Actionable communications and interventions to change HABITS Thank you. It’s good to see old friends, new friends. Dolores Albarracín University of Illinois at Urbana Champaign

Actionability Action calls (behavior is recommended) Actionable as behavior relevant (helps implement) Actionable as number of recommendations Actionable as action/inaction (d0 vs. not do)

Actionability Action calls Actionable as behavior relevant Actionable as number of recommendations Actionable as action/inaction

Action Calls Change we can believe in. (Barak Obama) Let's make America great again. (Donald Trump)

Action Messages on Twitter and HIV Prevalence (Ireland, Action Messages on Twitter and HIV Prevalence (Ireland,.., & Albarracin, 2016, Health Psychology) 1 billion tweets November 2008-January 2010 (random 10%) Action word dictionaries (e.g., act, fly, gaming, gym, movement, trip): Measure of county level action language Hypothesis: Association with county-level HIV prevalence

Action Messages as Action Calls and HIV Prevalence (Ireland, …& Albarracin, 2016)

Actionable Contents Action calls: Yes Actionable as behavior relevant Actionable as number of recommendations Actionable as action/inaction

Meta-Analysis of Condom Use Interventions (Albarracin et al., 2005) 224 groups or statistically-independent conditions Total N = 82,798 participants Average N of participants per group = 257 The search and selection led to an impressive universe of READ

Albarracin et al. (2005) North Dakota Idaho South Dakota Nebraska Utah Colorado Idaho Kansas Nebraska North Dakota South Dakota Utah Albarracin et al. (2005)

Active vs. Passive Interventions in HIV Prevention Behavioral skills training Client- centered counseling

Meta-Analysis of Condom Use Interventions (Albarracin et al., 2005) In this slide, I subtracted the average d when a given strategy was not present (e.g., the intervention did not present information) from when a given strategy was present. Thus, positive numbers indicate improvements in condom use as a function of the type of strategy. As can be seen, 2 strategies had no overall effect (info and fear), 1 decreased condom use (normative arguments), and the rest (attitudinal arguments, behavior-skills arguments, and condom provision) increased condom use.

Meta-Analyses of Multi-Behavior Interventions Lifestyle: Smoking, Diet, & Physical Activity (Wilson et al., 2014) HIV: Condom use, medication adherence, testing (Sunderrajan et al., 2017) Drugs/Alcohol: Prevention and treatment (Dai et al., 2017)

Multi-Behavior Change (Wilson, Durantini, Sanchez, & Albarracín, 2017, Health Psychology Review) At least 2 domains (smoking and exercise) Obtained d (post vs pre) to describe behavioral changes as well as changes in symptoms and biological measures Lifestyle (k = 270), HIV (k =250), Drugs/Alcohol (k = 142) Active vs. passive

Effect of Active Recommendations Lifestyle: Active = 0.20 vs. Passive = 0.33; Rx QB1 ns HIV: Active = 0.24 vs. Passive = 0.29; Rx QB1 ns Drugs/Alcohol: Active = 0.30 vs. Passive = 0.24; Rx QB1 ns

Actionability Action calls Actionable as behavior relevant: Yes but not in multi-goal cases. Questions ! Actionable as number of recommendations Actionable as action/inaction

Questions Puzzle: Too many recommendations? Too conflicting? Too many actions (initiation or increase of demanding behavior) vs. inactions (relaxation or decreasing)?

Actionable Contents Action calls Actionable as behavior relevant Actionable as number of recommendations Actionable as action/inaction

Number of Recommendations (Wilson, …, & Albarracin, ) The more the merrier? Less is more? Happy medium? Test: Lifestyle meta-analysis; Count of goals or recommendations

Lifestyle, Effects of Number of Recommendations on Behavioral & Clinical Change (d)

Across Domains, Effects of Number of Recommendations on Average Change (d)

Principle of Relation When the recommended changes are related , more is not disruptive! Alcohol   Drugs Smoking   Exercise, Diet ? Exercise Testing, condom use, adherence to ARV, alcohol/drugs (either or)

Actionable Contents Action calls Actionable as behavior relevant: Yes but… Actionable as number of recommendations: More of related (drugs/alcohol) but fewer unrelated (HIV) Actionable as action/inaction: What mix and which one is easier? Actionable Contents

Action/Inaction Direction of Recommendations (Wilson, Durantini, Sanchez, & Albarracín, 2017) Meta-analysis of lifestyle Begin aerobic exercise program (action) Rest between strength training sessions (inaction) Eat fruits and vegetables (action) Decrease fat intake (inaction) Quit smoking (inaction) Examining potential for change Assigned between 2 and 20 behavior instructions: Think positive thoughts as much as possible, exercise, learn to relax, quit smoking, don’t think negative thoughts at all 75% inactions, 50/50, 75% actions Measured recognition of behavior recommendations and compliance intentions

Principle of Relation Mix When the recommended changes are homogeneous, change is easier! Corollary: Homogeneous action/inaction direction seems better

Behavioral and Clinical Change (Wilson, Durantini, Sanchez, & Albarracín, 2017, Health Psychology Review) OR Random effects QB4 = 36.42, p < .001

Actionable Contents Action calls Actionable as behavior relevant: Yes but… Actionable as number of recommendations: More of related (drugs/alcohol) but fewer unrelated (HIV) Actionable as action/inaction: What mix? Homogeneous mix Actionable Contents

Behavioral and Clinical Change (Wilson, Durantini, Sanchez, & Albarracín, 2017, Health Psychology Review) OR Random effects QB4 = 36.42, p < .001

Experimental Work on Action vs. Inaction Is action overall more disruptive than inaction? Hypothesis: Yes; chronic action focus

Multiple Behavior GNG (Albarracin et al., 2017)   Mapping rules Go targets and # of trials No-go targets and # of trials High action-proportion (Action predominance) Health-12 Doctor-12 Energy-12 Green-12 Low action proportion (Inaction predominance) Health-12 Doctor-12 Energy-12 Multiple Behavior GNG (Albarracin et al., 2017)

Trials; G to Health, Doctor, Energy Action Predominance Health 👆 Doctor Energy Green Inaction Predominance Health 👆 Doctor Energy Green

Multiple Behavior GNG Mapping rules Go targets and # of trials   Mapping rules Go targets and # of trials No-go targets and # of trials High action-proportion = Lower Accuracy Health Doctor Energy Green Low action proportion = Higher Accuracy Health Doctor Energy Multiple Behavior GNG

Experiment 1 (Albarracin et al., 2017)

Experiment 2 (Albarracin et al., 2017)

Experiment 4: Introducing an Action Focus (Albarracin et al., 2017)

Actionable Contents Action calls Actionable as behavior relevant: Yes but… Actionable as number of recommendations: More of related (drugs/alcohol) but fewer unrelated (HIV) Actionable as action/inaction: What mix and which one is easier? Homogeneous mix and inactions over actions; inaction focus Actionable Contents

But Chronic focus on action Higher value for action than inaction (Sunderrajan & Albarracin, 2017) Pressing a button seen as better and more intentional than not pressing a button (Sunderrajan & Albarracin, 2017) Removing idealization of action may be part of the solution (Sunderrajan & Albarracin, 2017)

Health and Social Media Group Social Action Lab Health and Social Media Group National Institutes of Health And these are the members…Some of the people are at other institutions, NORC, Hopkins, Emory, and there are different disciplines: psychology, computer science, linguistics