"""
camcops_server/tasks/cesdr.py
===============================================================================
Copyright (C) 2012, University of Cambridge, Department of Psychiatry.
Created by Rudolf Cardinal (rnc1001@cam.ac.uk).
This file is part of CamCOPS.
CamCOPS is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
CamCOPS is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with CamCOPS. If not, see <https://www.gnu.org/licenses/>.
===============================================================================
"""
from typing import Any, Dict, List, Tuple, Type
from cardinal_pythonlib.classes import classproperty
from cardinal_pythonlib.stringfunc import strseq
from semantic_version import Version
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.sqltypes import Boolean
from camcops_server.cc_modules.cc_constants import CssClass
from camcops_server.cc_modules.cc_ctvinfo import CtvInfo, CTV_INCOMPLETE
from camcops_server.cc_modules.cc_db import add_multiple_columns
from camcops_server.cc_modules.cc_html import get_yes_no, tr, tr_qa
from camcops_server.cc_modules.cc_request import CamcopsRequest
from camcops_server.cc_modules.cc_summaryelement import SummaryElement
from camcops_server.cc_modules.cc_task import (
get_from_dict,
Task,
TaskHasPatientMixin,
)
from camcops_server.cc_modules.cc_text import SS
from camcops_server.cc_modules.cc_trackerhelpers import (
equally_spaced_int,
regular_tracker_axis_ticks_int,
TrackerInfo,
TrackerLabel,
)
# =============================================================================
# CESD-R
# =============================================================================
[docs]class Cesdr(TaskHasPatientMixin, Task, metaclass=CesdrMetaclass):
"""
Server implementation of the CESD task.
"""
__tablename__ = "cesdr"
shortname = "CESD-R"
info_filename_stem = "cesd"
provides_trackers = True
CAT_NONCLINICAL = 0
CAT_SUB = 1
CAT_POSS_MAJOR = 2
CAT_PROB_MAJOR = 3
CAT_MAJOR = 4
DEPRESSION_RISK_THRESHOLD = 16
FREQ_NOT_AT_ALL = 0
FREQ_1_2_DAYS_LAST_WEEK = 1
FREQ_3_4_DAYS_LAST_WEEK = 2
FREQ_5_7_DAYS_LAST_WEEK = 3
FREQ_DAILY_2_WEEKS = 4
N_QUESTIONS = 20
N_ANSWERS = 5
POSS_MAJOR_THRESH = 2
PROB_MAJOR_THRESH = 3
MAJOR_THRESH = 4
SCORED_FIELDS = strseq("q", 1, N_QUESTIONS)
TASK_FIELDS = SCORED_FIELDS
MIN_SCORE = 0
MAX_SCORE = 3 * N_QUESTIONS
[docs] @staticmethod
def longname(req: "CamcopsRequest") -> str:
_ = req.gettext
return _("Center for Epidemiologic Studies Depression Scale (Revised)")
# noinspection PyMethodParameters
@classproperty
def minimum_client_version(cls) -> Version:
return Version("2.2.8")
[docs] def is_complete(self) -> bool:
return (
self.all_fields_not_none(self.TASK_FIELDS)
and self.field_contents_valid()
)
def total_score(self) -> int:
return self.sum_fields(self.SCORED_FIELDS) - self.count_where(
self.SCORED_FIELDS, [self.FREQ_DAILY_2_WEEKS]
)
def get_depression_category(self) -> int:
if not self.has_depression_risk():
return self.CAT_SUB
q_group_anhedonia = [8, 10]
q_group_dysphoria = [2, 4, 6]
other_q_groups = {
"appetite": [1, 18],
"sleep": [5, 11, 19],
"thinking": [3, 20],
"guilt": [9, 17],
"tired": [7, 16],
"movement": [12, 13],
"suicidal": [14, 15],
}
# Dysphoria or anhedonia must be present at frequency
# FREQ_DAILY_2_WEEKS
anhedonia_criterion = self.fulfils_group_criteria(
q_group_anhedonia, True
) or self.fulfils_group_criteria(q_group_dysphoria, True)
if anhedonia_criterion:
category_count_high_freq = 0
category_count_lower_freq = 0
for qgroup in other_q_groups.values():
if self.fulfils_group_criteria(qgroup, True):
# Category contains an answer == FREQ_DAILY_2_WEEKS
category_count_high_freq += 1
if self.fulfils_group_criteria(qgroup, False):
# Category contains an answer == FREQ_DAILY_2_WEEKS or
# FREQ_5_7_DAYS_LAST_WEEK
category_count_lower_freq += 1
if category_count_high_freq >= self.MAJOR_THRESH:
# Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS)
# plus 4 other symptom groups at FREQ_DAILY_2_WEEKS
return self.CAT_MAJOR
if category_count_lower_freq >= self.PROB_MAJOR_THRESH:
# Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS)
# plus 3 other symptom groups at FREQ_DAILY_2_WEEKS or
# FREQ_5_7_DAYS_LAST_WEEK
return self.CAT_PROB_MAJOR
if category_count_lower_freq >= self.POSS_MAJOR_THRESH:
# Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS)
# plus 2 other symptom groups at FREQ_DAILY_2_WEEKS or
# FREQ_5_7_DAYS_LAST_WEEK
return self.CAT_POSS_MAJOR
if self.has_depression_risk():
# Total CESD-style score >= 16 but doesn't meet other criteria.
return self.CAT_SUB
return self.CAT_NONCLINICAL
def fulfils_group_criteria(
self, qnums: List[int], nearly_every_day_2w: bool
) -> bool:
qstrings = ["q" + str(qnum) for qnum in qnums]
if nearly_every_day_2w:
possible_values = [self.FREQ_DAILY_2_WEEKS]
else:
possible_values = [
self.FREQ_5_7_DAYS_LAST_WEEK,
self.FREQ_DAILY_2_WEEKS,
]
count = self.count_where(qstrings, possible_values)
return count > 0
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]:
line_step = 20
threshold_line = self.DEPRESSION_RISK_THRESHOLD - 0.5
# noinspection PyTypeChecker
return [
TrackerInfo(
value=self.total_score(),
plot_label="CESD-R total score",
axis_label=f"Total score ({self.MIN_SCORE}-{self.MAX_SCORE})",
axis_min=self.MIN_SCORE - 0.5,
axis_max=self.MAX_SCORE + 0.5,
axis_ticks=regular_tracker_axis_ticks_int(
self.MIN_SCORE, self.MAX_SCORE, step=line_step
),
horizontal_lines=equally_spaced_int(
self.MIN_SCORE + line_step,
self.MAX_SCORE - line_step,
step=line_step,
)
+ [threshold_line],
horizontal_labels=[
TrackerLabel(
threshold_line,
self.wxstring(req, "depression_or_risk_of"),
)
],
)
]
[docs] def get_clinical_text(self, req: CamcopsRequest) -> List[CtvInfo]:
if not self.is_complete():
return CTV_INCOMPLETE
return [CtvInfo(content=f"CESD-R total score {self.total_score()}")]
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]:
return self.standard_task_summary_fields() + [
SummaryElement(
name="depression_risk",
coltype=Boolean(),
value=self.has_depression_risk(),
comment="Has depression or at risk of depression",
)
]
def has_depression_risk(self) -> bool:
return self.total_score() >= self.DEPRESSION_RISK_THRESHOLD
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
score = self.total_score()
answer_dict = {None: None}
for option in range(self.N_ANSWERS):
answer_dict[option] = (
str(option) + " – " + self.wxstring(req, "a" + str(option))
)
q_a = ""
for q in range(1, self.N_QUESTIONS):
q_a += tr_qa(
self.wxstring(req, "q" + str(q) + "_s"),
get_from_dict(answer_dict, getattr(self, "q" + str(q))),
)
tr_total_score = tr_qa(f"{req.sstring(SS.TOTAL_SCORE)} (0–60)", score)
tr_depression_or_risk_of = tr_qa(
self.wxstring(req, "depression_or_risk_of") + "? <sup>[1]</sup>",
get_yes_no(req, self.has_depression_risk()),
)
tr_provisional_diagnosis = tr(
"Provisional diagnosis <sup>[2]</sup>",
self.wxstring(
req, "category_" + str(self.get_depression_category())
),
)
return f"""
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{self.get_is_complete_tr(req)}
{tr_total_score}
{tr_depression_or_risk_of}
{tr_provisional_diagnosis}
</table>
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="70%">Question</th>
<th width="30%">Answer</th>
</tr>
{q_a}
</table>
<div class="{CssClass.FOOTNOTES}">
[1] Presence of depression (or depression risk) is indicated by a
score ≥ 16
[2] Diagnostic criteria described at
<a href="https://cesd-r.com/cesdr/">https://cesd-r.com/cesdr/</a>
</div>
""" # noqa