"""
camcops_server/tasks/bdi.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.stringfunc import strseq
import cardinal_pythonlib.rnc_web as ws
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.schema import Column
from sqlalchemy.sql.sqltypes import Integer, String
from camcops_server.cc_modules.cc_constants import (
CssClass,
DATA_COLLECTION_ONLY_DIV,
)
from camcops_server.cc_modules.cc_ctvinfo import CTV_INCOMPLETE, CtvInfo
from camcops_server.cc_modules.cc_db import add_multiple_columns
from camcops_server.cc_modules.cc_html import answer, bold, doi, td, tr, tr_qa
from camcops_server.cc_modules.cc_request import CamcopsRequest
from camcops_server.cc_modules.cc_snomed import SnomedExpression, SnomedLookup
from camcops_server.cc_modules.cc_string import AS
from camcops_server.cc_modules.cc_summaryelement import SummaryElement
from camcops_server.cc_modules.cc_task import Task, TaskHasPatientMixin
from camcops_server.cc_modules.cc_text import SS
from camcops_server.cc_modules.cc_trackerhelpers import TrackerInfo
# =============================================================================
# Constants
# =============================================================================
BDI_I_QUESTION_TOPICS = {
# from Beck 1988, https://doi.org/10.1016/0272-7358(88)90050-5
1: "mood", # a
2: "pessimism", # b
3: "sense of failure", # c
4: "lack of satisfaction", # d
5: "guilt feelings", # e
6: "sense of punishment", # f
7: "self-dislike", # g
8: "self-accusation", # h
9: "suicidal wishes", # i
10: "crying", # j
11: "irritability", # k
12: "social withdrawal", # l
13: "indecisiveness", # m
14: "distortion of body image", # n
15: "work inhibition", # o
16: "sleep disturbance", # p
17: "fatigability", # q
18: "loss of appetite", # r
19: "weight loss", # s
20: "somatic preoccupation", # t
21: "loss of libido", # u
}
BDI_IA_QUESTION_TOPICS = {
# from [Beck1996b]
1: "sadness",
2: "pessimism",
3: "sense of failure",
4: "self-dissatisfaction",
5: "guilt",
6: "punishment",
7: "self-dislike",
8: "self-accusations",
9: "suicidal ideas",
10: "crying",
11: "irritability",
12: "social withdrawal",
13: "indecisiveness",
14: "body image change",
15: "work difficulty",
16: "insomnia",
17: "fatigability",
18: "loss of appetite",
19: "weight loss",
20: "somatic preoccupation",
21: "loss of libido",
}
BDI_II_QUESTION_TOPICS = {
# from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5889520/;
# also https://www.ncbi.nlm.nih.gov/pubmed/10100838;
# also [Beck1996b]
# matches BDI-II paper version
1: "sadness",
2: "pessimism",
3: "past failure",
4: "loss of pleasure",
5: "guilty feelings",
6: "punishment feelings",
7: "self-dislike",
8: "self-criticalness",
9: "suicidal thoughts or wishes",
10: "crying",
11: "agitation",
12: "loss of interest",
13: "indecisiveness",
14: "worthlessness",
15: "loss of energy",
16: "changes in sleeping pattern", # decrease or increase
17: "irritability",
18: "changes in appetite", # decrease or increase
19: "concentration difficulty",
20: "tiredness or fatigue",
21: "loss of interest in sex",
}
SCALE_BDI_I = "BDI-I" # must match client
SCALE_BDI_IA = "BDI-IA" # must match client
SCALE_BDI_II = "BDI-II" # must match client
TOPICS_BY_SCALE = {
SCALE_BDI_I: BDI_I_QUESTION_TOPICS,
SCALE_BDI_IA: BDI_IA_QUESTION_TOPICS,
SCALE_BDI_II: BDI_II_QUESTION_TOPICS,
}
NQUESTIONS = 21
TASK_SCORED_FIELDS = strseq("q", 1, NQUESTIONS)
MAX_SCORE = NQUESTIONS * 3
SUICIDALITY_QNUM = 9 # Q9 in all versions of the BDI (I, IA, II)
SUICIDALITY_FN = "q9" # fieldname
CUSTOM_SOMATIC_KHANDAKER_BDI_II_QNUMS = [4, 15, 16, 18, 19, 20, 21]
CUSTOM_SOMATIC_KHANDAKER_BDI_II_FIELDS = Task.fieldnames_from_list(
"q", CUSTOM_SOMATIC_KHANDAKER_BDI_II_QNUMS
)
# =============================================================================
# BDI (crippled)
# =============================================================================
class BdiMetaclass(DeclarativeMeta):
# noinspection PyInitNewSignature
def __init__(
cls: Type["Bdi"],
name: str,
bases: Tuple[Type, ...],
classdict: Dict[str, Any],
) -> None:
add_multiple_columns(
cls,
"q",
1,
NQUESTIONS,
minimum=0,
maximum=3,
comment_fmt="Q{n} [{s}] (0-3, higher worse)",
comment_strings=[
(
f"BDI-I: {BDI_I_QUESTION_TOPICS[q]}; "
f"BDI-IA: {BDI_IA_QUESTION_TOPICS[q]}; "
f"BDI-II: {BDI_II_QUESTION_TOPICS[q]}"
)
for q in range(1, NQUESTIONS + 1)
],
)
super().__init__(name, bases, classdict)
[docs]class Bdi(TaskHasPatientMixin, Task, metaclass=BdiMetaclass):
"""
Server implementation of the BDI task.
"""
__tablename__ = "bdi"
shortname = "BDI"
provides_trackers = True
bdi_scale = Column(
"bdi_scale",
String(length=10), # was Text
comment="Which BDI scale (BDI-I, BDI-IA, BDI-II)?",
)
[docs] @staticmethod
def longname(req: "CamcopsRequest") -> str:
_ = req.gettext
return _("Beck Depression Inventory (data collection only)")
[docs] def is_complete(self) -> bool:
return (
self.field_contents_valid()
and self.bdi_scale is not None
and self.all_fields_not_none(TASK_SCORED_FIELDS)
)
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]:
return [
TrackerInfo(
value=self.total_score(),
plot_label="BDI total score (rating depressive symptoms)",
axis_label=f"Score for Q1-21 (out of {MAX_SCORE})",
axis_min=-0.5,
axis_max=MAX_SCORE + 0.5,
)
]
[docs] def get_clinical_text(self, req: CamcopsRequest) -> List[CtvInfo]:
if not self.is_complete():
return CTV_INCOMPLETE
return [
CtvInfo(
content=(
f"{ws.webify(self.bdi_scale)} "
f"total score {self.total_score()}/{MAX_SCORE}"
)
)
]
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]:
return self.standard_task_summary_fields() + [
SummaryElement(
name="total",
coltype=Integer(),
value=self.total_score(),
comment=f"Total score (/{MAX_SCORE})",
)
]
def total_score(self) -> int:
return self.sum_fields(TASK_SCORED_FIELDS)
def is_bdi_ii(self) -> bool:
return self.bdi_scale == SCALE_BDI_II
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
score = self.total_score()
# Suicidal thoughts:
suicidality_score = getattr(self, SUICIDALITY_FN)
if suicidality_score is None:
suicidality_text = bold("? (not completed)")
suicidality_css_class = CssClass.INCOMPLETE
elif suicidality_score == 0:
suicidality_text = str(suicidality_score)
suicidality_css_class = ""
else:
suicidality_text = bold(str(suicidality_score))
suicidality_css_class = CssClass.WARNING
# Custom somatic score for Khandaker Insight study:
somatic_css_class = ""
if self.is_bdi_ii():
somatic_values = self.get_values(
CUSTOM_SOMATIC_KHANDAKER_BDI_II_FIELDS
)
somatic_missing = False
somatic_score = 0
for v in somatic_values:
if v is None:
somatic_missing = True
somatic_css_class = CssClass.INCOMPLETE
break
else:
somatic_score += int(v)
somatic_text = (
"incomplete" if somatic_missing else str(somatic_score)
)
else:
somatic_text = "N/A" # not the BDI-II
# Question rows:
q_a = ""
qdict = TOPICS_BY_SCALE.get(self.bdi_scale)
topic = "?"
for q in range(1, NQUESTIONS + 1):
if qdict:
topic = qdict.get(q, "??")
q_a += tr_qa(
f"{req.sstring(SS.QUESTION)} {q} ({topic})",
getattr(self, "q" + str(q)),
)
# HTML:
tr_somatic_score = tr(
td(
"Custom somatic score for Insight study <sup>[2]</sup> "
"(sum of scores for questions {}, for BDI-II only)".format(
", ".join(
"Q" + str(qnum)
for qnum in CUSTOM_SOMATIC_KHANDAKER_BDI_II_QNUMS
)
)
),
td(somatic_text, td_class=somatic_css_class),
literal=True,
)
tr_which_scale = tr_qa(
req.wappstring(AS.BDI_WHICH_SCALE) + " <sup>[3]</sup>",
ws.webify(self.bdi_scale),
)
return f"""
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{self.get_is_complete_tr(req)}
{tr(req.sstring(SS.TOTAL_SCORE),
answer(score) + " / {}".format(MAX_SCORE))}
<tr>
<td>
Suicidal thoughts/wishes score
(Q{SUICIDALITY_QNUM}) <sup>[1]</sup>
</td>
{td(suicidality_text, td_class=suicidality_css_class)}
</tr>
{tr_somatic_score}
</table>
</div>
<div class="{CssClass.EXPLANATION}">
All questions are scored from 0–3
(0 free of symptoms, 3 most symptomatic).
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="70%">Question</th>
<th width="30%">Answer</th>
</tr>
{tr_which_scale}
{q_a}
</table>
<div class="{CssClass.FOOTNOTES}">
[1] Suicidal thoughts are asked about in Q{SUICIDALITY_QNUM}
for all of: BDI-I (1961), BDI-IA (1978), and BDI-II (1996).
[2] Insight study: {doi("10.1186/ISRCTN16942542")}
[3] See the
<a href="https://camcops.readthedocs.io/en/latest/tasks/bdi.html">CamCOPS
BDI help</a> for full references and bibliography for the
citations that follow.
<b>The BDI rates “right now” [Beck1988].
The BDI-IA rates the past week [Beck1988].
The BDI-II rates the past two weeks [Beck1996b].</b>
1961 BDI(-I) question topics from [Beck1988].
1978 BDI-IA question topics from [Beck1996b].
1996 BDI-II question topics from [Steer1999], [Gary2018].
</ul>
</div>
{DATA_COLLECTION_ONLY_DIV}
""" # noqa
[docs] def get_snomed_codes(self, req: CamcopsRequest) -> List[SnomedExpression]:
scale_lookup = SnomedLookup.BDI_SCALE
if self.bdi_scale in (SCALE_BDI_I, SCALE_BDI_IA):
score_lookup = SnomedLookup.BDI_SCORE
proc_lookup = SnomedLookup.BDI_PROCEDURE_ASSESSMENT
elif self.bdi_scale == SCALE_BDI_II:
score_lookup = SnomedLookup.BDI_II_SCORE
proc_lookup = SnomedLookup.BDI_II_PROCEDURE_ASSESSMENT
else:
return []
codes = [SnomedExpression(req.snomed(proc_lookup))]
if self.is_complete():
codes.append(
SnomedExpression(
req.snomed(scale_lookup),
{req.snomed(score_lookup): self.total_score()},
)
)
return codes