# -*- coding: utf-8 -*-
import neuropsydia as n
questions_dictionary = {
"Item":{
1:"Neuropsydia is great",
2:"Neuropsydia is not great",
3:"Python is great",
4:"Python is not great"}
}
n.start()
n.questionnaire(questions_dictionary, anchors=["No","Yes"], results_save=True)
n.close()
# -*- coding: utf-8 -*-
import neuropsydia as n
questions_dictionary = {
"Item": {
1: "Is Neuropsydia great?",
2: "Is Neuropsydia not great?",
3: "Is Python great?",
4: "Is Python not great?"
},
"Reverse": {
1: False,
2: True,
3: False,
4: True
},
"Dimension": {
1: "Neuropsydia",
2: "Neuropsydia",
3: "Python",
4: "Python"
}
}
n.start()
n.questionnaire(questions_dictionary,
anchors=["No", "Yes"],
results_save=True,
dimensions_mean=True)
n.close()
3: False,
4: False,
5: False
}
}
n.start() # Initialize neuropsydia
participant_id = n.ask("Participant ID:", order=1) # Get participant id
participant_gender = n.ask("Gender:", order=2) # Get participant's gender
participant_age = n.ask("Age:", order=3) # get participant's age
df = n.questionnaire(questions_dictionary, # The questions
participant_id=participant_id,
analog=False, # Lickert-like
edges=[1, 4], # Values underneath
labels=["Almost never", "Sometimes", "Often", "Almost always"],
style="blue", # The cursor's color
instructions_text="A number of statements which people have used to describe themselves are given below. \nSelect the number that indicate how you feel right now, that is, at this moment. \nThere are no right or wrong answers. Do not spend too much time on any one statement but give the answer which seems to describe your present feelings best.") # Add instructions at the beginning
# Scoring
score = df["Answer"].sum()
# Cutoff based on Crawford et al. (2011). This just for illustration purposes, adapt it following your activity.
if score > 56:
interpretation = "Possible Anxiety"
else:
interpretation = "No anxiety"
# Add info and save
3: "Is Python great?",
4: "Is Python not great?"
},
"Reverse": {
1: False,
2: True,
3: False,
4: True
},
"Dimension": {
1: "Neuropsydia",
2: "Neuropsydia",
3: "Python",
4: "Python"
}
}
n.start()
n.questionnaire(questions_dictionary, # The questions
anchors=["Not at all", "Absolutely"], # The edges of the scale
results_save=True, # Should it save the data?
results_type="csv2", # Change the separator for ";" instead of "," (for France)
dimensions_mean=True, # Compute the mean by dimension?
analog=False, # Lickert-like
edges=[0, 7], # Values underneath
style="blue", # The cursor's colour
randomize=True, # Randomize the question's order
instructions_text="Here are the instructions") # Add instructions at the beginning
n.close()
# -*- coding: utf-8 -*-
import neuropsydia as n # Load neuropsydia
questions_dictionary = {
"Item": {
1: "Is Neuropsydia great?",
2: "Is Neuropsydia not great?",
3: "Is Python great?",
4: "Is Python not great?"
}
}
n.start()
n.questionnaire(questions_dictionary)
n.close()
2: "Is Neuropsydia not great?",
3: "Is Python great?",
4: "Is Python not great?"
},
"Reverse": {
1: False,
2: True,
3: False,
4: True
},
"Dimension": {
1: "Neuropsydia",
2: "Neuropsydia",
3: "Python",
4: "Python"
}
}
n.start()
n.questionnaire(questions_dictionary, # The questions
anchors=["Not at all", "Absolutely"], # The edges of the scale
results_save=True, # Should it save the data?
dimensions_mean=True, # Compute the mean by dimension?
analog=False, # Lickert-like
edges=[0, 7], # Values underneath
style="blue", # The cursor's colour
randomize=True, # Randomize the question's order
instructions_text="Here are the instructions") # Add instructions at the beginning
n.close()
# -*- coding: utf-8 -*-
import neuropsydia as n # Load neuropsydia
questions_dictionary = {
"Item": {
1: "Is Neuropsydia great?",
2: "Is Neuropsydia not great?",
3: "Is Python great?",
4: "Is Python not great?"
}
}
n.start()
n.questionnaire(questions_dictionary)
n.close()