scan.json (17264B)
1 { 2 "paper": { 3 "title": "Advancing nursing regulation in the digital era: Harnessing AI to bridge workforce gaps and strengthen practice competency and safety", 4 "authors": ["Elizabeth H. Zhong", "Nancy Spector", "Charlie O'Hara", "Nicole Livanos", "Jose Delfin Castillo III"], 5 "year": 2025, 6 "venue": "Journal of Nursing Regulation", 7 "doi": "10.1016/j.jnr.2025.08.015" 8 }, 9 "checklist": { 10 "artifacts": { 11 "code_released": { 12 "applies": false, 13 "answer": false, 14 "justification": "This is a narrative literature review with no code or computational analysis. No code artifact is expected." 15 }, 16 "data_released": { 17 "applies": true, 18 "answer": false, 19 "justification": "The review could have released its search corpus, extracted data tables, or reference list in structured form, but did not." 20 }, 21 "environment_specified": { 22 "applies": false, 23 "answer": false, 24 "justification": "No computational environment is involved in this narrative review." 25 }, 26 "reproduction_instructions": { 27 "applies": true, 28 "answer": false, 29 "justification": "No reproduction instructions are provided. The methodology section describes search terms and databases but lacks sufficient detail for systematic reproduction (no date ranges, no PRISMA flow, no exact hit counts)." 30 } 31 }, 32 "statistical_methodology": { 33 "confidence_intervals_or_error_bars": { 34 "applies": false, 35 "answer": false, 36 "justification": "Narrative review with no original quantitative analysis." 37 }, 38 "significance_tests": { 39 "applies": false, 40 "answer": false, 41 "justification": "No statistical comparisons are made in this review." 42 }, 43 "effect_sizes_reported": { 44 "applies": false, 45 "answer": false, 46 "justification": "No original quantitative analysis is performed." 47 }, 48 "sample_size_justified": { 49 "applies": false, 50 "answer": false, 51 "justification": "No original data collection or sampling." 52 }, 53 "variance_reported": { 54 "applies": false, 55 "answer": false, 56 "justification": "No original quantitative analysis." 57 } 58 }, 59 "evaluation_design": { 60 "baselines_included": { 61 "applies": false, 62 "answer": false, 63 "justification": "Narrative review; no system or method is evaluated against baselines." 64 }, 65 "baselines_contemporary": { 66 "applies": false, 67 "answer": false, 68 "justification": "No evaluation is conducted." 69 }, 70 "ablation_study": { 71 "applies": false, 72 "answer": false, 73 "justification": "No system with components to ablate." 74 }, 75 "multiple_metrics": { 76 "applies": false, 77 "answer": false, 78 "justification": "No evaluation metrics are used." 79 }, 80 "human_evaluation": { 81 "applies": false, 82 "answer": false, 83 "justification": "No system outputs are evaluated by humans." 84 }, 85 "held_out_test_set": { 86 "applies": false, 87 "answer": false, 88 "justification": "No experimental evaluation." 89 }, 90 "per_category_breakdown": { 91 "applies": true, 92 "answer": true, 93 "justification": "The review organizes findings across five thematic categories (workforce, education, practice, regulation, human factors) with detailed tables for each." 94 }, 95 "failure_cases_discussed": { 96 "applies": true, 97 "answer": true, 98 "justification": "The paper discusses challenges and risks of AI in nursing across multiple tables (Tables 4-7) and in the text, including failed workforce forecasts (Biviano et al., 2007) and AI decreasing efficiency (Becker et al., 2025)." 99 }, 100 "negative_results_reported": { 101 "applies": true, 102 "answer": true, 103 "justification": "The paper reports negative findings, e.g., that AI decreased developer efficiency in a controlled test (Becker et al., 2025) and that only 17% of nursing programs offer AI coursework." 104 } 105 }, 106 "claims_and_evidence": { 107 "abstract_claims_supported": { 108 "applies": true, 109 "answer": true, 110 "justification": "The abstract claims the review examines AI across five domains and highlights opportunities, risks, and regulatory gaps. The body addresses all five domains with supporting literature." 111 }, 112 "causal_claims_justified": { 113 "applies": true, 114 "answer": false, 115 "justification": "The paper makes causal-sounding claims like AI 'can alleviate workforce shortages' and 'enhance patient safety' without adequate causal evidence; these are largely aspirational statements drawn from limited evidence." 116 }, 117 "generalization_bounded": { 118 "applies": true, 119 "answer": false, 120 "justification": "The paper frequently makes broad claims about AI's transformative potential in nursing without bounding them to specific evidence. The title scope is very broad. The limitations section partially addresses this but the body text routinely overgeneralizes." 121 }, 122 "alternative_explanations_discussed": { 123 "applies": true, 124 "answer": false, 125 "justification": "The paper does not discuss alternative explanations for the patterns it identifies. For example, workforce shortages might be addressed by non-AI solutions, but alternatives are not systematically considered." 126 } 127 }, 128 "setup_transparency": { 129 "model_versions_specified": { 130 "applies": false, 131 "answer": false, 132 "justification": "No AI models are used or evaluated in this review." 133 }, 134 "prompts_provided": { 135 "applies": false, 136 "answer": false, 137 "justification": "No prompting is used." 138 }, 139 "hyperparameters_reported": { 140 "applies": false, 141 "answer": false, 142 "justification": "No AI models are run." 143 }, 144 "scaffolding_described": { 145 "applies": false, 146 "answer": false, 147 "justification": "No agentic scaffolding is used." 148 }, 149 "data_preprocessing_documented": { 150 "applies": true, 151 "answer": false, 152 "justification": "The methodology section describes databases searched and search strings but does not report hit counts, screening steps, or the number of papers included/excluded at each stage. No PRISMA flow or equivalent is provided." 153 } 154 }, 155 "limitations_and_scope": { 156 "limitations_section_present": { 157 "applies": true, 158 "answer": true, 159 "justification": "A dedicated 'Limitations' section is present (lines 1928-1958) with substantive discussion." 160 }, 161 "threats_to_validity_specific": { 162 "applies": true, 163 "answer": true, 164 "justification": "The limitations section identifies specific threats: reliance on three databases may exclude relevant studies, rapid AI development may outdate findings, grey literature introduces publication bias, and lack of nursing-specific evidence limits mitigation strategy discussion." 165 }, 166 "scope_boundaries_stated": { 167 "applies": true, 168 "answer": true, 169 "justification": "The paper explicitly states it 'focuses on a curated selection of core areas representing only the surface of a rapidly expanding field' and lists specific exclusions (clinical specialties, long-term societal implications)." 170 } 171 }, 172 "data_integrity": { 173 "raw_data_available": { 174 "applies": true, 175 "answer": false, 176 "justification": "No raw data (e.g., list of reviewed papers, extraction tables) is made available." 177 }, 178 "data_collection_described": { 179 "applies": true, 180 "answer": false, 181 "justification": "The methodology section describes search terms and databases but lacks detail: no date range for the search, no total number of results, no screening process documented." 182 }, 183 "recruitment_methods_described": { 184 "applies": false, 185 "answer": false, 186 "justification": "No human participants; data source is published literature. Standard benchmark NA rule applies." 187 }, 188 "data_pipeline_documented": { 189 "applies": true, 190 "answer": false, 191 "justification": "The paper describes search databases and Boolean operators but does not document the full pipeline from search results to final included studies. No counts at any filtering stage are provided." 192 } 193 }, 194 "conflicts_of_interest": { 195 "funding_disclosed": { 196 "applies": true, 197 "answer": false, 198 "justification": "No funding statement is present. The acknowledgements thank individuals but do not mention funding sources. All authors are affiliated with NCSBN, which suggests institutional support, but this is not explicitly disclosed as funding." 199 }, 200 "affiliations_disclosed": { 201 "applies": true, 202 "answer": true, 203 "justification": "All authors' affiliations with NCSBN are clearly listed. The paper is published in the Journal of Nursing Regulation, which is an NCSBN publication." 204 }, 205 "funder_independent_of_outcome": { 206 "applies": true, 207 "answer": false, 208 "justification": "All authors are affiliated with NCSBN, which has a direct interest in nursing regulation and AI adoption outcomes discussed in the paper. The journal is also an NCSBN publication. This potential conflict is not acknowledged." 209 }, 210 "financial_interests_declared": { 211 "applies": true, 212 "answer": true, 213 "justification": "The paper includes a 'Declaration of competing interest' section stating 'The authors declare no conflicts of interest.'" 214 } 215 }, 216 "contamination": { 217 "training_cutoff_stated": { 218 "applies": false, 219 "answer": false, 220 "justification": "No pre-trained model is evaluated on any benchmark." 221 }, 222 "train_test_overlap_discussed": { 223 "applies": false, 224 "answer": false, 225 "justification": "No model evaluation is performed." 226 }, 227 "benchmark_contamination_addressed": { 228 "applies": false, 229 "answer": false, 230 "justification": "No benchmark evaluation." 231 } 232 }, 233 "human_studies": { 234 "pre_registered": { 235 "applies": false, 236 "answer": false, 237 "justification": "No human participants. The paper explicitly states 'No human subjects were involved in this literature review.'" 238 }, 239 "irb_or_ethics_approval": { 240 "applies": false, 241 "answer": false, 242 "justification": "No human participants." 243 }, 244 "demographics_reported": { 245 "applies": false, 246 "answer": false, 247 "justification": "No human participants." 248 }, 249 "inclusion_exclusion_criteria": { 250 "applies": false, 251 "answer": false, 252 "justification": "No human participants." 253 }, 254 "randomization_described": { 255 "applies": false, 256 "answer": false, 257 "justification": "No human participants." 258 }, 259 "blinding_described": { 260 "applies": false, 261 "answer": false, 262 "justification": "No human participants." 263 }, 264 "attrition_reported": { 265 "applies": false, 266 "answer": false, 267 "justification": "No human participants." 268 } 269 }, 270 "cost_and_practicality": { 271 "inference_cost_reported": { 272 "applies": false, 273 "answer": false, 274 "justification": "Survey/review paper with no method that has inference costs." 275 }, 276 "compute_budget_stated": { 277 "applies": false, 278 "answer": false, 279 "justification": "Survey/review paper with no computational experiments." 280 } 281 } 282 }, 283 "claims": [ 284 { 285 "claim": "AI-powered smart labor market forecasting can provide real-time, high-resolution workforce analysis superior to traditional periodic surveys.", 286 "evidence": "Table 1 compares conventional headcount methods vs. AI-based forecasting across dimensions of data source, granularity, timeliness, accuracy, and adaptability. Cites Chen et al. (2025) and Howison et al. (2025).", 287 "supported": "weak" 288 }, 289 { 290 "claim": "Only 17% of U.S. nursing programs currently offer coursework in generative AI, and just 5% teach big data concepts.", 291 "evidence": "Cites Wolters Kluwer & NLN (2025) survey of more than 300 nursing schools.", 292 "supported": "moderate" 293 }, 294 { 295 "claim": "AI decreased efficiency in a controlled comparative test by producing unreliable or potentially misleading outputs.", 296 "evidence": "Cites Becker, Rush, Barnes, & Rein (2025) — a study of experienced open-source developers.", 297 "supported": "moderate" 298 }, 299 { 300 "claim": "Interstate licensure compacts are critical for enabling AI-powered workforce forecasting to reach its full potential.", 301 "evidence": "Discussed in the context of NLC and APRN Compact, citing multiple policy sources. The causal link between compacts and AI effectiveness is asserted, not empirically demonstrated.", 302 "supported": "weak" 303 }, 304 { 305 "claim": "By 2030, standardized protocols for AI deployment in nursing are expected to emerge.", 306 "evidence": "Cites Lekadir et al. (2025) and Medicines and Healthcare Products Regulatory Agency (2024). This is a projection, not an empirical finding.", 307 "supported": "unsupported" 308 } 309 ], 310 "methodology_tags": ["qualitative", "meta-analysis"], 311 "key_findings": "This narrative review examines AI applications in nursing across five domains: workforce planning, education, practice, regulation, and human factors. It finds that AI adoption in nursing education is very low (17% of programs offer generative AI coursework) and identifies significant regulatory gaps, particularly the absence of nursing-specific AI guidelines and inconsistent interstate telehealth policies. The paper proposes a conceptual framework for AI-powered workforce forecasting and catalogs regulatory barriers with proposed solutions, but provides no original empirical evidence.", 312 "red_flags": [ 313 { 314 "flag": "Institutional self-publication", 315 "detail": "All five authors are affiliated with NCSBN, and the paper is published in the Journal of Nursing Regulation, which is an NCSBN publication. The paper advocates for expanded NCSBN regulatory roles and AI adoption frameworks that would increase NCSBN's relevance, but this conflict is not acknowledged beyond a generic 'no conflicts of interest' declaration." 316 }, 317 { 318 "flag": "Unsystematic review presented as systematic", 319 "detail": "The methodology section claims a 'systematic literature search' but lacks essential systematic review components: no PRISMA flow, no date range, no inclusion/exclusion criteria counts, no quality assessment of included studies, and no total number of papers reviewed. This is a narrative review, not a systematic one." 320 }, 321 { 322 "flag": "Aspirational claims without evidence", 323 "detail": "Many claims about AI's transformative potential (e.g., 'AI can support nursing in preserving its core values') are aspirational rather than evidence-based. The paper frequently uses speculative language ('AI offers,' 'AI can,' 'AI will') without empirical grounding." 324 } 325 ], 326 "cited_papers": [ 327 { 328 "title": "Measuring the impact of early-2025 AI on experienced open-source developer productivity", 329 "authors": ["J. Becker", "N. Rush", "B. Barnes", "D. Rein"], 330 "year": 2025, 331 "doi": "10.48550/arXiv.2507.09089", 332 "relevance": "Directly relevant empirical study finding AI decreased developer efficiency — a counterpoint to productivity claims." 333 }, 334 { 335 "title": "The potential of artificial intelligence to improve patient safety: A scoping review", 336 "authors": ["D.W. Bates", "D. Levine", "A. Syrowatka"], 337 "year": 2021, 338 "doi": "10.1038/s41746-021-00423-6", 339 "relevance": "Scoping review of AI for patient safety, relevant to evaluating methodological quality of AI safety claims." 340 }, 341 { 342 "title": "Integration of artificial intelligence into nursing practice", 343 "authors": ["M.M. Abuzaid", "W. Elshami", "S. Mc Fadden"], 344 "year": 2022, 345 "doi": "10.1007/s12553-022-00697-0", 346 "relevance": "Earlier review of AI integration in nursing practice, useful for comparing review methodology." 347 }, 348 { 349 "title": "Revolutionizing healthcare: The role of artificial intelligence in clinical practice", 350 "authors": ["S.A. Alowais"], 351 "year": 2023, 352 "doi": "10.1186/s12909-023-04698-z", 353 "relevance": "Broad review of AI in clinical practice relevant to the survey's scope on AI in healthcare." 354 }, 355 { 356 "title": "Patient perspectives on AI for mental health care: Cross-sectional survey study", 357 "authors": ["N. Benda"], 358 "year": 2024, 359 "doi": "10.2196/58462", 360 "relevance": "Empirical study of patient attitudes toward AI in healthcare, relevant to human factors in AI adoption." 361 } 362 ] 363 }