Assessing the Impact of Intravenous and Parenteral Nutrition (IVPN) Network on the Development and Productivity of Pharmacists, Healthcare Providers, and Researchers
Bibliographic record
Abstract
BACKGROUND: Effective knowledge sharing and professional networking are critical for enhancing healthcare practice. The Intravenous and Parenteral Nutrition (IVPN) Network, originally focused on nutrition support, has expanded into a global platform supporting professional development across multiple disciplines. However, its broader impact on healthcare providers' growth and practice remains underexplored. This study aimed to evaluate the perceived influence of the IVPN Network through four objectives: (1) to assess awareness and usage, (2) to identify training needs, (3) to evaluate its impact on professional development, collaboration, and patient care, and (4) to measure user satisfaction and advocacy. METHODS: A cross-sectional, web-based survey was conducted between September 2024 and January 2025 using non-probability snowball sampling. Eligible participants were pharmacists, healthcare providers, and researchers aged ≥18 years who had engaged with IVPN activities within the past two years. The questionnaire, developed from literature and validated by experts (Cronbach's alpha ≥ 0.79), included demographic items and Likert-scale questions across the four study domains. Data were analyzed using SPSS version 26 (IBM Corp., Armonk, NY). Mann-Whitney U tests were used for sex-based comparisons, Pearson correlation for age and performance scores, and Kruskal-Wallis tests for training effects. RESULTS: A total of 493 healthcare professionals from 39 countries responded, with the majority from the Gulf region. Awareness of the IVPN Network was relatively high, although patterns of engagement varied. Formal or informal training was significantly associated with higher perceived benefits. Participants reported that the network enhanced access to clinical information, communication, and decision-making, and supported professional collaboration. Overall satisfaction was high, with 95.1% indicating they would recommend the platform. CONCLUSION: The IVPN Network is perceived to support professional development and collaboration among healthcare providers across diverse regions. While findings provide valuable insights into members' experiences, they reflect self-reported perceptions and cannot be interpreted as causal effects due to the cross-sectional design, reliance on subjective data, and absence of control groups. Future research should incorporate longitudinal designs, objective clinical outcome measures, and independent evaluations to confirm and extend these findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".