Base models, forms and admin for participant ICF for clinicedc/edc projects.
Project description
edc-consent
Add classes for the Informed Consent form and process.
Installation
Register your consent model, its version and period of validity, with site_consents. site_consents will autodiscover consents.py in any app listed in INSTALLED_APPS. For now we just create a version 1 consent. In consents.py add something like this:
import arrow
from datetime import datetime
from edc_consent.consent import Consent
from edc_consent.site_consents import site_consents
from edc_constants.constants import MALE, FEMALE
subjectconsent_v1 = Consent(
'edc_example.subjectconsent',
version='1',
start=arrow.get(datetime(2013, 10, 15)).datetime,
end=arrow.get(datetime(2016, 10, 15)).datetime,
age_min=16,
age_is_adult=18,
age_max=64,
gender=[MALE, FEMALE])
site_consents.register(subjectconsent_v1)
add to settings:
INSTALLED_APPS = [
...
'edc_consent.apps.AppConfig',
...
]
Below needs to be updated
Features
base class for an informed consent document
data for models that require consent cannot be add until the consent is added
consents have a version number and validity period
maximum number of consented subjects can be controlled.
data collection is only allowed within the validity period of the consent per consented participant
data for models that require consent are tagged with the consent version
TODO
link subject type to the consent model. e.g. maternal, infant, adult, etc.
version at model field level (e.g. a new consent period adds additional questions to a form)
allow a different subject’s consent to cover for another, for example mother and infant.
Usage
First, it’s a good idea to limit the number of consents created to match your enrollment targets. Do this by creating a mixin for the consent model class:
from edc_quota.client.models import QuotaMixin, QuotaManager
class ConsentQuotaMixin(QuotaMixin):
QUOTA_REACHED_MESSAGE = 'Maximum number of subjects has been reached or exceeded for {}. Got {} >= {}.'
class Meta:
abstract = True
Then declare the consent model:
class MyConsent(ConsentQuotaMixin, BaseConsent):
quota = QuotaManager()
class Meta:
app_label = 'my_app'
Declare the ModelForm:
class MyConsentForm(BaseConsentForm):
class Meta:
model = MyConsent
Now that you have a consent model class, identify and declare the models that will require this consent:
class Questionnaire(RequiresConsentMixin, models.Model):
consent_model = MyConsent # or tuple (app_label, model_name)
report_datetime = models.DateTimeField(default=timezone.now)
question1 = models.CharField(max_length=10)
question2 = models.CharField(max_length=10)
question3 = models.CharField(max_length=10)
@property
def subject_identifier(self):
"""Returns the subject identifier from ..."""
return subject_identifier
class Meta:
app_label = 'my_app'
verbose_name = 'My Questionnaire'
Notice above the first two class attributes, namely:
consent_model: this is the consent model class that was declared above;
report_datetime: a required field used to lookup the correct consent version from ConsentType and to find, together with subject_identifier, a valid instance of MyConsent;
Also note the property subject_identifier.
subject_identifier: a required property that knows how to find the subject_identifier for the instance of Questionnaire.
Once all is declared you need to:
define the consent version and validity period for the consent version in ConsentType;
add a Quota for the consent model.
As subjects are identified:
add a consent
add the models (e.g. Questionnaire)
If a consent version cannot be found given the consent model class and report_datetime a ConsentTypeError is raised.
If a consent for this subject_identifier cannot be found that matches the ConsentType a NotConsentedError is raised.
Specimen Consent
A participant may consent to the study but not agree to have specimens stored long term. A specimen consent is administered separately to clarify the participant's intention.
The specimen consent is declared using the base class BaseSpecimenConsent. This is an abridged version of BaseConsent. The specimen consent also uses the RequiresConsentMixin as it cannot stand alone as an ICF. The RequiresConsentMixin ensures the specimen consent is administered after the main study ICF, in this case MyStudyConsent.
A specimen consent is declared in your app like this:
class SpecimenConsent(BaseSpecimenConsent, SampleCollectionFieldsMixin, RequiresConsentMixin,
VulnerabilityFieldsMixin, AppointmentMixin, BaseUuidModel):
consent_model = MyStudyConsent
registered_subject = models.OneToOneField(RegisteredSubject, null=True)
objects = models.Manager()
history = AuditTrail()
class Meta:
app_label = 'my_app'
verbose_name = 'Specimen Consent'
Validators
The ConsentAgeValidator validates the date of birth to within a given age range, for example:
from edc_consent.validtors import ConsentAgeValidator
class MyConsent(ConsentQuotaMixin, BaseConsent):
dob = models.DateField(
validators=[ConsentAgeValidator(16, 64)])
quota = QuotaManager()
class Meta:
app_label = 'my_app'
The PersonalFieldsMixin includes a date of birth field and you can set the age bounds like this:
from edc_consent.validtors import ConsentAgeValidator
from edc_consent.models.fields import PersonalFieldsMixin
class MyConsent(ConsentQuotaMixin, PersonalFieldsMixin, BaseConsent):
quota = QuotaManager()
MIN_AGE_OF_CONSENT = 18
MAX_AGE_OF_CONSENT = 64
class Meta:
app_label = 'my_app'
Common senarios
Tracking the consent version with collected data
All model data is tagged with the consent version identified in ConsentType for the consent model class and report_datetime.
Reconsenting consented subjects when the consent changes
The consent model is unique on subject_identifier, identity and version. If a new consent version is added to ConsentType, a new consent will be required for each subject as data is reported within the validity period of the new consent.
Some care must be taken to ensure that the consent model is queried with an understanding of the unique constraint.
Linking the consent version to added or removed model fields on models that require consent
TODO
Infants use mother’s consent
TODO
By adding the property consenting_subject_identifier to the consent
Other TODO
Timepoint model update in save method of models requiring consent
handle added or removed model fields (questions) because of consent version change
review verification actions
management command to update version on models that require consent (if edc_consent added after instances were created)
handle re-consenting issues, for example, if original consent was restricted by age (16-64) but the re-consent is not. May need to open upper bound.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file edc_consent-0.2.35-py3-none-any.whl
.
File metadata
- Download URL: edc_consent-0.2.35-py3-none-any.whl
- Upload date:
- Size: 56.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5befc588270744b001ef09b7a6a86a161b0f82c28277daddff75039ee7cc5f52 |
|
MD5 | 3eaad9d961ae4c229a7d76bb8fe280f8 |
|
BLAKE2b-256 | 58d15dd28bc1f82c5c5fa1bbac531d130e58032db78081289341ff76951eddf9 |