Source code for camcops_server.tasks.cesdr

#!/usr/bin/env python

"""
camcops_server/tasks/cesdr.py

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

    Copyright (C) 2012-2019 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.classes import classproperty
from cardinal_pythonlib.stringfunc import strseq
from semantic_version import Version
from sqlalchemy.ext.declarative import DeclarativeMeta
from sqlalchemy.sql.sqltypes import Boolean

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 (
    get_yes_no, 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,
    TaskHasPatientMixin,
)
from camcops_server.cc_modules.cc_text import SS
from camcops_server.cc_modules.cc_trackerhelpers import (
    equally_spaced_int,
    regular_tracker_axis_ticks_int,
    TrackerInfo,
    TrackerLabel,
)


# =============================================================================
# CESD-R
# =============================================================================

[docs]class CesdrMetaclass(DeclarativeMeta): """ There is a multilayer metaclass problem; see hads.py for discussion. """ # noinspection PyInitNewSignature def __init__(cls: Type['Cesdr'], name: str, bases: Tuple[Type, ...], classdict: Dict[str, Any]) -> None: add_multiple_columns( cls, "q", 1, cls.N_QUESTIONS, minimum=0, maximum=4, comment_fmt=("Q{n} ({s}) (0 not at all - " "4 nearly every day for two weeks)"), comment_strings=[ "poor appetite", "unshakable blues", "poor concentration", "depressed", "sleep restless", "sad", "could not get going", "nothing made me happy", "felt a bad person", "loss of interest", "oversleeping", "moving slowly", "fidgety", "wished were dead", "wanted to hurt self", "tiredness", "disliked self", "unintended weight loss", "difficulty getting to sleep", "lack of focus", ] ) super().__init__(name, bases, classdict)
[docs]class Cesdr(TaskHasPatientMixin, Task, metaclass=CesdrMetaclass): """ Server implementation of the CESD task. """ __tablename__ = 'cesdr' shortname = 'CESD-R' provides_trackers = True extrastring_taskname = "cesdr" CAT_NONCLINICAL = 0 CAT_SUB = 1 CAT_POSS_MAJOR = 2 CAT_PROB_MAJOR = 3 CAT_MAJOR = 4 DEPRESSION_RISK_THRESHOLD = 16 FREQ_NOT_AT_ALL = 0 FREQ_1_2_DAYS_LAST_WEEK = 1 FREQ_3_4_DAYS_LAST_WEEK = 2 FREQ_5_7_DAYS_LAST_WEEK = 3 FREQ_DAILY_2_WEEKS = 4 N_QUESTIONS = 20 N_ANSWERS = 5 POSS_MAJOR_THRESH = 2 PROB_MAJOR_THRESH = 3 MAJOR_THRESH = 4 SCORED_FIELDS = strseq("q", 1, N_QUESTIONS) TASK_FIELDS = SCORED_FIELDS MIN_SCORE = 0 MAX_SCORE = 3 * N_QUESTIONS
[docs] @staticmethod def longname(req: "CamcopsRequest") -> str: _ = req.gettext return _('Center for Epidemiologic Studies Depression Scale (Revised)')
# noinspection PyMethodParameters @classproperty def minimum_client_version(cls) -> Version: return Version("2.2.8")
[docs] def is_complete(self) -> bool: return ( self.all_fields_not_none(self.TASK_FIELDS) and self.field_contents_valid() )
def total_score(self) -> int: return ( self.sum_fields(self.SCORED_FIELDS) - self.count_where(self.SCORED_FIELDS, [self.FREQ_DAILY_2_WEEKS]) ) def get_depression_category(self) -> int: if not self.has_depression_risk(): return self.CAT_SUB q_group_anhedonia = [8, 10] q_group_dysphoria = [2, 4, 6] other_q_groups = { 'appetite': [1, 18], 'sleep': [5, 11, 19], 'thinking': [3, 20], 'guilt': [9, 17], 'tired': [7, 16], 'movement': [12, 13], 'suicidal': [14, 15] } # Dysphoria or anhedonia must be present at frequency FREQ_DAILY_2_WEEKS anhedonia_criterion = ( self.fulfils_group_criteria(q_group_anhedonia, True) or self.fulfils_group_criteria(q_group_dysphoria, True) ) if anhedonia_criterion: category_count_high_freq = 0 category_count_lower_freq = 0 for qgroup in other_q_groups.values(): if self.fulfils_group_criteria(qgroup, True): # Category contains an answer == FREQ_DAILY_2_WEEKS category_count_high_freq += 1 if self.fulfils_group_criteria(qgroup, False): # Category contains an answer == FREQ_DAILY_2_WEEKS or # FREQ_5_7_DAYS_LAST_WEEK category_count_lower_freq += 1 if category_count_high_freq >= self.MAJOR_THRESH: # Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS) # plus 4 other symptom groups at FREQ_DAILY_2_WEEKS return self.CAT_MAJOR if category_count_lower_freq >= self.PROB_MAJOR_THRESH: # Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS) # plus 3 other symptom groups at FREQ_DAILY_2_WEEKS or # FREQ_5_7_DAYS_LAST_WEEK return self.CAT_PROB_MAJOR if category_count_lower_freq >= self.POSS_MAJOR_THRESH: # Anhedonia or dysphoria (at FREQ_DAILY_2_WEEKS) # plus 2 other symptom groups at FREQ_DAILY_2_WEEKS or # FREQ_5_7_DAYS_LAST_WEEK return self.CAT_POSS_MAJOR if self.has_depression_risk(): # Total CESD-style score >= 16 but doesn't meet other criteria. return self.CAT_SUB return self.CAT_NONCLINICAL def fulfils_group_criteria(self, qnums: List[int], nearly_every_day_2w: bool) -> bool: qstrings = ["q" + str(qnum) for qnum in qnums] if nearly_every_day_2w: possible_values = [self.FREQ_DAILY_2_WEEKS] else: possible_values = [self.FREQ_5_7_DAYS_LAST_WEEK, self.FREQ_DAILY_2_WEEKS] count = self.count_where(qstrings, possible_values) return count > 0
[docs] def get_trackers(self, req: CamcopsRequest) -> List[TrackerInfo]: line_step = 20 threshold_line = self.DEPRESSION_RISK_THRESHOLD - 0.5 # noinspection PyTypeChecker return [TrackerInfo( value=self.total_score(), plot_label="CESD-R total score", axis_label=f"Total score ({self.MIN_SCORE}-{self.MAX_SCORE})", axis_min=self.MIN_SCORE - 0.5, axis_max=self.MAX_SCORE + 0.5, axis_ticks=regular_tracker_axis_ticks_int( self.MIN_SCORE, self.MAX_SCORE, step=line_step ), horizontal_lines=equally_spaced_int( self.MIN_SCORE + line_step, self.MAX_SCORE - line_step, step=line_step ) + [threshold_line], horizontal_labels=[ TrackerLabel(threshold_line, self.wxstring(req, "depression_or_risk_of")), ] )]
[docs] def get_clinical_text(self, req: CamcopsRequest) -> List[CtvInfo]: if not self.is_complete(): return CTV_INCOMPLETE return [CtvInfo( content=f"CESD-R total score {self.total_score()}" )]
[docs] def get_summaries(self, req: CamcopsRequest) -> List[SummaryElement]: return self.standard_task_summary_fields() + [ SummaryElement( name="depression_risk", coltype=Boolean(), value=self.has_depression_risk(), comment="Has depression or at risk of depression"), ]
def has_depression_risk(self) -> bool: return self.total_score() >= self.DEPRESSION_RISK_THRESHOLD
[docs] def get_task_html(self, req: CamcopsRequest) -> str: score = self.total_score() answer_dict = {None: None} for option in range(self.N_ANSWERS): answer_dict[option] = str(option) + " – " + \ self.wxstring(req, "a" + str(option)) q_a = "" for q in range(1, self.N_QUESTIONS): q_a += tr_qa( self.wxstring(req, "q" + str(q) + "_s"), get_from_dict(answer_dict, getattr(self, "q" + str(q))) ) tr_total_score = tr_qa( f"{req.sstring(SS.TOTAL_SCORE)} (0–60)", score ) tr_depression_or_risk_of = tr_qa( self.wxstring(req, "depression_or_risk_of") + "? <sup>[1]</sup>", get_yes_no(req, self.has_depression_risk()) ) tr_provisional_diagnosis = tr( 'Provisional diagnosis <sup>[2]</sup>', self.wxstring(req, "category_" + str(self.get_depression_category())) ) return f""" <div class="{CssClass.SUMMARY}"> <table class="{CssClass.SUMMARY}"> {self.get_is_complete_tr(req)} {tr_total_score} {tr_depression_or_risk_of} {tr_provisional_diagnosis} </table> </div> <table class="{CssClass.TASKDETAIL}"> <tr> <th width="70%">Question</th> <th width="30%">Answer</th> </tr> {q_a} </table> <div class="{CssClass.FOOTNOTES}"> [1] Presence of depression (or depression risk) is indicated by a score &ge; 16 [2] Diagnostic criteria described at <a href="https://cesd-r.com/cesdr/">https://cesd-r.com/cesdr/</a> </div> """ # noqa