# -*- 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()