Resulting (Outcome vs. Decision Quality)

The Science Behind Resulting (Outcome vs. Decision Quality)

Resulting is a cognitive bias identified and named by professional poker player and decision strategist Annie Duke in her book *Thinking in Bets* (2018). It describes the deeply human tendency to judge the quality of a decision by its outcome, rather than by the quality of the reasoning behind it. In other words, if something works out, we assume we made a smart call. If it doesn't, we assume we made a poor one, regardless of whether either conclusion is actually warranted. This is a fundamental error in how we evaluate our own choices, and it has profound consequences for patient behaviour in allied health settings.

The psychology behind resulting runs deep. Our brains are pattern-recognition machines, wired to draw quick causal connections between actions and results. When a patient stops physiotherapy at session five and doesn't immediately deteriorate, their brain files this under 'good decision.' The absence of a bad outcome feels like confirmation that stopping was the right call. What the brain fails to account for is the role of chance, timing, and latent risk. A person might stop treatment prematurely and feel fine for weeks or months, not because stopping was wise, but because the underlying condition simply hasn't had time to reassert itself yet. Duke describes this as confusing 'I got lucky' with 'I made a good decision,' and the distinction is crucial.

This bias is compounded by what psychologists call 'motivated reasoning.' Patients who have already decided to stop treatment, often for financial or logistical reasons, are primed to interpret their continued wellbeing as vindication. They're not actively lying to themselves; they're doing what human brains do automatically. The result is that the very patients most at risk of recurrence are often the least likely to feel any urgency about returning for follow-up care. From the outside, a practitioner can see the risk clearly. From the inside, the patient feels perfectly justified in their decision.

For allied health practices, the implications are significant. Research consistently shows that premature discharge is one of the leading contributors to condition recurrence across musculoskeletal presentations, chronic pain, and postural dysfunction. Studies in physiotherapy literature suggest that a substantial proportion of patients who discontinue care before completing a full treatment plan experience a return of symptoms within six to twelve months. Yet these same patients rarely connect their recurrence to their earlier decision to stop, because resulting has already closed that mental loop. Understanding this bias is the first step toward building re-engagement strategies that actually work.

The Research

How to Apply This in Your Practice

The most effective way to counter resulting in lapsed patients is to make the invisible risk visible before they disengage, and then to reinforce that framing when you reach back out. During treatment, practise explicit probability-based conversations. Rather than saying 'we recommend six more sessions,' try: 'Research shows that patients with your presentation who stop at this stage have a significantly higher rate of recurrence within six months. You might be one of the people who does fine, but we can't know that yet, and here's what it would cost you if you're not.' This shifts the patient's mental model from 'I feel better, so I'm done' to 'I feel better, but the decision about stopping is separate from how I feel today.' That distinction is the entire game.

When re-engaging lapsed patients via SMS or email, the message needs to do the cognitive work of separating outcome from decision quality. A generic 'we miss you, book now' message will not move someone who believes they made a good decision by leaving. Instead, try something like: 'Hi [Name], we wanted to check in. Many patients with your condition who stop care around the stage you did feel great initially, about 30% stay that way long-term. The other 70% find symptoms return, often worse than before. We'd love to do a quick reassessment to make sure you're tracking well. Takes 20 minutes, no obligation.' This message does several things: it validates their current experience (you might be fine), it introduces probabilistic risk without fear-mongering, and it offers a low-commitment next step.

From a workflow perspective, your practice management system should flag patients who disengage before their recommended treatment plan is complete. Set an automated trigger at the 30-day mark post-lapse, followed by a 90-day follow-up if there's no response. The 30-day message should be warm and curious: 'How have you been feeling since your last visit?' This opens the door without immediately invoking risk. The 90-day message is where you introduce the probabilistic framing more directly, because by then the patient has had enough time to either confirm their good outcome (and become complacent) or start experiencing early warning signs they may be minimising.

It's also worth training your front-desk and clinical team to use resulting-aware language during the discharge conversation itself. When a patient says they want to 'take a break and see how they go,' the response shouldn't be a passive 'okay, call us if you need us.' It should be: 'That's completely your choice, can I share what we typically see with patients who pause at this stage? It might help you know what to watch for.' This positions your practice as a trusted advisor rather than a sales engine, and it plants a probabilistic anchor that the patient will carry with them. If their symptoms do return, they're far more likely to come back to you, because you predicted it without pressuring them.

Seeing It in Action

Your Action Plan

1. 1Audit your current discharge process and identify all patients who left before completing their recommended treatment plan in the last 12 months, these are your highest-priority re-engagement targets, as they are most susceptible to resulting bias.
2. 2Train your clinical team to use probabilistic language during sessions and at the point of disengagement, phrases like 'you might be in the lucky percentage, but here's what we typically see' are far more effective than generic recommendations to continue care.
3. 3Build a two-touch automated re-engagement sequence in your practice management software: a warm check-in message at 30 days post-lapse, followed by a probabilistic risk-framing message at 90 days that distinguishes current symptom experience from decision quality.
4. 4Craft condition-specific message templates that include realistic outcome statistics for your most common presentations (e.g., lower back pain, plantar fasciitis, rotator cuff issues), using qualified language where exact numbers aren't available, specificity builds credibility and counters the 'I'm probably fine' assumption.
5. 5Offer a low-barrier re-entry point such as a short reassessment appointment, positioning it as a check-in rather than a sales conversation, this removes the commitment anxiety that prevents lapsed patients from responding, and lets your clinical outcomes do the persuading.