0.1 Results

0.2 Within-person

  • Individuals in the mindfulness condition were significantly more likely to respond to alcohol prompts mindfully on active weeks, when they were prompted to respond mindfully, vs. on inactive weeks, when they were prompted to respond naturally (B = 18.06, CI95[13.14-22.99], p<.001

  • active week (M = 59.6; SD = 17.7) vs. inactive week(M = 49.5; SD =21.7).

0.2.1 Prep within-person dataframe

mindful = read.csv("~/Documents/Box Sync/CurrentProjects_Penn/MURI/Papers/EMA_intervention_effects/Study1/Study1modeling.csv", stringsAsFactors = FALSE) %>%
filter(Condition == 'mindful') #subset to only mindfulness ppt

#set inactve week as reference week
mindful$active_week <-as.factor(mindful$active_week)
mindful$active_week <- relevel(mindful$active_week,"control")

0.2.2 Plot within-person analysis

mindful %>%
  ggplot(aes(active_week, Alc_React_Mindful, color = active_week)) +
  #geom_jitter(alpha = .1, size = 1, width = .1) +
  stat_summary(fun.data = "mean_cl_boot", size = 1) +
  scale_color_manual(values = palette) +
  labs(x = "study week", y = "REACT MINDFUL to alcohol \n") +
  scale_x_discrete(labels=c("baseline", "mindful attention")) +
  plot_aes +
  theme(legend.position = "none")

0.2.3 Decriptives

descript_mindful = mindful %>% 
  group_by(SHINEID) %>% #grouping by SHINEID
  summarise(mindful_on_week = mean(Alc_React_Mindful[active_week %in% c("active")], na.rm=T),
            mindful_off_week = mean(Alc_React_Mindful[active_week %in% c("control")], na.rm=T)) %>% 
  ungroup()

table1::table1(~mindful_on_week + mindful_off_week, data = descript_mindful)
Overall
(N=37)
mindful_on_week
Mean (SD) 59.6 (17.7)
Median [Min, Max] 60.6 [1.00, 94.9]
Missing 1 (2.7%)
mindful_off_week
Mean (SD) 49.5 (21.7)
Median [Min, Max] 49.2 [2.05, 91.0]
Missing 3 (8.1%)

0.2.4 Model output

within = lmer(Alc_React_Mindful ~ active_week + (1|SHINEID), data = mindful)
tab_model(within)
  Alc React Mindful
Predictors Estimates CI p
(Intercept) 45.59 39.80 – 51.38 <0.001
active week [active] 18.06 13.12 – 23.00 <0.001
Random Effects
σ2 550.94
Ï„00 SHINEID 187.18
ICC 0.25
N SHINEID 37
Observations 382
Marginal R2 / Conditional R2 0.100 / 0.328

0.3 Between-person

  • On average, individuals in the mindfulness condition responded to alcohol prompts naturally significantly less frequently relative to individuals in the baseline condition, X2(2,N = 74) = -6.8, p < .01. (DOUBLE CHECK stats please)

  • baseline condition (M = 89.6; SD = 10.6) vs. mindful condition(M = 58.5; SD =22.2).

0.3.1 Prep between-person dataframe

#Load end of survey variables
end_vs <- read.csv("~/Documents/Box Sync/CurrentProjects_Penn/MURI/Papers/EMA_intervention_effects/Study1/SHINE_EMA_May19_2020.csv", stringsAsFactors = FALSE)
#remove 1ppt due to technical app difficulties
end_vs <- end_vs[which(end_vs$SHINEID!="muri035"),]
end_vs$shineid <- tolower(end_vs$SHINEID)

cond1 = end_vs %>%
  group_by(SHINEID)%>% #subset unique
  dplyr::mutate(mean_mindful = mean(EndQMindfu, na.rm =T),
                mean_natural = mean(EndQNatura, na.rm = T)) %>%
  filter(Condition != 'perspective') %>%
dplyr::select(Condition, SHINEID, mean_mindful,mean_natural) %>% distinct(SHINEID,.keep_all = TRUE) #get condition info

0.3.2 Plot between-person analysis

cond1 %>%
  ggplot(aes(Condition, mean_natural, color = Condition)) +
  #geom_jitter(alpha = .1, size = 1, width = .1) +
  stat_summary(fun.data = "mean_cl_boot", size = 1) +
  scale_color_manual(values = palette) +
  labs(x = "Condition", y = "REACT NATURALLY to alcohol \n") +
  scale_x_discrete(labels=c("baseline group", "mindful attention \n group")) +
  plot_aes +
  theme(legend.position = "none")

0.3.3 Descriptives

table1::table1(~mean_natural + mean_mindful| Condition, data = cond1)
control
(N=37)		 mindful
(N=37)		 Overall
(N=74)
mean_natural
Mean (SD) 89.6 (10.6) 58.5 (22.2) 74.1 (23.3)
Median [Min, Max] 89.0 [59.0, 100] 61.0 [10.0, 100] 80.5 [10.0, 100]
Missing 8 (21.6%) 8 (21.6%) 16 (21.6%)
mean_mindful
Mean (SD) 61.1 (21.8) 56.6 (22.3) 58.8 (22.0)
Median [Min, Max] 66.0 [27.0, 100] 60.0 [11.0, 86.0] 62.0 [11.0, 100]
Missing 8 (21.6%) 8 (21.6%) 16 (21.6%)

0.3.4 Output

t.test(cond1$mean_natural[cond1$Condition == 'mindful'],
       cond1$mean_natural[cond1$Condition == 'control'], paired = FALSE)
## 
##  Welch Two Sample t-test
## 
## data:  cond1$mean_natural[cond1$Condition == "mindful"] and cond1$mean_natural[cond1$Condition == "control"]
## t = -6.814, df = 40.217, p-value = 3.318e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -40.37202 -21.90384
## sample estimates:
## mean of x mean of y 
##  58.48276  89.62069