feat(questionnaire): integrate revised intake and follow-up monitoring

Add gated TSQ, Russian C-SSRS Recent, durable responses and notifications, diaries, schedules and audited clinical review. Preserve manual assessment when the Russian follow-up source is unavailable.

Refs #52

app/core/intake_questions.py

@@ -0,0 +1,141 @@
+"""Question selection and exact versioned content, with no side effects."""
+
+from dataclasses import dataclass
+
+import yaml
+
+from app.config import get_settings
+from app.core.cssrs_content import load_cssrs_russian
+from app.core.questionnaire import IntakePolicy, alcohol_expansion, score_alcohol, score_cssrs_recent
+from app.core.scales import ScaleDef, load_scale
+
+
+@dataclass(frozen=True)
+class Question:
+    id: str
+    text: str
+    options: tuple[tuple[object, str], ...] = ()
+    period: str = "context"
+    numeric: bool = False
+    optional: bool = False
+
+
+def content() -> dict:
+    return yaml.safe_load((get_settings().config_dir / "instruments/intake_forms.yaml").read_text())
+
+
+def texts() -> dict:
+    return yaml.safe_load((get_settings().config_dir / "texts/intake.yaml").read_text())
+
+
+def scale_question(scale_id: str, item_id: str) -> Question:
+    forms = content()["forms"]
+    scale = ScaleDef.model_validate(forms[scale_id]) if scale_id in forms else load_scale(scale_id)
+    item = next(i for i in scale.items if i.id == item_id)
+    instruction = scale.instruction or ""
+    # The beverage table is part of the approved questionnaire source.
+    if item_id == "rus_audit_2":
+        instruction += "\n" + texts()["standard_drinks"]
+    return Question(
+        item_id,
+        instruction + "\n\n" + item.text,
+        tuple((o.value, o.label) for o in item.options),
+        scale.recall_period or "",
+    )
+
+
+def group_answers(answers: dict, prefix: str) -> dict[str, int]:
+    return {k: v for k, v in answers.items() if k.startswith(prefix + "_")}
+
+
+def cssrs_answers(answers: dict) -> dict[str, int]:
+    return {k.removeprefix("cssrs_"): v for k, v in answers.items() if k.startswith("cssrs_")}
+
+
+def next_intake(answers: dict, policy: IntakePolicy, sex: str | None) -> Question | None:
+    c = score_cssrs_recent(cssrs_answers(answers))
+    if c.missing:
+        form = load_cssrs_russian()
+        item = next(i for i in form.items if i.id == c.missing[0])
+        period = texts()["periods"][item.recall_period]
+        # Guidance is interviewer-facing; retained in the source and record version.
+        return Question(
+            "cssrs_" + item.id,
+            period + "\n\n" + item.text,
+            tuple((o.value, o.label) for o in form.options),
+            item.recall_period,
+        )
+    for item in ("phq9_1", "phq9_2"):
+        if item not in answers:
+            return scale_question("phq9", item)
+    if "trauma" not in answers:
+        return Question(
+            "trauma", content()["trauma_introduction"] + "\n\n" + content()["trauma_filter"], ((1, "Да"), (0, "Нет"))
+        )
+    if answers["trauma"]:
+        for item in load_scale("tsq").item_ids:
+            if item not in answers:
+                return scale_question("tsq", item)
+        if "recent_trauma" not in answers:
+            return Question("recent_trauma", texts()["recent_trauma"], ((1, "Да"), (0, "Нет")))
+    for item in load_scale("rus_audit_s").item_ids:
+        if item not in answers:
+            return scale_question("rus_audit_s", item)
+    if sex is None and "sex" not in answers:
+        return Question("sex", texts()["sex"], (("f", "Женский"), ("m", "Мужской"), ("unknown", "Не указывать")))
+    for key in ("tbi", "psychotropics"):
+        if key not in answers:
+            return Question(key, texts()[key], ((1, "Да"), (0, "Нет")))
+    if answers["phq9_1"] + answers["phq9_2"] >= policy.phq2_expand_at:
+        for item in load_scale("phq9").item_ids:
+            if item not in answers:
+                return scale_question("phq9", item)
+    if answers["trauma"] and sum(group_answers(answers, "tsq").values()) >= policy.tsq_expand_at:
+        for item in load_scale("pcl5").item_ids:
+            if item not in answers:
+                return scale_question("pcl5", item)
+    alcohol = group_answers(answers, "rus_audit")
+    selected_sex = sex or (answers.get("sex") if answers.get("sex") in ("m", "f") else None)
+    short = score_alcohol(
+        {k: v for k, v in alcohol.items() if k in load_scale("rus_audit_s").item_ids}, short=True, sex=selected_sex
+    )
+    if alcohol_expansion(short, policy):
+        for item in load_scale("rus_audit").item_ids:
+            if item == "rus_audit_2" and alcohol.get("rus_audit_1") == 0:
+                continue
+            if item not in answers:
+                return scale_question("rus_audit", item)
+    return None
+
+
+def diary_questions(
+    modules: list[str], *, suicide_monitoring: bool, weekday: int, day_index: int | None = None
+) -> tuple[Question, ...]:
+    config = yaml.safe_load((get_settings().config_dir / "instruments/diary.yaml").read_text())
+    selected = ["core"]
+    detailed = [name for name in ("veteran", "depression") if name in modules]
+    if len(detailed) == 2:
+        detailed = [detailed[(day_index if day_index is not None else weekday) % 2]]
+    if "veteran" in detailed:
+        selected.append("ptsd")
+    if "depression" in detailed:
+        selected.append("depression")
+    if suicide_monitoring or "depression" in modules:
+        selected.append("suicide")
+    questions = []
+    for section in selected:
+        for item in config[section]:
+            if item.get("weekly") and weekday != 0:
+                continue
+            questions.append(
+                Question(
+                    item["id"],
+                    item["text"],
+                    tuple((o["value"], o["label"]) for o in item.get("options", [])),
+                    "past_week" if item.get("weekly") else "past_day",
+                    item.get("numeric", False),
+                    item.get("optional", False),
+                )
+            )
+    questions.sort(key=lambda q: q.id != "death_thoughts")
+    return tuple(questions)