A Mixed Methods Approach Incorporating Text Analytics to Examine Persistence of Depression

ABSTRACT

Background Some patients’ depression persists despite evidence-based interventions; understanding factors associated with depression persistence could inform screening and treatment. We used a novel mixed-methods approach to examine demographic, clinical, and social factors affecting depression persistence among older, low-income women; we also assessed the utility of this approach for evaluating intervention fidelity.

Methods Data used for this study were generated from a comparative effectiveness study comparing the impact of prevention care management (PCM) versus a collaborative care intervention (CCI) on depression among women overdue for cancer screening: We reviewed 700 care manager logs to identify themes among patients’ experiences and analyzed language use using NVivo®’s natural language processing (NLP) functionality. 757 women age 50-64 who screened positive for depression at baseline using the Patient Health Questionnaire (PHQ)-9 and were overdue for ≥1 cancer screening test (breast, cervical, and/or colorectal) participated. All received primary care in XXX Federally Qualified Health Centers. We used NLP to quantify differences in language use across intervention groups and explored how often themes appeared in logs of participants whose depression did not meaningfully improve based on PHQ-9 scores. Differences in demographic, clinical, and social factors were examined.

Results Participants with persistent depression were more likely to discuss pain, fear, and transportation. Asthma and anxiety were associated with lower likelihood of depression remission, while no differences were observed in depression remission rates among those with diabetes or hypertension. Patient-centered words, including “needs” and “feelings”, were more common in the CCI group, while procedure-related words, like “screening” and “mammography”, appeared more frequently in the PCM group.

Conclusions Patient-related factors and social barriers contributed to depression persistence. NLP identified patterns of language use in case logs, suggesting unmet needs among depressed patients. NLP is an efficient, effective method for identifying themes in unstructured text and monitoring intervention fidelity.

Competing Interest Statement

The authors have declared no competing interest.

Clinical Trial

NCT02273206

Funding Statement

Patient Centered Outcomes Research Institute (PCORI) [IH-12-11-4522] with additional infrastructure support provided through Agency for Healthcare Research and Quality (AHRQ) [5P30-HS-021667].

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethics committee/IRB of Clinical Directors Network (New York, NY) gave ethical approval for this work; Ethics committee/IRB of Montefiore Medical Center (Bronx, NY) gave ethical approval for this work; Ethics committee/IRB of NYC Health+Hospitals/Lincoln Hospital (Bronx, NY) gave ethical approval for this work.

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Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors

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