All-Inclusive Resorts and Dietary Self-Regulation (Part 1)


1: Introducing the all-inclusive resort analogy

In October/November I spent 15 nights in Playa del Carmen to circumvent the US travel ban and get into the US to see my partner for the first (non-Zoom/WhatsApp) time in 13 months. I decided to splash out, and spent far more on this holiday than I ever have on any trip in my life—especially one on my own.

It struck me right from the moment of typing in my credit card details that this was a nicely anti-anorexic thing to be doing: 1) Spend a lot of money, just on myself, and not because I “had” to, i.e. buying myself something more than I “had” to. What I didn’t realize at that point was how much broader the implications of the all-inclusive vacation model could be for thinking about how to do eating disorder recovery successfully—and maybe even about broader questions around how to do healthy eating and exercise successfully.

Here’s the thesis in brief. All-inclusive is the epitome of incentivizing “more than necessary”: You’re paying to encourage yourself to have as much as possible. You’re paying to put the limits (on eating, drinking, and whatever else your package includes) so high as to be practically irrelevant (I guess you could camp out at the resort bar or restaurant and eventually get told you can’t have any more? but probably not until after you passed out / threw up). The idea is that this is beneficial (e.g. relaxing) because then you get to self-regulate without some major standard constraints (e.g. cost) getting in the way.

In this miniseries I’ll argue that the all-inclusive framework is, structurally speaking, the same framework that’s needed to recover from a restrictive eating disorder (or from chronic dieting): the limit is raised high enough to be irrelevant. (The same applies for a compulsive exercise problem, but switched around: Here the limit is made low enough to be irrelevant.) Only then can you start self-regulating, i.e. start using feedback (e.g. on how you feel, what other outcomes you’re getting), rather than blindly applying rules (e.g. how many calories or minutes or kilometres regardless of everything else).

Of course, the all-inclusive benefits may not, in the vacation or the recovery context, be immediate. Self-regulation may take time to be learnt—maybe a lot of time. I guess some people do all-inclusive and binge-eat/drink in a way that makes them miserable, and some others do it in as miserly a way as if they were paying for every drink and meal, and some people do it just fine but don’t enjoy themselves because too many other things are wrong. Equally, learning how to self-regulate in recovery, and then getting the payoffs for the rest of life, obviously isn’t instant—although in some cases, the instincts for how to do it may snap back into place a lot more quickly than expected.

Letting internal regulation take over.

Following step 1 (spend a lot of money on something where everything is included, i.e. the incentive is now to consume more not less) allows for the magic of step 2: Let the self-regulation happen. For me this autumn, the eating-specific effects weren’t particularly salient, because I’m already self-regulating happily in that realm, but the way eating and drinking adjusted effortlessly to the absence of ordinary constraints was a pleasant part of a broader ease in adapting to having pretty near zero limitations or responsibilities. The most strikingly beautiful part of this holiday—even more so than the blue-green Caribbean water, the palm trees, and the ocean sunrises from my balcony—was how everything simply took care of itself, effortlessly, in the absence of almost all readymade guidelines. 

I don’t recall any time in my adult life when there were so few requirements on me—self-imposed or otherwise. I had a few coaching calls in the calendar, but I deliberately cleared other work commitments for this fortnight, so otherwise it was empty. And this being all-inclusive, there was nothing practical (shopping, cooking, cleaning, etc.) to think about. There were no pre-decided boundaries in my day. Being on my own, there weren’t even anyone else’s preferences to accommodate. There were, basically, no “should”s.

So, what happens when you take the ought out of your life?

In many senses, of course, two weeks lounging around in a swanky hotel has little to do with the rest of life. But it can provide some important illumination for the rest—clarifying it ex negativo, through the absence of what’s ordinarily present. What it does is remove almost all the accreted habits that normally prevent us from answering that question from scratch. There’s never a blank slate, but the slate is a lot freer of old scrawls when everyday busyness is prevented from fooling us into believing we have no options.

“Ditching the ought” has to become a reflex in recovery from anorexia. For a while, a new version of “ought” (eat more, move less) has to replace the old; later, the whole idea of “ought” has to change its nature, become more malleable by context. This progression obviously applies to the diet and exercise specifics, but it’s also about much broader questions concerning how we choose to live and why—which are what the great excitement of fully recovering really amounts to. Now that I get to choose how to live, rather than an illness always already having dictated 90% of the answer, how do I in fact choose to?

If this still feels a million miles away from you, trudging across the endless grey tundra of recovery, this series may serve two purposes: 1) illustrate the basics of how to make recovery work, via the all-inclusive vacation analogy; 2) encourage you to try out such a vacation for real, as a pleasurably literal way to accelerate the process. At the end I’ll also offer some observations relevant to eating well (in the fullest sense of that term) in the absence of an eating disorder but the presence of all the screechy sociocultural signals that can make it feel so hard to find and maintain personal equilibrium.

2: The anorexic vacation

Unless you’re far more profoundly motivated by the desire not to waste money than most people are, there’s not much point in doing the literal all-inclusive vacation with full-blown anorexia if you’ve done none of the analogous practice of lifting constraints and shifting incentives beforehand. I can imagine with tedious ease exactly what this Mexican fortnight would have been if anorexia had still been running the show. The “oughts” would have kept doing what they always did. 

First of all, I would have had to be brought kicking and screaming (well, the pallid, flaccid anorexic version of that) here in the first place. There’s not much point in someone with anorexia actively choosing a place that costs a lot and is remotely worth the cost only if you enjoy eating and drinking plenty, at civilized times of day. I would have been horrified by everything from the price tag to the idea of eating every meal in a restaurant (though I guess I’d have approved of the fridge and coffee machine in the room, the former topped up by a man with a trolley full of cold cans and snacks every day, the latter adaptable to make tolerable cups of tea). So, I would have needed a really compelling reason to do this at all. Let’s say a parent generously gave this to me, hoping it would do me good.

So I’m here. I arrive on a Sunday evening; the bellboy shows me to my room. Despite the long trip and jetlag I force myself to stay up long enough to have several hot drinks as a prelude to my nighttime meal. I’ve obviously brought lots of special foods with me, probably including cereal bars, cereal, maybe some soy milk to tide me over before I find a shop, maybe bread and/or margarine and lettuce, and of course lots of chocolate and other extremely sweet things. And I’ve gathered up all the plane food to eat tonight—not the main course, which I worried about getting through customs or spilling in my bag, but the bread rolls and the brownie dessert and the mini butters and everything. And I have my electronic kitchen scale (and I’ve probably emailed the hotel in advance to ask whether they have body scales) and I work out how to incorporate these into the immovable framework for my single meal of the day. And that meal is an urgent ecstasy, as always. And I sleep deeply until lunchtime at the earliest. 

When I wake up, I consult Maps to find an acceptable walk to take me to a supermarket to buy more “essentials” and keep me walking for long enough to be comparable to the daily bike ride at home. And when that’s all done and there are maybe a few daylight hours left, I might lie out in the sun on the beach or balcony, self-conscious about my thinness if in public, probably chilled by the slightest warmest breeze. And I feel guilty or at least on edge the whole time about not being productive, and I have some work-related book to read that I’m making faint pencil marks in the margins of (since it’s a library book), and I’m bored by all of them and maybe grant myself a half hour for something I wanted to read, like fiction, but only once it’s night again. 

And because I’m obsessed with not wasting money (I don’t care very much about other people’s money, but still a little bit), I go to the “barefoot bar” and order a wrap or a panini and factor it into my late-night meal, and I go to the café every day to get free coffees and eye up all the cakes and pastries and get several of them every day to have at the nightly high point of my life: eating fat and sugar. 

And the days pass, and I stay in my haze, and my skin gets a tiny bit of colour but I miss half the daylight hours, and I bless the brief respite from serious cold but keep my body unable to insulate itself, and I turn a short daily sea swim into a non-negotiable ordeal, and I don’t speak more than a few words to anyone but make a whole lot of people feel vaguely sad or uncomfortable, and so my time in sunnier climes comes to an end. And I go home the same sad person who spends 21 hours of her day wishing time onwards just so she can eat.

I shudder to imagine this. I drafted this section over wine in between courses and banter with the waiters at the breezy outdoor restaurant. It was hard to write because I wasted so many holidays this way. And I defended the waste, for fuck’s sake. That’s what’s really so infuriating and incomprehensible about this illness: how it makes its hosts think their life is better without it, not so much worse it barely counts as living.

3: The recovered vacation

So take instead the reality. Not the version where every new possibility is already precluded by a “no”, every old habit already insisted on by an “it couldn’t be any other way”. The version where the decisions make themselves—as they always in reality do, but in all the beauty of their self-determining nakedness. The version where days start at 6 or 7 or 8 or whenever I happen to wake up, and where I maybe start reading a bit of one of my holiday paperbacks (Anne Tyler, Yan Hang, Muriel Spark) in bed, or more likely get straight up, take a quick peek out from behind the net curtain to check the state of the sky, pull on a minimal negligee (I’d always rather be clothes-free), put a teabag and water in the coffee machine, go to the loo, clean my teeth and face, and go onto the balcony to sit watching the sunrise sea while I write my diary and drink my tea. And then most mornings I go to 8am yoga, and usually to some other class later (it was fun to try all kinds of things I never would otherwise: HIIT boxing, TRX, a crazy fitness challenge thing on the main lawn in full view of all the pool-goers), and after yoga I have some variants on eggs, cheese, and meat in the outdoor restaurant, and then the rest of the day is a lazy, soft-edged mixture, drifting between balcony, pool, and beach; between reading, writing, email, work/pleasure Zooms, dozing, eating, drinking, swimming, wandering into town for something. There are few set times for anything, only pretty capacious meal deadlines (breakfast by 10:30, lunch by 4, sometimes a dinner booking); and instead there have been instincts that have come and gone: to drift into a fictional world for a while, to crystallize a new bit of a course idea in writing; to get coffee and a cake (going into the café and not handing over money in return for a latte just doesn’t get old!); maybe to go and lift something a bit heavy in the gym; to have an evening swim in the uplit pool or to sit on the balcony with a beer and salty snacks instead. The extreme luxury of 14 whole days of this feels almost surreal. I don’t talk to a great many people beyond the waiters, but I get lots of cheery hair compliments and have a few interesting chats with waiters and other guests.

And imagining it being gently poisoned from the start is easy—just as easy as imagining it being utterly annihilated by severe anorexia. Take pseudo-recovery, the place so many people stop. What version do you get here? 

4: The pseudo-recovered version

If you’ve stopped halfway in recovery, you get the version where you do a lot of comparing of how much you’re eating and exercising with how much you would do at home. Where you need to get your daily exercise in before you can relax. Where you think about calories when choosing from menus. Where if you had just the couscous and chicken salad for lunch one day you go without the panini or the wrap every day after that because the lower precedent has now been set (and the same with adding flour tortillas to breakfast, or cake to coffee, or dessert at dinner). Where you have to have a certain number of swims per day, of a certain length, aimed at calorie burning or muscle maintenance (which is all really aimed at how slim or toned you look). Where you limit yourself to alcohol x days a week rather than deciding whether or not you feel like it. Where once you’ve found out about the fitness class schedule, you have to go to all of them, or some subset non-negotiably. Where you spend a lot of time looking at your swimsuited self in mirrors and comparing your body with other people’s. 

(Or, at a slightly more advanced stage of pseudo or partial recovery, where you manage to resist some or all of these instincts but you still feel a lot of guilt and doubt and preoccupation as you do so.)

And this version is a bit less hard to get frustrated or angry about, because it’s easier to see how you kid yourself it’s decent. But it makes me just as sad to think about, maybe more so, because it has even more of an inbuilt self-perpetuation mechanism than the acute-AN version. This is the “stopping halfway” that I’ve written about before, and that many readers said they felt powerful recognition of. (PT removed all comments from all blog posts last year, but I have a copy of the hundreds that were posted in response to the “stopping halfway” piece, and all the others.)

This is the state that tries to pass itself off as the best of both worlds—still relatively thin and relatively free—rather than the worst: not particularly thin, still deluded that thinness matters, and not remotely free.

I guess it looks a lot—at least if you squint and look away pretty quick—like the best you can reasonably expect to get, because pseudo-recovery and normality are getting harder and harder to tell apart. But if you’re in the former camp, you have one great advantage over those in the latter. You know that this is part of a process that you’ve begun and that you can decide to resume and complete. You’ve already got from 0% to 80% or 90% recovered; you can certainly manage the last 10% or 20%. 

If it helps, start planning a vacation like this (or not at all like this, but dreamily different from the everyday and opening up the space for self-regulation in whatever way works for you) and remember how elusive but how entirely unfakeable the difference is between the experience you get if you complete this process versus if you don’t. 

It’s not quite like being a child again, the good version, but it also kind of is: It’s doing what you want, when you want, and not even any parents to tell you not to, because now you know enough to sense when you want and need your own bedtime to be.

Read on to a milkshake-themed Part 2 here.

13 Things I Learned Dining Out Alone for 14 Days


Reasons to schedule solo restaurant meals into your recovery, or your life.

When did you last eat out alone?

Until last month, for me the answer would have been “I have no idea—not for years, maybe never.” That’s if you mean doing it properly: going into a restaurant on your own, ordering an entire multicourse meal, and eating it alone.

Done properly, eating out alone ticks a bunch of big anti-anorexic boxes: Eating unfamiliar foods; eating foods prepared by other people; likely eating more than usual; eating around other people; doing nothing else whilst eating; spending “unnecessary” money on food; spending “unnecessary” money on yourself.

This autumn, the perfect chance for a crash course in solo dining came up. The US travel ban meant I hadn’t been able to see my partner (who used to live in Pasadena, now New York) in person for a year, and although the internet was constantly full of mutterings about the ban being relaxed, it kept not actually happening (it finally did last week). In the end I decided it was worth doing the “standard” workaround: Spend 14 days in a non-banned country and enter the States from there. Mexico seemed like a good bet, and I spent ages on TripAdvisor et al. trying to choose a hotel.

All-inclusive seemed a nicely low-hassle way to do things, and I ended up splashing out on 15 nights at a swanky beach resort south of Cancun. Unless you want to go wild on room service, doing all-inclusive means eating a lot in restaurants, and unless you’re keen on making fast friends, doing all-inclusive on your own means eating a lot in restaurants on your own.

I was interested in how this would go. I had some predictions, most of them not particularly optimistic, e.g.:

1. Assuming hardly anyone else will be on their own, I’ll feel self-conscious or even embarrassed about it.

2. It’ll feel weird/difficult to not be doing anything else while I’m eating—but I also don’t want to be reading a book or on my phone, especially in the evening.

3. It’ll feel like a waste of time to do this several times a day; it’ll be boring.

4. It’ll get easier with practice.

If this hadn’t been all-inclusive, the final prediction would have been:

5. This will feel like a colossal overindulgence and waste of money.

The last prediction was actually one of my reasons for choosing this format: I wanted to give myself a strong incentive to do all the nice things without money being an issue.

As it turned out, my first three pessimistic predictions were miles off. The fourth was, as usual, spot on.

I arrived mid-evening (after a 16-hour journey plus 6 hours of jet lag) so having dinner straightaway made sense to kickstart the timezone adjustment. I’d had the sense in advance that it would be important to begin well: to make doing this restaurant thing the norm from the outset. I chose from the six or seven resort restaurants at random, kept it to one course (plus bread and wine), and was tired enough that my main feeling was gratitude for the wine and the simplicity of being brought things that tasted nice. I was soon done and off to bed.

The next morning, the outdoor place for breakfast was a delight—and remained that way for all my 14 mornings. It was lovely to sit down and be brought limitless decaf refills, feel the Caribbean warmth, and admire the blue skies beyond the covered terrace. That first morning I was a bit zonked from the travel and the heat and humidity, and simply from being in a different country after all this time stuck in Britain, and my huevos rancheros went down extremely well.

As the days and meals passed, I learnt the breakfast menu off by heart, stopped bothering with other restaurants because this was the only one with proper outdoor seating, and got friendly with the morning and the evening waiters. At breakfast I sometimes read the New York Times morning briefing or similar on my phone, or brought a magazine with me. At dinner I rarely used my phone (occasionally for a few WhatsApp messages or something—or to take these photos!) and sometimes took my notebook to scribble in.

At lunch I used the sandwich bar for panini, wraps, etc., and the novelty of getting a latte and a cake from the café and handing over no money never got old. I saw I think a total of two other people eating on their own—it was a very couply place, and mostly a bit older than me—but I never once felt remotely uncomfortable about it. Indeed, the luxury of eating this way is a big part of what made the trip a bright serene oasis in my year, in the living and the remembering.

I thoroughly recommend dining out alone as a way to accelerate your recovery or just to acquire the skill of taking pleasure in something you might otherwise never have realized you could. The more conflicted you feel about trying it, the more good it may do you. To make the case and give my top tips, here’s what I learnt from my two weeks of solo eating out:

1. Using your phone defeats the entire purpose of practising being alone. I therefore recommend a strict no-phone rule to begin with. The rule can be relaxed once phone-free has become a comfortable default. (See this post for more on why phone-free time matters so much in recovery.)

2. Doing nothing else while eating needn’t be a rule, in recovery or the rest of life, but with encouragement it can become a nice default. (I’m now deliberately not getting something to read or listen to while eating when alone at home. It feels nice for the baseline to be no accompaniment.)

3. It is possible to be gently aware of your surroundings and other people without feeling like (or giving the impression that) you’re either staring at people or ignoring them. I shared some smiles and other nice little acknowledging kind of interactions with people (and once joined a couple for tequilas at their table), but on the whole just got on with my thing as they did theirs.

4. The typical lack of awareness of one’s surroundings when in a group or (especially) a couple is very noticeable when you’re observing from the outside. (No real point to this other than: Being alone really does enhance a certain kind of mindful embodied presence.)

5. Time passes. An evening meal, for example, has lovely natural rhythms: water, wine, ordering, bread and butter, starter, main, maybe pudding. These rhythms take over; they look after you. Curated mealtime structures become part of the rhythms of a day that is begun and ended and punctuated with them.

6. If you don’t do anything else with this time, it can become time for experiencing and for thinking that would not have existed otherwise. I had some interesting and important thoughts whilst sitting and sipping and taking mouthfuls of things. None of us is bored nearly enough these days, and new thoughts tend to come only when we’re a bit bored, i.e. where there’s not yet another thing keeping us occupied. A mealtime setting (eating and drinking to be doing, but nothing else) is a nice way to create a state that’s “boring” enough to be fertile but not so much so that we resent and curtail it.

7. Having a table at the edge of the room, looking inwards, helps. (Once I sat in the middle and had a slightly uncomfortable feeling of not knowing what was going on behind me. I’m sure this would improve with practice too.)

8. Waiters being lovely helps.

9. Alcohol helps 🙂

10. Taking the money out of it (except tips, sadly) helps.

11. Everything gets easier with repetition. And for me at least, this proved to be one of the many things that get ultra-easy with very few repetitions.

12. Morning scrambled eggs are improved by the addition of black bean sauce.

13. Nightcap sambuca is not improved by the addition of coffee beans.

If you give this a go, I strongly recommend doing it more than once (if not 28 times) before drawing your conclusions.

My conclusions are: Eating out alone is a liberated luxury, and it’s lovely to be able to experience it as such. Trying it out could be a great way to test the strength of your recovery, and to strengthen it further.

Doing this experiment has also given me an idea I wouldn’t have had otherwise. Editing this post, it just occurred to me that there could be no more fitting way to remember my father on the tenth anniversary of his death than to eat rare rib-eye and béarnaise and fries and drink claret at the place where I did so with him back in 2008, a few months into my recovery. Being alone feels right for this, because I won’t be.

Recovery Memoir Experiment: Call for Participants


Help shape the future of an unpublished book about recovery from anorexia.

A new study investigates the effects of reading a book about recovery from anorexia designed specifically to encourage positive therapeutic effects and discourage harmful responses.

I’m excited to announce an opportunity to take part in an experiment investigating how reading habits and eating disorders intersect. As I outlined in my post on “Consuming fictions”, when it comes to narrative reading and eating disorders (or illness in general) the assumptions far outweigh the known facts. There’s quite a bit of evidence on the benefits of self-help bibliotherapy (reading a relevant self-help book with or without professional guidance), but we know very little about books in other genres, like novels, short stories, or memoirs. This feels to me like a gap that needs filling (Troscianko, 2018a).

Previous research

The empirical eating disorder-specific research that’s been done so far has, to my knowledge, mainly been conducted by me and by my colleague Rocío Riestra Camacho. In a large-scale survey study published in the Journal of Eating Disorders in 2018 (Troscianko, 2018b), I found that fiction about eating disorders (which in practice our respondents, most of whom had personal experience of an eating disorder, also took to include memoir) was perceived to have had almost universally negative effects on all the dimensions we investigated, sometimes thanks to deliberate self-triggering. By contrast, fiction that has nothing to do with eating disorders was generally perceived as having been neutral or positive in its effects. 

In a more recent study conducted as part of her PhD, Rocío presented her cohort of healthy volunteers with two works of young adult sports fiction by Miranda Kenneally: one group read both as published, the other group with a reading guide (presented via pop-up messages in the margin) specially designed to help readers draw out positive lessons from the texts with respect to eating, the body, and exercise. The choice of genre was an interesting one: Sports fiction obviously thematizes food, exercise, and the body, but in a context quite different from an eating disorder. The study found a significant difference between groups on level of espousal of gendered body stereotypes, which reduced for the group reading with the guide. There were also statistically nonsignificant trends towards improved results on the EAT-26 (a standard measure of eating disorder susceptibility) in the reading-guide group and towards worsened results in the control group who read the books in their standard form. You can hear more about how Rocío designed the experiment and what she learned in a recent Textual Therapies podcast episode.

Thus the little evidence we have highlights the real potential for reading to have eating disorder-relevant effects, in both desired and undesired ways. As far as I know, however, no experimental research has been conducted involving participants with an active eating disorder reading an entire book that isn’t a self-help book. Memoirs are a troublesome genre: They may often or usually be written with the professed aim of being useful to readers, yet the same authors often also remark that reading other people’s memoirs about eating disorders exacerbated their illness (Jones, 2020). Memoirs may of course be written with “usefulness” aims that aren’t therapeutic—most often, with a vague “awareness raising” intention (which may or may ever get meaningfully furthered). Or the intent may be explicitly or implicitly self-therapeutic, or “cathartic”: more about what the writing process does for the writer than about what the finished product may or may not do for its readers. In any case, most authors don’t attempt to systematically find out, before or after publication, what uses readers put their books to, or what responses they may have elicited in readers, inadvertently or otherwise.

This experiment

This study, on which Rocío and I are collaborating, will be the first to assess the effects of reading a book about recovery from anorexia versus the effects of reading a book with no relation to eating disorders (though with structural and thematic similarities in other respects). The book about recovery is called The Hungry Anorexic. The book hasn’t yet been published, and the experiment will determine whether it gets published—in its current form, in an edited form, or not at all. Precise statistical cutoffs have been specified in advance, and if the book “fails” these tests, it will not be released. If specific elements turn out to be significantly problematic, they will be revised. 

This project invites a new kind of readerly involvement in the authorial process, and I’m excited to find out what happens when readers get to shape the publication trajectory of a text.

The experiment involves reading one of the books (you’ll be assigned randomly to one group or the other) within a roughly 2-week period, and completing some questionnaires and open-ended questions 1 week before, at intervals during, and 2 weeks after. You’ll be asked not to read any other books about eating disorders during the 5 weeks of the study. If you’re interested in taking part, and you’re 18 or over, currently have a restrictive eating disorder or are recovering from it, have a BMI of 15 or over, and are fluent in English, as well as identifying as female, you’re warmly invited to read more and consider signing up to take part. Everyone who completes the study can choose to be entered into a prize draw to win one of four prizes of GPB 100 (roughly USD 140).

You can read more and sign up for the study here: Do get in touch with me via the contact form if you have any questions not addressed by the information sheet.

And if you’re interested in reading in the recovery context, but don’t want or aren’t able to take part in this experiment, you might like to check out the final section of the post I mentioned earlier for some recommendations on how to read in recovery. Tldr: Read things you love that have nothing to do with eating disorders, and keep eating!


Jones, K. (2020). Representing young men’s experience of anorexia nervosa: A French-language case study. Medical Humanities. Direct PDF download (preprint) here.

Troscianko, E.T. (2018a). Fiction-reading for good or ill: Eating disorders, interpretation and the case for creative-bibliotherapy research. Medical Humanities, online first 21 April. Direct PDF download here.

Troscianko, E.T. (2018b). Literary reading and eating disorders: Survey evidence of therapeutic help and harm. Journal of Eating Disorders, 6, 8. Open access here

The Mathematics of Optimization in Recovery


How to optimize the optimization process that is recovery from anorexia.

If you prefer, you can find abridged versions of the three parts in this miniseries on Psychology Today starting here.

Part 1: Introducing cost functions and their limitations

“Optimizing for” something has a simple colloquial meaning of setting things up to get as much as you can of something—anything from health to happiness to salary payments in the bank at the end of the month. It also has a more specific meaning in the mathematics of optimization: selecting the best option (with regard to an agreed-upon scoring metric) from a set of alternatives. 

In the last two parts of my recent series on cognitive dissonance, I used optimization in the first sense: as a simple concept to structure questions we can usefully ask ourselves about what we’re doing in life and why. In this new series of posts I’d like to explore how the more technical aspects of optimization theory can also provide tools to help in recovery from an eating disorder. This series has been written in collaboration with my partner James Anderson, an engineer/mathematician who specializes in optimization amongst other topics (and who also made this excellent contribution to the blog a few years ago), so you needn’t take my word for it! Our aim is to convince you that a little maths goes a long way when it comes to any big life decisions you may be making, recovery included.

So what are we doing when we’re optimizing for something, in technical terms? A typical optimization problem consists of three key elements: the decision variables (the choices you’re making), the cost function (often referred to as the objective function), and a set of constraints (not all problems necessarily have these). Imagine you’re an investment banker tasked with creating a stock portfolio. Here the decision variables are the number of each stock you want to buy. The objective is to maximize the predicted profits (an alternative objective could be minimize risk), and the constraints are that you only have certain amount of money to spend. The choice of stock that produces the maximum profit without exceeding the budget is the optimal choice.

Likewise, we can frame recovery from an eating disorder as an optimization problem. Here our goal is to either maximize some utility, e.g. health or happiness, or minimize costs, e.g. time off work/studies, or discomfort, or weight gain (more on this later), or probably to do both simultaneously. An algorithm is at play, with some degree of explicitness, constantly trying to find the optimal solution to the choice between getting more of the utility and incurring more of the costs. Optimization algorithms are iterative, i.e. they begin at some initial point with a candidate decision variable, and then proceed by incrementally adjusting the decision variable until it is not possible to make the objective function cost any smaller (or larger if you’re maximizing).

Figure 1. The red curve is the cost function. It associates a cost for every choice of x (the decision variable). The optimal solution is choosing x=2, corresponding to a cost of -7. No other choice of x gives a lower cost, thus it’s optimal.

Figure 1 shows a simple example of an optimization problem with one variable and no constraints. Our goal is to choose a value of x that makes our cost function as small as possible. On the horizontal axis are the possible values of x that we can choose from. The points on the red curve tell us what the cost is for choosing that particular value of x. In this example, the optimal solution (the choice of x that provides the lowest cost) is attained at x=2, and the associated cost is -7. By definition of it being optimal, there is no other choice of x that returns a lower cost. Because this example is very small (only one decision variable), we can easily visualize the problem. The optimal point denoted by the gold circle is at the bottom of the bowl. A sub-optimal choice of x is any other point on the red curve (one choice is given by the green circle which corresponds to choosing x=-6, and has a cost of 9). Intuitively, it seems that to obtain an optimal solution, we could pick any point on the curve and simply walk downhill until it flattens out. You may have heard of “machine learning” in the news a lot recently. Believe it or not, this idea of walking downhill is behind the scenes in just about every ML technique invented.

The cost function we used was x^2-4x-3. (This is just made up for illustration; there’s nothing meaningful about this choice other than it looks pretty!) The red line is obtained by plotting this value for various choices of x. In our banking example, should our banker be dabbling in the FTSE 100, then the curve would exist in 100 dimensions and we wouldn’t be able to draw it and visually find the bottom. But even in 100 dimensions, mathematically the concept of down is still defined and so we can use a computer to tell us which way to go.

So now we have the basics of how the decision variable, the cost function, and the constraints interact in any optimization process. Optimization is a powerful framework for generating decisions in response to complex sets of aims and constraints, but like everything, it has its limitations. The main two inherent limitations of optimization algorithms are as follows:

  • The optimization algorithm is based on a model of the process, and the model is the only reality that exists for the purposes of this algorithm. With respect to the banking example, our friendly investment banker has to model how she thinks the market will behave, and from this extract a cost function. Of course, there is no model that exactly describes this process and so simplifying assumptions are made. She may also introduce other types of assumption that make solving the problem more tractable (more on this later in the series). The point is, at some point the cost function and constraints are specified and you have to set about solving the problem. If your model is garbage, your solution will be too. This means a solution that is technically optimal (satisfies the constraints, and is the best choice according to your cost function) can be practically useless, like if the banker’s definition of shareholder value bears no relation to what any actual shareholder would want, or (in the personal context) if your definition of happiness actually amounts to “what my mother taught me happiness should look like” and you’re not a lot like your mother. In such cases, then what is optimal in your model will not in fact be the best thing you can do.
  • Optimization algorithms are myopic. At each iteration, the algorithm will always choose to update its choice of decision variable so as to reduce its cost. Graphically, this corresponds to always going downhill until you no longer can. In the example in Figure 1 this strategy is a good one, because no matter where you start, going downhill always reduces your cost. Unfortunately, real life doesn’t look like Figure 1 (it would be kind of dull if it did). A more lifelike example is shown in Figure 2. 
Figure 2. Most real-world problems suffer from having many “local” minima. The green and blue solutions, though each at the bottom of a valley, may be significantly worse than the optimal (gold) solution.

In this example, simply going downhill won’t guarantee that you obtain the lowest cost. The optimal solution (the choice of x that has the lowest cost associated with it) is shown in gold. However, there are three “valleys” in this example and using the “head downhill” strategy will fail to take you to the optimal solution if you start in the wrong place. If you were to start at the grey triangle, going downhill will take you to the blue circle, and here you get stuck. It’s true that you’re better off now than the position you started at, but the “locally optimal” choice of x has a cost which is far worse than the true optimal solution.

If you start from the grey star, a slightly strange thing happens. Moving in the downhill direction (to the right—which corresponds to the algorithm choosing a larger x) will decrease your cost. However, if you were to go left, a small initial increase in cost would then give way to a large decrease in cost as you find the optimal solution at the foot of the valley. So which way should you go? Looking at the figure, you’re probably saying to yourself, “go left, it’s obvious—a small discomfort followed by a huge gain”! You are of course correct. But it’s not quite that simple. We’ve neglected to tell you precisely what information the algorithm has access to when working out where to go. Recall, the algorithm’s only goal is to choose a decision vector x that makes the cost as small as possible. The easiest way to explain how the algorithm chooses x to achieve this is through metaphor. 

Imagine you’re skiing on a mountain range with lots of valleys and your hotel is at the bottom of the lowest one. You’ve been skiing all day, lost track of time, and now it’s getting dark and more annoyingly you’re surrounded by thick fog. A few minutes ago you got off a chairlift which took you up to a pass. All you can see is the ground around you within a 6 foot radius. It’s relatively straightforward to work out which way down is by looking at the ground, but what you can’t assess is whether this piste is taking you down into the right valley. You now have three options:

  1. Stay where you are—you’re guaranteed not to get home tonight and risk freezing (though if you’re lucky a pisteur will turn up and rescue you).
  2. Ski downhill—you’re in a densely populated ski area with resorts at the bottom of every valley, and even if this is the wrong valley, an expensive cab ride home is better than a cold night on the mountain. 
  3. Sidestep or carry your skis uphill—hopefully you’ll get back to a sign telling you which way to your resort (unfortunately you don’t know how far up you will have to go, you’ll definitely expend a lot of energy, and it’s possible your resort isn’t even in the neighbouring valley). 

To summarize, the optimization algorithm has the same local information as our unfortunate skier: With access to only local information, skiing down the mountain (reducing the cost) certainly has its benefits: temperature increases as altitude decreases, ski resorts are likely positioned at the foot of a piste. But it’s also possible that clambering uphill to get to the ridge will enable you to find your valley and get home safely. The problem is, you can’t see what’s over the ridge. 

This optimization viewpoint provides an interesting lens through which to view semi-recovery. You were initially ill, and you have made some progress towards recovery. Through a sequence of choices you have got a bit better, but then something happens that makes you realize you’re not done yet. Let’s say you notice you’re getting a bit obsessive about having the “right” snacks in your bag whenever you go out. You take some action: you stop packing the snacks. Unfortunately this gets you to the foot of the wrong valley: Now when you go out you don’t have to bother with the forward planning, but now you get hungry, you don’t manage to spontaneously buy things to eat, and your old dysfunctional hunger responses kick back in. Only drastic (non-obvious) action (i.e., going uphill even although it feels unnatural) will get you to full recovery—the global optimum. In this case that might look like making a plan for always taking snacks with you, and of bigger and scarier and more varied kinds than you were having before, until the distorting effects of your long-term malnutrition are fully eliminated and you get relaxed about spontaneously buying things when you want them. Rather than pretending you can already do without any planning, temporarily planning more is what will actually get you fully better.

This starts to show how we can use the optimization lens as a way of thinking about how we ended up in semi-recovery in the first place. Recall the two limitations of an optimization algorithm. Limitation 1 (the model is the only reality for the algorithm) suggests that one reason for getting stuck was that for some reason your model of health (or whatever your recovery endpoint is) was incorrect. It was implicitly modelled (the cost function was chosen) such that healthy living looked like Figure 1, in which case any improvement in eating habits (e.g. eating more like healthy people do) would take you closer to perfect health, when in fact, reality looks much more like Figure 2, and there are choices that reduce local costs but get you further away from health. (In our example, skipping straight to a casual “I don’t need to carry food around with me” attitude, when you’re not yet physically robust enough to weather long periods without food without slipping back into disordered ways.) Armed with this incorrect model, Limitation 2 dooms you to failure. You make small gains, but unfortunately towards a local optimum (functional and passing as “normal” in the day-to-day, but getting further from actually resolving your malnutrition and its after-effects). If you’re lucky, the cost of being stuck in the local valley is not too different from being fully healthy, but often the cost is much more.

Coming back to the first limitation, the problem of not knowing (whether) the deeper valley exists at all may be a question of model accuracy too. Let’s say you want to stop counting calories. You’re considering deliberately aiming for some weight gain to help you stop, because calorie-counting’s purpose for you has always been to prevent you from gaining weight, so making weight gain an explicit aim should help you get rid of it. You may overestimate the steepness and/or length of the local incline in making the calculation about whether to incur the weight-gain cost. For instance, you may assume that as soon as you count less you’ll balloon in size, or even that your counting is an effective weight control strategy in the first place, when in fact neither is true: there may be far more effective mechanisms available to regulate bodyweight than your counting habit, and the amount you’ll need to gain to reach that self-sustaining stability is, let’s say, 2 kg rather than 10. An extreme case of this, where model fit starts to look increasingly delusional, is in obsessive compulsive disorder (a temporary version of which is often a consequence of malnutrition), where the short-term costs of not doing the checking or counting or other ritualized behaviour are radically overestimated, the long-term costs of doing it are radically underestimated, and the model is equally radically adrift from the real world. We’ll come back to the question of how to test out whether the model you have is actually representative of reality, and how to make it more so if it isn’t.

In conclusion, then, the locally optimal point denoted by the blue circle is the mathematical modelling of the classic semi-recovered state: thinking that this life—in which you’re not terribly unwell anymore but are still restricting and exercising and counting and doing all you can to control your body size—is as good as it gets. You’re too terrified of the costs of change (most often, these amount to not much more than “weight gain”) to give yourself a chance to get to really recovered—because you’re not sure whether really recovered (the gold circle) really exists, or is possible for you. You hesitate, and then quite likely you do nothing, because even the local optimum has stability, which is attractive—but this is a problem when the stability is keeping you somewhere globally suboptimal. One half of the problem is that the valley you’re in feels like home because you’ve been here so long that it seems like it should be. The other half of the problem is that you don’t know what the costs of getting out of it really are, or how most efficiently to incur them. What you need is a trusty tour guide to get you over the ridge and back to where you should be.

In the next part of this series, we’ll move beyond the limitations of optimization as they apply to semi-recovery to explore more ways in which the recovery process is an optimization process and can itself be optimized by viewing it through this lens. This amounts, if you like, to turning yourself into the tour guide you trust.

Part 2: Multiple cost functions, aka optimizing for more than one thing at once

In Part 1 we considered two limitations of optimization processes and the light they shed on pseudo-recovery. Let’s now think more about what the implications of optimization are for getting full recovery to happen. In Part 1 we only considered problems where there was just a single objective, i.e. just one thing to be minimized or maximized. Of course this is not necessarily realistic. In this post we will concentrate on the more lifelike situation of optimization with multiple objectives. For simplicity, we focus on the case of two objectives, but everything carries over to an arbitrary number of objectives. Equally, the cartoon idealization of optimization as “finding the floor of the valley” that we introduced in Part 1 will carry over to this setting, as we’ll be combining the two objectives into a single parameterized objective function (sounds far more complicated than it really is) to be minimized.  

Recall our friendly stockbroker. While her job is to build a profitable portfolio for her investors, most investors don’t have the stomach for highly volatile stocks—even although this often leads to greater profits. In order to keep everyone happy she should ideally minimize risk whilst maximizing profit. Unfortunately, these are conflicting objectives. Government bonds are very stable, but the profit margin is small. A new startup may return huge profits, but may also tank! It’s not possible to make huge profits while taking no risk. In this multi-objective setting, there is no longer a single obviously optimal solution (as there was in the “deepest valley” case with only one objective). Whenever you’re trying to optimize for more than one objective, there is always a family of solutions. Each member of this family will be optimal for a particular weighting of objectives. Let’s make this concrete using our investment banking example. Our banker wants to select a portfolio with two objectives: minimize loss (for our purposes this the same as maximizing profit: we view a negative loss as a profit) and minimize risk. We combine these two objectives into one optimization problem with a new cost function that looks like

Cost: w*loss(x)+(1-w)*risk(x),

recalling that the goal is to pick to make the cost as small as possible.  The parameter w can take any value in between 0 and 1, and our friendly banker selects a value to control how much she cares about profits versus risk. For example, if she selects w=1 then the cost reduces to simply minimizing loss(x), i.e. the optimization problem she solves to select her portfolio ignores risk. To see why this is the case, set w=1 in cost and you end up with 0*risk(x)—which is always equal to zero regardless of the choice of x. (We said it’s not as complicated as it sounds!) Using an identical argument, if she chooses w=0, then when she optimizes, she ignores making a profit in favour of being risk-averse. A value of w=0.5 places equal emphasis on profit and risk mitigation, and any other choice favours one over the other. The point is, any choice of will result in an optimization problem for which there exists an optimal solution, and you cannot say one solution is “better” than another. Technically they are all optimal. In Figure 3 we depict this graphically. 

Figure 3. Points along the dotted curve denote solutions to the multi-objective optimization problem for different values of w. Points off the curve are either suboptimal or not achievable. Note that a distinction that needs to be made is that w is not a decision variable. It has to be fixed a priori by the banker. Then, the optimization problem is solved using the cost with that fixed value of w.

The curve represents the family of solutions for a given choice of w. Points not on the curve represent either suboptimal or impossible solutions. In the suboptimal case, risk could be decreased making less profit, profit could be increased without incurring any more risk, or both! The cloud illustrates the space where you can do both at once to improve your solution: there’s really no reason to hang around here. Points to the left of the curve are unattainable: either the conflicting objectives simply don’t permit you make this choice, or else to be at this point means violating a constraint, e.g., the banker spending more money than she has access to. An extreme case of this is indicated by the heart. Here you would make huge profits while incurring no risk at all. Sounds great, but never going to happen! 

Again, the key message here is that we cannot say that any one point on the curve (i.e., any single solution) is better than any other: they’re all technically optimal (just for different values of the weight parameter w). Let’s say your two cost functions are, with whatever degree of explicitness, ill health and bodyweight. (We choose ill health rather than good health for simplicity, so we’re minimizing both the “bad” things: as with minimizing loss, negative ill health is good health! And we choose bodyweight because fear of weight gain tends to be the greatest sticking point for the majority of people who struggle to get fully better from restrictive eating disorders, i.e. this fear is a primary driver in the psychological optimization process.) This means there are multiple different combinations of ill health and bodyweight that will satisfy the optimality requirement, because where you get more of one you typically get less of the other.

In the perceived trade-off between ill health and bodyweight, being extremely underweight or overweight is similar to the heart point in Figure 3: it is not allowed because a constraint in the optimization problem would rule this out. Of course, if your model of health is wrong, and does allow for runway-model stick-thinness, then the corresponding optimization problem doesn’t bear any resemblance to reality and being extremely underweight will be seen as a viable optimal solution. This is an example of Limitation 1 mentioned in Part 1: If your model is garbage, so is your solution. A lot of what it means to grow up and gather maturity and wisdom is probably (hopefully!) that we learn to make our models less like garbage, by working out what the meaningful constraints are and within what range they operate, often through the pain of trial and error. What you like to eat and how much of it is just one example, but a critical one—and one that far too many people let be guided by poor dietary science, advertising, peer pressure, and other factors that have little to do with what will help your life feel good. 

Alongside the problem of lacking the appropriate model constraints, a possibly more important because more common problem arises when the model is correct, but you look at extreme points on the curve of solutions. There may be points on the curve that correspond to solutions of optimization problems where it is possible to be under- or overweight relative to health. Such a situation occurs if too much “weight” is given to one objective, i.e., is very close to 1 or 0. Although technically an optimal solution, that doesn’t necessarily make it a sensible choice. For example, this may correspond to a BMI of 18, which although healthy according to some of the more irresponsible of the researchers who conduct clinical trials on therapeutic interventions for anorexia, is not compatible with full health for most people, especially not for almost anyone emerging from long-term malnutrition. Thinking back to our banker, this could correspond to a choice of w=1 and the profit being minuscule but highly risk-averse. Here you’re prioritizing keeping your weight low over reducing your ill health, and the outcome is the predictable standard case post-anorexia: years or decades of stuckness in partial recovery.

As the example of the misguided clinical definitions of a “healthy” BMI suggests, it is easy to revert to “textbook” versions of an optimization processes, where you treat readymade parameters as all you need, without remembering that the constraints and the weightings need to be right for you. Algorithms of often fiendish complexity are at work in our lives all the time, whether or not we realize it, and if we don’t realize it, the default parameters will tend to dominate. Given how low-quality much eating disorder treatment is, and how well it aligns with the most common anorexic fears, the defaults are unlikely to do you as much good as your tailored versions could: They’re likely to push you into errors such as fruitless psychologizing and/or adhering to nonsensically low BMI limits (Troscianko and Leon, 2020). Your personal definition of health combined with your body’s physiology, for example, mean that not all points on the theoretically optimal curve are equally optimal for you. In the optimization processes constantly running to dictate our behaviours (anything from whether to walk or run over to the window, to whether to up my energy intake by 500 calories from tomorrow), choices are being made, with priors shaped by a lifetime’s worth of learning, and decisions reached via rapid and complex simulations of predicted outcomes. Turning a critical gaze on some of these often near-automatic choices, via the injection of a bit more individually oriented intuition (or common sense, whatever you want to call it) is often crucial to helping algorithmically optimal translate into actually good. 

In a more directly positive sense, too, the existence of a curve of optimal solutions is a useful thing to bear in mind because it counters the paralysis it’s easy to feel during recovery at the idea that there is only one endpoint. This often manifests in the form of feeling you’ve “messed up recovery” already so there’s no point carrying on; that you have no clue where to go from here; that all your options feel wrong, etc. Pretty much everyone feels some version of this at some point, partly because every recovery process is nonlinear: something as life-changing and extended and periodically frightening as this always involves stopping and starting, regressing and restarting, making good progress in some areas while flatlining on others. An unhelpful notion of the perfect (and nonexistent) recovery process, which is likely to make you give up when your recovery doesn’t correspond to it, arises partly as a function of an unhelpful notion of the perfect (and nonexistent) recovery outcome: the idea that there’s a single, possibly quite brittle, hard-to-find destination, and that all the odds are stacked against you ever actually stumbling upon it.  

This is in stark contrast to the reality, which is that fully recovered is by definition flexible, nonsingular. Being well again is about comfortably inhabiting a range of options, in your bodyweight and everything else. It’s anorexia, after all, that has always insisted on narrow stasis. Relatedly, the perceived brittleness of recovery as process and endpoint may relate to the perceived narrowness of “normality” as a guide and/or an intended endpoint. You can read more about the complications involved in aspiring to normality in a previous post (“Who wants to be normal?”), but for our purposes here, it’s worth noting that there are as many normalities as there are sampling methods: what you decide are your relevant dimensions, your relevant demographic, your way of ascertaining the actual behaviours and/or values of the demographic you’re observing—all these factors determine what gets spat out at the end that you choose to label “normality”. If you choose to sample from catwalk fashion or bikini competitions, you’ll end up with a particularly unpleasant brittleness of definition. All real people and sets of people have their curves, and the extent to which they’re OK with moving around on them, and away from and back towards them, is a decent proxy for how relaxed a life they’re living, and how much you might want to aspire to something similar. If you choose to emulate in your later recovery that subset of your friends who go on about how much less good they’d feel without their 3 x weekly Peloton and their quarterly juice cleanses, you can expect to end up as brittle as they are—actually more so, because of your history of disordered eating and exercise. If you choose more flexible models, or create your own if no decent ones are available around you, you have a far better chance of achieving a recovery that deserves the name.

In the third and final part of this series, we’ll run through some options to help you keep the optimization process that is recovery keep on track despite the complexities of competing objectives.

Part 3: Applied optimization

In Part 2 of this series we considered what happens when you have an optimization problem (let’s say recovery) with multiple competing objectives (let’s say getting healthy whilst having a bodyweight that is acceptable to you). In this final part of the series, we consider some troubleshooting options to help recovery stay on track despite the complexities of competing objectives that change as you do.

As we saw in Part 2, as soon as you have more than one objective, you have more than one optimal solution: specifically, you have a whole curve populated with optimal solutions. It often doesn’t feel this way when we’re doing something difficult where we’re having to balance multiple aims. The most immediate reason why we don’t see the curve is usually fear and misinformation. Hiding the curve from you is what fear does best, because fearing something means, in optimization terms, trying to minimize the hell out of it. This means that you radically reduce the number of available optimization options. With respect to Figure 3 in Part 2, this would be as if you could see only a tiny fraction of the curve that has  all the optimal points on it, because e.g. only a tiny range of weight gain is acceptable to you thanks to your fear. 

This fear is probably responsible for the fact that the majority of people who have anorexia don’t get fully better, i.e. never even get to the optimal curve. And even if it doesn’t prevent you from reaching the optimal curve, fear might well persuade you, once you’re on it, that you’re not on a curve, i.e. inhabiting one of a family of equally good points, but at a unique optimal point that must not be deviated from. You might have got to a weight where you are truly capable of full health, but be terrified about gaining or losing even a kilo or two, in case that wrecks everything. This sense of having no options, no freedom of movement, will reliably endanger any potentially fully-recovered state through paradoxical fear of its endangerment. It’s worth remembering that misinformation comes in many forms, including dressed up in medical clothing. For example, one form of life-wrecking misinformation is the notion that a BMI of 20 to 25 is healthy and that this is all any of us should aim for or consider acceptable, whatever our genetics or our life circumstances. 

Figure 4. The cost function is different for different demographics. A narrow biomedical view considers that “healthy” exists only within a certain BMI range (where the cost is uniformly low), with quantized steps up to ranges of increasing unhealthiness. The “average” person’s view shows a much smoother distribution, while somebody with a restrictive eating disorder has a completely skewed cost function—the optimal point of which is a very low BMI.  

Figure 4 gives a crude approximation of the biomedical view, in which BMI 20 to 25 counts as uniformly “healthy” and every increment above or below is an immediate jump into the next category, all of which are considered problematic, and increasingly so as their distance from “healthy” increases. This is reflected by an increase in cost with each increment. A standard somewhat more sensible view is given in green, with a curve denoting gradual increases in costs away from a “low-20s” BMI. An anorexic viewpoint given in red is the “20 is already fat” view. Recall that as viewed as an optimization problem, the goal is to “choose” a BMI that takes you to the bottom of these curves. All these views are profoundly limited in their applicability to your specific life and health, not least because BMI is such a profoundly limited measure and because the optimum may be quite a bit higher than we tend to think (Nuttall, 2015), but it’s obvious that the anorexic model is considerably more damaging than the other two, while shaped by both. A therapeutic process will typically try to align the red curve closer with the green.

Emily has listened to a depressing number of anecdotes about doctors and therapists telling their patient/client at the start of weight restoration, “don’t worry, we won’t let you get too fat, you can stop when you get to 20 [or insert even lower number here]”. This type of approach is great for pandering to the eating disorder and so reducing some forms of conflict within the therapeutic relationship, and potentially for getting initial buy-in from the ill person. Unfortunately, it also condemns their recovery effort to failure, because dictating your health based on an arbitrary number is what you’ve been doing all along, and in no way solves your problem. It also makes people who have already got to 19 or 20 and are in no way better yet feel they’ve done something terribly wrong, when all they’ve done is the thing most people do: not go far enough. The “get to a minimally ‘healthy’ BMI and then start dieting” model of “recovery” is a function of the terror of “overweight” that has grown medically normalized even amongst professionals treating people whose primary problem is that very terror.

This brings us to the question of where the optimization objectives come from. Why should bodyweight be pitted against health in the first place? Let’s say that your model includes this health/bodyweight tradeoff because your concept of attractiveness is tied tightly to body size and shape, i.e. overall you believe that slimness correlates with attractiveness. Your belief that this is the case has numerous dodgy foundations (explored in this pair of “Is thin beautiful?” posts), but it is the model you’re currently imposing on reality. “Reality” here is other people’s perceptions of you—the people you want to be attractive for—and let’s say that it happens that 99% of the people you want to attract would actually find you more attractive at a higher weight than you’re at now. Your messed-up model is thus pushing you to keep engaging in weight control behaviours to avoid an outcome that would make you both healthier and more attractive. The model may also be predicated on the assumption that being “attractive” to other people will result in more success, happiness, or other things you want. This too may not turn out to be true: For instance, being “attractive” beyond a certain level may result in less not more professional respect. The point is, how we expect the world to work and how it does are often not particularly well aligned. Again this is illustrated in Figure 4. The eating disorder sufferer’s curve gets arbitrarily high for increases in BMI beyond a certain point and never increases as BMI decreases. In contrast, the notional “average” person considers very high and very low BMIs to be poor “choices”.

What to do? How do you improve your model? The best way is to perform tests against the structure of reality followed by feedback of the results into the prior model to create an updated, better one. In the real world, tests against reality usually look like changing one thing and seeing what else changes, e.g. in this case gaining 5 kilos and seeing whether the relevant other people interact differently with you, and if so how. Another method might be via model-focused attitude change prior to behaviour (and then body) change. For example, one way of changing a model is to change the weightings on the various functions it includes, e.g. in this case deciding on a 2:1 ratio of ill health to bodyweight. Doing so would put you on a completely different part of the curve in Figure 3 from the fear-dictated segment you were on before. One way to make this change really happen might be by giving yourself an opportunity to exacerbate your cognitive dissonance around body ideals, as I described in this post: People who have to publicly criticise the thin ideals they currently endorse experience a level of unpleasant dissonance that can drive significant attitude change in service of reducing the dissonance. That is, you come to really believe your criticisms (that the thin ideal is one of the best ways to keep women docile, say) because it’s so uncomfortable having to make those criticisms while still deep down believing the opposite (that being thinner really is just better).

In general, though, attitude change tends to be more reliably achieved by starting with behaviour, not least because behaviours have a two-in-one efficacy: they directly change both physical (e.g. bodyweight) and also psychological states. In the end, nothing will really make you care less about being thin other than getting less thin—partly because of the cognitive rigidity and obsessiveness that are malnutrition’s inevitable consequences, partly because, as with most other everyday worries, fearing and avoiding things tends to make far greater spectres of them than actually living them.

Therapy, counselling, coaching, and other forms of professional support are of course another context where model improvement is one of the main stated aims. When you’re seriously ill, everything tends to look bad, and when you’re seriously ill with an eating disorder, change (involving weight restoration) tends to look especially bad. Therapy may help you see that there is in fact a downhill, cost-reducing direction to be (often quite straightforwardly) taken. Returning to our simple one-objective model in Part 1, therapy may also be invaluable in helping you out of the shallow valley towards the one where things are genuinely good, not just tolerable. Therapeutic guidance may, more generally, help you improve the accuracy of your model by smoothing out the perceived spikiness of the curve, as we show in Figure 5.

Figure 5. Once recovery begins, your model of health changes. It now bears more resemblance to the green curve in Figure 4. However, at each BMI point in a possible recovery process, the perceived costs of the next BMI point may be unreasonably high.

Figure 5 shows how the anorexic view often changes once recovery has started. During recovery, each new change that induces weight gain is perceived as coming with significant costs. Each time you do make the change and gain the weight, you tend to get a little bit more sensible about it: you recognise that you’re getting all kinds of benefits (i.e. negative costs!) associated with the weight you’ve gained, and you have a little more confidence in your ability to make the changes and keep making them. Still, it often remains difficult. You gain a bit, you get stuck thanks to your perception of radically increased costs from continuing for the next little phase, then you continue anyway. There will probably be significant perceived costs to allowing your weight to increase further once it’s reached the biomedical “healthy” range.

Crucially, just as in the previous figures, this is all about perceptions, not reality. And your “pretty much zero perceived costs” may turn out to be anywhere! It’s really unlikely to be anywhere near where the eating disorder viewpoint would originally have put it, though. It’s amazing how different things seem looking back from looking forward: you weigh 20 kg more than you used to, and you feel less fat and less bothered about fat than you ever did at the lower weight. It feels like magic, but it isn’t, it’s just your cost function finally getting some updates. Throughout this process, one of the jobs of anyone supporting you through your recovery is to help you smooth out the perceived costs curve: to reduce the spikiness of the spikes, so that each incremental portion of progress is less agonized. In this sense, it’s precisely the mismatch in models, and the fact that the therapist’s is a closer fit to ground truth, that drives the therapeutic method.

A less happy outcome is that there is model discrepancy in a different sense: with respect to the objective function being worked towards. It sometimes happens, especially with “severe and enduring” cases of anorexia, that therapists or other professionals are tacitly optimizing for damage limitation rather than recovery. In effect, in such a case we have the opposite of the desired effect of helping you towards the home valley: Here the therapist thinks you’re at grey triangle in Figure 2 (see Part 1) and that you don’t have what it takes to get all the way over to the globally optimal gold circle. They may think they have good reasons for this, for instance that aiming for full recovery, with the intensive demands for behavioural and physical change this entails, is more likely to result in further deterioration than in success. Regardless of whether any evidence supports this (we know of none that does), not making the therapeutic agenda explicit is never acceptable. The fact that it often happens is a reminder, however, not to take for granted that everyone’s model or objective function is what you think it is, or is the same as yours. This is all the more important when they have as powerful a status in your life as anyone does who is helping manage your recovery. 

We hope this may have given you some new ideas about how to configure the optimization processes you’re engaged in—the recovery one and any others. Finally, it’s worth reiterating the basic point that all this is in a fundamental sense a process. Recovery is nothing if not iterative experimentation: try something, see what happens, assess, remodel, try something new. And, again, when optimizing for more than one objective in tension with each other, there are always multiple solutions. These two facts combined open out into a more flexible way of conceiving of recovery than may be your default.

Just remember: You can only ever optimize the model you have, and hope it’s representative of real life—or take steps to make it more so. There’s a bunch of choices where you can’t say one is better than the other. They’re just different: they give you more of one thing and less of another. There’s no free lunch: everything is a tradeoff, and you get to decide which you like best. Don’t let anyone else decide for you.


Nuttall, F. Q. (2015). Body mass index: Obesity, BMI, and health: A critical review. Nutrition Today50(3), 117. Open-access full text here.

Troscianko, E. T., & Leon, M. (2020). Treating eating: A dynamical systems model of eating disorders. Frontiers in Psychology, 11, 1801. Open-access full text here.