Background:  The Center for Nature Informed Therapy (CNIT) recently piloted the Nature‑Informed Biopsychosocial‑Spiritual Model with Nature Relatedness Assessment (NIBSMA) to quantify the multidimensional benefits of nature‑based interventions. Lydia Asisten’s capstone evaluated the first full NIBSMA dataset to explore whether participation in CNIT programs measurably improves well‑being.

Methods:  Pre‑ (n = 51) and post‑program (n = 48) surveys collected between February and April 2025 were cleaned and analyzed. Exploratory Data Analysis (EDA) generated descriptive statistics, density plots, boxplots, and a correlation matrix. Sub‑scale means were calculated for Anxiety/Stress (reverse‑scored), Cognitive Functioning, Social Connectedness, Spiritual Well‑being, and Nature Relatedness (all 1–5). Cluster structure was examined with k‑means and hierarchical algorithms on z‑standardized sub‑scale scores. Qualitative reflections (open‑ended items) were visualized with word clouds.

Results:  Mean scores increased on every dimension: Anxiety (3.21 → 4.15), Cognitive (3.47 → 4.23), Social (3.71 → 4.32), Spiritual (3.93 → 4.18), and Nature Relatedness (4.11 → 4.34). Standard deviations narrowed for four domains, indicating more uniform gains across participants. Pre‑program k‑means revealed three heterogeneous clusters; post‑program data converged into a dominant “high well‑being” cluster (56 % of cases), suggesting consistent therapeutic impact. Word‑cloud analysis showed a lexical shift from “anxiety,” “stress,” “calm” (pre) to “less,” “happy,” “relaxed,” “connected” (post), mirroring quantitative improvements.

Conclusions:  Preliminary evidence supports the effectiveness of CNIT’s nature‑based interventions in reducing anxiety, enhancing cognitive clarity, strengthening social and spiritual well‑being, and deepening nature connectedness. Reduced score dispersion and cluster convergence imply that benefits are broadly distributed rather than limited to a subset of participants. Future work should employ non‑parametric paired tests, expand sample size, and integrate qualitative themes to refine NIBSMA items for larger‑scale validation.