R: Multiple regression continuous independent variable interpretation I have mental health score as my dependent variable, the relationship with people as one of my independent variables, which has 7 scores representing the mood from the most happy to the most bad. Another control variable represents the frequency of people working from home, which is labelled as 4 scores representing always, often, sometimes and never.I wanted to code both variable as continuous variables. When I first ran the models, it showed me that the coefficient for each independent variable and control variable.  But now when I ran the model, it gives me the coefficient for each level of my variable. eg.there are three coefficients of wfh-always, wfh-often and wfh-sometimes. R might automatically treat my variable as categorical variable? Is there a reason for this and is there a way to just see one coefficient for each variable? Thank you!!!

It does seem R is reading your "wah" variable as factor. This usually does not happen for variables that have numeric values. If your "wah" variable does have numeric values (e.g. 1, 2, 3, 4), you can try telling R it is indeed numeric:
data$wah<-as.numeric(data$wah)

If your "wah" variable has the often, sometimes etc. as levels (i.e., each participant has one of these words as value for this variable), then your variable is in string form and you need to recode it. There are several ways to do this, this is kind of clumsy but easiest to me:
EDIT. PLEASE NOTE ROLAND'S CORRECTION BELOW, this is not the way
levels(data$wah)<-c("1", "2", "3", "4")
data$wah<-as.numeric(data$wah)

