Psychotherapy Bulletin

Psychotherapy Bulletin

Measurement Based Care for Depression

PHQ-9’s Suicidality & Functional Items

Clinical Impact Statement: The findings presented in the present article highlight the benefits of a technology assisted platform facilitating the implementation of measurement-based care. The routine administration and interpretation of suicidality and life functioning items on the PHQ-9 were found to have the potential to significantly contribute to clinical decisions.

Depressive disorders are highly prevalent mental health conditions (NIH, 2022). Although effective treatments exist, barriers to care frequently interfere with access to care (Mojtabai et al., 2011). In the absence of prompt interventions, depressive symptoms can last over six months (Whiteford et al., 2013). Thus, there is an imperative to for the mental health field to facilitate access to care, while promoting the delivery of high quality, evidence-based care. There are several evidence-based psychotherapies (EBPs) for depressive conditions that are currently available (see Cuijpers et al., 2021; Munder et al., 2019). Moreover, EBPs, demonstrated in RCTs, display similar efficacy and effectiveness in naturalistic clinical settings (Minami et al., 2008; Reese et al., 2014). 

To accompany theoretically and empirically driven approaches for treating depression, researchers have found that clinician engagement in measurement-based care (MBC) can further enhance outcomes (Bugatti et al., 2022; Lambert et al., 2018; Miller et al., 2015). MBC consists of the routine treatment outcomes monitoring, which is indicative of client progress (or lack thereof) and undergirds clinical responsiveness. As further evidence supporting the importance of MBC, the American Psychological Association (APA) has recently established an Advisory Committee for the Measurement-Based Care and the Mental Behavioral Health Registry to delineate practice guidelines informing the implementation of MBC (Boswell et al., in press). Although clinicians’ embracement of MBC is an ongoing process, clients commonly express a desire to be part of the assessment process, have a clear rationale for how the MBC will assist their treatment, and for it to be discussed each session (Solstad et al., 2019).  

MBC has been found to improve treatment outcomes and reducing client dropouts (see Lambert et al., 2018). Yet, very few therapists (about 1 in 5) utilize MBC in their practice (Lewis et al., 2019). Some of the reservations reported by therapists for not engaging in MBC include insufficient training on the effective use of MBC and the time/effort burden associated with this practice (Cuperfain et al., 2021). To overcome these barriers, several technology companies have developed platforms streamlining the administration and interpretation of MBC data. This supportive use of technology has improved the accessibility and relevance of MBC to both clients and therapists. For example, a currently available behavioral health technology platform offers clinical support services which include automated MBC. These services comprise the automated administration and interpretation of routinely administered outcomes measures, including the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and a life functioning scale. Additionally, some platforms lead clinical engagement efforts, such as facilitating access to guidelines, workshops, and materials supporting the implementation of MBC. While some of these additional support tools (e.g., visualization and psychoeducational services) are unique to this platform, many of the described services supporting the implementation of MBC are consistent with the best practices outlined by Boswell et al. (in press). These advances could benefit from further investigation of the predictive nature of the MBC measures. 

The current study aims to examine the PHQ-9 in the treatment of depression for clients who were receiving treatment through private practice licensed therapists. While the PHQ-9 is commonly examined based on the overall score, there is an opportunity to gain more understanding about the predictive nature of the suicide ideation item and over impact to life functioning item on therapy outcomes. We will examine the association between these two items and therapy outcomes, as well as test whether these associations vary based on initial severity of depressive symptomology. 



We utilized a sample of clients (N = 1,464) who were diagnosed with depressive conditions (mainly Major Depression Disorder) who completed the PHQ-9 over the course of their treatment. We restricted the sample to those who scored a 10 or higher on the PHQ-9, which is a common indicator of moderate to severe depressive symptoms and who had complete data. Clients were on average 32 years old (SD = 12.64), and were mainly women (70.4%), 25.6% were men, 2.9% were non-binary, and 1.1% preferred not to answer. Due to some technical issues, race/ethnicity were not able to be reported. 


Patient Health Questionnaire-9. The Patient Health Questionnaire-9 (PHQ-9; Kroenke et al., 2001) is a 9-item, self-report scale. It was designed to be administered to adult individuals to measure depressive symptomatology. The suicide ideation item is: “Thoughts that you would be better off dead or hurting yourself in some way” and the function item is: “If you checked off any problems, how difficult have these problems made it for you to do your work, take care of things at home, or get along with other people?” For this item, the rating scale ranges from “Not difficult at all” (0) to “Extremely difficult” (4). In a validation study (Kroenke et al., 2001), the PHQ-9 demonstrated excellent internal reliability (Cronbach’s α = 0.89), and test-retest reliability. In the present study, the PHQ-9 was administered electronically. The SonderMind platform is designed to automatically send, via email, a link to an electronic version of the PHQ-9 to clients 48 hours prior to their first scheduled psychotherapy session. Clients who are diagnosed with a depressive disorder by their therapist are then automatically sent a link to complete an electronic version of the PHQ-9 before every session. Clients are given 48 hours from the receipt of each email to complete the assessment.

Research-Practice Network

SonderMind is a technology-based platform that supports therapist-client matching for psychotherapy and medication management, though the present study focused exclusively on psychotherapy services. Therapists registered on SonderMind report their demographic and professional characteristics. Additionally, they are asked to report three clinical specialty areas. Prospective clients who register on SonderMind are asked to report several preferences, including preferred demographic and professional therapist characteristics, as well as preferences for certain aspects of treatment (e.g., psychotherapy approach). The SonderMind platform enters these preferences and characteristics into a proprietary algorithm that produces a set of therapist-client matches. Therapists who are matched with a new prospective client are informed of the match and are allowed to confirm or decline. Besides supporting this matching process, the SonderMind platform offers additional services, such as MBC (i.e., routine clinical administration of measures), access to clinical training and resources (e.g., webinars, evidence-based practice guidelines), and administrative support (e.g., credentialing, billing). While SonderMind therapists are free to select clinical interventions based on their clinical judgment, they are also supported toward the achievement of required clinical group standards, which include the implementation of evidence-based practices such as MBC. Therapists registered on SonderMind deliver psychotherapy as part of their private practice and rely on the SonderMind platform as a means of finding new clients, while also taking advantage of its clinical and administrative support features. 


The pre-PHQ-9 mean score was 16.04 (SD = 4.23) and the post-PHQ-9 score was 11.21 (SD = 5.74). As such, the overall pre-post effect size was Cohen’s d = 1.14. We conducted a regression model predicting PHQ-9 post score by PHQ-pre score, suicide ideation item, and the PHQ-functioning item. Both items significantly predicted therapy outcomes: suicide ideation item (b = 0.54, p <.001) and functional item (b = 0.53, p <.001). That is, clients who reported more suicide ideation and more difficulty functioning in life had worse therapy outcomes. Next, we tested whether pre-PHQ-9 scores would moderate the association of these two items and therapy outcomes. The results demonstrated that pre-PHQ-9 scores significantly moderated the relationship between the functional item and therapy outcomes (b = 0.53, p <.001). For clients who reported more depressive symptoms at pre and reported more difficulty functioning in life had worse therapy outcomes than those with less difficulty functioning in life. Pre-PHQ-9 scores were not a significant moderator for the association between suicide ideation item and therapy outcomes. 


Two main findings were illuminated through the current study. First, as to be expected, clients struggling with suicidal ideation tend to have worse therapy outcomes. Clearly, suicidal ideation is a strong indicator that clients are suffering and potentially might require more intense treatments. Based on the PHQ-9, the suicidal ideation item was rated at 2 (More than the days) or 3 (Nearly every day) by 14.7% of the sample. Accordingly, therapists could benefit from utilizing the PHQ-9, suicidal ideation as a screener and then conduct a more in-depth suicide assessment. Second, clients who report that their depressive symptoms were impacting their life functioning also had worse therapy outcomes. In addition, those with more depressive symptoms prior to therapy this effect was compounded. Previous research has shown that life functioning takes longer to change in therapy (e.g., Owen et al., 2016). This study adds to this literature, highlighting the potential interaction between life functioning and symptoms. Accordingly, therapists may benefit from attending to this rating in concert with the overall level of depressive symptomology to guide treatment. Targeting inventions that promote healthy engagement with others while attending to emotion regulation of the depressive symptoms may be well suited for these clients to promote change on both dimensions.

This study also highlights the benefits of a technology assisted platform to help facilitate MBC. By removing the burden of sending out MBC measures as well as having interactive visual displays can be a step to enable MBC. There were also some limitations of this study. For instance, we do not know how therapists were utilizing the PHQ-9 in their sessions. But, as seen in Bugatti et al., (2022), therapists who viewed the measures more had better outcomes, and that higher severity at baseline was associated with more views of the PHQ-9. We also do not know what types of treatment/techniques were being utilized. Although we have some information provided by the therapist, there were no adherence checks. In conclusion, there appears to be some nuances in understanding how the additional item on the PHQ-9 may benefit therapists.  

Dr. Bugatti is a postdoctoral research fellow at University of Denver. His research interests include measurement-based care and the personalization of evidence-based psychotherapies.

Cite This Article

Bugatti, M., Owen, J., Richardson, Z., Rasmussen, W., & Newton, D. (2022). Measurement based care for depression: PHQ-9’s suicidality & functional items. Psychotherapy Bulletin, 57(2), 21-25.


Boswell, J. F., Hepner, K. A., Lysell, K., Rothrock, N., Bott, N., Childs, A. W., Douglas, S., Owings-Fonner, N., Wright, V. C., Stephens, K. A., Bard, D. E., Aajmain, S., & Bobbitt, B. L. (in press). The need for measurement-based care professional practice guideline. Psychotherapy

Bugatti, M., Owen, J., Reese, R. J., Coleman, J., Richardson, Z., Rasmussen, W., & Newton, D. (2022). Access to care as predictors of early psychotherapy dropout: Findings from a technology-based platform. Manuscript submitted for publication

Cuijpers, P., Quero, S., Noma, H., Ciharova, M., Miguel, C., Karyotaki, E., Cipriani, A., Cristea, I. A., & Furukawa, T. A. (2021). Psychotherapies for depression: a network meta‐analysis covering efficacy, acceptability and long‐term outcomes of all main treatment types. World Psychiatry, 20(2), 283-293. 

Cuperfain, A. B., Hui, K., Berkhout, S. G., Foussias, G., Gratzer, D., Kidd, S. A., Kozloff, N., Kurdyak, P., Linaksita, B., & Miranda, D. (2021). Patient, family and provider views of measurement-based care in an early-psychosis intervention programme. BJPsych Open, 7(5). 

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ‐9: validity of a brief depression severity measure. Journal of general internal medicine, 16(9), 606-613. 

Lambert, M. J., Whipple, J. L., & Kleinstäuber, M. (2018). Collecting and delivering progress feedback: A meta-analysis of routine outcome monitoring. Psychotherapy, 55(4), 520. 

Lewis, C. C., Boyd, M., Puspitasari, A., Navarro, E., Howard, J., Kassab, H., Hoffman, M., Scott, K., Lyon, A., Douglas, S., Simon, G., & Kroenke, K. (2019). Implementing Measurement-Based Care in Behavioral Health: A Review. JAMA Psychiatry, 76(3), 324-335. 

Miller, S. D., Hubble, M. A., Chow, D., & Seidel, J. (2015). Beyond measures and monitoring: Realizing the potential of feedback-informed treatment. Psychotherapy, 52(4), 449. 

Minami, T., Wampold, B. E., Serlin, R. C., Hamilton, E. G., Brown, G. S. J., & Kircher, J. C. (2008). Benchmarking the effectiveness of psychotherapy treatment for adult depression in a managed care environment: a preliminary study. Journal of Consulting and Clinical Psychology, 76(1), 116. 

Mojtabai, R., Olfson, M., Sampson, N. A., Jin, R., Druss, B., Wang, P. S., Wells, K. B., Pincus, H. A., & Kessler, R. C. (2011). Barriers to mental health treatment: results from the National Comorbidity Survey Replication. Psychological medicine, 41(8), 1751-1761. 

Munder, T., Flückiger, C., Leichsenring, F., Abbass, A., Hilsenroth, M. J., Luyten, P., Rabung, S., Steinert, C., & Wampold, B. E. (2019). Is psychotherapy effective? A re-analysis of treatments for depression. Epidemiology and Psychiatric Sciences, 28(3), 268-274. 

NIH. (2022).  Retrieved 3/3/2022 from

Owen, J. J., Adelson, J., Budge, S., Kopta, S. M., & Reese, R. J. (2016). Good-enough level and dose-effect models: Variation among outcomes and therapists. Psychotherapy research, 26(1), 22-30. 

Reese, R. J., Duncan, B. L., Bohanske, R. T., Owen, J. J., & Minami, T. (2014). Benchmarking outcomes in a public behavioral health setting: Feedback as a quality improvement strategy. Journal of Consulting and Clinical Psychology, 82(4), 731. 

Solstad, S. M., Castonguay, L. G., & Moltu, C. (2019). Patients’ experiences with routine outcome monitoring and clinical feedback systems: A systematic review and synthesis of qualitative empirical literature. Psychotherapy research, 29(2), 157-170. 

Whiteford, H. A., Harris, M., McKeon, G., Baxter, A., Pennell, C., Barendregt, J., & Wang, J. (2013). Estimating remission from untreated major depression: a systematic review and meta-analysis. Psychological medicine, 43(8), 1569-1585. 


Submit a Comment

Your email address will not be published. Required fields are marked *