Pop Health Eval Midterm

What is PALS used for and what does it stand for?

1. Multiple ways to define community and how people’s sense of identity and belonging shape civic involvement and health

2. Population, Activity, Locus, Shared Values

Are Community Health, Population Health, and Public Health related?

Related but has distinct approaches with different primary focus, unit of analysis, and key questions

Community Health

The health status of a defined community and the organized, participatory, place-based activities and resources that communities use to maintain and improve health, with emphasis on assets, engagement, equity, and collective action

• emphasizes place-based, participatory, and asset-focused work (preventative care)

Population Health

An approach that systematically examines health outcomes, determinants, and inequities across defined populations (by geography, demographics, or other characteristics), using data to identify patterns and target interventions

• uses data to examine patterns and determinants across defined populations (trends)

Public Health

The science and practice of protecting and promoting health through organized community efforts, emphasizing prevention, policy, and systems-level approaches

• focuses on organized community efforts, prevention, and policy

What is the Community Health Assessment (CHA)?

• A systematic process that combines secondary data, community observation, and asset mapping, primary data from community members (surveys, interviews, focus groups), and a literature review to understand why health disparities exist in a specific community and develop actionable recommendations

How to tell if a group qualifies as a community

Share a place, identity, activity, and values (shared connection)

Secondary Data

Existing data collected by others (e.g., CDC surveillance, NYC DOHMH Community Health Profiles, census/ACS, published literature) that can be used to describe patterns and context for your health topic and community

Primary Data

Data collected directly by the research team (e.g., surveys, interviews, focus groups, systematic observation) to answer specific questions that existing data cannot address

What is each secondary source used for? (CDC, DOHMH, Census, PubMed)

1. CDC → National disease trends

2. DOHMH → NYC Specific health data

3. Census → demographics (income, race, housing)

4. PubMed → research studies

What are the steps in CHA?

1. Define community

2. Collect and analyze data

3. Prioritize community health and social concerns (identify the problem)

4. Form a hypothesis (rely heavily on secondary data for an initial picture)

5. Collect more targeted data

What is a CHA used for in practice?

• Describes the health status of a population

• Identify areas for health improvement

• Determine contributing factors

• Identify assets and resources that can be mobilized for population health improvement (ex. health departments, hospitals, and community organizations)

Is secondary data quantitative or qualitative?

Quantitative because it consists of existing datasets (vital statistics, surveillance systems, surveys, census/ACS, environmental monitoring, clinical/administrative data)

Is primary data quantitative or qualitative?

Qualitative because its data collected by the CHA team (surveys, interviews, focus groups, observations)

Major population and area-level data sources

Vital statistics, disease surveillance systems, large health surveys, census and American Community Survey, environmental monitoring and clinical/administrative datasets

Vital Statistics (Use, Strength, and Limitation)

• Use: need mortality data, cause of death, birth rates, infant mortality/life expectancy patterns

• Strengths: Near universal coverage → everyone born/died is counted

• Limitations: Only captures births and deaths, NOT ILLNESS OR HEALTH BEHAVIOR

Disease Surveillance Systems (Use, Strength, and Limitation)

• Use: Need to track trends in specific reportable diseases over time or detect outbreaks

• Strengths: Ongoing and systematic → good for monitoring disease trends and early warning

• Limitations: Underreporting as passive systems miss cases that never reach the healthcare system

Large Health Surveys: NHANES, BRFSS, NYC Community Health Survey (Use, Strength, and Limitation)

• Use: Need data on health behaviors, risk factors, or self-reported health status that isn’t captured in administrative records

• Strengths: Capture behaviors, chronic conditions, and attitudes + allows population-level estimates

• Limitations: Social Desirability Bias (underrepresents undocumented, unhoused, or incarcerated populations) + not always available at the neighborhood level

Census and American Community Survey (Use, Strength, and Limitation)

• Use: Need demographic and socioeconomic context at the neighborhood level

• Strength: Large, detailed, free to access + essential for describing social determinants of health

• Limitation: Undercounts marginalized populations (undocumented immigrants, unhoused people, and incarcerated individuals)

Environmental Monitoring Data (Use, Strength, and Limitation)

• Use: Health topic involves air/water quality, heat exposure, or other environmental exposures

• Strength: Measured data rather than self-report → linked geographically to health outcomes

• Limitation: monitoring stations may not be evenly distributed + might not capture indoor exposures

Clinical and Administrative Datasets: Hospital Discharge/Insurance Claims (Use, Strength, and Limitation)

• Use: Need data on healthcare utilization (hospitalizations, ED visits, diagnoses, procedures/treatments)

• Strength: Large volumes of reach patient encounter data (who is using the health system and for what)

• Limitation: Misses the uninsured, undocumented, or those who avoid the system (cost/mistrust)

When to use each NYC data tool

• Vital stats → births/deaths

• Surveillance system → disease pattern

• Survey → behaviors

• Census → demographics

• DOHMH profiles → neighborhood health

• Atlas → mapping disparities

Hypothesis

An empirically testable statement about a relationship involving two or more variables, specifying a direction or pattern that may or may not exist under particular conditions

• In Harlem neighborhoods with higher housing instability, asthma hospitalization rates are higher

• Must be specific, measurable, and comparable

Epistemology

The study of the nature, scope, and justification of knowledge—that is, how and what we can know; in health research, it specifies what counts as valid evidence and whose knowledge is centered

Objectivism / Positivism

A stance assuming an objective reality that can be numerically measured

• uses quantitative methods (surveys, experiments, registries) to estimate patterns, test hypotheses, and seek generalizable laws

• Strength: clear, measurable patterns

• Risk: ignores context and lived experience

Interpretivism/Subjectivism

A stance emphasizing that meaning is constructed by actors; lived experiences

• uses qualitative/narrative methods (interviews, FGD, observations) to understand how people experience and interpret health and care

• Strength: rich insight into lived experience

• Risk: less generalizable

Critical / health equity stance

An approach that treats power, racism, and structural oppression as a main focus of research

• challenges deficit narratives, and insists on methodological choices that make structural inequity visible

• Uses participatory research, ethnography

Quantitative study

Research that collects and analyzes numerical data to estimate the size and statistical significance of associations or disparities across populations

• ex. registry data on ED restraint use

• focused, fixed designs, deductive, and objective

Qualitative study

Research that collects and analyzes textual, narrative, or observational data to understand experiences, meanings, and mechanisms

• ex. how racism is perceived and enacted in ED care

• uses interviews, focus groups, narratives

• Holistic, flexible, inductive, and subjective

What does the JAMA Internal Medicine ED-Restraints disparities study show?

• quantitative, objectivist/positivist

• shows how large racial disparities in restraint use are across populations

• numbers based

What does the JAMA Health Forum Black patient-perspectives article show?

• Qualitative, subjectivist/interpretivist

• Shows how racism is experienced and enacted in everyday emergency care

• more of a story

What is Bowleg’s Critical health equity research stance?

• Epistemology shapes

  • What is considered "real" and "scientific"

  • Whose knowledge is legitimate

  • What questions get asked about racism and structural inequity

• a critical stance explicitly names power and structural oppression and links epistemology to methodology.

What did Clarke/Sinkewicz‘s video “Neighborhoods as a Social Determinant of Health show about neighborhoods as SDOH framework?

4 ways neighborhoods shape health

• Physical environment (housing quality, green space, walkability)

• Service environment (healthcare, food, transportation access)

• Social environment (cohesion, safety, isolation)

• Policy environment (zoning, investment, segregation)

What did Clarke/Sinkewicz‘s video “Neighborhoods as a Social Determinant of Health show about spatial scale?

Spatial scale matters

• bigger geography (county) = HIDES disparities

• smaller geography (census tract) = REVEALS disparities

• zooming in = more inequality

What did Clarke/Sinkewicz‘s video “Neighborhoods as a Social Determinant of Health show about neighborhood-level data and measures?

Data tools used

• Census/ACS = demographics

• Neighborhood deprivation index (NSI)= socioeconomic conditions (think neighborhood = socioeconomic disparities)

• Walkability scores = built environment

• Mapping = visualize patterns geographically

What did Clarke/Sinkewicz‘s video “Neighborhoods as a Social Determinant of Health show about structural inequities and power?

Neighborhoods are not naturally different, as differences are created by structural forces

• Redlining

• Segregation

• Disinvestment

• Policy choices

Neighborhood health differences does not equal to individual choices or natural variation

How does Clarke/Sinkewicz‘s video “Neighborhoods as a Social Determinant of Health relate to Harlem CHA?

Each assigned health topic in their chosen Harlem neighborhood has its own neighborhood-level determinants

How can both JAMA studies (IM and Patient Perspectives) be Critical/Transformative?

• Explicitly name structural racism

• advocate for systemic change

• center marginalized voices

Neighborhoods as social determinants of health

The concept that the physical, social, service, and policy environments of the places where people live, work, and gather systematically shape health outcomes and create or reduce health inequities

Spatial scale (in neighborhood research)

The level of geographic aggregation (e.g., county, ZIP code, census tract, block group) at which data are collected and analyzed

• the choice of scale affects what patterns are visible and whose disparities are counted

• Zip Code = the most accurate and specific data on who is at the highest risk

Neighborhood pathways to health

Neighborhood conditions influence health

• physical environment (housing, air quality, walkability)

• service environment (access to care, food, transportation)

• Social environment (cohesion, safety, networks)

• Policy environment (zoning, investment, policing)

Structural inequities in neighborhoods

• Systematic differences in neighborhood conditions (e.g., disinvestment, segregation, lack of services)

• Produced by historical and ongoing policies, racism, and power imbalances

• Not by individual choices or "natural" variation

Epistemological deconstruction

Process of analyzing a research study

• identify its underlying assumptions about what counts as valid knowledge

• whose perspectives are centered

• how those choices shape the questions asked, methods used, and conclusions drawn

Why does the CHA use both qualitative and quantitative approaches?

Understand not just the magnitude of health problems but also the contexts, meanings, and mechanisms that shape pop health

Quality of Qualitative Data

Quality depends on the data collection instrument, the skill of the data collector, the rigor of the analyst, and the clarity of the presenter/writer

Reasoning Approaches to Quantitative Research

Quantitative research typically uses deductive reasoning (general theory, specific data, testing theory)

Reasoning Approaches to Qualitative Research

Qualitative research typically uses inductive reasoning (specific observations, general patterns, generating theory)

Rigor Criteria for Quantitative Research

Evaluated on

• internal validity, external validity, reliability, and objectivity

• Is it accurate, generalizable, repeatable, and unbiased?

Rigor Criteria for Qualitative Research

Evaluated on

• credibility ("truth value"), transferability (applicability), trustworthiness (reliability), and confirmability (neutrality)

• Is there a sense of all of these in the data?

Pragmatic qualitative approaches for CHA

Pragmatic qualitative methods focused on practical problem-solving

• participant observation (systematic watching of community settings)

• in-depth interviewing (key informant interviews with service providers)

• focus groups (structured group discussions with community members)

• Practical questions aimed at understanding real world issues programs problems (results in problem solving and action)

Mixed Methods Research in CHA

Research combining quantitative data with qualitative data to build a comprehensive understanding of community health that neither method alone could provide

Deductive Reasoning

• Deductive → Digits → Quantitative

• Moving from general theory/hypotheses to specific observations and data

• Typically used to test existing theories or hypotheses using structured, predetermined measures

Inductive Reasoning

• Inductive → Ideas → Qualitative

• Moving from specific observations and data to broader patterns, themes, and theories

• Typically used to generate new understanding or theory from real-world observations

Participant observation

• A qualitative method involving sustained, systematic observation of people in naturalistic settings as they go about routine activities

• Observer documents what happens, who is present, how spaces are used, and what patterns emerge

In-depth interviewing (for CHA)

A qualitative method

• Open-ended, relatively unstructured questioning to explore participants' thoughts, feelings, experiences, and perspectives in detail

• Applied through Key Informant Interviews with service providers and expert

Focus groups (for CHA)

• Qualitative method involving facilitated group discussions among participants (typically 6-10 people) on specific topics of interest

• Allows exploration of shared experiences, differing perspectives, and community norms

Community asset mapping

• Structured process to identify, describe, and geographically locate community resources and strengths (services, organizations, places, networks) relevant to health

• Shifts focus from deficits to existing capacity

Asset-based approach

A framework that recognizes and builds on existing community strengths, resources, capacities, and skills rather than focusing primarily on problems, needs, or deficits

• identifies what communities have (not just what they lack) and builds on those foundations

Disease pathway (for asset mapping)

The sequence of stages from risk and exposure through prevention, screening, diagnosis, treatment, and long-term management

• Used to identify which types of community assets are relevant at each stage

• risk/exposure → prevention → screening/early detection → diagnosis → treatment → long-term management

Systematic observation (social observation)

Purposeful, structured watching and documenting of community settings, people, interactions, and patterns using predetermined observation categories or checklists

• Transforms impressions into analyzable field notes

Asset Inventory

A structured list or table documenting each identified community resource with key details

• Name, location, type, services offered, access information (hours, cost, languages, transportation)

• Direct observations from fieldwork

Interpretive statement (in qualitative CHA)

An analytical statement that

1. Synthesizes observations into meaningful insights

2. connects what was observed (description) to what it suggests about health access or equity (interpretation)

3. Why it matters for community health and disparities (significance)

Three part structure of interpretive statements

1. Observation: what did you see? (descriptive, grounded in specific field notes or asset table data)

2. Interpretation: what might this mean? (analytical, connecting observations to patterns or mechanisms)

3. Significance – why does this matter for community health and health equity? (implications for disparities, access, or intervention)

Clusters and gaps (in asset mapping)

Spatial patterns showing where health-related services and resources are concentrated versus areas with few or no relevant assets

Where are clusters and gaps located?

• Clusters: often near major transit or commercial corridors

• Gaps: often in more isolated or disinvested areas

Geographic barriers (to health access)

• Physical distance

• Lack of proximity to public transportation

• Need for multiple bus/subway transfers

• Long travel times

• Terrain/infrastructure challenges that make reaching services difficult/impossible for some residents

Structural/institutional barriers

Policies, rules, or organizational practices that exclude or deter certain populations

• limited hours (only weekday daytime, conflicting with work)

• insurance requirements (excluding Medicaid or uninsured)

• documentation requirements (excluding undocumented immigrants)

• appointment-only systems (no walk-in access for urgent needs)

Social/Cultural Barriers

Stigma associated with certain health conditions or services

• Lack of culturally responsive or linguistically appropriate care

• Historical mistrust of medical institutions (especially among communities harmed by medical racism or exploitation)

• Exclusions based on gender, age, sexual orientation, or identity

Information/awareness barriers

• Lack of knowledge that services exist

• Poor or misleading signage

• Limited community outreach

• Misconceptions about cost or eligibility

• Failure to advertise services in languages or media channels used by target populations

Equity implications (in CHA analysis)

The consequences of observed patterns (asset distribution, access barriers, service design) for health disparities

• which populations are advantaged or disadvantaged

• How barriers compound for people with multiple marginalized identities (intersectionality)

• How these patterns perpetuate or reduce inequities

Positionality (in qualitative observation)

1. Awareness of the researcher's own social location, identities, privileges, and relationship to the community being studied

2. Recognizing how being an outside observer (medical student, not Harlem resident, not affected by the health condition) shapes what can be seen, what is missed, and whose perspectives are centered or invisible

Observation method limits

Recognition that systematic observation can document visible features (what services exist, hours, physical environment, who is present)

Limitations

• cannot reveal experiences, meanings, motivations, insider perspectives, or community priorities without talking to people

Solution

• Need for interviews and participatory methods

Specificity vs. Vagueness

• Strong interpretive statements use concrete details (ex. A resident at 150th & Amsterdam without a car would need two bus transfers, 35-40 minutes each way, making weekly appointments nearly impossible for someone working full-time)

• Vague claims: Transportation is a barrier

What are asset tables used to analyze?

Identify patterns in who can actually access services and what systemic barriers exist

What do interpretive statements link what was observed in Harlem fieldwork to broader concepts?

1. Structural inequities (redlining, disinvestment, policy)

2. Social determinants (income, work schedules, insurance status, language, immigration status)

3. Intersectionality (compounding barriers for people with multiple marginalized identities)

Main purpose of Interpretive Statements

Raise unanswered questions that can be explored through KII, FGD, or surveys to identify what observation alone cannot reveal

Key Informant Interview (KII)

A qualitative research method involving in-depth, semi-structured interviews with individuals who have specialized knowledge, expertise, or unique perspectives on a community health issue

• Key informants are selected purposively because they can provide insights that general population surveys or observation cannot reveal

KII Purpose

1. Answer questions that observation alone cannot reveal

• Why services are organized the way they are

• How decisions get made

• What residents experience

• What barriers exist that you can't see from the outside

2. Complements Asset mapping (What exists → mechanics + meaning)

3 Categories of key informants

1. Organizational Leaders (introduction, informed consent, rapport-building)

2. Specialized Experts (3-4 broad topic areas aligned with CHA questions)

3. Community “eyes and ears” (8-10 core questions that allow informants to share in their own words)

Reflexivity

Awareness of how the interviewer's own identities, assumptions, privileges, and relationship to the community shape what gets asked, what gets heard, and what gets missed

• Being reflexive makes you a better, more ethical researcher

Researcher positionality

Recognizing

• Discomfort (some feel safer observing while others prefer direct conversation)

• Power dynamics (medical students interviewing community members or service providers)

• Assumptions about "the problem" or solutions

What is a semi-structured interview guide?

• A flexible interview framework with predetermined domains and core open-ended questions

• Allows the interviewer to adapt question order, add probes, and follow unexpected but relevant tangents

• Balances consistency (covering key topics across all interviews) with flexibility (responding to what each informant uniquely knows)

Interview domains

• Broad topic areas or themes that organize an interview guide

• Typically 3-4 per guide

• Each domain corresponds to a cluster of related CHA questions and contains 2-3 core questions

Examples for CHA:

• Barriers to accessing diabetes care

• Community perceptions of local clinics

• Gaps in mental health services

Purposive sampling (for KIIs)

• Intentional, non-random selection of interview participants based on their relevance to the research question

• Informants are chosen because they have specific expertise, experience, or perspective that can answer CHA questions

  • Clinic director knows why services are structured a certain way

Information-rich informants

Individuals who can provide deep, detailed, insightful information about the topic of interest because of their position, experience, or knowledge

• Ex. A diabetes program coordinator who knows referral pathways

Open-ended questions

Questions that cannot be answered with a simple "yes" or "no" and invite detailed responses in the informant's own words

• Ex. "How do residents in this neighborhood typically access mental health services?"

Probes (in interviewing)

Neutral follow ups

1. Follow-up prompts used to encourage informants to elaborate, clarify, or provide examples

• Ex. "Can you tell me more about that?" "What do you mean by [specific term]?

2. Probes deepen understanding without leading the informant

Semi-structured interview Format

1. Opening (introduction, informed consent, rapport-building)

2. Interview domains (3-4 broad topic areas aligned with CHA questions)

3. Open-ended questions (8-10 core questions that allow informants to share in their own words)

4. Probes (follow-up prompts to deepen responses)

5. Closing (thanks, next steps, opportunity for informant to add anything missed)

Focus Group Discussion (FGD)

• A qualitative research method involving a structured group conversation (typically 6-8 participants) led by a trained facilitator

• Explore shared experiences, beliefs, norms, and perceptions about a specific health topic

• Data are generated through group interaction (how people respond to each other), not just individual answers

• Used to understand community perspectives (shared norms, peer influence, points of agreement/disagreement) that observation and individual interviews cannot reveal

FGD vs. KII

FGD

• Community members

• Group discussion

• Purpose: Norms, stigma, social dynamics

• Hard to coordinate

KII

• Experts/providers

• One on One

• Purpose: Systems, policies, and workflows

• Easier to schedule

FGD Moderator

Leads discussion, stays neutral, manages dynamics, probes for depth

FGD Co-Facilitator/Note-taker

Captures quotes, monitors time, and supports moderator

FGD Guide Structure (60-90 min)

1. Opening: Rapport, easy for all to answer (5 min)

2. Transition: move toward the topic, assess general awareness (5-10 min)

3. Core questions: heart of the discussion → explore barriers, access, norms, gaps, explicitly linked to mapped assets and CHA focus (30-40 min)

4. Closing question: Final thoughts/action oriented (10 min)

5 Key Questions to Planning Decisions

1. WHO: Lived experience of topic (homogenous vs. heterogenous)

2. HOW MANY: 2-4 FGDs per stratum to reach saturation

3. WHERE/WHEN: accessible, neutral, safe location (community center, library, clinic conference room), timing that works for participants (evenings, weekends)

4. ROLES: moderator (leads discussion), co-facilitator/note-taker (captures quotes, assists), optional observer (tracks dynamics)

5. LOGISTICS: refreshments, childcare, transportation assistance, incentive/compensation, translation services if needed

Homogenous Group Composition

• Focus group participants who are similar on key characteristics

• Create safer space for discussing sensitive topics, easier facilitation, and can reveal cultural/social barriers that diverse groups might miss

• Often used when exploring stigmatized health issues or when power imbalances could suppress disclosure in mixed groups

Heterogenous Group Composition

• Focus group participants who are diverse in key characteristics

• Generate a broader range of perspectives, and can reveal points of disagreement/debate

• Harder to facilitate

• Power imbalances exist → may lead some participants to withhold views

Saturation (theme saturation in FGD)

• Point at which conducting additional focus groups yields no new themes or insights (ideas begin to repeat)

• Researchers plan multiple FGDs (typically 2-4 per topic/stratum) and stop when saturation is reached

• 2-3 FGDs → 80% of key themes

• 3-6 FGDs → 90%

• Saturation ensures findings are not based on 1 FGD

Challenges to FGD + Solution

One person dominates

• Let’s hear from others

Silence

• Wait 5-10 sec, rephrase

Off-Topic Tangent

• Acknowledge, redirect

DIsagreement

• It’s okay to have different views; both are important

Ground rules (in FGD)

Norms established at the start of a focus group by the moderator to create a safe, respectful space

1. Speak one at a time so everyone can be heard

2. No right or wrong answers (we want your honest experiences)

3. Skip any question or pass if uncomfortable

4. What is shared here stays here (though confidentiality cannot be guaranteed)

5. Respect different opinions

Confidentiality limits (in FGD ethics)

• Cannot guarantee confidentiality because multiple participants hear each other's stories and disclosures

• Researchers establish a ground rule ('What's shared here stays here') but must acknowledge they cannot control it

• Affects what participants feel safe disclosing and requires careful attention to composition and ethical consent processes