health outcomes (20, 21), improved patient-clinician communication may lower symptoms of mental illness as a result of a better therapeutic alliance. By enhancing clinicians’ perspective taking (22), decreasing clinicians’ attribution error (23), and increasing patient-clinician collaboration, DECIDE-PC is a clinician intervention, incorporating workshops and individualized coaching, that was found to improve shared decision making (24). However, little is known about the effect of clinician interventions on the association between patient activation and symptoms of mental illness. The extent to which DECIDE-PA and DECIDE-PC improve patient activation and mental illness symptoms has not been previously examined.
Interventions to improve patient activation should be considered within continued efforts to reduce racial-ethnic mental health disparities (25). For example, underestimating less communicative patients’ need for information, clinicians sometimes spend less time offering information about illness and treatment options to less activated patients (26), many of whom are from racial-ethnic minority groups (27–29). Some of these patients hold traditional cultural views of patient roles, and thus they may feel less comfortable communicating with clinicians, compared with patients from nonminority groups. For instance, Vietnamese patients may consider it inappropriate to question an authority (30), and Latino patients may have concerns that expressing their needs will weaken the patient-clinician relationship (16). Poor patient-clinician communication (27) may put racially-ethnically diverse patients at greater risk of treatment noncompliance (31) and treatment dropout (32).
To the best of our knowledge, no study has investigated the influence of patient and clinician interventions on the relationship between mental illness symptoms and patient activation. In this study, we explored the effect of patient and clinician interventions on both mental illness symptoms and patient activation, as well as the relationship between symptoms and activation, in a diverse clinical sample. Because the DECIDE interventions target patient activation with a focus on improving patient-clinician communication, we hypothesized that both interventions would improve patient activation and, therefore, mental illness symptoms. One might expect that an improvement in patient activation would reduce mental illness symptoms; however, it is possible that improvements in mental health have a positive effect on patient activation. This study was exploratory in nature given the gaps in prior research. We also explored whether the effect of the interventions on mental illness symptoms was different in patient-clinician dyads that were racially-ethnically discordant or linguistically discordant and whether the effect differed by patient gender, given past research on communication for diverse patients (33, 34).
Methods
Setting and Sample
The study used data from a randomized clinical trial assessing the effectiveness of DECIDE-PA and DECIDE-PC to improve shared decision making and patient-perceived quality of care. A full description of the four-arm study (PC and PA, PA only, PC only, and neither) and a report of its findings have been published elsewhere (24). Eligible patients and clinicians were recruited and randomly assigned to participation in the DECIDE interventions across 13 community- and hospital-based outpatient mental health clinics in Massachusetts (September 2013 to September 2016). Most clinics served predominantly low-income patients from racial-ethnic minority groups. Eligible clinicians were behavioral health practitioners (e.g., social workers, psychologists, and psychiatrists). A total of 79 clinicians provided written consent to participate (five withdrew before randomization to the intervention). Eligible patients were ages 18 to 80; spoke English, Spanish, or Mandarin; and were enrolled in individual behavioral health care treatment (e.g., psychotherapy or psychopharmacology) with a clinician also enrolled in the study. Patients 65 years or older with a positive screen for cognitive impairment, mania, psychosis, or active suicidal ideation were excluded from the trial. Following these criteria, 312 patients providing informed consent and 74 clinicians participated in a cross-level 2 × 2 randomized clinical trial in which patients were nested within clinicians. The study was approved by the institutional review boards of the participating institutions. All study staff fully complied with the approved protocol and procedures.
Procedure
After initial screening and recruitment of participants, patients and clinicians completed three assessments: a baseline assessment within the first 30 days after recruitment and before the first training session (time 1); a follow-up assessment 1 month after baseline for patients and within 4 months after baseline for clinicians (time 2), and a final assessment 3 months after follow-up for patients and within 1 month after follow-up for clinicians (time 3). The clinician intervention included a 12-hour workshop taught by behavioral health professionals and communication experts (coaches) at time 1, followed by up to six coaching calls between times 1 and 3. The patient intervention included up to three 60-minute training sessions between times 1 and 3. All assessments included patient self-reports of patient activation (identical measures of patient activation at times 1, 2, and 3), but only the baseline and final assessments included patient self-reports about mental health (identical measures of mental illness symptoms at times 1 and 3).
Measures
Patient assessments were administered in English (N=205), Spanish (N=89), or Mandarin (N=17), based on patient preference.
Sociodemographic characteristics.
Patients and clinicians completed a baseline sociodemographic questionnaire (i.e., gender, age, race-ethnicity, primary language, region of origin, personal income, and education and employment status). Clinicians indicated their professional specialty (psychologist, psychiatrist, social worker, or other).
Patient Activation Scale.
A modified version of the Patient Activation Scale (PAS) (35–37) contains nine items assessing patient activation during a medical encounter. The PAS was used because of its strength in capturing the communication aspects of patient activation. A representative item was, “How much have you discussed treatment options for your emotional, mental health or substance abuse problems with your provider?” Items are rated on a 10-point scale (1, not at all, to 10, very) and summed (possible score range 10–90), with higher scores reflecting better patient activation.
We studied the psychometrics of the PAS version for the study sample (α=0.82) and for the translated measures (α=0.83, α=0.79, and α=0.84 in English, Spanish and Mandarin, respectively). A factor analysis indicated the one-factor solution to be the most appropriate. The two-factor model in the English and Spanish measures had better fit statistics, but there were no items loading onto a second factor in the Spanish version. More important, because only 17 participants were administered the measure in Mandarin, the two-factor model did not converge for this version.
Patient Health Questionnaire–depression module.
The depression module from Patient Health Questionnaire (PHQ-9) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders (35–39). It includes nine items corresponding to DSM-IV criteria for major depression, rated on a 4-point scale (0, not at all, to 3, nearly every day) that are summed (possible score range 0–27), with higher scores indicating worse depressive symptoms.
Generalized Anxiety Disorder screener.
The seven-item Generalized Anxiety Disorder (GAD-7) is a self-report screener designed to assess symptom severity of generalized anxiety (40). Participants were asked how often, during the past 2 weeks, they had been bothered by each of the seven core symptoms of generalized anxiety disorder; they used a 4-point scale (0, not at all, to 3, nearly every day). These ratings were summed (possible score range 0–21), with higher scores reflecting worse anxiety symptoms.
Statistical Analysis
We first estimated the effect of the DECIDE-PA and -PC interventions on patient activation and mental illness symptoms. Using results from this analysis, we then examined the relationship between mental illness symptoms and patient activation.
We considered the effect of the DECIDE interventions on four primary outcomes: PAS score at time 2, PAS score at time 3, PHQ-9 score at time 3, and GAD-7 score at time 3. Each outcome had different amounts of missing information at either time 2 or time 3, with outcome data missing from 46 (14.7%) for PAS at time 3 to 74 (23.7%) for PAS at time 2. Analysis of attrition patterns for each outcome revealed no significant differences in either patient or clinician baseline characteristics, except for patient education. (A table in an online supplement to this article presents results of this analysis.) To account for missing data, we applied multiple imputation with Stata chained equations (42–44), but we nevertheless decided to control for patient education throughout the analyses.
We used multilevel, mixed-effects models in two types of analysis. First, we estimated effects of the DECIDE interventions (PA and PC) on outcomes on the basis of assignment to the intervention or control group, independent of treatment receipt (intent to treat). We then examined whether the effect of the interventions was a function of training dosage, with dosage defined as the number of completed training sessions divided by the number of intended sessions (three for patients and six for clinicians). We also estimated the effects of training dosage by racial-ethnic discordance between patients and clinicians, linguistic discordance between patients and clinicians, and patient gender. Analyses were performed with Stata software, version 15.1 (42), with all significance tests adjusted for multiple imputation and small sample size (45, 46). Regression models accounted for nesting of patients within clinicians and used robust empirical standard errors (47).
The intent-to-treat and training dosage analyses indicated that the DECIDE interventions had no effect on any of the primary outcomes except for the GAD-7 score: the clinician training dosage improved the patient’s anxiety symptoms. We used this result to examine the relationship between the patients’ anxiety symptoms (GAD-7 scores) and patient activation (PAS scores). Examining this relationship was challenging because changes in anxiety symptoms could have influenced patient activation; however, changes in patient activation could also have affected anxiety symptoms. In addition, unobserved factors (e.g., self-motivation) may have affected both anxiety symptoms and patient activation at the same time, and changes in these outcomes could be due to such unobserved factors. Because our training dosage analyses indicated that the clinician dosage influenced the GAD-7 score but did not directly affect the PAS score at time 3, we could use the clinician dosage as an instrument for measuring how changes in anxiety symptoms affected patient activation. Clinician dosage could serve as an instrument because it could have affected patient activation (PAS score) only through its effect on anxiety symptoms (GAD-7 score). Thus we were interested in how clinician dosage affected the association between patient activation and anxiety symptoms.
We estimated a multilevel, mixed-effects simultaneous-equation model to assess the effect of improved GAD-7 scores at time 3 on PAS scores at time 3 (48). A multilevel model was used to allow for clustering of patients within clinicians, and a simultaneous-equation model was used to adjust for the endogeneity of the GAD-7 score. Patient activation and anxiety were treated as a bivariate response, and a multilevel model was defined for each response (with clinician random effects included in each). The patient activation model, in which PAS score at time 3 was the dependent variable, controlled for PAS score at time 1 and baseline patient and clinician characteristics. The anxiety model, in which GAD-7 score at time 3 was the dependent variable, controlled for GAD-7 score at time 1 and the same baseline patient and clinician characteristics as in the patient activation model (see table in online supplement for this model). The random effects could be correlated across patient activation and anxiety equations. Analyses were performed with reweighted iterative generalized least squares as implemented in MLwiN software, version 3.02 (49).
Results
Effects of DECIDE Interventions on Patient Activation and Mental Illness Symptoms
Table 1 presents results of intent-to-treat and training dosage analyses. No significant differences were found in the baseline outcome measures between patients in the control and treatment groups. Therefore, changes in PAS scores and measures of mental illness symptoms between baseline and time 2 or time 3 were interpreted as an effect of the DECIDE interventions. The omnibus test in the intent-to-treat analysis was not significant for any outcome (all p values >.05); however, the omnibus test for training dosage was significant for the GAD-7 scores (F=3.62, df=3, 1,843.1, p=0.013). On a 21-point scale, the mean±SD GAD-7 score in the final assessment (7.30±5.39) was 1.43 points lower when clinicians received more of the recommended sessions, compared with when clinicians received no coaching (b=−1.43, SE=0.60, p=0.017; Cohen’s d=–0.27). No other omnibus test or individual test was significant.
| Baseline measure | Control | Intervention | tb | p |
|---|---|---|---|---|
| Patient Activation Scale (PAS) mean score | 70.70±13.86 | 70.61±12.16 | –.06 | .95 |
| Nine-item Patient Health Questionnaire (PHQ-9) mean score | 9.54±5.99 | 10.40±6.08 | 1.25 | .21 |
| Seven-item Generalized Anxiety Disorder (GAD-7) | 7.80±5.63 | 8.77±5.60 | 1.53 | .13 |
| Intervention effect | Coeff. | SE | Cohen’s d | p |
| PAS (time 2)c | ||||
| Patient intervention | –.83 | 1.17 | –.07 | .48 |
| Clinician intervention | –.42 | 1.21 | –.03 | .73 |
| Patient and clinician intervention | 2.56 | 2.35 | .21 | .28 |
| PAS (time 3)d | ||||
| Patient intervention | .17 | 1.20 | .01 | .89 |
| Clinician intervention | –.17 | 1.36 | –.01 | .90 |
| Patient and clinician intervention | 3.65 | 2.41 | .28 | .13 |
| PHQ–9 (time 3)e | ||||
| Patient intervention | –.20 | .59 | –.03 | .73 |
| Clinician intervention | –.44 | .61 | –.07 | .47 |
| Patient and clinician intervention | .21 | 1.15 | .03 | .86 |
| GAD-7 (time 3)f | ||||
| Patient intervention | –.69 | .46 | –.13 | .13 |
| Clinician intervention | –.90 | .46 | –.17 | .05 |
| Patient and clinician intervention | –.28 | .92 | –.05 | .77 |
| Intervention effect as a function of training dosageg | Coeff. | SE | Cohen’s d | p |
| PAS (time 2)h | ||||
| Patient dosage | –.38 | 1.67 | –.03 | .82 |
| Clinician dosage | –2.74 | 2.65 | –.23 | .30 |
| Patient and clinician dosage | 10.85 | 6.20 | .89 | .08 |
| PAS (time 3)i | ||||
| Patient dosage | 2.14 | 1.33 | .17 | .11 |
| Clinician dosage | .33 | 1.99 | .03 | .87 |
| Patient and clinician dosage | 4.78 | 3.64 | .37 | .19 |
| PHQ-9 (time 3)j | ||||
| Patient dosage | –.18 | .62 | –.03 | .78 |
| Clinician dosage | –.86 | .80 | –.13 | .28 |
| Patient and clinician dosage | –1.39 | 1.68 | –.22 | .41 |
| GAD-7 (time 3)k | ||||
| Patient dosage | –.59 | .48 | –.11 | .22 |
| Clinician dosage | –1.43 | .60 | –.27 | .02 |
| Patient and clinician dosage | –1.54 | 1.32 | –.29 | .24 |
a
Patient and clinician interventions were DECIDE-PA and DECIDE-PC, respectively. A baseline assessment was conducted within the first 30 days (time 1), a follow-up assessment in the 4 following months (time 2), and a final assessment at the end of the study, 5 to 6 months after recruitment (time 3). All analyses and significance tests were adjusted for multiple imputation and small sample size. All models controlled for the outcome measure at baseline and patient education level. Results did not change when patient education was excluded.
b
df values for t tests: PAS, df=310; PHQ-9, df=309; GAD-7, df=310.
c
Intervention joint significance test: F=.62, df=3, 1,178.7, p=.60.
d
Intervention joint significance test: F=.78, df=3, 1,949.2, p=.50.
e
Intervention joint significance test: F=.27, df=3, 2,365, p=.84.
f
Training dosage reflects the number of DECIDE sessions completed.
g
Intervention joint significance test: F=2.1, df=3, 2,014.3, p=.10.
h
Intervention joint significance test: F=1.29, df=3, 1,741, p=.28.
i
Intervention joint significance test: F=1.25, df=3, 2,228, p=.29.
j
Intervention joint significance test: F=1.01, df=3, 2,648.3, p=.39.
k
Intervention joint significance test: F=3.62, df=3, 1,843.1, p=.01.
Moderation Analyses
We conducted moderation analyses to test whether the effect of the DECIDE training dosage on GAD-7 scores was different depending on whether the patient-clinician dyad was racially-ethnically discordant or linguistically discordant and on patient gender (Table 2). No moderation effects were noted with respect to linguistic discordance or patient gender, but significant moderation effects were found for patients’ anxiety symptoms with respect to racial-ethnic discordance (F=3.19, df=3, 3,619.5, p=0.023). When patients and clinicians were not of the same race-ethnicity, the clinician dosage had a stronger effect on patients’ anxiety symptoms (b=−2.80, SE=1.17, p=.017, Cohen’s d=−0.52),), and the patient and clinician dosage together seemed to have a weaker effect on patients’ anxiety symptoms (b=5.76, SE=2.77, p=0.037, Cohen’s d=1.07).
| Group and variable | Coeff. | SE | Cohen’s d | p |
|---|---|---|---|---|
| Racial-ethnic discordanceb | ||||
| Patient dosage | –.77 | .59 | –.14 | .19 |
| Clinician dosage | –.10 | .76 | –.02 | .89 |
| Patient and clinician dosage | –4.09 | 1.71 | –.76 | .02 |
| Discordance coefficient | .00 | .51 | .00 | 1.00 |
| Discordance and patient dosage | –.06 | .99 | –.01 | .96 |
| Discordance and clinician dosage | –2.80 | 1.17 | –.52 | .02 |
| Discordance and patient dosage and clinician dosage | 5.76 | 2.77 | 1.07 | .04 |
| Linguistic discordancec | ||||
| Patient dosage | –1.02 | .55 | –.19 | .06 |
| Clinician dosage | –.91 | .63 | –.17 | .14 |
| Patient and clinician dosage | –2.22 | 1.50 | –.41 | .14 |
| Discordance coefficient | –.31 | .57 | –.06 | .59 |
| Discordance and patient dosage | 1.27 | 1.06 | .24 | .23 |
| Discordance and clinician dosage | –2.70 | 1.64 | –.50 | .10 |
| Discordance and patient dosage and clinician dosage | 3.67 | 2.87 | .68 | .20 |
| Patient genderd | ||||
| Patient dosage | –.83 | .55 | –.15 | .13 |
| Clinician dosage | –1.19 | .65 | –.22 | .06 |
| Patient and clinician dosage | –2.23 | 1.66 | –.41 | .18 |
| Gender main effect (female) | –.61 | .44 | –.11 | .17 |
| Female × patient dosage | 1.26 | 1.18 | .23 | .28 |
| Female × clinician dosage | –1.31 | 1.20 | –.24 | .28 |
| Female × patient × clinician dosage | 3.36 | 3.53 | .62 | .34 |
a
Training dosage indicates the number of DECIDE-PA (patient) and DECIDE-PC (clinician) sessions completed. Anxiety symptoms were assessed at time 3, the final assessment, which was conducted at the end of the study, 5 to 6 months after recruitment. All analyses and significance tests were adjusted for multiple imputation and small sample size.
b
Model controlled for the outcome measure at baseline, patient and clinician race-ethnicity, and patient education level. Intervention joint significance test (discordance interactions): F=3.19, df=3, 3,619.5, p=.02.
c
Model controlled for the outcome measure at baseline, patient and clinician language, and patient education level. Intervention joint significance test (discordance interactions): F=1.59, df=3, 3,377.7, p=.19.
d
Model controlled for the outcome measure at baseline, patient gender, and patient education level. Intervention joint significance test of all female interactions: F=1.01, df=3, 4,388.0, p=.39.
Simultaneous-Equation Analyses
We analyzed whether the improvement in GAD-7 scores because of greater clinician training dosage influenced PAS scores at time 3. Because the clinician dosage did not have an effect on PAS scores, the clinician dosage can be correlated with PAS scores only through the effect of dosage on GAD-7 scores. Comparing the standard model with the simultaneous-equation model showed that without an instrument, the coefficient on the GAD-7 score was biased upwards. That is, the effect of GAD-7 scores on PAS scores would be overestimated without the instrument. Use of the clinician dosage as an instrument (b=–0.30, SE=0.12, p=0.013, Cohen’s d=–0.03) indicated that a 1-point decrease in the GAD-7 score increased patient activation by 0.30 points on a 10- to 90-point scale (mean=72.3±12.83).
Analysis of all simultaneous-equation model coefficients [see online supplement ] showed that neither patient characteristics nor clinician characteristics predicted PAS scores in the patient activation model. Only one clinician characteristic (Asian race-ethnicity) was significant in the anxiety model, but the omnibus test for all categories in the race-ethnicity group was not significant.
Discussion
Although the effects of patient and clinician interventions on mental illness symptoms and patient activation were not significant, clinicians who received more of the DECIDE-PC intervention were significantly better at easing patients’ anxiety symptoms. Clinicians who received more training may have been better able to ally with patients (50) by encouraging their feedback (51, 52). Patients’ reduced anxiety symptoms may have corresponded to feeling heard and understood by the clinician (24). Offering clinicians opportunities to naturally and routinely practice the principles of patient-clinician communication, vis-à-vis the DECIDE-PC, may benefit patients by lessening their anxiety.
The findings further indicated that the effect of clinician training dosage on reducing patients’ anxiety symptoms was stronger for racially-ethnically discordant patient-clinician pairs, compared with concordant pairs. DECIDE-PC can be an integral part of efforts to reduce mental health disparities, according to evidence documenting that patients from racial-ethnic minority groups are more likely to receive care from a racially-ethnically discordant provider and that these therapeutic dyads are more likely than concordant dyads to involve patient-clinician miscommunication (53, 54) and patient dropout (33, 55). The finding that reduced anxiety symptoms appeared to improve patient activation suggests that alleviation of anxiety symptoms could facilitate the development of patients’ motivation to manage their health and health care.
The findings differ from those in previous studies (4, 35) in that our study did not find a significant effect of the patient intervention on patient activation. This may be related to the double-blind design of the original trial—some patients in the intervention group did not receive the full benefit of the entire intervention at the time of the final assessment (see the original study [24] for further explanation). Another methodological consideration concerns the fact that the sample in the study was highly educated, with a higher baseline level of activation, raising questions of a potential ceiling effect. However, the significant finding that a reduction in anxiety symptoms appeared to improve patient activation speaks to the importance of lowering anxiety symptoms for patients from racial-ethnic minority groups. Given that clinician dosage was effective in lowering patients’ anxiety, clinicians who received coaching sessions in the intervention may have been able to improve patient activation even in a highly activated patient population. Because of the design, we were unable to assess the effect of the interventions on patient activation and mental illness symptoms beyond three observation periods. Future studies examining the relationship between the development of patient activation and mental illness symptoms may consider a longer longitudinal design that allows for observation of this relationship over time.
Although the study examined the relationship between mental illness symptoms and patient activation in the context of the DECIDE interventions, this was not a treatment study of mental health outcomes; therefore, the results do not have implications regarding the therapeutic effectiveness of these interventions. Participants’ symptoms at baseline were consistent with those of a sample of patients receiving community behavioral health care, although the included measures did not indicate diagnoses. The results, therefore, cannot be generalized to patients with specific psychiatric diagnoses. Future studies of patients in mental health treatment that examine the association between patient activation and mental illness symptoms may consider examining treatment-related factors (e.g., clinical diagnoses and time in treatment) that contribute to the association between patient activation and a reduction in symptoms of mental illness.
Conclusions
Behavioral health clinicians face new demands in connecting with patients of diverse backgrounds, whose customs and values may differ from their own. The DECIDE-PC is a clinician intervention that was found to lessen patients’ anxiety, and reduced anxiety was found to be associated with improved patient activation. Clinicians working with diverse behavioral health patients are encouraged to obtain regular training to routinely integrate into their practice a collaborative style of open communication with patients, with the goal of improving patient activation.
Footnote
The sponsor had no role in the study design or conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation or approval of the manuscript. The views presented in this publication are solely the responsibility of the authors and do not necessarily represent the views of PCORI, its Board of Governors, or its Methodology Committee.
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References
1.
Chen J, Mullins CD, Novak P, et al: Personalized strategies to activate and empower patients in health care and reduce health disparities. Health Educ Behav 2016; 43:25–34
2.
Hibbard JH, Greene J, Tusler M: Improving the outcomes of disease management by tailoring care to the patient’s level of activation. Am J Manag Care 2009; 15:353–360
3.
Hibbard JH, Stockard J, Mahoney ER, et al: Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res 2004; 39:1005–1026
4.
Alegría M, Polo A, Gao S, et al: Evaluation of a patient activation and empowerment intervention in mental health care. Medical Care 2008; 46:247
5.
McCusker J, Lambert SD, Cole MG, et al: Activation and self-efficacy in a randomized trial of a depression self-care intervention. Health Educ Behav 2016; 43:716–725
6.
Green CA, Perrin NA, Polen MR, et al: Development of the Patient Activation Measure for mental health. Adm Policy Ment Health Ment Health Serv Res 2010; 37:327–333
7.
Greene J, Hibbard JH: Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. J Gen Intern Med 2012; 27:520–526
8.
Hibbard JH, Mahoney E: Toward a theory of patient and consumer activation. Patient Educ Couns 2010; 78:377–381
9.
Chinman M, Oberman RS, Hanusa BH, et al: A cluster randomized trial of adding peer specialists to intensive case management teams in the Veterans Health Administration. J Behav Health Serv Res 2015; 42:109–121
10.
Lara-Cabrera ML, Salvesen Ø, Nesset MB, et al: The effect of a brief educational programme added to mental health treatment to improve patient activation: a randomized controlled trial in community mental health centres. Patient Educ Couns 2016; 99:760–768
11.
Cabassa LJ, Manrique Y, Meyreles Q, et al: Bridges to Better Health and Wellness: an adapted health care manager intervention for Hispanics with serious mental illness. Adm Policy Ment Health Ment Health Serv Res 2016; 45:163–173
12.
Goldberg RW, Dickerson F, Lucksted A, et al: Living Well: an intervention to improve self-management of medical illness for individuals with serious mental illness. Psychiatr Serv 2013; 64:51–57
13.
Hochhalter AK, Song J, Rush J, et al: Making the Most of Your Healthcare intervention for older adults with multiple chronic illnesses. Patient Educ Couns 2010; 81:207–213
14.
Harvey L, Fowles JB, Xi M, et al: When activation changes, what else changes? The relationship between change in Patient Activation Measure (PAM) and employees’ health status and health behaviors. Patient Educ Couns 2012; 88:338–343
15.
Mittal D, Fortney JC, Pyne JM, et al: Predictors of persistence of comorbid generalized anxiety disorder among veterans with major depressive disorder. J Clin Psychiatry 2011; 72:1445–1451
16.
Alegría M, Sribney W, Perez D, et al: The role of patient activation on patient–provider communication and quality of care for US and foreign born Latino patients. J Gen Intern Med 2009; 24:534–541
17.
Horvath AO, Greenberg LS: Development and validation of the Working Alliance Inventory. J Couns Psychol 1989; 36:223
18.
Tracey TJ, Kokotovic AM: Factor structure of the Working Alliance Inventory. Psychol Assess 1989; 1:207
19.
Allen ML, Cook BL, Carson N, et al: Patient-provider therapeutic alliance contributes to patient activation in community mental health clinics. Adm Policy Ment Health Ment Health Serv Res 2017; 44:431–440
20.
Flückiger C, Del Re AC, Wampold BE, et al: The alliance in adult psychotherapy: a meta-analytic synthesis. Psychotherapy 2018; 316–340
21.
Zilcha-Mano S: Is the alliance really therapeutic? Revisiting this question in light of recent methodological advances. Am Psychol 2017; 72:311–325
22.
Galinsky AD, Magee JC, Inesi ME, et al: Power and perspectives not taken. Psychol Sci 2006; 17:1068–1074
23.
Nakash O, Alegría M: Examination of the role of implicit clinical judgments during the mental health intake. Qual Health Res 2013; 23:645–654
24.
Alegria M, Nakash O, Johnson K, et al: Effectiveness of the DECIDE interventions on shared decision making and perceived quality of care in behavioral health with multicultural patients: a randomized clinical trial. JAMA Psychiatry 2018; 75:325–335
25.
Rosenthal B, Wilson WC: Mental health services: use and disparity among diverse college students. J Am Coll Health 2008; 57:61–68
26.
Waitzkin H: Information giving in medical care. J Health Soc Behav 1985; 26:81–101
27.
Aggarwal NK, Pieh MC, Dixon L, et al: Clinician descriptions of communication strategies to improve treatment engagement by racial/ethnic minorities in mental health services: a systematic review. Patient Educ Couns 2016; 99:198–209
28.
Cooper-Patrick L, Gallo JJ, Gonzales JJ, et al: Race, gender, and partnership in the patient-physician relationship. JAMA 1999; 282:583–589
29.
Levinson W, Stiles WB, Inui TS, et al: Physician frustration in communicating with patients. Medical Care 1993; 285–295
30.
Nguyen GT, Barg FK, Armstrong K, et al: Cancer and communication in the health care setting: experiences of older Vietnamese immigrants: a qualitative study. J Gen Intern Med 2008; 23:45–50
31.
Kalichman SC, Catz S, Ramachandran B: Barriers to HIV/AIDS treatment and treatment adherence among African-American adults with disadvantaged education. J Natl Med Assoc 1999; 91:439–446
32.
Takeuchi DT, Mokuau N, Chun C-A: Mental health services for Asian Americans and Pacific Islanders. J Ment Health Adm 1992; 19:237–245
33.
Alegría M, Roter DL, Valentine A: Patient–clinician ethnic concordance and communication in mental health intake visits. Patient Educ Couns 2013; 93:188–196
34.
Meuter RFI, Gallois C, Segalowitz NS, et al: Overcoming language barriers in healthcare: a protocol for investigating safe and effective communication when patients or clinicians use a second language. BMC Health Serv Res 2015; 15:371
35.
Alegría M, Polo A, Gao S, et al: Evaluation of a patient activation and empowerment intervention in mental health care. Medical Care 2008; 46:247–256
36.
Armstrong K, Hughes-Halbert C, Asch DA: Patient preferences can be misleading as explanations for racial disparities in health care. Arch Intern Med 2006; 166:950–954
37.
Meredith LS, Mendel P, Pearson M, et al: Implementation and maintenance of quality improvement for treating depression in primary care. Psychiatr Serv 2006; 57:48–55
38.
Kroenke K, Spitzer RL: The PHQ-9: a new depression diagnostic and severity measure. Psychiatr Ann 2002; 32:509–515
39.
Kroenke K, Spitzer RL, Williams JB: The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001; 16:606–613
40.
Spitzer RL, Kroenke K, Williams JB, et al: A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 2006; 166:1092–1097
41.
Löwe B, Decker O, Müller S, et al: Validation and standardization of the Generalized Anxiety Disorder screener (GAD-7) in the general population. Med Care 2008; 46:266–274
42.
Stata Statistical Software: Release 15. College Station, TX, StataCorp LP, 2017
43.
Raghunathan TE, Lepkowski JM, Van Hoewyk J, et al: A multivariate technique for multiply imputing missing values using a sequence of regression models. Surv Methodol 2001; 27:85–96
44.
Rubin DB: Multiple Imputation for Nonresponse in Surveys. Hoboken, NJ, Wiley, 2004
45.
Barnard J, Rubin DB: Small-sample degrees of freedom with multiple imputation. Biometrika 1999; 86:948–955
46.
Reiter JP: Small-sample degrees of freedom for multi-component significance tests with multiple imputation for missing data. Biometrika 2007; 94:502–508
47.
White H: A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 1980; 48:817–838
48.
Steele F, Vignoles A, Jenkins A: The effect of school resources on pupil attainment: a multilevel simultaneous equation modelling approach. J R Stat Soc Ser A Stat Soc 2007; 170:801–824
49.
Charlton C, Rasbash J, Browne WJ, et al: MLwiN, Version 3.00. Bristol, United Kingdom, University of Bristol, Centre for Multilevel Modelling, 2017
50.
Adler G, Shahar B, Dolev T, et al: The development of the working alliance and its ability to predict outcome in emotion-focused therapy for social anxiety disorder. J Nerv Ment Dis 2018; 206:446–454
51.
DeFreitas SC, Crone T, DeLeon M, et al: Perceived and personal mental health stigma in Latino and African American college students. Front Public Health 2018; 6:49
52.
Villatoro AP, Mays VM, Ponce NA, et al: Perceived need for mental health care: the intersection of race, ethnicity, gender, and socioeconomic status. Soc Ment Health 2018; 8:1–24
53.
Cooper LA, Beach MC, Johnson RL, et al: Delving below the surface: understanding how race and ethnicity influence relationships in health care. J Gen Intern Med 2006; 21(suppl 1):S21–S27
54.
Ghods BK, Roter DL, Ford DE, et al: Patient-physician communication in the primary care visits of African Americans and whites with depression. J Gen Intern Med 2008; 23:600–606
55.
Meyer OL, Zane N: The influence of race and ethnicity in clients’ experiences of mental health treatment. J Community Psychol 2013; 41:884–901
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History
Received: 30 April 2018
Revision received: 28 November 2018
Revision received: 7 February 2019
Accepted: 14 March 2019
Published online: 14 May 2019
Published in print: August 01, 2019
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Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
Patient-Centered Outcomes Research Institutehttp://dx.doi.org/10.13039/100006093: CD-12-11-4187
The study was supported by contract CD-12-11-4187 with the Patient-Centered Outcomes Research Institute (PCORI).Metrics & Citations
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