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We read the study by Chair et al. (2026) with great interest. Examining theory-guided positive psychological interventions in breast cancer care. By restricting inclusion to randomized controlled trials and explicitly foregrounding theoretical frameworks, the authors advance an important agenda for strengthening the scientific foundation of psychosocial nursing interventions. The decision to aggregate interventions under the category of “theory-guided” provides conceptual coherence, yet it also introduces interpretive complexity with clinical consequences. The theoretical models applied across the included trials differed substantially in their proposed mechanisms, temporal focus and therapeutic targets. Treating these frameworks as functionally equivalent risks obscures the theoretical approaches that align most closely with specific clinical needs, such as acute treatment-related distress versus long-term survivorship adjustment. In nursing practice, this aggregation limits actionable guidance when selecting interventions tailored to individual patient trajectories (Kociolek et al. 2025). The pooled effect on the quality of life achieved statistical robustness; however, clinical interpretation requires greater precision. Standardized mean differences offer comparability across instruments but do not inherently convey patient-perceptible benefits. Without anchoring effect sizes to minimal clinically important differences in widely used quality-of-life measures, clinicians lack a clear benchmark to judge whether observed improvements translate into meaningful changes in daily functioning, symptom burden, or coping capacity. This distinction is central to allocating limited psychosocial resources to oncology services (Mouelhi et al. 2020). All included trials employed structured intervention protocols delivered under controlled conditions. While this supports internal validity, translation into routine nursing care demands the consideration of contextual variability. Patients with breast cancer encounter fluctuating treatment phases, comorbidities and social constraints that influence engagement with psychological interventions. Evidence derived from protocol-driven delivery does not automatically indicate effectiveness in real-world settings, where session adherence, staffing capacity and continuity of care shape clinical outcomes. Subgroup analyses based on duration and format provide descriptive insights, but offer limited guidance for individualized care planning. Duration and delivery mode alone rarely drive therapeutic responses in psychosocial interventions (Gloster et al. 2024). Alignment between theoretical mechanisms and patient-specific psychological priorities holds greater clinical relevance. For example, interventions grounded in meaning-making frameworks may serve patients confronting existential distress, whereas self-regulation models address treatment adherence challenges better. Without an explicit linkage between theory, patient phenotype and outcome domain, broad recommendations risk uniform application, where selective deployment would better support patient-centered care. This review contributes a valuable synthesis to psychosocial oncology nursing by reinforcing the importance of a theory-informed intervention design. Clarifying the clinical significance of effect sizes, differentiating theoretical mechanisms and strengthening the bridge between controlled trials and everyday practice would further enhance their utility. Such refinement supports the responsible integration of positive psychological interventions into breast cancer care while preserving the central role of individualized nursing judgement. S.D. contributed to conceptualization, nursing and psychosocial interpretation and drafting of the manuscript. A.P. contributed to methodological appraisal, oncology nursing interpretation and serves as the corresponding author. S.D. (Shivarajkumar) contributed to clinical practice and education-based interpretation and manuscript review. All authors reviewed, edited and approved the final version of the manuscript. The authors have nothing to report. Generative AI Disclosure: Generative AI tools were used solely for language refinement and formatting assistance. All scientific interpretation, critique and conceptual analysis were independently developed by the authors. The authors have nothing to report. The authors have nothing to report. The authors declare no conflicts of interest. The authors have nothing to report.