What the sober days in your data are telling you

Most of the frameworks we've discussed so far approach substance use by examining the problem: what triggers it, what maintains it, what cognitive distortions protect it from scrutiny. This is useful. But there's an approach that deliberately inverts the question , and has a growing evidence base for doing so.

Solution-focused brief therapy (SFBT) was developed by Steve de Shazer and Insoo Kim Berg in Milwaukee in the 1970s and 80s. Its central observation is deceptively simple: the problem is not happening all the time. There are exceptions , moments, days, periods when the problematic behaviour is absent or reduced. And those exceptions are not random. They're happening for reasons. The therapeutic task is to find those reasons and amplify them.

This is genuinely different from the deficit model that dominates most mental health and substance use treatment. It doesn't start with what's broken. It starts with what's already working , even if it's only working some of the time.

The exception-finding question

The foundational technique of SFBT is the exception question. A therapist might ask: "Tell me about a recent time when you were in a situation where you would normally have used more than you wanted to, but you didn't. What was different about that time?"

The question is designed to surface data that the person already has but hasn't examined. Most people in the grey area with their substance use can identify times when things were easier , when they drank less than expected, when an urge passed without being acted on, when a difficult evening didn't end the way it usually does. These aren't celebrated or examined because the focus is almost always on the times when things went wrong. The exceptions go unnoticed.

But the exceptions contain information. They happened for reasons. The reasons may be identifiable. And if they're identifiable, they may be replicable.

How your data surfaces the exceptions

The ayodee log, reviewed through an SFBT lens, is an exception-finding tool.

After a few weeks of consistent logging, look not for your worst days but for your best ones. Specifically:

Days when use was zero or minimal, in a context where you might have expected it to be higher. What was different? Was it a social situation that usually involves drinking but didn't? A stressful day that ended without reaching for something? A weekend that was lower than the typical weekend? What was happening that wasn't happening on the comparison days?

The weeks where the pattern was different from average. Most data shows variability , some weeks are harder, some are easier. The easier weeks aren't luck. They're caused. Looking at what was structurally different , sleep quality, exercise, social schedule, work pressure, routine , tends to reveal factors that the person already knew mattered but hadn't connected to outcomes this explicitly.

The urges that didn't result in use. The urge log that shows a craving at intensity 6 on a Tuesday evening that wasn't acted on , what was the context? What happened instead? Where were you? Who were you with? What were you doing? Each of these is an exception: evidence that the automatic cue-response pattern can be interrupted, in specific conditions that you can identify.

The miracle question as a data exercise

SFBT practitioners use a technique called the miracle question: "Suppose tonight, while you were sleeping, a miracle happened and this problem was solved. When you woke up tomorrow, what would be different? What would you notice?"

The answers are usually concrete: I'd wake up feeling rested. I wouldn't have that slight fog. I'd feel like exercising. I'd be more present with the people I care about. I'd be less anxious.

These answers , the picture of life without the problem , are the goal. Not "stop drinking," which is abstract, but "wake up rested and clear," which is specific and felt.

Now look at the sleep quality data from your alcohol-free nights. The mood scores from the mornings after low-consumption days. The energy ratings on the days that followed better choices. The miracle question answer is already in the data , it's what your actual experience looks like on the exception days. Not hypothetical. Documented.

Why this framing is useful for the grey area

The deficit framing , "here's what's going wrong with your substance use, here are the problems it's causing" , is often counterproductive for people in the grey area who don't identify as having a problem and who respond to deficit framing with defensiveness.

The SFBT framing is genuinely different in its psychological ask. It's not "acknowledge the damage." It's "tell me about the times when things were easier , what was different?" This is a question most people are willing to engage with, because it's not requiring them to accept a label or a diagnosis or a level of severity they don't identify with.

And it's an answerable question. The data makes it answerable. The exceptions are in the log.

Building on what already works

The intervention that follows exception-finding in SFBT is deceptively simple: do more of what was happening on the exception days. Not a new programme. Not a treatment. Just a deliberate amplification of the conditions that were already associated with better outcomes.

The exception days are already yours. The conditions that produced them are already known to you , once the data makes them visible. What SFBT suggests is that this is already more than enough to work with. You don't need to build something new. You need to see what's already working and make more of it deliberate.

ayodee tracks every day , the difficult ones and the easier ones. The exception data is in your log. Anonymous, no account needed.

References de Shazer, S. (1985). Keys to Solution in Brief Therapy. Norton.

Gingerich, W.J., & Peterson, L.T. (2013). Effectiveness of solution-focused brief therapy: a systematic qualitative review of controlled outcome studies. Research on Social Work Practice, 23(3), 266–283.

Berg, I.K., & Miller, S.D. (1992). Working with the Problem Drinker: A Solution-Focused Approach. Norton.