IMPACT (IMproving Proactive Approaches for Cancer Survivors' Mental Health Treatment)

Medical University of South Carolina (MUSC)

Status: Enrolling

Conditions: Depressive Symptoms; Cancer; Depression

Treatments: Behavioral: Treatment as Usual; Behavioral: Behavioral Activation Therapy App

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT06582784

Pro00137447

1R01CA281740-01A1 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

The purpose of this research study is to evaluate a mobile application (app) for depression treatment called "Moodivate" among cancer survivors. Moodivate was developed by our research team to assist with the treatment of depressed mood.

Participants will be randomly assigned to either download the mobile app, "Moodivate", or not. Approximately 2/3 of participants enrolled will receive the mobile app and the remaining 1/3 will not.

All participants will complete electronic questionnaire measures throughout the study period. Questionnaires will assess symptoms of depression, as well as your experiences using Moodivate and participating in this trial. Participation in this study will take about 12 weeks, beginning today.

Participation in this study may help in the treatment of future cancer survivors. The greatest risks of this study include frustration, worsening of emotional distress, data breach, and/or loss of confidentiality. Alternative treatments include contacting your primary care provider or your oncology care team to discuss other available treatments for depressed mood.

Full description

Individuals living with likely incurable cancer (ILLIC) are a heterogeneous, growing subpopulation of cancer survivors who live with cancer as a chronic relapsing disease. As a result of their transitions through multiple lines of cancer therapy and prognostic uncertainty, ILLIC have unique survivorship care needs. Principal among these is the need for depression treatment. Up to half of ILLIC report depressive symptoms with negative sequalae including lower quality of life, reduced adherence to anti-cancer therapies, suicidal ideation, and desire for hastened death. Numerous trials and meta-analyses have documented that evidence-based psychosocial treatment improves depression outcomes for ILLIC. However, multilevel barriers, including transportation issues, stigma, and a scarcity of oncology mental health providers, limit access. Thus, ILLIC need feasible, accessible evidence-based depression treatment options3.

Consistent with Commission on Cancer accreditation standards, short depression screeners (e.g., PHQ-2) are routinely administered in oncology settings with results recorded in structured Electronic Health Record (EHR) fields. Despite widespread screening adoption, treatment referral rates remain low (10-50%) across cancer centers. To address this depression screening vs. treatment referral gap, screening data can be used to proactively (i.e., remotely, outside an encounter) link survivors in need of depression treatment to scalable options. While depression screening data can be readily used for proactive identification (ID), as noted by NCI, there is a critical need to develop methods to identify and enumerate ILLIC. Data necessary to determine curability likelihood (e.g., advanced stage, metastatic), are typically recorded in unstructured EHR fields, necessitating labor-intensive, manual chart review to identify ILLIC. To realize the goal of delivering scalable evidence-based depression care for ILLIC, accurate, automated approaches to identify ILLIC are needed.

Self-guided digital mental health interventions (DMHIs) can be paired with proactive ID to create a scalable depression treatment delivery model. Our team recently developed "Moodivate" as a DMHI-based approach to deliver Behavioral Activation, an evidence-based first-line depression treatment for cancer survivors. In a pilot that informs this R01, we: 1) gathered stakeholder feedback and tailored Moodivate for the unique needs of ILLIC, 2) developed infrastructure and refined the approach for proactive ID of ILLIC with depression, and 3) conducted a pilot RCT (N=15) to evaluate feasibility, acceptability, and preliminary efficacy of a proactive ID + DMHI approach. In our RCT, ILLIC with depressive symptoms were proactively identified via structured (depression) and unstructured (ILLIC) EHR data, remotely enrolled, and randomized to proactive ID + DMHI (Moodivate tailored for ILLIC) or proactive ID + usual care (UC). Our preliminary data show that this care delivery model is feasible (60% of eligible patients accrued; Moodivate mean rating of excellent on the System Usability Scale), acceptable (70% used Moodivate continuously for one month), and may improve depression (40% reported a clinically meaningful improvement). Importantly, a sustainable treatment model must also address chronic evidence-to-practice gaps. Thus, implementation outcomes and determinants of the proactive ID + DMHI approach must be concurrently evaluated across multiple care delivery levels to enhance future adoption.

Enrollment: 279 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age > 18 years
• ILLIC (as determined during manual chart review)
• Elevated depressive symptoms, defined as a score of ≥ 8 on the PHQ-9
• Current owner of an iOS- or Android-compatible smartphone
• Willingness to utilize a mobile app for the treatment of depressed mood (response of "yes" on yes/no item)
• Have a valid e-mail address that is checked regularly or have regular access to text messages (to access follow-up assessments)
• English language fluency

Exclusion criteria

• Current suicidal ideation at study screening, defined as a response greater than or equal to 1 on item nine of the PHQ-9
• Severe cognitive impairment that precludes completion of informed consent. For the purposes of assessing eligibility, this criterion is operationalized as:
• Prior diagnosis of dementia, or Major Neurocognitive Disorder indicated either via self-report or in the EHR; or
• Self-report of cognitive difficulties that impair functional independence

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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279 participants in 2 patient groups

Treatment as Usual

Other group

Description:

Participants in the treatment as usual group will be provided educational material about mood management available via the EHR with the suggestion to discuss questions with their oncology provider. Participants will be asked to complete questionnaire measures weekly for 8 weeks with a final follow up at 12 weeks.

Treatment:

Behavioral: Treatment as Usual

Moodivate

Experimental group

Description:

Participants randomized to the Moodivate condition will be instructed to utilize Moodivate regularly, at least once per day, for the treatment of depressed mood among cancer survivors. Participants in the Moodivate group will receive a download code to download the Moodivate mobile application. Moodivate is a mobile app for individuals with elevated symptoms of depression. Within the app, users identify values, create activities, schedule activities, and rate mood daily. Participants will be asked to complete questionnaire measures weekly for 8 weeks with a final follow up at week 12.

Treatment:

Behavioral: Behavioral Activation Therapy App