Healthcare Literature Review Topics

Healthcare research moves fast—thousands of new studies hit journals each month, and a smart topic choice saves hours of work and strengthens your argument. Today we at TopicSuggestions will share ideas you can actually use, drawing on what we track as researchers across public health, clinical practice, health systems and policy, mental health, health tech and data, and ethics and equity. We know students need topics that are current, feasible with standard databases, and meaningful for coursework, so we kept accessibility and clear research questions in mind.

Literature Review Topic Ideas on Healthcare

Our thesis is simple: choose a topic at the intersection of relevance, manageable scope, and available evidence, and your literature review will be sharper and quicker to write. To make that easy, we’ve grouped the topics by category and added brief angles to guide your focus and keywords.

Now let’s get to the list.

1. Ambient Smart-Device Chatter as a “Witness”: How We Think IoT Narratives Reshape Forensic Inference

– We ask how jurors’ causal attributions shift when passive IoT logs are narrated as a “witness” versus presented as raw data.
– We test whether suspects exposed to their home’s device transcripts experience self-perception shifts that influence confession likelihood.
– We examine whether carefully crafted judicial instructions can reduce automation bias without undermining legitimate probative value.
– We explore how we, as fact-finders, anthropomorphize “the home’s voice” and whether that skews credibility judgments.

2. Self-Generated Deepfakes as Alibi Artifacts: How We Parse Identity, Intent, and Memory in Court

– We investigate how exposure to a defendant’s self-produced deepfake alters jurors’ perceptions of intent, deceit, and character.
– We test whether we contaminate eyewitness memory when we view manipulated footage prior to testimony.
– We evaluate whether we can design evidentiary warnings that preserve source-monitoring accuracy without priming undue skepticism.

3. Prosody Misalignment in Neurodivergent–Police Interviews: We Propose a New Index for Deception Misattribution

– We develop and validate a Prosody Misalignment Index to quantify conversational rhythm mismatches during investigative interviews.
– We test whether we systematically misread prosodic differences as deception among autistic and ADHD populations.
– We assess whether interviewer training on prosodic diversity helps us reduce false suspicion and improve rapport.

4. Virtual Reality Crime-Scene Walkthroughs and the Illusion of Knowledge: How We Gain Confidence Without Accuracy

– We measure whether immersive presence inflates our confidence beyond actual comprehension of evidentiary detail.
– We examine how VR reconstructions affect our temporal ordering of events and source-monitoring errors.
– We test whether pre-briefing or debriefing protocols help us calibrate confidence to accuracy in juror decision-making.

5. Explaining Algorithmic Risk in Court: How We Psychologically Delegate Blame to Scores and Their Authors

– We evaluate how different explanation styles (mechanistic, case-based, counterfactual) shift our accountability attributions among judges and jurors.
– We test whether we use risk thresholds as moral anchors that skew sentencing severity.
– We examine whether we diffuse responsibility between tool designers and decision-makers when outcomes are adverse.

6. Human–AI Dyads in Forensic Pattern Comparison: How We Track Micro-Trust Oscillations and Error Cascades

– We map moment-to-moment trust shifts as we accept or override AI suggestions in fingerprint or footwear analysis.
– We test whether subtle interface cues nudge us toward overreliance or reactance, creating error cascades.
– We design and evaluate debiasing protocols that keep our trust appropriately calibrated across varying base rates.

7. Trauma-Informed Interviewing for Child Suspects: How We Distinguish Needs From Those of Child Witnesses

– We compare how cognitive load and rights comprehension differ when we interview child suspects versus child witnesses.
– We test whether trauma-informed adaptations reduce our rates of suggestion and false confession among minors.
– We evaluate how our interviewer stance (supportive, neutral, inquisitorial) shapes disclosure quality and legal outcomes.

8. Avatar-Mediated Forensic Interviewing in Game Worlds: How We Balance Presence, Disinhibition, and Evidence Quality

– We study whether avatar embodiment affects how we disclose sensitive information and how we perceive interviewer authority.
– We test platform affordances (voice, text, emotes) to see how they alter our recall, coherence, and resistance to suggestion.
– We develop ethical guardrails that let us preserve rapport while safeguarding voluntariness and reliability.

9. Text-Based Coercive Control in Intimate Partner Cases: How We Teach Juries to See Harm Without Physical Injury

– We identify which linguistic patterns lead us, as jurors, to reliably recognize coercive control in message logs.
– We test how expert testimony and pattern learning tools shift our thresholds for perceiving psychological harm.
– We evaluate instruction prototypes that help us integrate digital context without overvaluing salacious content.

10. Moral Injury in Digital Forensic Teams: How We Conceptualize and Treat Vicarious Harm From Graphic Evidence

– We develop a forensic-psych framework that distinguishes our moral injury from burnout and secondary trauma in cyber units.
– We test peer-support and supervision models that help us maintain decision quality under cumulative exposure.
– We validate brief screening tools that let us monitor team risk while protecting confidentiality and case integrity.

11. Remote haptic-feedback monitoring for chronic wound care adherence

We propose to review evidence on devices and protocols that use haptic or tactile feedback to prompt patient wound-care behaviors.
We ask: 1) What are the reported effects of haptic-feedback reminders on adherence and wound-healing outcomes? 2) How have studies measured patient acceptance, skin integrity safety, and equity of access? 3) What implementation barriers and device-design features predict success?
We will work by conducting a scoping review across engineering, nursing, and rehabilitation literature, extracting device type, feedback parameters, adherence metrics, clinical endpoints, and qualitative user-reports, then mapping gaps for RCTs and human-factors testing.

12. Influence of AI-synthesized patient narratives on clinician diagnostic empathy and decision-making

We examine literature that evaluates clinician responses to generated patient narratives (e.g., voice or text summaries created by generative models) rather than original patient speech.
We ask: 1) How does exposure to AI-rewritten or condensed patient stories alter clinicians’ empathy scores, diagnostic hypotheses, and testing/treatment choices? 2) What safeguards or presentation formats preserve clinical judgment? 3) What ethical frameworks have been proposed for AI-mediated narrative use?
We will synthesize mixed-methods studies and ethical analyses, coding for narrative fidelity, clinician outcome measures, bias amplification, and recommended mitigation strategies.

13. Microbiome-targeted surface and hand-rub interventions in neonatal intensive care units (NICUs)

We target literature exploring interventions designed to shift environmental or hand-surface microbiomes (probiotic sprays, bacteriophage coatings, microbiome-friendly hand rubs) to reduce neonatal colonization and infection.
We ask: 1) What interventions have been trialed in NICUs to modulate surface/skin microbiomes, and with what infection/outcome signals? 2) How robust are methods for microbiome monitoring and attribution of clinical effects? 3) What safety and regulatory concerns are reported for vulnerable neonates?
We will conduct a targeted systematic search across microbiology, infection control, and neonatology journals, extract study designs, sequencing approaches, clinical endpoints, and synthesize evidence strength and translational barriers.

14. Ambient scent modulation in hospitals: effects on patient recovery, delirium, and staff performance

We investigate the literature on purposeful scenting (aromatherapy, odor masking) in inpatient settings and its associations with recovery metrics, cognitive outcomes like delirium, and clinician performance.
We ask: 1) What scents and exposure protocols have been studied, and which patient populations show measurable benefit or harm? 2) How are outcomes (pain, sleep, delirium incidence, nursing error rates) defined and measured? 3) What are allergenicity, cultural acceptability, and regulatory considerations?
We will pair a systematic review of clinical trials with a narrative synthesis of human-factors and occupational-health reports, highlighting methodological heterogeneity and proposing standardized outcome measures.

15. Blockchain-enabled consent logs and longitudinal data-sharing in rare disease registries

We assess literature on using distributed ledger technology to record dynamic consent and audit trails for sharing longitudinal biospecimens and clinical data in rare disease research.
We ask: 1) What architectures and governance models have been proposed or piloted, and how do they affect participant trust and data reuse rates? 2) How do privacy, scalability, and interoperability trade-offs manifest in reported deployments? 3) What legal/regulatory analyses address cross-border rare-disease data flows with blockchain?
We will perform a technology-and-policy literature review, classify reported use-cases, synthesize empirical evaluations of participant attitudes, and identify standards required for registry adoption.

16. Precision nutrition guided by metabolomic clustering in type 2 diabetes: a literature mapping

We explore reviews and primary studies that use metabolomic phenotyping to tailor dietary interventions for people with type 2 diabetes.
We ask: 1) Which metabolomic clusters have been reproducibly identified and matched to differential dietary responses? 2) What is the evidence that metabolomics-guided diets improve glycemic control beyond conventional personalization strategies? 3) What methodological standards exist for metabolomic-driven dietary trials?
We will map study designs, clustering methods, intervention types, and clinical outcomes, and assess reproducibility and translational readiness through quality appraisal and recommendations for trial harmonization.

17. Digital twin models for predicting hospital bed flow under concurrent hazards (pandemic plus environmental disasters)

We examine literature on digital twin and agent-based models used to forecast hospital capacity when multiple hazards (infectious surges, heatwaves, flooding) co-occur.
We ask: 1) How have models integrated multi-hazard inputs and supply-chain/staffing dynamics to predict bed occupancy and ICU demand? 2) What validation strategies and real-world deployments exist? 3) How have equitable resource-allocation implications been treated?
We will synthesize modeling approaches, validation evidence, stakeholder-engagement reports, and propose standardized metrics for operational usefulness and equity assessment.

18. Clinician use of generative-AI draft notes: ethnographic and medico-legal literature synthesis

We compile qualitative and legal literature on how clinicians adopt AI-drafted clinical notes and how this practice affects documentation accuracy, clinician workload, and medico-legal responsibility.
We ask: 1) What themes emerge about shifts in authorship, oversight, and trust when clinicians rely on AI drafting? 2) How have regulatory bodies and professional liability frameworks responded? 3) What practical governance and audit strategies are recommended?
We will perform a thematic synthesis of ethnographies, mixed-methods studies, and policy documents, highlighting tensions between efficiency gains and accountability.

19. Climate-adaptive architecture in long-term care facilities and its impact on infectious-disease transmission

We review literature on architectural adaptations (ventilation upgrades, decentralized wards, flood-resilient design) intended to both mitigate climate risks and influence infection transmission in long-term care settings.
We ask: 1) Which built-environment interventions demonstrate reduced respiratory or enteric transmission among residents? 2) How do climate-driven design choices intersect with resident wellbeing and care delivery models? 3) What cost-effectiveness and equity analyses exist?
We will integrate evidence from infection control, architectural engineering, gerontology, and health economics to produce cross-disciplinary recommendations and identify evaluation gaps.

20. Health-equity consequences of tiered telehealth reimbursement policies for marginalized populations

We assess literature on how reimbursement structures (parity vs. reduced rates, geographic eligibility tiers) influence telehealth access, quality, and outcomes across marginalized groups (rural, low-income, non-English speakers).
We ask: 1) How do different reimbursement models correlate with utilization disparities, care continuity, and health outcomes? 2) What unintended incentives affect platform choice, visit length, and provider distribution? 3) Which policy designs mitigate inequitable effects?
We will perform a policy-focused systematic review combined with a realist synthesis of mechanisms linking reimbursement rules to access and outcome differentials, and identify high-priority empirical comparisons.

21. Microclimate-controlled hospital bed microbial dynamics and patient outcomes

We propose to study how the immediate microclimate (localized temperature, humidity, airflows at the mattress-skin interface) shapes microbial community composition and hospital-acquired infection (HAI) risk. Research questions: 1) How do bed-surface microclimate fluctuations correlate with pathogen load and patient skin microbiome shifts? 2) Can adaptive bed-surface climate modulation reduce viable pathogen counts and HAI incidence? 3) What engineering and behavioral constraints affect real-world implementation? We will deploy high-resolution microclimate sensors and longitudinal microbiome sampling at bedside, apply metagenomic sequencing and culture for pathogens, and run a crossover intervention trial with adaptive bed-surface conditioning to evaluate clinical and microbiological outcomes.

22. Algorithmic transparency metrics for clinical decision support in low-resource languages

We aim to create objective, usable transparency metrics for CDS explanations tailored to clinicians who use low-resource languages. Research questions: 1) Which explanation elements (visual, textual, examples) are interpretable across linguistic and cultural contexts with limited terminology resources? 2) How do transparency metrics predict clinician trust, acceptance, and correct use? 3) Can lightweight localized explanations be generated without large parallel corpora? We will co-design explanation prototypes with clinicians in target regions, develop psychometric transparency scales, and validate them through controlled usability studies and task-based performance metrics.

23. Temporal mismatch between consumer circadian trackers and hospital biomarker rhythms

We plan to quantify and correct timing misalignments between consumer wearable circadian outputs and hospital-derived biomarkers (hormones, cytokines, metabolic measures). Research questions: 1) What systematic phase offsets exist between wearable-derived circadian markers and clinical biomarkers in hospitalized patients? 2) Can algorithmic alignment improve prediction of clinical events (delirium, sepsis onset)? 3) How do illness, medication, and environment modulate these offsets? We will collect simultaneous wearable data and serial biomarker panels, build statistical phase-alignment models, and test whether aligned circadian features enhance prognostic models.

24. Carbon footprint of personalized oncology regimens and survival trade-offs

We intend to map the life-cycle carbon costs of precision oncology pathways and evaluate trade-offs with survival and quality-adjusted life-years (QALYs). Research questions: 1) What are the per-patient greenhouse gas emissions for different personalized oncology regimens (sequencing, targeted therapy, combination immunotherapy)? 2) How can carbon metrics be integrated into shared decision-making without compromising outcomes? 3) What low-carbon modifications preserve clinical efficacy? We will perform cradle-to-grave life-cycle assessments for representative regimens, integrate carbon into decision-analytic models with survival/QALY outcomes, and conduct clinician-patient focus groups on acceptability.

25. Neurocognitive impacts of prolonged telepresence in pediatric telemedicine

We will investigate whether frequent telemedicine encounters during key developmental windows affect attention, executive function, and socio-emotional skills in children. Research questions: 1) Does high-frequency telepresence exposure change short-term attention and classroom behavior compared with in-person visits? 2) Which telemedicine interface features mitigate potential negative effects on social cognition? 3) Are effects age-dependent or moderated by socioeconomic factors? We will run a longitudinal cohort study with standardized neurocognitive batteries, classroom teacher ratings, and randomized UI/interaction feature trials to identify protective design elements.

26. Epigenetic signatures of extended mask-wearing among front-line immune cells

We aim to assess whether prolonged mask use in healthcare workers associates with durable epigenetic modifications in peripheral immune cells and whether these correlate with infection susceptibility or inflammatory profiles. Research questions: 1) Are there differential DNA methylation or chromatin accessibility patterns linked to cumulative mask-wearing hours? 2) Do any identified epigenetic changes correspond to altered cytokine responses or clinical respiratory outcomes? 3) What confounders (stress, sleep, exposures) must be adjusted? We will enroll longitudinal HCW cohorts with exposure logs, perform sorted immune-cell epigenomic profiling, measure functional immune responses, and apply causal inference methods to adjust for confounders.

27. Ethical AI triage under intermittent connectivity in disaster zones

We plan to design and evaluate triage algorithms that ethically degrade under intermittent data connectivity and limited inputs during disasters. Research questions: 1) How should triage decision rules prioritize equity and harm minimization when key predictors are missing or delayed? 2) What transparency and override protocols are required for frontline responders to trust degraded-mode outputs? 3) How do simulated degraded algorithms perform compared with clinician-only triage? We will develop robust, graceful-degradation algorithmic strategies, simulate disaster data loss scenarios, run tabletop and field exercises with emergency responders, and convene ethicist-clinician workshops to derive operational governance.

28. Social network resilience and vaccine misinformation spread after natural disasters

We will examine how social ties restructure following natural disasters and how that restructuring alters pathways of vaccine misinformation amplification or attenuation. Research questions: 1) How does post-disaster reconfiguration of local digital and physical networks change misinformation susceptibility? 2) Can targeted rebuilding of trusted nodes reduce misinformation spread and improve vaccination uptake? 3) What timing and channel strategies are most effective in the post-disaster window? We will combine pre/post disaster social network mapping (digital traces, surveys), diffusion modeling, and rapid-deployment interventions that seed accurate information through high-trust nodes, assessing downstream changes in beliefs and vaccine behavior.

29. Impact of automated clinical voice assistants’ prosody on patient medication adherence

We propose to test whether prosodic features (pitch contour, tempo, affect) of clinical voice assistants influence comprehension, trust, and medication adherence in chronic disease populations. Research questions: 1) Which acoustic prosody parameters measurably improve adherence and recall of instructions? 2) Are effects mediated by patient demographics, health literacy, or cultural expectations? 3) How stable are effects over long-term exposure? We will produce prototype voice variants, conduct randomized trials measuring objective adherence (pharmacy refill, pill sensors), comprehension tests, and qualitative interviews to refine prosodic design recommendations.

30. Biodegradable implantable sensors’ degradation products and local tissue microbiome interplay

We aim to characterize how chemical degradation products from biodegradable implantable sensors influence the local tissue microbiome and biofilm formation over time. Research questions: 1) Do specific polymer degradation byproducts promote or inhibit colonization by opportunistic pathogens? 2) How do degradation kinetics and local immune responses interact to shape microbiome composition and device-associated infection risk? 3) What material design principles minimize adverse microbiome shifts? We will perform controlled in vitro biofilm assays with degradation product gradients, animal implantation studies with serial microbiome and histology sampling, and materials-testing to recommend composition and coating strategies.

31. Clinician micro-interruptions from wearable alerts: cognitive load, error propagation, and mitigation strategies

We focus on brief (15–60s) wearable-triggered task interruptions and their cumulative effects.
Research questions: 1) How do stacked micro-interruptions alter diagnostic decision accuracy and time-to-completion? 2) Which alert-batching or prioritization strategies minimize error propagation? 3) How do individual differences (experience level, working-memory capacity) moderate effects?
Overview: We design controlled simulation studies with timed interruptions, measure task performance and physiological markers (EEG/HRV), and run randomized trials of alert management algorithms in clinical pilots; we complement with time-motion observation and mixed-method interviews to refine mitigation designs.

32. Algorithmic bias in rural telemedicine triage involving indigenous languages and low-resource speech models

We examine triage performance when automated speech/translation models handle indigenous-language consultations.
Research questions: 1) To what extent do current speech/translation models produce triage-relevant errors for indigenous-language speakers? 2) What fairness metrics best capture harm in clinical triage contexts? 3) How can participatory model-retraining reduce disparities without degrading overall accuracy?
Overview: We collect paired clinical triage transcripts, benchmark off-the-shelf models, compute task-specific fairness metrics (false-negative triage rates), and co-design dataset augmentation and on-device adaptation with community stakeholders; we evaluate via prospective teletriage pilots.

33. Longitudinal epigenetic signatures following ICU delirium and their relation to post-ICU cognitive decline

We investigate whether delirium episodes leave persistent epigenetic marks predictive of later cognitive impairment.
Research questions: 1) Are there differential DNA methylation patterns detectable months after ICU delirium? 2) Do such patterns correlate with objective neurocognitive outcomes at 6–12 months? 3) Can epigenetic markers improve post-ICU risk stratification beyond clinical scores?
Overview: We establish a longitudinal ICU cohort with baseline and follow-up blood sampling, perform epigenome-wide assays, run neuropsychological batteries, and apply multivariable models integrating clinical and epigenetic data; we validate candidate loci in external cohorts.

34. Carbon footprint and lifecycle emissions of clinical genomic sequencing pipelines and low-carbon optimization strategies

We quantify greenhouse-gas emissions across sequencing workflows and test operational changes to reduce impact.
Research questions: 1) What are the major emissions hotspots in clinical sequencing (lab prep, compute, cold storage)? 2) What trade-offs arise between turnaround time, cost, and emissions when implementing low-carbon workflows? 3) Which procurement or scheduling policies yield largest emissions reductions at scale?
Overview: We perform a life-cycle assessment (LCA) on real clinical lab pipelines, model emission scenarios under alternative compute/storage/lab protocols, and pilot low-carbon interventions (batching, spot compute, energy-sourced scheduling) with cost-effectiveness and quality comparisons.

35. Influence of hospital NICU architectural acoustics on staff behavior and airborne/ surface microbiome transmission

We explore whether acoustic design features indirectly affect microbial transmission via altered staff behavior and airflow.
Research questions: 1) Do specific acoustic profiles (reverberation, noise masking) change staff movement and speaking patterns relevant to transmission? 2) Are microbiome composition and dispersion patterns associated with acoustic zones? 3) Can acoustic interventions reduce transmission-prone behaviors without harming care quality?
Overview: We map acoustic properties in NICU zones, conduct synchronized behavioral observation and microbial air/surface sampling, run computational fluid dynamics to model flow-behavior coupling, and pilot acoustic treatment interventions measuring both behavior and microbiome outcomes.

36. Peer-to-peer encrypted messaging networks for patient-driven symptom surveillance during outbreaks: data quality and ethical trade-offs

We pilot decentralized symptom reporting via P2P encrypted apps and assess surveillance utility and privacy-preserving design.
Research questions: 1) How does decentralized, encrypted symptom reporting compare with centralized systems in timeliness and signal accuracy? 2) What biases emerge in participation and reporting across demographics? 3) What governance and consent models best balance public-health usefulness and privacy risk?
Overview: We develop a prototype P2P reporting app, run community pilots during seasonal outbreaks, compare syndromic signals to public-health baselines, analyze participation bias, and conduct stakeholder deliberations to produce ethical deployment guidelines.

37. Pharmacogenomic-guided deprescribing algorithms deployed within automated community pharmacy dispensing systems

We evaluate integrating PGx data into automated dispensing logic to suggest deprescribing or dose adjustments at point-of-dispense.
Research questions: 1) Does PGx-enabled automated deprescribing reduce medication-related adverse events compared with usual care? 2) What are pharmacist and patient acceptance barriers to algorithmic deprescribing suggestions? 3) How does integration affect dispensing workflow and dispensing errors?
Overview: We develop clinically validated deprescribing rules linked to PGx profiles, integrate with pharmacy dispensing software in a cluster-randomized trial across community pharmacies, measure clinical outcomes and workflow metrics, and use mixed methods to assess acceptability and implementation barriers.

38. AI-synthesized voice assistants tuned for low-literacy populations: effects on medication adherence and comprehension

We assess whether conversational agents whose speech and dialogue are optimized for low literacy improve adherence among vulnerable patients.
Research questions: 1) Do voice assistants with simplified language, prosody adjustments, and culturally concordant speech increase medication comprehension and adherence? 2) What design features (repetition patterns, teach-back prompts) have highest marginal benefit? 3) Are there unintended harms (misinterpretation, overreliance) associated with synthesized voices?
Overview: We co-design voice profiles with target users, run randomized controlled trials comparing standard versus literacy-optimized voice assistants, measure comprehension, adherence (pill counts/wearables), and qualitatively explore trust and misuse.

39. Presurgical “green prescriptions” (structured nature exposure) prescribed by surgeons to improve postoperative outcomes in elective surgery

We test whether brief, clinician-prescribed nature exposure programs before elective procedures enhance recovery and reduce analgesic needs.
Research questions: 1) Does a prehabilitation regimen emphasizing nature exposure (measured via time outdoors and green space engagement) shorten length of stay or reduce postoperative pain scores? 2) What biological or psychological mediators (stress biomarkers, sleep quality) explain effects? 3) Is surgeon prescribing acceptable and feasible within pre-op workflows?
Overview: We design a standardized nature-exposure protocol, randomize patients to prescription vs usual pre-op care, monitor recovery metrics and biomarkers, and survey clinicians on feasibility to form implementation guidance.

40. Clinical and operational impacts of introducing indoor vertical-farmed produce into hospital foodservices on patient nutrition and recovery

We evaluate if locally produced vertical-farm vegetables in hospital meals affect nutritional intake, patient satisfaction, and clinical recovery markers.
Research questions: 1) Do meals incorporating vertical-farmed produce increase intake of key micronutrients and reduce malnutrition risk? 2) Are there measurable effects on recovery metrics (wound healing, infection rates, length of stay)? 3) What are cost, supply-chain, and acceptability trade-offs for hospital foodservice operations?
Overview: We implement a phased substitution of hospital menu items with vertical-farmed produce, collect dietary intake and biochemical nutrient markers, track clinical recovery outcomes, and perform cost-effectiveness and operational feasibility analyses with foodservice stakeholders.

41. Integrating indoor vertical hospital farms and patient recovery outcomes

We propose studying how small-scale hydroponic/vertical farming units placed in inpatient units alter air quality, microbial ecology, nutritional access, and patient recovery metrics. Research questions: 1) How do vertical farms change airborne particulate, VOCs, and room microbiomes compared with standard rooms? 2) Do patients in rooms with farms demonstrate shorter LOS, reduced pain scores, or faster mobility recovery? 3) Can inpatient access to freshly harvested produce measurably affect nutritional biomarkers? We will run a stepped-wedge pilot with environmental sampling, patient clinical endpoints, dietary intake tracking, and mixed-methods staff/patient interviews to create protocols for larger trials.

42. AI-driven empathy training using synthetic patient avatars derived from de-identified EHR narratives

We propose creating EHR-derived synthetic patient avatars to train clinician communication and empathy skills in realistic, diverse scenarios. Research questions: 1) Does avatar-based simulated exposure improve validated empathy scales and patient-reported experience compared with standard role-play? 2) Can machine-generated avatars reproduce complex social determinants and multimorbidity to enhance clinician diagnostic accuracy? 3) What ethical safeguards and de-identification thresholds ensure safety and realism? We will develop avatars from de-identified records, run randomized controlled training sessions with pre/post assessments (empathy, diagnostic accuracy, physiological stress markers), and conduct qualitative acceptability studies.

43. Predictive metagenomic signatures on operating-theatre surfaces for anticipating surgical site infection clusters

We propose longitudinal metagenomic mapping of OR surfaces to discover microbial community patterns that precede increases in surgical site infections (SSIs). Research questions: 1) Are there reproducible shifts in surface metagenomes that temporally predict SSI clusters? 2) How do different cleaning regimens and traffic patterns modulate those predictive signatures? 3) Can a real-time surveillance algorithm reduce SSI incidence when integrated with infection-control workflows? We will implement daily surface swabbing with shotgun metagenomics, correlate signatures to SSI incidence, train predictive ML models, and pilot an intervention that triggers targeted cleaning when risk thresholds are met.

44. Nighttime blue-light filtering policies in postnatal wards and effects on neonatal breastfeeding and circadian entrainment

We propose testing whether systematic blue-light filtering and lighting schedules in postpartum units improve newborn sleep-wake patterns, breastfeeding initiation/duration, and maternal sleep. Research questions: 1) Does blue-light reduction during night shifts increase infant nighttime sleep consolidation and improve breastfeeding frequency/duration? 2) Do maternal circadian biomarkers and sleep quality improve under filtered lighting? 3) Are there downstream effects on early infant weight gain and neonatal jaundice? We will conduct a cluster randomized trial across maternity wards measuring actigraphy, feeding logs, salivary melatonin, and breastfeeding metrics alongside staff adherence audits.

45. Commuting environment of healthcare workers as a determinant of infectious-workplace absenteeism

We propose linking healthcare worker commute modes, durations, and microenvironment exposures to patterns of infectious absenteeism and workplace transmission. Research questions: 1) Are certain commute profiles (crowded public transit, shared rides, active commuting) associated with higher rates of infectious absenteeism among HCWs? 2) How does commute-related exposure interact with workplace PPE and vaccination to predict absenteeism? 3) Can targeted scheduling or transport support reduce infection-related staff shortages? We will run a prospective cohort with GPS-enabled travel diaries, self-reported exposures, serial symptom/infection testing, and multivariable models to estimate attributable risk and simulate interventions.

46. Telepresence robots in long-term dementia care: effects on agitation, social connectedness, and family attachment

We propose evaluating whether structured telepresence robot visits (mobile video/interaction platforms) reduce agitation episodes and preserve perceived family connectedness for residents with moderate-to-severe dementia. Research questions: 1) Do scheduled telepresence robot interactions reduce frequency and duration of agitation or wandering compared with standard video calls? 2) How do residents’ physiological stress markers and staff workload change with robot-mediated visits? 3) What are family members’ perceptions of attachment and care satisfaction? We will perform a crossover-controlled trial in LTC units, collect behavioral scales (Cohen-Mansfield), wearable physiological data, staff time-motion observations, and qualitative interviews.

47. Pharmacogenomic-guided opioid tapering protocols for chronic non-cancer pain to minimize withdrawal and persistent opioid use

We propose tailoring opioid taper schedules by pharmacogenomic profiles (CYP2D6, CYP3A4, OPRM1) to reduce withdrawal severity and facilitate successful discontinuation. Research questions: 1) Does genotype-informed tapering reduce withdrawal symptom burden and improve taper completion rates versus standard protocols? 2) Are certain genotypes predictive of relapse to opioid use or need for adjunct therapies? 3) What is the cost-effectiveness of pre-taper genotyping in primary-care pain programs? We will conduct an RCT stratified by metabolizer status, monitor withdrawal scales, urine toxicology, pain/function outcomes, and health-economics modeling.

48. Hospital architectural stair accessibility and its impact on postoperative ambulation and venous thromboembolism (VTE) incidence

We propose studying whether visible, inviting internal stair design and wayfinding leads to increased postoperative ambulation and reduced VTE events compared with stair-removed or elevator-dominant layouts. Research questions: 1) Does proximity and aesthetic stair accessibility increase voluntary stair use and step counts in postoperative inpatients? 2) Is increased stair use associated with lower rates of VTE and faster functional recovery? 3) What behavioral nudges and signage maximize stair engagement without compromising mobility safety? We will use quasi-experimental designs in hospitals undergoing renovation, combine wearable mobility trackers, VTE surveillance, and behavioral audits to quantify effects.

49. Crowd-sourced symptom mapping platforms for real-time triage during localized chemical exposure incidents

We propose creating a citizen reporting app to capture geotagged symptoms during suspected chemical exposures to augment official triage and resource allocation. Research questions: 1) Can crowd-sourced symptom clusters improve early detection and localization of chemical releases compared with emergency calls alone? 2) How accurate and timely are public-reported symptom maps in guiding on-scene triage and hospital surge planning? 3) What privacy, data validation, and misinformation controls are required for safe deployment? We will build a prototype platform, run tabletop and live-drill validations with simulated exposures, compare triage outcomes, and model integration pathways with public health EMS systems.

50. Personalized HRV-synced music therapy playlists to shorten ICU delirium duration

We propose developing individualized music playlists that adapt tempo and structure to patients’ heart-rate variability (HRV) signatures to modulate autonomic tone and reduce delirium duration in ICU patients. Research questions: 1) Does HRV-synchronized music reduce delirium days and severity versus standard music or no music? 2) What HRV features best predict responsiveness to music-based autonomic modulation? 3) Are EEG or biomarker correlates observable that mediate delirium improvement? We will implement a crossover RCT using real-time HRV analysis to generate adaptive playlists, assess delirium with CAM-ICU, track physiological and EEG markers, and perform responder subgroup analyses.