Source code for camcops_server.tasks.edeq

#!/usr/bin/env python

"""
camcops_server/tasks/edeq.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/>.

===============================================================================

**Eating Disorder Examination Questionnaire (EDE-Q 6.0) task.**

"""

import statistics
from typing import Any, Dict, List, Optional, Type, Tuple

from cardinal_pythonlib.stringfunc import strnumlist, strseq
from sqlalchemy import Column
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.sqltypes import Boolean, Float, Integer

from camcops_server.cc_modules.cc_constants import CssClass
from camcops_server.cc_modules.cc_db import add_multiple_columns
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_task import TaskHasPatientMixin, Task
from camcops_server.cc_modules.cc_text import SS


class EdeqMetaclass(DeclarativeMeta):
    def __init__(
        cls: Type["Edeq"],
        name: str,
        bases: Tuple[Type, ...],
        classdict: Dict[str, Any],
    ) -> None:

        add_multiple_columns(
            cls,
            "q",
            1,
            12,
            coltype=Integer,
            minimum=0,
            maximum=6,
            comment_fmt="Q{n} - {s}",
            comment_strings=[
                "days limit the amount of food 0-6 (no days - every day)",
                "days long periods without eating 0-6 (no days - every day)",
                "days exclude from diet 0-6 (no days - every day)",
                "days follow rules 0-6 (no days - every day)",
                "days desire empty stomach 0-6 (no days - every day)",
                "days desire flat stomach 0-6 (no days - every day)",
                "days thinking about food 0-6 (no days - every day)",
                "days thinking about shape 0-6 (no days - every day)",
                "days fear losing control 0-6 (no days - every day)",
                "days fear weight gain 0-6 (no days - every day)",
                "days felt fat 0-6 (no days - every day)",
                "days desire lose weight 0-6 (no days - every day)",
            ],
        )

        add_multiple_columns(
            cls,
            "q",
            13,
            18,
            coltype=Integer,
            comment_fmt="Q{n} - {s}",
            comment_strings=[
                "times eaten unusually large amount of food",
                "times sense lost control",
                "days episodes of overeating",
                "times made self sick",
                "times taken laxatives",
                "times exercised in driven or compulsive way",
            ],
        )

        add_multiple_columns(
            cls,
            "q",
            19,
            21,
            coltype=Integer,
            minimum=0,
            maximum=6,
            comment_fmt="Q{n} - {s}",
            comment_strings=[
                "days eaten in secret (no days - every day)",
                "times felt guilty (none of the times - every time)",
                "concern about people seeing you eat (not at all - markedly)",
            ],
        )

        add_multiple_columns(
            cls,
            "q",
            22,
            28,
            coltype=Integer,
            minimum=0,
            maximum=6,
            comment_fmt="Q{n} - {s}",
            comment_strings=[
                "weight influenced how you judge self (not at all - markedly)",
                "shape influenced how you judge self (not at all - markedly)",
                "upset if asked to weigh self (not at all - markedly)",
                "dissatisfied with weight (not at all - markedly)",
                "dissatisfied with shape (not at all - markedly)",
                "uncomfortable seeing body (not at all - markedly)",
                "uncomfortable others seeing shape (not at all - markedly)",
            ],
        )

        setattr(
            cls,
            "mass_kg",
            Column("mass_kg", Float, comment="Mass (kg)"),
        )

        setattr(
            cls,
            "height_m",
            Column("height_m", Float, comment="Height (m)"),
        )

        setattr(
            cls,
            "num_periods_missed",
            Column(
                "num_periods_missed",
                Integer,
                comment="Number of periods missed",
            ),
        )

        setattr(
            cls,
            "pill",
            Column(
                "pill", Boolean, comment="Taking the (oral contraceptive) pill"
            ),
        )

        super().__init__(name, bases, classdict)


[docs]class Edeq(TaskHasPatientMixin, Task, metaclass=EdeqMetaclass): __tablename__ = "edeq" shortname = "EDE-Q" N_QUESTIONS = 28 MEASUREMENT_FIELD_NAMES = ["mass_kg", "height_m"] COMMON_FIELD_NAMES = strseq("q", 1, N_QUESTIONS) + MEASUREMENT_FIELD_NAMES FEMALE_FIELD_NAMES = ["num_periods_missed", "pill"] RESTRAINT_Q_NUMS = [1, 2, 3, 4, 5] RESTRAINT_Q_STR = ", ".join(str(q) for q in RESTRAINT_Q_NUMS) RESTRAINT_FIELD_NAMES = strnumlist("q", RESTRAINT_Q_NUMS) EATING_CONCERN_Q_NUMS = [7, 9, 19, 20, 21] EATING_CONCERN_Q_STR = ", ".join(str(q) for q in EATING_CONCERN_Q_NUMS) EATING_CONCERN_FIELD_NAMES = strnumlist("q", EATING_CONCERN_Q_NUMS) SHAPE_CONCERN_Q_NUMS = [6, 8, 10, 11, 23, 26, 27, 28] SHAPE_CONCERN_Q_STR = ", ".join(str(q) for q in SHAPE_CONCERN_Q_NUMS) SHAPE_CONCERN_FIELD_NAMES = strnumlist("q", SHAPE_CONCERN_Q_NUMS) WEIGHT_CONCERN_Q_NUMS = [8, 12, 22, 24, 25] WEIGHT_CONCERN_Q_STR = ", ".join(str(q) for q in WEIGHT_CONCERN_Q_NUMS) WEIGHT_CONCERN_FIELD_NAMES = strnumlist("q", WEIGHT_CONCERN_Q_NUMS)
[docs] @staticmethod def longname(req: CamcopsRequest) -> str: _ = req.gettext return _("Eating Disorder Examination Questionnaire")
[docs] def is_complete(self) -> bool: if self.any_fields_none(self.COMMON_FIELD_NAMES): return False if self.patient.sex == "F" and self.any_fields_none( self.FEMALE_FIELD_NAMES ): return False return True
[docs] def get_task_html(self, req: CamcopsRequest) -> str: score_range = "[0–6]" rows = "" for q_num in range(1, self.N_QUESTIONS + 1): field = "q" + str(q_num) question_cell = self.xstring(req, field) rows += tr_qa(question_cell, self.get_answer_cell(req, q_num)) mass = getattr(self, "mass_kg") if mass is not None: mass = f"{mass} kg" height = getattr(self, "height_m") if height is not None: height = f"{height} m" rows += tr_qa(self.xstring(req, "mass_kg"), mass) rows += tr_qa(self.xstring(req, "height_m"), height) if self.patient.is_female(): for field in self.FEMALE_FIELD_NAMES: rows += tr_qa(self.xstring(req, field), getattr(self, field)) html = """ <div class="{CssClass.SUMMARY}"> <table class="{CssClass.SUMMARY}"> {tr_is_complete} {global_score} {restraint_score} {eating_concern_score} {shape_concern_score} {weight_concern_score} </table> </div> <table class="{CssClass.TASKDETAIL}"> <tr> <th width="60%">Question</th> <th width="40%">Score</th> </tr> {rows} </table> <div class="{CssClass.FOOTNOTES}"> [1] Mean of four subscales. [2] Mean of questions {restraint_q_nums}. [3] Mean of questions {eating_concern_q_nums}. [4] Mean of questions {shape_concern_q_nums}. [5] Mean of questions {weight_concern_q_nums}. </div> """.format( CssClass=CssClass, tr_is_complete=self.get_is_complete_tr(req), global_score=tr( req.sstring(SS.TOTAL_SCORE) + " <sup>[1]</sup>", f"{answer(self.global_score())} {score_range}", ), restraint_score=tr( self.wxstring(req, "restraint") + " <sup>[2]</sup>", f"{answer(self.restraint())} {score_range}", ), eating_concern_score=tr( self.wxstring(req, "eating_concern") + " <sup>[3]</sup>", f"{answer(self.eating_concern())} {score_range}", ), shape_concern_score=tr( self.wxstring(req, "shape_concern") + " <sup>[4]</sup>", f"{answer(self.shape_concern())} {score_range}", ), weight_concern_score=tr( self.wxstring(req, "weight_concern") + " <sup>[5]</sup>", f"{answer(self.weight_concern())} {score_range}", ), rows=rows, restraint_q_nums=self.RESTRAINT_Q_STR, eating_concern_q_nums=self.EATING_CONCERN_Q_STR, shape_concern_q_nums=self.SHAPE_CONCERN_Q_STR, weight_concern_q_nums=self.WEIGHT_CONCERN_Q_STR, ) return html
def get_answer_cell( self, req: CamcopsRequest, q_num: int ) -> Optional[str]: q_field = "q" + str(q_num) score = getattr(self, q_field) if score is None or (13 <= q_num <= 18): return score meaning = self.get_score_meaning(req, q_num, score) answer_cell = f"{score} [{meaning}]" return answer_cell def get_score_meaning( self, req: CamcopsRequest, q_num: int, score: int ) -> str: if q_num <= 12 or q_num == 19: return self.wxstring(req, f"days_option_{score}") if q_num == 20: return self.wxstring(req, f"freq_option_{score}") if score % 2 == 1: previous = self.wxstring(req, f"how_much_option_{score-1}") next_ = self.wxstring(req, f"how_much_option_{score+1}") return f"{previous}{next_}" return self.wxstring(req, f"how_much_option_{score}") def restraint(self) -> Optional[float]: return self.subscale(self.RESTRAINT_FIELD_NAMES) def eating_concern(self) -> Optional[float]: return self.subscale(self.EATING_CONCERN_FIELD_NAMES) def shape_concern(self) -> Optional[float]: return self.subscale(self.SHAPE_CONCERN_FIELD_NAMES) def weight_concern(self) -> Optional[float]: return self.subscale(self.WEIGHT_CONCERN_FIELD_NAMES) def subscale(self, field_names: List[str]) -> Optional[float]: if self.any_fields_none(field_names): return None return self.mean_fields(field_names) def global_score(self) -> Optional[float]: subscales = [ self.restraint(), self.eating_concern(), self.shape_concern(), self.weight_concern(), ] if None in subscales: return None return statistics.mean(subscales)