"""
camcops_server/tasks/mfi20.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/>.
===============================================================================
**Multidimensional Fatigue Inventory (MFI-20) task.**
"""
from camcops_server.cc_modules.cc_constants import CssClass
from camcops_server.cc_modules.cc_html import tr_qa, tr, answer
from camcops_server.cc_modules.cc_request import CamcopsRequest
from camcops_server.cc_modules.cc_sqla_coltypes import (
CamcopsColumn,
ONE_TO_FIVE_CHECKER,
)
from camcops_server.cc_modules.cc_summaryelement import SummaryElement
from camcops_server.cc_modules.cc_task import TaskHasPatientMixin, Task
from camcops_server.cc_modules.cc_text import SS
from cardinal_pythonlib.stringfunc import strseq
from sqlalchemy import Integer
from sqlalchemy.ext.declarative import DeclarativeMeta
from typing import List, Type, Tuple, Dict, Any
class Mfi20Metaclass(DeclarativeMeta):
# noinspection PyInitNewSignature
def __init__(
cls: Type["Mfi20"],
name: str,
bases: Tuple[Type, ...],
classdict: Dict[str, Any],
) -> None:
comment_strings = [
"feel fit",
"physically little",
"feel active",
"nice things",
"tired",
"do a lot",
"keep thought on",
"take on a lot",
"dread",
"think little",
"concentrate",
"rested",
"effort concentrate",
"bad condition",
"plans",
"tire",
"get little done",
"don't feel like",
"thoughts wander",
"excellent condition",
]
score_comment = "(1 yes - 5 no)"
for q_index in range(0, cls.N_QUESTIONS):
q_num = q_index + 1
q_field = "q{}".format(q_num)
setattr(
cls,
q_field,
CamcopsColumn(
q_field,
Integer,
permitted_value_checker=ONE_TO_FIVE_CHECKER,
comment="Q{} ({}) {}".format(
q_num, comment_strings[q_index], score_comment
),
),
)
super().__init__(name, bases, classdict)
[docs]class Mfi20(TaskHasPatientMixin, Task, metaclass=Mfi20Metaclass):
__tablename__ = "mfi20"
shortname = "MFI-20"
prohibits_clinical = True
prohibits_commercial = True
N_QUESTIONS = 20
MIN_SCORE_PER_Q = 1
MAX_SCORE_PER_Q = 5
MIN_SCORE = MIN_SCORE_PER_Q * N_QUESTIONS
MAX_SCORE = MAX_SCORE_PER_Q * N_QUESTIONS
N_Q_PER_SUBSCALE = 4 # always
MIN_SUBSCALE = MIN_SCORE_PER_Q * N_Q_PER_SUBSCALE
MAX_SUBSCALE = MAX_SCORE_PER_Q * N_Q_PER_SUBSCALE
ALL_QUESTIONS = strseq("q", 1, N_QUESTIONS)
REVERSE_QUESTIONS = Task.fieldnames_from_list(
"q", {2, 5, 9, 10, 13, 14, 16, 17, 18, 19}
)
GENERAL_FATIGUE_QUESTIONS = Task.fieldnames_from_list("q", {1, 5, 12, 16})
PHYSICAL_FATIGUE_QUESTIONS = Task.fieldnames_from_list("q", {2, 8, 14, 20})
REDUCED_ACTIVITY_QUESTIONS = Task.fieldnames_from_list("q", {3, 6, 10, 17})
REDUCED_MOTIVATION_QUESTIONS = Task.fieldnames_from_list(
"q", {4, 9, 15, 18}
)
MENTAL_FATIGUE_QUESTIONS = Task.fieldnames_from_list("q", {7, 11, 13, 19})
[docs] @staticmethod
def longname(req: "CamcopsRequest") -> str:
_ = req.gettext
return _("Multidimensional Fatigue Inventory")
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]:
subscale_range = f"[{self.MIN_SUBSCALE}–{self.MAX_SUBSCALE}]"
return self.standard_task_summary_fields() + [
SummaryElement(
name="total",
coltype=Integer(),
value=self.total_score(),
comment=f"Total score [{self.MIN_SCORE}–{self.MAX_SCORE}]",
),
SummaryElement(
name="general_fatigue",
coltype=Integer(),
value=self.general_fatigue_score(),
comment=f"General fatigue {subscale_range}",
),
SummaryElement(
name="physical_fatigue",
coltype=Integer(),
value=self.physical_fatigue_score(),
comment=f"Physical fatigue {subscale_range}",
),
SummaryElement(
name="reduced_activity",
coltype=Integer(),
value=self.reduced_activity_score(),
comment=f"Reduced activity {subscale_range}",
),
SummaryElement(
name="reduced_motivation",
coltype=Integer(),
value=self.reduced_motivation_score(),
comment=f"Reduced motivation {subscale_range}",
),
SummaryElement(
name="mental_fatigue",
coltype=Integer(),
value=self.mental_fatigue_score(),
comment=f"Mental fatigue {subscale_range}",
),
]
[docs] def is_complete(self) -> bool:
if self.any_fields_none(self.ALL_QUESTIONS):
return False
if not self.field_contents_valid():
return False
return True
def score_fields(self, fields: List[str]) -> int:
total = 0
for f in fields:
value = getattr(self, f)
if value is not None:
if f in self.REVERSE_QUESTIONS:
value = self.MAX_SCORE_PER_Q + 1 - value
total += value if value is not None else 0
return total
def total_score(self) -> int:
return self.score_fields(self.ALL_QUESTIONS)
def general_fatigue_score(self) -> int:
return self.score_fields(self.GENERAL_FATIGUE_QUESTIONS)
def physical_fatigue_score(self) -> int:
return self.score_fields(self.PHYSICAL_FATIGUE_QUESTIONS)
def reduced_activity_score(self) -> int:
return self.score_fields(self.REDUCED_ACTIVITY_QUESTIONS)
def reduced_motivation_score(self) -> int:
return self.score_fields(self.REDUCED_MOTIVATION_QUESTIONS)
def mental_fatigue_score(self) -> int:
return self.score_fields(self.MENTAL_FATIGUE_QUESTIONS)
[docs] def get_task_html(self, req: CamcopsRequest) -> str:
fullscale_range = f"[{self.MIN_SCORE}–{self.MAX_SCORE}]"
subscale_range = f"[{self.MIN_SUBSCALE}–{self.MAX_SUBSCALE}]"
rows = ""
for q_num in range(1, self.N_QUESTIONS + 1):
q_field = "q" + str(q_num)
question_cell = "{}. {}".format(q_num, self.wxstring(req, q_field))
score = getattr(self, q_field)
rows += tr_qa(question_cell, score)
html = """
<div class="{CssClass.SUMMARY}">
<table class="{CssClass.SUMMARY}">
{tr_is_complete}
{total_score}
{general_fatigue_score}
{physical_fatigue_score}
{reduced_activity_score}
{reduced_motivation_score}
{mental_fatigue_score}
</table>
</div>
<table class="{CssClass.TASKDETAIL}">
<tr>
<th width="60%">Question</th>
<th width="40%">Answer <sup>[8]</sup></th>
</tr>
{rows}
</table>
<div class="{CssClass.FOOTNOTES}">
[1] Questions 2, 5, 9, 10, 13, 14, 16, 17, 18, 19
reverse-scored when summing.
[2] Sum for questions 1–20.
[3] General fatigue: Sum for questions 1, 5, 12, 16.
[4] Physical fatigue: Sum for questions 2, 8, 14, 20.
[5] Reduced activity: Sum for questions 3, 6, 10, 17.
[6] Reduced motivation: Sum for questions 4, 9, 15, 18.
[7] Mental fatigue: Sum for questions 7, 11, 13, 19.
[8] All questions are rated from “1 – yes, that is true” to
“5 – no, that is not true”.
</div>
""".format(
CssClass=CssClass,
tr_is_complete=self.get_is_complete_tr(req),
total_score=tr(
req.sstring(SS.TOTAL_SCORE) + " <sup>[1][2]</sup>",
f"{answer(self.total_score())} {fullscale_range}",
),
general_fatigue_score=tr(
self.wxstring(req, "general_fatigue") + " <sup>[1][3]</sup>",
f"{answer(self.general_fatigue_score())} {subscale_range}",
),
physical_fatigue_score=tr(
self.wxstring(req, "physical_fatigue") + " <sup>[1][4]</sup>",
f"{answer(self.physical_fatigue_score())} {subscale_range}",
),
reduced_activity_score=tr(
self.wxstring(req, "reduced_activity") + " <sup>[1][5]</sup>",
f"{answer(self.reduced_activity_score())} {subscale_range}",
),
reduced_motivation_score=tr(
self.wxstring(req, "reduced_motivation")
+ " <sup>[1][6]</sup>",
f"{answer(self.reduced_motivation_score())} {subscale_range}",
),
mental_fatigue_score=tr(
self.wxstring(req, "mental_fatigue") + " <sup>[1][7]</sup>",
f"{answer(self.mental_fatigue_score())} {subscale_range}",
),
rows=rows,
)
return html