75 mood items from the Motivational State Questionnaire for 3032 unique participants
Emotions may be described either as discrete emotions or in dimensional terms. The Motivational State Questionnaire (MSQ) was developed to study emotions in laboratory and field settings. The data can be well described in terms of a two dimensional solution of energy vs tiredness and tension versus calmness. Alternatively, this space can be organized by the two dimensions of Positive Affect and Negative Affect. Additional items include what time of day the data were collected and a few personality questionnaire scores. 3032 unique participants took the MSQ at least once, 2753 at least twice, 446 three times, and 181 four times. The 3032 participants also took the sai
state anxiety inventory at the same time. Some studies manipulated arousal by caffeine, others manipulations included affect inducing movies.
data("msqR")
A data frame with 6411 observations on the following 88 variables.
active
a numeric vector
afraid
a numeric vector
alert
a numeric vector
alone
a numeric vector
angry
a numeric vector
aroused
a numeric vector
ashamed
a numeric vector
astonished
a numeric vector
at.ease
a numeric vector
at.rest
a numeric vector
attentive
a numeric vector
blue
a numeric vector
bored
a numeric vector
calm
a numeric vector
clutched.up
a numeric vector
confident
a numeric vector
content
a numeric vector
delighted
a numeric vector
depressed
a numeric vector
determined
a numeric vector
distressed
a numeric vector
drowsy
a numeric vector
dull
a numeric vector
elated
a numeric vector
energetic
a numeric vector
enthusiastic
a numeric vector
excited
a numeric vector
fearful
a numeric vector
frustrated
a numeric vector
full.of.pep
a numeric vector
gloomy
a numeric vector
grouchy
a numeric vector
guilty
a numeric vector
happy
a numeric vector
hostile
a numeric vector
inspired
a numeric vector
intense
a numeric vector
interested
a numeric vector
irritable
a numeric vector
jittery
a numeric vector
lively
a numeric vector
lonely
a numeric vector
nervous
a numeric vector
placid
a numeric vector
pleased
a numeric vector
proud
a numeric vector
quiescent
a numeric vector
quiet
a numeric vector
relaxed
a numeric vector
sad
a numeric vector
satisfied
a numeric vector
scared
a numeric vector
serene
a numeric vector
sleepy
a numeric vector
sluggish
a numeric vector
sociable
a numeric vector
sorry
a numeric vector
still
a numeric vector
strong
a numeric vector
surprised
a numeric vector
tense
a numeric vector
tired
a numeric vector
unhappy
a numeric vector
upset
a numeric vector
vigorous
a numeric vector
wakeful
a numeric vector
warmhearted
a numeric vector
wide.awake
a numeric vector
anxious
a numeric vector
cheerful
a numeric vector
idle
a numeric vector
inactive
a numeric vector
tranquil
a numeric vector
kindly
a numeric vector
scornful
a numeric vector
Extraversion
Extraversion from the EPI
Neuroticism
Neuroticism from the EPI
Lie
Lie from the EPI
Sociability
Sociability from the EPI
Impulsivity
Impulsivity from the EPI
gender
1= male, 2 = female (coded on presumed x chromosome). Slowly being added to the data set.
TOD
Time of day that the study was run
drug
1 if given placebo, 2 if given caffeine
film
1-4 if given a film: 1=Frontline, 2= Halloween, 3=Serengeti, 4 = Parenthood
time
Measurement occasion (1 and 2 are same session, 3 and 4 are the same, but a later session)
id
a numeric vector
form
msq versus msqR
study
a character vector of the experiment name
The Motivational States Questionnaire (MSQ) is composed of 75 items, which represent the full affective space (Revelle & Anderson, 1998). The MSQ consists of 20 items taken from the Activation-Deactivation Adjective Check List (Thayer, 1986), 18 from the Positive and Negative Affect Schedule (PANAS, Watson, Clark, & Tellegen, 1988) along with the affective circumplex items used by Larsen and Diener (1992). The response format was a four-point scale that corresponds to Russell and Carroll's (1999) "ambiguous–likely-unipolar format" and that asks the respondents to indicate their current standing (“at this moment") with the following rating scale:
0—————-1—————-2—————-3
Not at all A little Moderately Very much
The original version of the MSQ included 70 items. Intermediate analyses (done with 1840 subjects) demonstrated a concentration of items in some sections of the two dimensional space, and a paucity of items in others. To begin correcting this, 3 items from redundantly measured sections (alone, kindly, scornful) were removed, and 5 new ones (anxious, cheerful, idle, inactive, and tranquil) were added. Thus, the correlation matrix is missing the correlations between items anxious, cheerful, idle, inactive, and tranquil with alone, kindly, and scornful.
2605 individuals took Form 1 version, 3806 the Form 2 version. 3032 people (1218 form 1, 1814 form 2) took the MSQ at least once. 2086 at least twice, 1112 three times, and 181 four times.
To see the relative frequencies by time and form, see the first example.
Procedure. The data were collected over nine years in the Personality, Motivation and Cognition laboratory at Northwestern, as part of a series of studies examining the effects of personality and situational factors on motivational state and subsequent cognitive performance. In each of 38 studies, prior to any manipulation of motivational state, participants signed a consent form and in some studies, consumed 0 or 4mg/kg of caffeine. In caffeine studies, they waited 30 minutes and then filled out the MSQ. (Normally, the procedures of the individual studies are irrelevant to this data set and could not affect the responses to the MSQ at time 1, since this instrument was completed before any further instructions or tasks. However, caffeine does have an effect.) The MSQ post test following a movie manipulation) is available in affect
as well as here.
The XRAY study crossed four movie conditions with caffeine. The first MSQ measures are showing the effects of the movies and caffeine, but after an additional 30 minutes, the second MSQ seems to mainly show the caffeine effects. The movies were 9 minute clips from 1) a BBC documentary on British troops arriving at the Bergen-Belsen concentration camp (sad); 2) an early scene from Halloween in which the heroine runs around shutting doors and windows (terror); 3) a documentary about lions on the Serengeti plain, and 4) the "birthday party" scene from Parenthood.
The FLAT study measured affect before, immediately after, and then after 30 minutes following a movie manipulation. See the affect
data set.
To see which studies used which conditions, see the second and third examples.
The EA and TA scales are from Thayer, the PA and NA scales are from Watson et al. (1988). Scales and items:
Energetic Arousal: active, energetic, vigorous, wakeful, wide.awake, full.of.pep, lively, -sleepy, -tired, - drowsy (ADACL)
Tense Arousal: Intense, Jittery, fearful, tense, clutched up, -quiet, -still, - placid, - calm, -at rest (ADACL)
Positive Affect: active, alert, attentive, determined, enthusiastic, excited, inspired, interested, proud, strong (PANAS)
Negative Affect: afraid, ashamed, distressed, guilty, hostile, irritable , jittery, nervous, scared, upset (PANAS)
The PA and NA scales can in turn can be thought of as having subscales: (See the PANAS-X) Fear: afraid, scared, nervous, jittery (not included frightened, shaky) Hostility: angry, hostile, irritable, (not included: scornful, disgusted, loathing guilt: ashamed, guilty, (not included: blameworthy, angry at self, disgusted with self, dissatisfied with self) sadness: alone, blue, lonely, sad, (not included: downhearted) joviality: cheerful, delighted, energetic, enthusiastic, excited, happy, lively, (not included: joyful) self-assurance: proud, strong, confident, (not included: bold, daring, fearless ) attentiveness: alert, attentive, determined (not included: concentrating)
The next set of circumplex scales were taken from Larsen and Diener (1992). High activation: active, aroused, surprised, intense, astonished Activated PA: elated, excited, enthusiastic, lively Unactivated NA : calm, serene, relaxed, at rest, content, at ease PA: happy, warmhearted, pleased, cheerful, delighted Low Activation: quiet, inactive, idle, still, tranquil Unactivated PA: dull, bored, sluggish, tired, drowsy NA: sad, blue, unhappy, gloomy, grouchy Activated NA: jittery, anxious, nervous, fearful, distressed.
Keys for these separate scales are shown in the examples.
In addition to the MSQ, there are 5 scales from the Eysenck Personality Inventory (Extraversion, Impulsivity, Sociability, Neuroticism, Lie). The Imp and Soc are subsets of the the total extraversion scale based upon a reanalysis of the EPI by Rocklin and Revelle (1983). This information is in the msq
data set as well.
In December, 2018 the caffeine, film and personality conditions were added. In the process of doing so, it was discovered that the EMIT data had been incorrectly entered. This has been fixed.
Data collected at the Personality, Motivation, and Cognition Laboratory, Northwestern University.
Larsen, R. J., & Diener, E. (1992). Promises and problems with the circumplex model of emotion. In M. S. Clark (Ed.), Review of personality and social psychology, No. 13. Emotion (pp. 25-59). Thousand Oaks, CA, US: Sage Publications, Inc.
Rafaeli, Eshkol and Revelle, William (2006), A premature consensus: Are happiness and sadness truly opposite affects? Motivation and Emotion, 30, 1, 1-12.
Revelle, W. and Anderson, K.J. (1998) Personality, motivation and cognitive performance: Final report to the Army Research Institute on contract MDA 903-93-K-0008. (https://www.personality-project.org/revelle/publications/ra.ari.98.pdf).
Smillie, Luke D. and Cooper, Andrew and Wilt, Joshua and Revelle, William (2012) Do Extraverts Get More Bang for the Buck? Refining the Affective-Reactivity Hypothesis of Extraversion. Journal of Personality and Social Psychology, 103 (2), 206-326.
Thayer, R.E. (1989) The biopsychology of mood and arousal. Oxford University Press. New York, NY.
Watson,D., Clark, L.A. and Tellegen, A. (1988) Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6):1063-1070.
make.keys
, scoreItems
and scoreOverlap
for instructions on how to score multiple scales with and without item overlap. Also see fa
and fa.extension
for instructions on how to do factor analyses or factor extension.
Given the temporal ordering of the sai
data and the msqR
data, these data are useful for demonstrations of testRetest
reliability. See the examples in testRetest
for how to combine the sai
tai
and msqR
datasets.
data(msqR) table(msqR$form,msqR$time) #which forms? table(msqR$study,msqR$drug) #Drug studies table(msqR$study,msqR$film) #Film studies table(msqR$study,msqR$TOD) #To examine time of day #score them for 20 short scales -- note that these have item overlap #The first 2 are from Thayer #The next 2 are classic positive and negative affect #The next 9 are circumplex scales #the last 7 are msq estimates of PANASX scales (missing some items) keys.list <- list( EA = c("active", "energetic", "vigorous", "wakeful", "wide.awake", "full.of.pep", "lively", "-sleepy", "-tired", "-drowsy"), TA =c("intense", "jittery", "fearful", "tense", "clutched.up", "-quiet", "-still", "-placid", "-calm", "-at.rest") , PA =c("active", "excited", "strong", "inspired", "determined", "attentive", "interested", "enthusiastic", "proud", "alert"), NAf =c("jittery", "nervous", "scared", "afraid", "guilty", "ashamed", "distressed", "upset", "hostile", "irritable" ), HAct = c("active", "aroused", "surprised", "intense", "astonished"), aPA = c("elated", "excited", "enthusiastic", "lively"), uNA = c("calm", "serene", "relaxed", "at.rest", "content", "at.ease"), pa = c("happy", "warmhearted", "pleased", "cheerful", "delighted" ), LAct = c("quiet", "inactive", "idle", "still", "tranquil"), uPA =c( "dull", "bored", "sluggish", "tired", "drowsy"), naf = c( "sad", "blue", "unhappy", "gloomy", "grouchy"), aNA = c("jittery", "anxious", "nervous", "fearful", "distressed"), Fear = c("afraid" , "scared" , "nervous" , "jittery" ) , Hostility = c("angry" , "hostile", "irritable", "scornful" ), Guilt = c("guilty" , "ashamed" ), Sadness = c( "sad" , "blue" , "lonely", "alone" ), Joviality =c("happy","delighted", "cheerful", "excited", "enthusiastic", "lively", "energetic"), Self.Assurance=c( "proud","strong" , "confident" , "-fearful" ), Attentiveness = c("alert" , "determined" , "attentive" )) #acquiscence = c("sleepy" , "wakeful" , "relaxed","tense") #Yik Russell and Steiger list the following items Yik.keys <- list( pleasure =psych::cs(happy,content,satisfied, pleased), act.pleasure =psych::cs(proud,enthusiastic,euphoric), pleasant.activation = psych::cs(energetic,full.of.pep,excited,wakeful,attentive, wide.awake,active,alert,vigorous), activation = psych::cs(aroused,hyperactivated,intense), unpleasant.act = psych::cs(anxious,frenzied,jittery,nervous), activated.displeasure =psych::cs(scared,upset,shaky,fearful,clutched.up,tense, ashamed,guilty,agitated,hostile), displeaure =psych::cs(troubled,miserable,unhappy,dissatisfied), Ueactivated.Displeasure = psych::cs(sad,down,gloomy,blue,melancholy), Unpleasant.Deactivation = psych::cs(droopy,drowsy,dull,bored,sluggish,tired), Deactivation =psych::cs( quiet,still), pleasant.deactivation = psych::cs(placid,relaxed,tranquil, at.rest,calm), deactived.pleasure =psych::cs( serene,soothed,peaceful,at.ease,secure) ) #of these 60 items, 46 appear in the msqR Yik.msq.keys <- list( Pleasure =psych::cs(happy,content,satisfied, pleased), Activated.Pleasure =psych::cs(proud,enthusiastic), Pleasant.Activation = psych::cs(energetic,full.of.pep,excited,wakeful,attentive, wide.awake,active,alert,vigorous), Activation = psych::cs(aroused,intense), Unpleasant.Activation = psych::cs(anxious,jittery,nervous), Activated.Displeasure =psych::cs(scared,upset,fearful, clutched.up,tense,ashamed,guilty,hostile), Displeasure = psych::cs(unhappy), Deactivated.Displeasure = psych::cs(sad,gloomy,blue), Unpleasant.Deactivation = psych::cs(drowsy,dull,bored,sluggish,tired), Deactivation =psych::cs( quiet,still), Pleasant.Deactivation = psych::cs(placid,relaxed,tranquil, at.rest,calm), Deactivated.Pleasure =psych::cs( serene,at.ease) ) yik.scores <- psych::scoreItems(Yik.msq.keys,msqR) yik <- yik.scores$scores f2.yik <- psych::fa(yik,2) #factor the yik scores psych::fa.plot(f2.yik,labels=colnames(yik),title="Yik-Russell-Steiger circumplex",cex=.8, pos=(c(1,1,2,1,1,1,3,1,4,1,2,4))) msq.scores <- psych::scoreItems(keys.list,msqR) #show a circumplex structure for the non-overlapping items fcirc <- psych::fa(msq.scores$scores[,5:12],2) psych::fa.plot(fcirc,labels=colnames(msq.scores$scores)[5:12]) #now, find the correlations corrected for item overlap msq.overlap <- psych::scoreOverlap(keys.list,msqR) f2 <- psych::fa(msq.overlap$cor,2) psych::fa.plot(f2,labels=colnames(msq.overlap$cor), title="2 dimensions of affect, corrected for overlap") #extend this solution to EA/TA NA/PA space fe <- psych::fa.extension(cor(msq.scores$scores[,5:12],msq.scores$scores[,1:4]),fcirc) psych::fa.diagram(fcirc,fe=fe,main="Extending the circumplex structure to EA/TA and PA/NA ") #show the 2 dimensional structure f2 <- psych::fa(msqR[1:72],2) psych::fa.plot(f2,labels=colnames(msqR)[1:72],title="2 dimensions of affect at the item level") #sort them by polar coordinates round(psych::polar(f2),2) #the msqR and sai data sets have 10 overlapping items which can be used for #testRetest analysis. We need to specify the keys, and then choose the appropriate #data sets sai.msq.keys <- list(pos =c( "at.ease" , "calm" , "confident", "content","relaxed"), neg = c("anxious", "jittery", "nervous" ,"tense" , "upset"), anx = c("anxious", "jittery", "nervous" ,"tense", "upset","-at.ease" , "-calm" , "-confident", "-content","-relaxed")) select <- psych::selectFromKeys(sai.msq.keys$anx) #The following is useful for examining test retest reliabilities msq.control <- subset(msqR,is.element( msqR$study , c("Cart", "Fast", "SHED", "SHOP"))) msq.film <- subset(msqR,(is.element( msqR$study , c("FIAT", "FILM","FLAT","MIXX","XRAY")) & (msqR$time < 3) )) msq.film[((msq.film$study == "FLAT") & (msq.film$time ==3)) ,] <- NA msq.drug <- subset(msqR,(is.element( msqR$study , c("AGES","SALT", "VALE", "XRAY"))) &(msqR$time < 3)) msq.day <- subset(msqR,is.element( msqR$study , c("SAM", "RIM")))
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