Causality and Causal Reasoning Validity and threats to validity Examples of causal studies

Snow on Cholera London Cholera epidemic of August 1854 It was assumed that cholera was airborne, but Snow argued that it was in water Cholera was unevenly distributed, with some anomalies

What Do We Mean by Causality? In the strictest case, when A causes B we mean that: A precedes B No B without A If A exists then B always exists But in science we allow for contributions to statistical changes in rates. The difference between prediction and causality is usually specifying mechanism.

Analyzing and Mapping Research Articles Read the article to identify key components: Hypothesis (sometimes this needs to be constructed from the text) Predictors (the hypothesized cause): High-level construct Variable that is measured Actual measures or metrics Mediator/Mechanisms/Intervening variables (what are the actual causes or necessary steps) Outcomes Constructs, variables, measures Controls (what is held constant to reduce alternate explanations) Mediators (what amplifies or reduces the effect) Plausible alternative hypotheses (that are correlated with predictor)—this should reflect a knowledge of the world and literature Statistical methods Generalizability questions Map the articles using the template

Effects of nature window view on pain following surgery (Ulrich, 1984) Number of Pain Drug Doses (days 2-5 after surgery) Analgesic NATURE WALL Strength patients patients Strong 0.96 2.48 Moderate 1.74 3.65 Weak 5.39 2.57

Generalizability questions Alternative explanations View Through a Window Hypothesis: View of nature improves recovery from surgery Ulrich, R.(1984). View through a window may influence recovery. Science, 224(4647), 224-225. Outcomes <Construct> Recovery from surgery <Variables> Variables: Length of stay Analgesic use Anxiety medications Patient sleep disturbance Patient anxiety Minor complications (Patient cardio arousal) (Patient wound healing) <Measures> Day of surgery to day of discharge Weighted score of minor complications Number of positive or negative notes Average number of analgesic doses per patient by strength level for days 2-5, 6-7 Predictor Variables <Construct> restorative effect of natural view <Variable> View of nature <Measure> Window view with trees v Window view of walls Mediators/Mechanism Stress Control variables Controls Matching on 23 pairs for sex, age, smoker/non-smoker, obesity, previous hospitalization, year of surgery, floor level, wall color, physician (7 pairs) Surgery type: cholecystectomy (gall bladder) Summer season (1 May-20 October) Statistical methods Multivariate two-sample Hotelling test for analgesic dosages, antianxiety drugs Chi-square for frequency of dosages Generalizability questions Does this apply to other patients, diseases, treatment cultures, care processes? Partly addressed by citing other studies. Alternative explanations Chance occurrence Exposure to natural light

Generalizability questions Alternative explanations When the World Is Closing In Hypothesis: View of nature improves recovery from surgery Okken, V. S., van Rompay, T. J. L., & Pruyn, A. Th. H. (2013). When the world is closing in: Effects of perceived room brightness and communicated threat during patient-physician interaction. Health Environments Research & Design Journal, 7(1), 37–53. Outcomes <Construct> Recovery from surgery <Variables> Variables: Affective experience Intended self-disclosure Liking (of physician) <Measures> Self report scales Mediators/Mechanism Spaciousness of environment Predictor Variables <Construct> Perceived room Brightness Communicated threat <Variable> Brightness of photograph of simulated scene Seriousness of discussion <Measure> Light v dark photograph Manipulated script Control variables People were their own controls within a threat condition Moderators Brightness Threat Statistical methods ANOVA Generalizability questions Does this apply real world conditions? Alternative explanations Chance occurrence

Implementation variable (intermediate steps) Name of the article Causal hypothesis Reference APA 6 style Use dotted lines and italics if the article doesn't discuss Predictors/independent variables <Construct> High level idea from the research or professional literature <Variable> What is being measured? <Measure> How is it actually measured (what metrics, scales, etc.)? Outcomes/Dependent Variable <Construct> <Variables> <Measures> Mediators/Mechanism/Intervening variables Implementation variable (intermediate steps) Control variables Controls What is held constant in the population or settings studied to reduce likelihood of other causes? Moderators/”Bridging” variables What amplifies or reduces the effect such as demographics, vulnerability of patients, etc? Add key assumptions if you can Alternative explanations What plausible alternative explanations might explain this effect (and is correlated with the predictor)? Should come from the literature Statistical methods e.g., Multivariate two-sample Hotelling test for analgesic dosages, antianxiety drugs Chi-square for frequency of dosages Latent/unintended consequences What happened outside of the hypotheses that was unexpected or has design implications? Generalizability questions Do results reasonably apply to other settings, patients, diseases, treatment cultures, care processes?