#!/usr/bin/env python
# camcops_server/tasks/bprs.py
"""
===============================================================================
Copyright (C) 2012-2018 Rudolf Cardinal (rudolf@pobox.com).
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 <http://www.gnu.org/licenses/>.
===============================================================================
"""
from typing import Any, Dict, List, Tuple, Type
from cardinal_pythonlib.stringfunc import strseq
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.sqltypes import Integer
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 answer, 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,
TaskHasClinicianMixin,
TaskHasPatientMixin,
)
from camcops_server.cc_modules.cc_trackerhelpers import TrackerInfo
# =============================================================================
# BPRS
# =============================================================================
class BprsMetaclass(DeclarativeMeta):
# noinspection PyInitNewSignature
def __init__(cls: Type['Bprs'],
name: str,
bases: Tuple[Type, ...],
classdict: Dict[str, Any]) -> None:
add_multiple_columns(
cls, "q", 1, cls.NQUESTIONS,
minimum=0, maximum=7,
comment_fmt="Q{n}, {s} (1-7, higher worse, 0 for unable to rate)",
comment_strings=[
"somatic concern", "anxiety", "emotional withdrawal",
"conceptual disorganisation", "guilt", "tension",
"mannerisms/posturing", "grandiosity", "depressive mood",
"hostility", "suspiciousness", "hallucinatory behaviour",
"motor retardation", "uncooperativeness",
"unusual thought content", "blunted affect", "excitement",
"disorientation", "severity of illness", "global improvement"]
)
super().__init__(name, bases, classdict)
[docs]class Bprs(TaskHasPatientMixin, TaskHasClinicianMixin, Task,
metaclass=BprsMetaclass):
__tablename__ = "bprs"
shortname = "BPRS"
longname = "Brief Psychiatric Rating Scale"
provides_trackers = True
NQUESTIONS = 20
TASK_FIELDS = strseq("q", 1, NQUESTIONS)
SCORED_FIELDS = [x for x in TASK_FIELDS if (x != "q19" and x != "q20")]
MAX_SCORE = 126
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]:
return [TrackerInfo(
value=self.total_score(),
plot_label="BPRS total score",
axis_label="Total score (out of {})".format(self.MAX_SCORE),
axis_min=-0.5,
axis_max=self.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="BPRS total score {}/{}".format(self.total_score(),
self.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="Total score (/{})".format(self.MAX_SCORE)),
]
[docs] def is_complete(self) -> bool:
return (
self.are_all_fields_complete(Bprs.TASK_FIELDS) and
self.field_contents_valid()
)
def total_score(self) -> int:
return self.sum_fields(Bprs.SCORED_FIELDS, ignorevalue=0)
# "0" means "not rated"
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
main_dict = {
None: None,
0: "0 — " + self.wxstring(req, "old_option0"),
1: "1 — " + self.wxstring(req, "old_option1"),
2: "2 — " + self.wxstring(req, "old_option2"),
3: "3 — " + self.wxstring(req, "old_option3"),
4: "4 — " + self.wxstring(req, "old_option4"),
5: "5 — " + self.wxstring(req, "old_option5"),
6: "6 — " + self.wxstring(req, "old_option6"),
7: "7 — " + self.wxstring(req, "old_option7")
}
q19_dict = {
None: None,
1: self.wxstring(req, "q19_option1"),
2: self.wxstring(req, "q19_option2"),
3: self.wxstring(req, "q19_option3"),
4: self.wxstring(req, "q19_option4"),
5: self.wxstring(req, "q19_option5"),
6: self.wxstring(req, "q19_option6"),
7: self.wxstring(req, "q19_option7")
}
q20_dict = {
None: None,
0: self.wxstring(req, "q20_option0"),
1: self.wxstring(req, "q20_option1"),
2: self.wxstring(req, "q20_option2"),
3: self.wxstring(req, "q20_option3"),
4: self.wxstring(req, "q20_option4"),
5: self.wxstring(req, "q20_option5"),
6: self.wxstring(req, "q20_option6"),
7: self.wxstring(req, "q20_option7")
}
q_a = ""
for i in range(1, Bprs.NQUESTIONS - 1): # only does 1-18
q_a += tr_qa(
self.wxstring(req, "q" + str(i) + "_title"),
get_from_dict(main_dict, getattr(self, "q" + str(i)))
)
q_a += tr_qa(self.wxstring(req, "q19_title"),
get_from_dict(q19_dict, self.q19))
q_a += tr_qa(self.wxstring(req, "q20_title"),
get_from_dict(q20_dict, self.q20))
h = """
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{tr_is_complete}
{total_score}
</table>
</div>
<div class="{CssClass.EXPLANATION}">
Ratings pertain to the past week, or behaviour during
interview. Each question has specific answer definitions (see
e.g. tablet app).
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="60%">Question</th>
<th width="40%">Answer <sup>[2]</sup></th>
</tr>
{q_a}
</table>
<div class="{CssClass.FOOTNOTES}">
[1] Only questions 1–18 are scored.
[2] All answers are in the range 1–7, or 0 (not assessed, for
some).
</div>
""".format(
CssClass=CssClass,
tr_is_complete=self.get_is_complete_tr(req),
total_score=tr(
req.wappstring("total_score") +
" (0–{maxscore}; 18–{maxscore} if all rated) "
"<sup>[1]</sup>".format(maxscore=self.MAX_SCORE),
answer(self.total_score())
),
q_a=q_a,
)
return h