Matthew
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Multi-domain longitudinal pattern
Since mid-April, Matthew's behavioral signals have shifted in a temporally clustered way. The strongest pattern is convergent psychomotor and circadian disruption: sleep duration dropped from a 7h baseline to ~5.4h with delayed sleep onset, daily step count fell 71%, and meal regularity collapsed. Concurrently, social engagement markers decreased and goal adherence dropped from 78% to 23%. Medication adherence (93%) and therapy attendance held — these are strengths worth noting explicitly.
The data is consistent with multiple framings, all of which the AI is holding open:
(1) Single MDD episode — features fit, but episode-level framings warrant durability assessment beyond the current 6-week window. (2) Adjustment Disorder with Depressed Mood — the April 18 inflection coincides with an identifiable compound stressor (own brain MRI scare Apr 4–15 + father's MRI Apr 18 per Dr. Reyes's May 21 session notes); ADW-DM may be the more accurate frame if symptoms remain stressor-coupled. (3) Trauma-spectrum (ICD-11 PTSD or CPTSD) — passive data shows arousal and avoidance signals; intrusion symptoms and trauma history are not visible in passive data and require direct assessment. CPTSD specifically is not in DSM-5-TR but is a commonly missed framework. (4) Late-recognized autism and/or ADHD presenting as recurrent treatment-partial depression — this is the framework most often missed in adults who are verbally articulate, cognitively capable, and work-integrated. What looks like a depressive episode triggered by stress may, in some patients, be autistic burnout — the predictable result of sustained sensory and social load without recovery infrastructure. The same data points can mean very different things depending on which framework you read them through. Recommend AQ-10 or RAADS-R + ASRS-v1.1 screening alongside LEC-5 + ITQ for trauma.
Financial behavior shows night-window patterns (entertainment spend +340%, late-night purchases 11pm–3am). This looks like it could be hypomanic-spectrum but the full pattern (no energy elevation, no sleep-need reduction, mood-congruent consumption, high return rate) argues against bipolar. Pattern is mood-coupled, not bipolar-spectrum based on currently visible data — but MDQ recommended given the 10+ year average delay in bipolar II diagnosis.
Screen time +83% with passive-consumption dominant (social media +214%, late-night scrolling clustering 11 PM–3 AM). Active communication dropped 61% concurrently — Matthew is on his phone more but talking to people less.
No safety triggers fired (C-SSRS clean). Recommend in-session safety screen regardless. Suggested Thursday priorities: PHQ-9 + GAD-7, LEC-5 + ITQ for trauma-spectrum framings + AQ-10 / ASRS-v1.1 for neurodevelopmental framings, MDQ for bipolar-spectrum awareness, explore precipitants around April 4–18 (own MRI + father's MRI), review medication response, safety check, collaborative behavioral activation plan. Hold the differential open longer than feels comfortable — the wrong framing here is more costly than the indecision, and the framings the U.S. system most often misses are exactly the ones most consequential to miss.
Behavioral pattern mapping
Differential considerations · multiple framings held open
- Can see: behavioral pattern, longitudinal trajectory, magnitude of change, cross-domain coupling, timing of inflection.
- Cannot see: trauma history (current or childhood), family psychiatric history, prior episodes pre-2023, in-session affect quality, cultural meaning of stressor, Matthew's subjective narrative.
- Implication: the framings below are weighted by what the data can evaluate. Confidence is limited by the resolvable signal — not the underlying complexity of the patient.
This is the framing the AI most needs the clinician to evaluate. CPTSD is not in DSM-5-TR and is therefore systematically under-considered in U.S. clinical practice. It commonly presents as MDD + GAD with affect dysregulation and is one of the most clinically consequential missed diagnoses — wrong frame leads to wrong treatment.
Matthew's pre-April baseline was healthy, which makes a current CPTSD episode less likely. But unrecognized historical trauma activated by current interpersonal stressor is a known clinical pattern — and one that's systematically missed in patients who present as cognitively capable, verbally articulate, and high-masking. CPTSD requires direct trauma-history elicitation; it is not visible in 14 months of passive behavioral data alone.
For PTSD specifically: arousal/avoidance signals present; intrusion symptoms not detectable in passive data; Criterion A trauma evaluation requires direct interview.
For anticipatory grief: a meaningful framing because Matthew's stressor is a pending loss. Anticipatory grief shares features with depressive presentations but is conceptually distinct — pathologizing it as primary MDD risks medicalizing a normal human response.
This deserves the same diagnostic humility as CPTSD. Late-recognized autism in adults — particularly in those who present as cognitively capable, work-integrated, and verbally articulate — is one of the most systematically missed clinical pictures in U.S. mental health practice. The signature is often years of cycling through depression and anxiety treatments with partial response, sometimes plus a single significant life stressor that produces what looks like an episode but is really autistic burnout — the predictable consequence of sustained sensory and social load without recovery infrastructure.
What the data could be telling a different story about: Some of what we read as "symptoms" — reduced social communication, withdrawal from sensory-loaded environments, executive overwhelm under stress, sleep disruption from sensory input — can be neurodivergent baselines rather than depressive features, especially when they intensify under stress and recover under accommodation. The same passive data point can mean very different things depending on whether the framework is depression or autistic burnout. Treatment that addresses one without considering the other often produces partial response at best.
Strengths the framework wouldn't naturally surface: Matthew's 14 months of consistent self-monitoring data, his exceptional medication adherence (93%) under significant distress, his ability to articulate the precipitating events when asked, and his preserved engagement with structured care — these are capabilities, not just baseline expected behavior. A strengths-based formulation accounts for what he is doing well alongside what he is struggling with.
Standardized screener recommendations
Behavioral signal timeline
Pre-visit notes
Mood state over time
Daily State of Mind · last 30 days
What's worth surfacing in session
Matthew's journal language has shifted from active to passive voice over the past 6 weeks. February entries used agentive constructions ("I decided", "I want to", "I'm going to"); May entries lean on receptive/depleted forms ("nothing matters", "I'm just tired", "what's the point"). This is consistent with the affect-action coupling literature on depressive cognition.
The April 18 inflection doesn't appear in his self-report — he hasn't named a precipitant. But across his data: a calendar event "Mom call: Dad's MRI" appears two days prior; voice journal mentions of family rise 4× that week and then drop entirely. Worth gently probing in session.
- Behavioral activation candidates from his past data: drawing (Procreate, last active March 31), running (Strava, last active April 18 — same date), Sunday calls with mother.
- Sleep–mood coupling is r = 0.71 in his data. Late-night journaling (11 entries post-midnight) is both a symptom and a maintaining factor. Worth pairing CBT-I with the depression work.
- Therapeutic alliance is intact — Matthew has attended every session and rates them 8.5+/10 in post-session check-ins. Medication adherence has held at 93%. He is participating in care; the system is what's slipping.
Cross-domain correlations · Matthew's data
Eating window · last 14 days median
Macronutrient distribution
Cooking vs delivery
Food-related app usage
What this picture tells you before you meet
Matthew's nutrition pattern is secondary to his mood shift, not a primary disorder, but it's now reinforcing it. He isn't dieting or restricting deliberately — he's forgetting and skipping. The behavioral signature is unmistakable:
- Meal planning infrastructure abandoned April 18. Both NYT Cooking and Paprika went silent on the same date. The mental energy for "what am I going to eat" is gone.
- Convenience apps have absorbed the gap. DoorDash up 380%, Uber Eats up 240%. Average order time clusters 9 PM – 12 AM — he eats once a day, late, fast.
- Protein is the most actionable gap. ~60g/day estimated. Delivery patterns lean carb-heavy (Thai, pasta, pizza). Low protein is itself a fatigue-and-mood amplifier — a feedback loop.
- Caffeine has replaced food as energy source. 4.6 cups/day, last cup median 4:42 PM. This degrades sleep, which degrades mood, which degrades appetite — closing the loop.
- Unintentional weight loss (4 lb / 2.8% over 5 weeks) meets DSM-5 MDD Criterion A3 threshold. Worth flagging on the medical side.
Practical wins for a first session: protein-forward grab-and-go breakfast (no cooking required), reinstate one app reminder, move caffeine cutoff to noon, schedule one shared cooked meal/week with partner. Don't lead with meal planning — his executive bandwidth can't carry it right now.
Nutrition cross-correlations
24-hour usage heatmap · last 14 days
App categories · last 14 days
Top individual apps · this week
Phone as coping mechanism
Matthew's screen time pattern looks like distress-driven passive consumption, not engaged use. Three signals:
- Communication is down 61% while total time is up 83% — he's on his phone more but talking to people less. Phone use has shifted from connective to consumptive.
- Late-night doom-scrolling pattern: 47% of sessions are post-11 PM. Longest single session was 4h 14m on TikTok last Saturday night. Avg session length on social media has tripled.
- TikTok was installed April 22 — 4 days after the inflection point. New high-stimulation app adoption is a classic mood-management behavior.
Worth exploring: what does Matthew reach for the phone instead of? In session, framing his phone as a coping tool (not a moral failure) opens up healthier substitutes.
App data confirms the food story
Screen data corroborates what's happening with eating:
- DoorDash usage peaks 9 PM – midnight — exactly when he does eat.
- NYT Cooking + Paprika went silent April 18. He lost the planning muscle on the same day the broader pattern broke.
- MyFitnessPal logging down 72% — but he didn't delete the app. Reactivating logging may be a low-friction first step.
- Starbucks app +130%. Mobile order ahead = coffee replacing meals.
Screen behavior as a primary sleep disruptor
Matthew's last app interaction averages 2:48 AM. The 30 minutes before sleep onset are dominated by high-stimulation short-form video. Two specific findings worth raising in care planning:
- Pickups-in-bed: avg 22 per night between getting into bed and falling asleep (motion-data-confirmed).
- Wake-and-scroll: in 9 of the past 14 nights, Matthew woke between 3–5 AM, opened his phone, and stayed on it 20+ minutes before returning to sleep. This is a high-yield CBT-I intervention target.
Sleep stages · last 30 nights
Sleep architecture · last 14 nights
Pre-sleep behavior
- In-bed phone use48 min
- Avg pickups before sleep22
- Last caffeine (median)4:42 PM
- Last meal11:42 PM
- Bedroom light off2:08 AM
- Wind-down routineSkipped 12 of 14
This is mood-driven phase delay, not idiopathic insomnia
The pattern looks like secondary insomnia + delayed sleep phase coupled to depressive features:
- Late bedtime, delayed onset, fragmented mid-sleep, normal-to-slightly-early morning wake.
- Pre-existing baseline (Aug 2023 – Mar 2026) was healthy: 7h, low latency, 1.1 wake events.
- Coupling to mood is tight (r = 0.71). CBT-I likely high-yield, but standalone CBT-I without treating the mood substrate will under-perform.
Highest-leverage targets: charge phone outside bedroom, caffeine cutoff at noon, fixed wake time (not bedtime), bright light exposure 7–9 AM. Sertraline timing review with prescriber if AM activation overlaps with daytime fatigue.
Daily steps · last 90 days
Psychomotor slowing visible in passive data
The activity drop is sharper than mood-related withdrawal alone would predict. Two findings worth attention:
- Walking speed has declined 18% (from 3.4 mph to 2.8 mph), independent of step count. Speed is a fairer measure than count here — it reflects gait effort, not just opportunity.
- Stairs avoided: elevator-vs-stairs ratio flipped from 30/70 to 92/8 in the office building over the same period.
Both metrics return when he has a "good day" mood log — suggesting state-dependent psychomotor slowing rather than fixed deconditioning. Worth a brief functional check in-session.
Autonomic signature consistent with mood & stress state
The +9 BPM resting HR and ~38% HRV reduction are characteristic of sustained sympathetic dominance, consistent with depressive-anxious states. No findings suggesting primary cardiac pathology in the passive data (no ectopy patterns, no high-HR events, no oxygen desaturation overnight).
Worth noting for medication review: Sertraline is generally HR-neutral, but check whether dose change or other meds have changed. If clinical picture warrants, a 12-lead and basic labs would rule out thyroid or anemia overlay.
Active medications
Prior medication trials & reactions
Side effect surveillance · current medications
Drug-drug interaction check
Mild anticholinergic + SSRI = low risk; safe for short-term seasonal use.
No interaction.
4.6 cups/day vs 2.0 baseline. Not a true DDI but worth noting — high caffeine + SSRI can amplify anxious activation.
Mild anticholinergic + SSRI = low risk; OK for short-term seasonal use.
Pharmacogenomic considerations
Treatment response question
Matthew has been on Sertraline 100mg for 21 months with documented prior response. Current presentation suggests either breakthrough symptoms, dose-relative subtherapeutic response, or a precipitant-driven episode despite ongoing treatment. Adherence remains strong (93%) — this is not a non-compliance picture.
Options ranked in the Treatment Plan panel. Briefly: (A) dose-increase Sertraline 100→150mg is first-line and likely sufficient; (B) bupropion augmentation is contraindicated by prior adverse response; (C) venlafaxine class-switch is reserve; (D) aripiprazole augmentation is premature; (E) treating the medical layer (Vit D, ferritin, repeat TSH) should run in parallel. PGx testing now becomes reasonable if Option A doesn't produce response at 8 weeks.
State-dependent psychomotor slowing
Mobility metrics have declined in proportion with overall energy. The pattern is bilateral, symmetric, and reverses on good-mood days — strongly consistent with depressive psychomotor slowing rather than physical pathology. No fall risk indicators. No need for PT referral unless decline persists post-mood-recovery.
Unintentional weight loss flag
2.8% body-weight loss over 5 weeks is not severe in isolation but is clinically meaningful in context:
- It is unintentional (no diet, no GLP-1, no procedure).
- Trajectory matches reduced intake (~530 kcal/day deficit) — the math checks out.
- It meets DSM-5 MDD Criterion A3 ("significant unintentional weight loss").
- Continued at this rate, would total ~5% loss by next monthly visit — worth a weigh-in.
Address by treating the upstream nutrition/mood pattern; rule out medical contributors if loss continues past behavioral intervention window.
Spending pattern · last 90 days
Spending category breakdown · last 30 days
Time-of-day spending pattern
What's still working
This spending is mood-congruent, not hypomanic
The +340% discretionary spend by itself looks like it could be a hypomanic-spectrum signal. It isn't. The full pattern argues against bipolar:
- No paired energy elevation. Hypomanic spending typically co-occurs with reduced sleep need, elevated activity, and goal-directed pursuit. Matthew's sleep is reduced with fatigue, his steps are down 71%, and his goal-pursuit is collapsed. Activity and spending are decoupled — not the bipolar signature.
- Purchase content is consumption-oriented, not ambition-oriented. Hypomanic spending often clusters around projects, plans, expansion (business courses, large items, travel). Matthew's purchases are passive: streaming, doomscrolling-adjacent retail, instant gratification.
- Late-night timing aligns with insomnia, not energy. The 11 PM – 3 AM cluster overlaps the doom-scroll window. This is "I can't sleep so I scroll-and-buy", not "my mind is racing and I'm building things."
- Return rate (16%) is high. Buyer's-regret pattern, consistent with impulse-with-low-conviction. Hypomanic purchases tend to feel justified in the moment and later.
- 14-month longitudinal data shows no prior hypomanic episodes. No previous spending spikes, no energy elevations, no decreased-sleep-with-mood-elevation patterns.
MDQ would likely score low. Bipolar differential should remain considered but unsupported by passive data. If Matthew endorses any past energy/spending pairings on direct interview, revisit.
Spending as coping behavior — three patterns to discuss
The spending is doing emotional work for him. Three distinct sub-patterns:
- Numbing (entertainment, streaming subscriptions, in-app purchases): purchased when distress is acute · cluster around 11 PM – 1 AM · doesn't require physical presence · low engagement threshold.
- Replacement-for-effort (food delivery, mobile coffee orders): substitutes for activities he used to do herself (cook, walk to coffee) · executive-function-conserving · also functions as caretaking-from-outside when he can't caretake herself.
- Pseudo-control (Amazon impulse buys, returned items): buying gives a moment of agency-feeling that his broader life isn't providing · the act of buying matters more than the items · 16% return rate suggests the goods themselves aren't the point.
Worth gently surfacing in session — without shame. Matthew is using money the way another patient might use food, alcohol, or work. Frame it as a coping tool that has worked enough to keep doing, not as a failure. Healthier substitutes (calling a friend, a 10-minute walk) need to be at least as accessible as the phone in his hand.
Stability infrastructure is intact — buy time for recovery
Critically, Matthew's baseline financial stability is not threatened. Income is stable (W-2 paychecks deposited on time, no reduced hours), savings continues to accumulate, no debt acceleration. He has ~$84 in monthly slip from late fees + drift + subscription creep — annoying, not catastrophic.
The actionable interventions are protective, not restrictive:
- Audit + cancel the 3 forgotten trials and pause Equinox until Matthew is using it again. ~$212/mo recovered with minimal effort.
- Late-night purchase pause — most cards support a "24-hour cooling" or app-level spending limit. Reduces post-11 PM purchases without removing access.
- Auto-pay every bill — eliminate the executive-function load of paying bills manually when his bandwidth is low. Eliminates late fees entirely.
- Don't touch the emergency fund auto-transfer — it's working without his attention, which is the design.
Financial intervention here is protective infrastructure, not behavior change. The behavior will follow when the mood recovers.
Cross-domain correlations · Matthew's financial data
Headphones as social-shield, not hearing risk
Audio levels themselves are safe. The behavioral signal is the 8.4hr/day exposure — up 4.7× from baseline. This often co-occurs with social withdrawal (audio in = world out). Worth surfacing gently, not as a hearing concern but as a coping-shape question.
No respiratory findings
All respiratory metrics within normal range. No evidence of sleep-disordered breathing contributing to Matthew's poor sleep quality — the sleep issue is behavioral and mood-driven, not respiratory.
Logged symptoms · last 30 days
Active providers
+ InviteRecent care team activity
Role-based access matrix
| Data category | Therapist | Psychiatrist | PCP | Neurology | Radiologist | Endo | RD | LCSW (fin) |
|---|---|---|---|---|---|---|---|---|
| Behavioral / BridgeKPI | RW | RW | R | R | — | — | R | R |
| Session recordings + AI synopses | RW | — | — | — | — | — | — | — |
| Psychotherapy notes | RW | sealed | sealed | sealed | — | — | — | sealed |
| Medications | R | Rx | Rx | Rx | R | Rx | R | — |
| Labs & vitals | R | R | RW | RW | R | RW | R | — |
| Imaging / radiology reports | R | R | R | RW | RW | RW | — | — |
| Allergies | R | R | RW | RW | R | RW | R | — |
| Nutrition plans | R | R | R | R | — | — | RW | — |
| Financial / SDOH | R | — | R | — | — | — | — | RW |
| Substance use (42 CFR Part 2) | sep | sep | sep | sep | sep | sep | sep | sep |
Therapy session · Matthew Wright
Past sessions
Across the last six sessions, therapeutic alliance scores have held steady at 8.4/10 (Matthew's post-session rating) even as his mood has declined. Speaking-time ratio has shifted: Matthew spoke 62% of session time in April, 51% in mid-May, 47% on May 21. This is consistent with depressive withdrawal, not disengagement — he shows up and stays engaged but talks less.
Topic clusters have shifted from active (running, work projects, social plans) to receptive (sleep, fatigue, family worry). Father's MRI was first mentioned April 30 — that's the precipitant flagged in the longitudinal data.
Matthew opened the session describing persistent fatigue and difficulty getting started in the morning. He mentioned sleeping "okay-ish" but waking multiple times and feeling tired regardless. Mood self-report: 4 out of 10, down from 6 the previous week.
Significant emotional moment around minute 12: Matthew disclosed that his father's MRI results came back showing a brain lesion on April 18, and he has been "trying not to think about it." This is the first session in which the date has surfaced explicitly — it aligns with the inflection point flagged in his behavioral data. He expressed guilt about not visiting his parents and about pulling away from his mother's weekly calls.
Discussion shifted to behavioral activation. Matthew identified drawing and running as activities he misses but feels "too tired" for. Dr. Reyes proposed a "smallest version" approach (10-minute walk, 15-minute drawing) — Matthew was tentatively willing. Homework: one walk and one drawing session before next visit.
Medication response reviewed. Matthew confirmed he is taking Sertraline daily (93% adherence on app data). Discussed dose adjustment vs. waiting; deferred decision pending two-week behavioral activation trial. Safety screen administered — Matthew denied current ideation, plan, or intent; expressed wanting to "feel like myself again" rather than not exist.
Closing: Dr. Reyes acknowledged Matthew's continued engagement in care despite low energy. Matthew rated the session 8/10. Next session Thursday May 28.
Emotional tone over time
Body language & nonverbal indicators
Topics discussed
Key moments timeline
AI-suggested chart note · editable
What April actually looked like for Matthew — compound stressors visible across the data
Comprehensive panel · Apr 22, 2026
What this lab work changes about Matthew's picture
Three findings shift the differential meaningfully and warrant team-wide awareness:
- Subclinical hypothyroidism (TSH 4.8, free T4 normal). This is a known depression mimic — fatigue, weight changes, low mood. The mood picture may have a meaningful endocrine layer worth treating in parallel with psychiatric care. Recommend re-check TSH + free T4 in 6 weeks. If TSH rises further or T4 drops, initiate low-dose levothyroxine in coordination with Dr. Almeida (psychiatry).
- Vitamin D deficiency (18 ng/mL). Strongly associated with depressive symptoms in observational studies; replacement is low-risk and high-value. Initiate D3 5,000 IU daily × 8 weeks then re-check.
- Low-normal ferritin (22). Iron deficiency without anemia can contribute to fatigue and cognitive symptoms. In a 34M without menstrual loss, this finding warrants a dietary and GI consideration — workup if persistent. Recommend oral iron supplementation with monitoring; re-check ferritin in 12 weeks; consider basic GI evaluation if doesn't improve.
Critically: these findings do not rule out psychiatric framing — they add a treatable medical layer that may have been amplifying psychiatric symptoms. The wrong move is to either (a) attribute everything to thyroid and stop psychiatric care, or (b) ignore the labs and treat psychiatrically alone. Both modalities indicated.
Drug allergies
Food allergies
Environmental & testing history
How Matthew's allergy profile shapes treatment options
- Sulfa allergy rules out certain antibiotic classes (Bactrim) but does not contraindicate sulfa-containing drugs without an aromatic amine group (most modern psychiatric medications are safe).
- Penicillin allergy rules out beta-lactams unless evaluated by allergist for graded challenge.
- Tree nut allergy requires checking excipients in any new medication — some capsule formulations and certain compounded medications can contain tree nut oils. System auto-flags this on every Rx review.
- No psychiatric medication allergies on record — Sertraline, prior SSRIs, and bupropion previously tolerated without allergic reaction (separate from side effect tolerability).
- Cetirizine PRN seasonal use noted — no interaction concerns with current Rx; mild anticholinergic effect with chronic use worth noting.