#!/usr/bin/env python
"""
camcops_server/tasks/demqol.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, Optional, Tuple, Type, Union
from cardinal_pythonlib.stringfunc import strseq
import cardinal_pythonlib.rnc_web as ws
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.sqltypes import Float, Integer
from camcops_server.cc_modules.cc_constants import CssClass
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,
get_yes_no,
subheading_spanning_two_columns,
tr_qa,
)
from camcops_server.cc_modules.cc_request import CamcopsRequest
from camcops_server.cc_modules.cc_sqla_coltypes import (
CamcopsColumn,
PermittedValueChecker,
)
from camcops_server.cc_modules.cc_summaryelement import SummaryElement
from camcops_server.cc_modules.cc_task import (
get_from_dict,
Task,
TaskHasClinicianMixin,
TaskHasPatientMixin,
TaskHasRespondentMixin,
)
from camcops_server.cc_modules.cc_trackerhelpers import TrackerInfo
# =============================================================================
# Constants
# =============================================================================
DP = 2
MISSING_VALUE = -99
PERMITTED_VALUES = list(range(1, 4 + 1)) + [MISSING_VALUE]
END_DIV = f"""
</table>
<div class="{CssClass.FOOTNOTES}">
[1] Extrapolated total scores are: total_for_responded_questions ×
n_questions / n_responses.
</div>
"""
COPYRIGHT_DIV = f"""
<div class="{CssClass.COPYRIGHT}">
DEMQOL/DEMQOL-Proxy: Copyright © Institute of Psychiatry, King’s
College London. Reproduced with permission.
</div>
"""
# =============================================================================
# DEMQOL
# =============================================================================
class DemqolMetaclass(DeclarativeMeta):
# noinspection PyInitNewSignature
def __init__(
cls: Type["Demqol"],
name: str,
bases: Tuple[Type, ...],
classdict: Dict[str, Any],
) -> None:
add_multiple_columns(
cls,
"q",
1,
cls.N_SCORED_QUESTIONS,
pv=PERMITTED_VALUES,
comment_fmt="Q{n}. {s} (1 a lot - 4 not at all; -99 no response)",
comment_strings=[
# 1-13
"cheerful",
"worried/anxious",
"enjoying life",
"frustrated",
"confident",
"full of energy",
"sad",
"lonely",
"distressed",
"lively",
"irritable",
"fed up",
"couldn't do things",
# 14-19
"worried: forget recent",
"worried: forget people",
"worried: forget day",
"worried: muddled",
"worried: difficulty making decisions",
"worried: poor concentration",
# 20-28
"worried: not enough company",
"worried: get on with people close",
"worried: affection",
"worried: people not listening",
"worried: making self understood",
"worried: getting help",
"worried: toilet",
"worried: feel in self",
"worried: health overall",
],
)
super().__init__(name, bases, classdict)
[docs]class Demqol(
TaskHasPatientMixin, TaskHasClinicianMixin, Task, metaclass=DemqolMetaclass
):
"""
Server implementation of the DEMQOL task.
"""
__tablename__ = "demqol"
shortname = "DEMQOL"
provides_trackers = True
q29 = CamcopsColumn(
"q29",
Integer,
permitted_value_checker=PermittedValueChecker(
permitted_values=PERMITTED_VALUES
),
comment="Q29. Overall quality of life (1 very good - 4 poor; "
"-99 no response).",
)
NQUESTIONS = 29
N_SCORED_QUESTIONS = 28
MINIMUM_N_FOR_TOTAL_SCORE = 14
REVERSE_SCORE = [1, 3, 5, 6, 10, 29] # questions scored backwards
MIN_SCORE = N_SCORED_QUESTIONS
MAX_SCORE = MIN_SCORE * 4
COMPLETENESS_FIELDS = strseq("q", 1, NQUESTIONS)
[docs] @staticmethod
def longname(req: "CamcopsRequest") -> str:
_ = req.gettext
return _("Dementia Quality of Life measure, self-report version")
[docs] def is_complete(self) -> bool:
return (
self.all_fields_not_none(self.COMPLETENESS_FIELDS)
and self.field_contents_valid()
)
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]:
return [
TrackerInfo(
value=self.total_score(),
plot_label="DEMQOL total score",
axis_label=(
f"Total score (range {self.MIN_SCORE}–{self.MAX_SCORE}, "
f"higher better)"
),
axis_min=self.MIN_SCORE - 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=(
f"Total score {ws.number_to_dp(self.total_score(), DP)} "
f"(range {self.MIN_SCORE}–{self.MAX_SCORE}, higher better)"
)
)
]
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]:
return self.standard_task_summary_fields() + [
SummaryElement(
name="total",
coltype=Float(),
value=self.total_score(),
comment=f"Total score ({self.MIN_SCORE}-{self.MAX_SCORE})",
)
]
def totalscore_extrapolated(self) -> Tuple[float, bool]:
return calc_total_score(
obj=self,
n_scored_questions=self.N_SCORED_QUESTIONS,
reverse_score_qs=self.REVERSE_SCORE,
minimum_n_for_total_score=self.MINIMUM_N_FOR_TOTAL_SCORE,
)
def total_score(self) -> float:
(total, extrapolated) = self.totalscore_extrapolated()
return total
def get_q(self, req: CamcopsRequest, n: int) -> str:
nstr = str(n)
return "Q" + nstr + ". " + self.wxstring(req, "proxy_q" + nstr)
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
(total, extrapolated) = self.totalscore_extrapolated()
main_dict = {
None: None,
1: "1 — " + self.wxstring(req, "a1"),
2: "2 — " + self.wxstring(req, "a2"),
3: "3 — " + self.wxstring(req, "a3"),
4: "4 — " + self.wxstring(req, "a4"),
MISSING_VALUE: self.wxstring(req, "no_response"),
}
last_q_dict = {
None: None,
1: "1 — " + self.wxstring(req, "q29_a1"),
2: "2 — " + self.wxstring(req, "q29_a2"),
3: "3 — " + self.wxstring(req, "q29_a3"),
4: "4 — " + self.wxstring(req, "q29_a4"),
MISSING_VALUE: self.wxstring(req, "no_response"),
}
instruction_dict = {
1: self.wxstring(req, "instruction11"),
14: self.wxstring(req, "instruction12"),
20: self.wxstring(req, "instruction13"),
29: self.wxstring(req, "instruction14"),
}
# https://docs.python.org/2/library/stdtypes.html#mapping-types-dict
# http://paltman.com/try-except-performance-in-python-a-simple-test/
h = f"""
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{self.get_is_complete_tr(req)}
<tr>
<td>Total score ({self.MIN_SCORE}–{self.MAX_SCORE}),
higher better</td>
<td>{answer(ws.number_to_dp(total, DP))}</td>
</tr>
<tr>
<td>Total score extrapolated using incomplete
responses? <sup>[1]</sup></td>
<td>{answer(get_yes_no(req, extrapolated))}</td>
</tr>
</table>
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="50%">Question</th>
<th width="50%">Answer</th>
</tr>
"""
for n in range(1, self.NQUESTIONS + 1):
if n in instruction_dict:
h += subheading_spanning_two_columns(instruction_dict.get(n))
d = main_dict if n <= self.N_SCORED_QUESTIONS else last_q_dict
q = self.get_q(req, n)
a = get_from_dict(d, getattr(self, "q" + str(n)))
h += tr_qa(q, a)
h += END_DIV + COPYRIGHT_DIV
return h
# =============================================================================
# DEMQOL-Proxy
# =============================================================================
class DemqolProxyMetaclass(DeclarativeMeta):
# noinspection PyInitNewSignature
def __init__(
cls: Type["DemqolProxy"],
name: str,
bases: Tuple[Type, ...],
classdict: Dict[str, Any],
) -> None:
add_multiple_columns(
cls,
"q",
1,
cls.N_SCORED_QUESTIONS,
pv=PERMITTED_VALUES,
comment_fmt="Q{n}. {s} (1 a lot - 4 not at all; -99 no response)",
comment_strings=[
# 1-11
"cheerful",
"worried/anxious",
"frustrated",
"full of energy",
"sad",
"content",
"distressed",
"lively",
"irritable",
"fed up",
"things to look forward to",
# 12-20
"worried: memory in general",
"worried: forget distant",
"worried: forget recent",
"worried: forget people",
"worried: forget place",
"worried: forget day",
"worried: muddled",
"worried: difficulty making decisions",
"worried: making self understood",
# 21-31
"worried: keeping clean",
"worried: keeping self looking nice",
"worried: shopping",
"worried: using money to pay",
"worried: looking after finances",
"worried: taking longer",
"worried: getting in touch with people",
"worried: not enough company",
"worried: not being able to help others",
"worried: not playing a useful part",
"worried: physical health",
],
)
super().__init__(name, bases, classdict)
[docs]class DemqolProxy(
TaskHasPatientMixin,
TaskHasRespondentMixin,
TaskHasClinicianMixin,
Task,
metaclass=DemqolProxyMetaclass,
):
__tablename__ = "demqolproxy"
shortname = "DEMQOL-Proxy"
extrastring_taskname = "demqol"
info_filename_stem = "demqol"
q32 = CamcopsColumn(
"q32",
Integer,
permitted_value_checker=PermittedValueChecker(
permitted_values=PERMITTED_VALUES
),
comment="Q32. Overall quality of life (1 very good - 4 poor; "
"-99 no response).",
)
NQUESTIONS = 32
N_SCORED_QUESTIONS = 31
MINIMUM_N_FOR_TOTAL_SCORE = 16
REVERSE_SCORE = [1, 4, 6, 8, 11, 32] # questions scored backwards
MIN_SCORE = N_SCORED_QUESTIONS
MAX_SCORE = MIN_SCORE * 4
COMPLETENESS_FIELDS = strseq("q", 1, NQUESTIONS)
[docs] @staticmethod
def longname(req: "CamcopsRequest") -> str:
_ = req.gettext
return _("Dementia Quality of Life measure, proxy version")
[docs] def is_complete(self) -> bool:
return (
self.all_fields_not_none(self.COMPLETENESS_FIELDS)
and self.field_contents_valid()
)
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]:
return [
TrackerInfo(
value=self.total_score(),
plot_label="DEMQOL-Proxy total score",
axis_label=(
f"Total score (range {self.MIN_SCORE}–{self.MAX_SCORE},"
f" higher better)"
),
axis_min=self.MIN_SCORE - 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=(
f"Total score {ws.number_to_dp(self.total_score(), DP)} "
f"(range {self.MIN_SCORE}–{self.MAX_SCORE}, higher better)"
)
)
]
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]:
return self.standard_task_summary_fields() + [
SummaryElement(
name="total",
coltype=Float(),
value=self.total_score(),
comment=f"Total score ({self.MIN_SCORE}-{self.MAX_SCORE})",
)
]
def totalscore_extrapolated(self) -> Tuple[float, bool]:
return calc_total_score(
obj=self,
n_scored_questions=self.N_SCORED_QUESTIONS,
reverse_score_qs=self.REVERSE_SCORE,
minimum_n_for_total_score=self.MINIMUM_N_FOR_TOTAL_SCORE,
)
def total_score(self) -> float:
(total, extrapolated) = self.totalscore_extrapolated()
return total
def get_q(self, req: CamcopsRequest, n: int) -> str:
nstr = str(n)
return "Q" + nstr + ". " + self.wxstring(req, "proxy_q" + nstr)
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
(total, extrapolated) = self.totalscore_extrapolated()
main_dict = {
None: None,
1: "1 — " + self.wxstring(req, "a1"),
2: "2 — " + self.wxstring(req, "a2"),
3: "3 — " + self.wxstring(req, "a3"),
4: "4 — " + self.wxstring(req, "a4"),
MISSING_VALUE: self.wxstring(req, "no_response"),
}
last_q_dict = {
None: None,
1: "1 — " + self.wxstring(req, "q29_a1"),
2: "2 — " + self.wxstring(req, "q29_a2"),
3: "3 — " + self.wxstring(req, "q29_a3"),
4: "4 — " + self.wxstring(req, "q29_a4"),
MISSING_VALUE: self.wxstring(req, "no_response"),
}
instruction_dict = {
1: self.wxstring(req, "proxy_instruction11"),
12: self.wxstring(req, "proxy_instruction12"),
21: self.wxstring(req, "proxy_instruction13"),
32: self.wxstring(req, "proxy_instruction14"),
}
h = f"""
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{self.get_is_complete_tr(req)}
<tr>
<td>Total score ({self.MIN_SCORE}–{self.MAX_SCORE}),
higher better</td>
<td>{answer(ws.number_to_dp(total, DP))}</td>
</tr>
<tr>
<td>Total score extrapolated using incomplete
responses? <sup>[1]</sup></td>
<td>{answer(get_yes_no(req, extrapolated))}</td>
</tr>
</table>
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="50%">Question</th>
<th width="50%">Answer</th>
</tr>
"""
for n in range(1, self.NQUESTIONS + 1):
if n in instruction_dict:
h += subheading_spanning_two_columns(instruction_dict.get(n))
d = main_dict if n <= self.N_SCORED_QUESTIONS else last_q_dict
q = self.get_q(req, n)
a = get_from_dict(d, getattr(self, "q" + str(n)))
h += tr_qa(q, a)
h += END_DIV + COPYRIGHT_DIV
return h
# =============================================================================
# Common scoring function
# =============================================================================
[docs]def calc_total_score(
obj: Union[Demqol, DemqolProxy],
n_scored_questions: int,
reverse_score_qs: List[int],
minimum_n_for_total_score: int,
) -> Tuple[Optional[float], bool]:
"""Returns (total, extrapolated?)."""
n = 0
total = 0
for q in range(1, n_scored_questions + 1):
x = getattr(obj, "q" + str(q))
if x is None or x == MISSING_VALUE:
continue
if q in reverse_score_qs:
x = 5 - x
n += 1
total += x
if n < minimum_n_for_total_score:
return None, False
if n < n_scored_questions:
return n_scored_questions * total / n, True
return total, False