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Record W4414922772 · doi:10.2196/77636

Feasibility and Acceptability of a Positive Psychological Intervention for Patients With Metastatic Breast Cancer: Pre-Post Pilot Study

2025· article· en· W4414922772 on OpenAlexvenueno aff
Claire C. Conley, Elizabeth L. Addington, Mikaela A. Velazquez-Sosa, Brenna Mossman, Lesley Glenn, Shontè Drakeford, Claudine Isaacs, Ami Chitalia, Christopher Gallagher, Suzanne C. O’Neill, Judith T. Moskowitz

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsIntervention (counseling)Randomized controlled trialPilot trialEthnically diverseMetastatic breast cancerPsychological interventionSelf-efficacy

Abstract

fetched live from OpenAlex

Background: Depression and anxiety are prevalent among patients with metastatic breast cancer (MBC), but there are few evidence-based psychological interventions specifically designed for this population. Objective: This study aimed to assess the feasibility, acceptability, and clinical impact of a multicomponent positive psychological intervention, enhanced with an ecological momentary intervention for symptom management, for patients with MBC. Methods: We recruited patients with MBC from a National Cancer Institute-designated comprehensive cancer center. Participants completed 5 weekly virtual individual sessions with a study counselor focused on positive emotion regulation skills. Participants also reported physical and psychological symptoms daily between sessions via SMS text messaging. Clinically elevated symptoms triggered a personalized coaching SMS text message tailored to the symptoms reported and the skills learned that week. Primary outcomes were intervention feasibility and acceptability. We also examined pre- to postintervention changes in depression, anxiety, positive affect, and positive emotion regulation skill use. Finally, a subset of participants completed qualitative exit interviews focusing on their experience in the study; interview data were analyzed using rapid qualitative analysis. Results: We approached 20 patients with MBC, established contact with 15 (75%), received consent from 10 (67%), and retained 9 (90%) patients through the end of the study. Participants were 55 (SD 14.4, range 35-75) years old on average and identified as non-Hispanic White (5/10, 50%), non-Hispanic Black (4/10, 40%), or Latina (1/10, 10%). Participants attended 92% (46/50) of intervention sessions (mean 50, SD 9, range 36-71 min). On average, they completed 85% (SD 18%, range 46%-100%) of daily symptom assessments and received 23 (SD 5, range 13-31) coaching messages. Participants reported high perceived intervention feasibility (mean 4.81/5, SD 0.44), acceptability (mean 4.78/5, SD 0.33), and appropriateness for patients with MBC (mean 4.83/5, SD 0.35), above our a priori cutoff of ≥4. All 9 participants (n=9, 100%) recommended the intervention for other patients with MBC. We observed pre- to postintervention decreases in depression (d=-0.32) and anxiety (d=-0.27) and increases in positive affect (d=0.30) and positive emotion regulation skill use (d=0.99). Rapid qualitative analysis results demonstrate participants' positive experiences with the intervention, as well as suggestions for improvement. Conclusions: This pilot study supports the feasibility of enrolling and retaining racially and ethnically diverse patients with MBC to this trial, the acceptability of the positive psychological intervention enhanced with ecological momentary intervention, and preliminary intervention impacts on depression, anxiety, positive affect, and positive emotion regulation skill use. A large-scale randomized controlled trial is needed to assess intervention efficacy for outcomes of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.475
Teacher spread0.404 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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