Add classes for the Informed Consent form and process.
pip install git+https://github.com/botswana-harvard/edc-consent@develop#egg=edc_consent
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 |
- 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
- 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.
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 ofMyConsent
;
Also note the property subject_identifier
.
- subject_identifier: a required property that knows how to find the
subject_identifier
for the instance ofQuestionnaire
.
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.
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'
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'
All model data is tagged with the consent version identified in ConsentType
for the consent model class and report_datetime.
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.
TODO
TODO
By adding the property consenting_subject_identifier
to the consent
Timepoint
model update insave
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.