Joiner Lab Research Questions for Computers in Psychology Course
1. Is level of belongingness related to level of suicidal ideation?
a. Use these variables to compute level of belongingness: bel1, bel2, bel3, bel4, bel5,
bel6, bel7, bel8, bel9, bel10.
b. Create a sum score for belongingness by adding the following variables:
bel1+bel2+bel3+bel4+bel5+bel6+bel7+bel8+bel9+bel10. This can be done in PASW
using the dropdown menu and clicking Transform  compute variable  naming
the target variable “belong” and typing in
“bel1+bel2+bel3+bel4+bel5+bel6+bel7+bel8+bel9+bel10” in the numeric expression
box. I already took care of the reverse coding that is necessary and computed a
total score for belonging, which now appears at the end of the variable list in the
dataset. NOTE: higher scores on belonging indicate higher levels of belongingness
c. Use these variables to compute level of suicidal ideation: bss1, bss2, bss3, bss4,
bss5, bss6, bss7, bss8, bss9, bss10, bss11, bss12, bss13, bss14, bss15, bss16, bss17,
bss18, bss19, bss20, bss21.
d. Create a sum score for suicidal ideation by adding bss1 through bss21 using the
instructions noted in bullet point b above. I already computed a total score for
suicidal ideation, which now appears at the end of the variable list in the dataset.
NOTE: higher scores on suicidal ideation indicate higher levels of suicidal
ideation. Suicidal ideation has a low base-rate in the population, so that is why
most participants scored a 0 on this scale.
e. To test whether belongingness is related to level of suicidal ideation, run a
bivariate correlation between the belonging and suicidal ideation variables.
2. Is level of perceived burdensomeness related to level of suicidal ideation?
a. Use these variables to compute level of burdensomeness: bur1 through bur15.
b. Create a sum score for belongingness by adding the following variables: bur1
through bur15. I already took care of the reverse coding that is necessary and
computed a total score for burdensomeness, which now appears at the end of the
variable list in the dataset. NOTE: higher scores on burden indicate higher levels
of burdensomeness
c. Use these variables to compute level of suicidal ideation: bss1, bss2, bss3, bss4,
bss5, bss6, bss7, bss8, bss9, bss10, bss11, bss12, bss13, bss14, bss15, bss16, bss17,
bss18, bss19, bss20, bss21.
d. Create a sum score for suicidal ideation by adding bss1 through bss21 using the
instructions noted in bullet point b above. I already computed a total score for
suicidal ideation, which now appears at the end of the variable list in the dataset.
NOTE: higher scores on suicidal ideation indicate higher levels of suicidal
ideation. Suicidal ideation has a low base-rate in the population, so that is why
most participants scored a 0 on this scale.
e. To test whether burdensomeness is related to level of suicidal ideation, run a
bivariate correlation between the belonging and suicidal ideation variables.
3. Is level or loneliness related to level of belongingness?
a. Loneliness variables = ucla1 through ucla20. Compute total score by summing the
scores on ucla1 through ucla20 (I took care of reverse scoring). I also computed the
total score for loneliness, which now appears at the end of the dataset. Higher
scores = higher levels of loneliness
b. Belongingness variables = see #1 above.
c. Compute bivariate correlation between loneliness and belongingness.
4. Is level of depressive symptoms associated with level of suicidal ideation?
a. Depressive symptoms variables = bdi1 through bdi21. Compute total score by
summing the scores on bdi1 through bdi21. I computed the total score for
depression, which now appears at the end of the dataset. Higher scores = higher
levels of depression
b. Suicidal ideation variables = see #1 above.
c. Compute bivariate correlation between depression and suicidal ideation.
5. Is level of anxiety symptoms associated with level of suicidal ideation?
a. Anxiety symptoms variables = bai1 through bai21. Compute total score by summing
the scores on bai1 through bai21. I computed the total score for anxiety, which now
appears at the end of the dataset. Higher scores = higher levels of anxiety
b. Suicidal ideation variables = see #1 above.
c. Compute bivariate correlation between anxiety and suicidal ideation.
6. Is level loneliness associated with level of depressive symptoms?
a. Loneliness variables = see #3 above
b. Depression variables = see #4 above
c. Compute bivariate correlation between loneliness and depressive symptoms.
7. Are there gender differences in individuals’ level of self-reported depressive symptoms?
a. Gender variable = gender
b. Depression variables = see #4 above
c. Compute a chi square test with gender as the independent variable and depressive
symptoms as the dependent variable.
8. Are there gender differences in individuals’ level of self-reported loneliness?
a. Gender variable = gender
b. Loneliness variables = see #3 above
c. Compute a chi square test with gender as the independent variable and loneliness
as the dependent variable.
9. Is there a relationship between the number of reasons for living one endorses and level of
suicidal ideation?
a. Reasons for living variables = reason1 through reason7. Compute total score by
summing the scores on reason1 through reason7. I computed the total score, which
now appears at the end of the dataset, titled “reasons.” Higher scores indicate
more reasons for living.
b. Suicidal Ideation variables = see #1 above.
c. Compute bivariate correlation between reasons for living and suicidal ideation.