The University as big business:

The case of King's College London

 

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King's College London is in the news for all the wrong reasons. In a document full of weasel words ('restructuring', 'consultation exercise'), staff in the schools of medicine and biomedical sciences, and the Institute of Psychiatry were informed last month that 120 of them were at risk of redundancy. The document was supposed to be confidential but was leaked to David Colquhoun who has posted a link to it on his blog.  This isn't the first time KCL has been in the news for its 'robust' management style. A mere four years ago, a similar though smaller purge was carried out at the Institute of Psychiatry, together with a major divestment in Humanities at KCL.

Any tale of redundancies on such a scale is a human tragedy, whether it be in a car factory or a University. But the two cases are not entirely parallel. For a car factory, the goal of the business is to make a profit. A sensible employer will try to maintain a cheerful and committed workforce, but ultimately they may be sacrificed if it proves possible to cut costs by, for instance, getting machines to do jobs that were previously done by people. The fact that a University is adopting that approach – sacking its academic staff to improve its bottom line – is an intellectual as well as a human tragedy. It shows how far we have moved towards the identification of universities with businesses.

Traditionally, a university was regarded as an institution whose primary function was the furtherance of learning and knowledge. Money was needed to maintain the infrastructure and pay the staff, but the money was a means to an end, not an end in itself. However, it seems that this quaint notion is now rejected in favour of a model of a university whose success is measured in terms of its income, not in terms of its intellectual capital.

The opening paragraph of the 'consultation document' is particularly telling: "King’s has built a reputation for excellence and has established itself as a world class university. Our success has been built on growing research volumes in key areas, improving research quality, developing our resources and offering quality teaching to attract the best students in an increasingly competitive environment." Note there is no mention of the academic staff of the institution. They are needed, of course, to "grow research volumes" (ugh!), just as factory workers are needed to manufacture cars. But they aren't apparently seen as a key feature of a successful academic institution. Note too the emphasis is on increasing the amount of research rather than research quality.

The most chilling feature of the document is the list of criteria that will be used to determine which staff are 'at risk'.  You are safe if you play a key role in teaching, or if you have grant income that exceeds a specified amount, dependent on your level of seniority.
What's wrong with this? Well, here are four points just for starters:

1. KCL management justifies its actions as key for "maintaining and improving our position as one of the world’s leading institutions". Sorry, I just don't get it. You don't improve your position by shedding staff, creating a culture of fear, and deterring research superstars from applying for positions in your institution in future.

2. The 'restructuring' treats individual scientists as islands. The Institute of Psychiatry has over the years built up a rich research community, where there are opportunities for people to bounce ideas off each other and bring complementary skills to tackling difficult problems. Making individuals redundant won't just remove an expense from the KCL balance sheet – it will also affect the colleagues of those who are sacked. 

3. As I've argued previously, the use of research income as a proxy measure of research excellence distorts and damages science. It provides incentives for researchers to get grants for the sake of it – the more numerous and more expensive the better. We end up with a situation where there is terrific waste because everyone has a massive backlog of unpublished work.
 
4. I suspect that part of the motivation behind the "restructuring" is in the hope that new buildings and infrastructure might reverse the poor showing of KCL in recent league tables of student satisfaction. If so, the move has backfired spectacularly. The student body at KCL has started a petition against the sackings, which has drawn attention to the issue worldwide.I urge readers to sign it.

Management at KCL just doesn't seem to get a very basic fact about running a university: Its academic staff are vital for the university's goal of achieving academic excellence. They need to be fostered, not bullied. One feels that if KCL were falling behind in a boat race, they'd respond by throwing out some of the rowers.

How wishful thinking is damaging PETA's cause

I was appalled a couple of weeks ago to see this advert by PETA - People for the Ethical Treatment of Animals.

Readers of this blog will be aware that spurious claims of links with autism is one subject that gets me extremely cross - parents have quite enough to contend with, without the host of irresponsible people who come up with a new autism cause every day.

Needless to say, there is no scientific evidence for a link between milk consumption and autism, and so I wondered why on earth PETA should be promoting such an idea.

I didn't know much about them until this advert cropped up. I first came across PETA when I was in Australia and they had a campaign protesting about "sheep ships" - live export of animals to the Middle East. I was impressed at the way they highlighted the treatment of the animals, who were taken on a long sea voyage in vile conditions just so that they could be slaughtered in a particular way on arrival.

Now that I've read more background, I realise that the autism advert is, alas, a classic case of the "wishful thinking" fallacy, which tends to crop up in debate when there are complex ethical issues involved. Human rights and animal rights often come into conflict, and many of us find it difficult to steer a course between the competing demands. For instance, should I eat meat? I like the taste and it's a good source of protein and iron, but does that justify farming and killing animals? Should we experiment on animals? It may lead to important breakthroughs for conditions such as Parkinson's disease and Alzheimer's disease, but large numbers of animals will be subjected to unpleasant procedures as a result. Many people when confronted with such choices will give priority to the needs of humans, while at the same time trying to ensure the treatment of animals is as humane as possible.

PETA campaigners, however, take an absolute stance, arguing that "animals are not ours to eat, wear, experiment on, use for entertainment or abuse in any way." Their agenda, then, is not to improve conditions for animals used by humans, but to prevent such use altogether.

This poses a problem. Most people aren't going to be persuaded to become vegan on ethical grounds. It seems that PETA therefore decided we need to be presented with other motivations, namely the idea that milk is bad for you. It would be convenient for PETA if this were true, because it would mean that sensible people would stop drinking milk, regardless of their attitude to animals. In this regard, it's wishful thinking. The claim was challenged last week by Sense About Science, whose conversation with a representative from PETA is described here. Rather than accepting that the evidence for an autism link was not supported by science, Ben Williamson of PETA responded with further outlandish claims, maintaining that consumption of milk contributes to “asthma, constipation, recurrent ear infections, iron deficiency, anaemia and even some cancers”.

The same wishful thinking style of argument is used by those who want to ban all animal experimentation and who consequently argue that all such work is pointless, has never achieved anything, and is only done to promote the careers of those doing the experiments. A moment's thought reveals the fallacy of this viewpoint: it would have to mean that all of those doing animal experiments are either so stupid they can't see the pointlessness of their work, or are sadists who enjoy being unpleasant to animals. Neither proposition is credible. But if it were true, the argument would be easy to win.

The wishful thinkers try to bypass ethically difficult decisions by arguing that there are good practical reasons for adopting their preferred solution. We should become vegan to avoid autism, they say. We should stop animal experimentation because it achieves nothing, they say. Would that life were so simple.

Not only is it logically indefensible to take this line, it is actually counterproductive. PETA's response to Sense About Science confirms that this is an organisation that cannot be trusted to get things right. They will say whatever is convenient to promote their views and will distort the evidence if it helps. Their latest campaign has destroyed any credibility they might have had with the scientifically literate public.

Should Rennard be reinstated?

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Things could not be much worse for Liberal Democrat party. After catastrophic results at both council and European elections a couple of weeks ago, there have been questions raised about Nick Clegg's leadership, and resignation of senior LibDem Matthew Oakeshott. Now it's being suggested that Chris Rennard, former Chief Executive who was suspended from the party in January after allegations of sexual harassment were made against him, should be reinstated.

A few days ago, Rennard issued an apology to the women who had complained about him, something he'd been asked to do before his suspension. His supporters, who include powerful people such as Alex Carlile and David Steel, argue that the party needs him: he has undoubted skills that have come from experience of managing the party over many years. In particular, Carlile is quoted as saying that Rennard had now done ‘everything asked of him’, and:

Lord Rennard has been harassed by this inquiry for a year and a half nearly…He [Rennard] may have misjudged situations and been less aware of the personal space of his interlocutors and has misjudged the effect of what he perceived as friendliness would have on them. That’s exactly what he apologised for

I was particularly intrigued by comments from Shirley Williams, who said on Radio 4 that the case had been 'blown up'. She told BBC Radio 4's Today programme: "He was a very decent and loyal member of the party as the chief executive, he did huge amounts for the party," adding: "If I may say so, there are some comparisons which suggest there are real, serious sexual harassments and so forth, and I don't think he's one of the most serious cases."

Meanwhile, Rennard is threatening legal action against the Lib Dems if he is expelled from the party.

So it seems that the case in favour of Rennard's reinstatement is that:

• He is a superb politician of value to his party
• He didn't do anything wrong - or at least not intentionally
• Insofar as other people think he did something wrong, he's said he's sorry that they are upset
• He could cause a lot of trouble for the party if they don't let him back in
• He has suffered enough

I'm amazed that powerful supporters of Rennard seem to think that this makes a credible case for Rennard's reinstatement.

Of course politicians aren't perfect. They are human beings like the rest of us, doing a difficult job. I don't like deceit but I reckon, for instance, that infidelity is so common a human failing that it would be ridiculous to sack a politician over an affair. Furthermore, I don't assume that a man who makes sexual advances to a woman is a sexist beast: if no man ever did that, then the human race would die out. And let's not pretend that such advances are always shunned by women.

But context is everything. Flirting was invented as a means of establishing whether your advances are indeed welcome. If a man isn't receiving clear signals of interest from a woman he should keep well away. To impose yourself on another person who is giving you no encouragement whatsoever is a violation of personal space. It's hard to believe that Rennard can't read the signals - rather, it seems he chose to ignore them.

I disagree with Shirley Williams that this is not serious. I'm sure Shirley will have had her fair share of hands on knees or pats on the bottom over the years, and either ignored them or given a withering put-down. Some of the women who complained about Rennard have been interviewed on TV and, as you would expect for women who have made a mark in politics, they are articulate and gutsy and look well able to stand up for themselves. Nevertheless, it's clear that they were upset and disturbed by Rennard's behaviour - my impression was that it was partly because it was so surprising - a sudden grope out of left field, so to speak, without any warning.

Then there's the question of power. This piece by Polly Toynbee argues it better than I could, emphasising that  more powerful you get, the less likely you are to be challenged in anything you do.  Since complaints about Rennard date back at least to 2007, it's clear that this is a pattern. I find myself wondering whether the incidents that we're aware of are just the tip of the iceberg, and whether other women were also affected but too afraid to speak out.

Perhaps the strongest argument against Rennard, though, is not his wandering hands, but the way he responded as events unfolded. First with denial ("I didn't do anything wrong"), then with threats ("I'll take you to court") and finally with a plea for our sympathy ("the events of the last fourteen months have been a most unhappy experience for him, his family and friends"). The apology was supposed to "draw a line" under this issue, but it does just the opposite. If there's one thing his apology makes clear, it's that he just doesn't get it - and nor, it seems, do his supporters. His words (with my emphasis) speak for themselves:

He does recognise as suggested in the full report, that he may well have encroached upon “personal space”. In relation to this, Alistair Webster suggested in his report that Lord Rennard “may well wish to consider an apology”. He would therefore like to apologise sincerely for any such intrusion and assure them that this would have been inadvertent. He hereby expresses his regret for any harm or embarrassment caused to them or anything which made them feel uncomfortable.

Here's what a proper apology might have looked like:

I accept that I encroached upon personal space of the women, and in so doing caused them harm and embarrassment. I sincerely regret doing so and undertake not to make unwanted physical advances to women in future.

Alas, we're not going to see that, because Rennard doesn't think it's true. And as long as that remains the case, then he, and his supporters, are a massive liability to the party.

Data sharing: Exciting but scary

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Yesterday I did something I've never done before in many  years of publishing. When I submitted a revised manuscript of a research report to a journal, I also posted the dataset on the web, together with the script I'd used to extract the summary results. It was exciting. It felt as if I was part of a scientific revolution that has been gathering pace over the past two or three years, which culminated in adoption of a data policy by PLOS journals last February. This specified that authors were required to make the data underlying their scientific findings available publicly immediately upon publication of the article. As it happens, my paper is not submitted to PLOS, and so I'm not obliged to do this, but I wanted to, having considered the pros and cons. My decision was also influenced by the Wellcome Trust, who fund my work and encourage data sharing.

The benefits are potentially huge. People usually think about the value to other researchers, who may be able to extract useful information from your data, and there's no doubt this is a factor.  Particularly with large datasets, it's often the case that researchers only use a subset of the data, and so valuable information is squandered and may be lost forever.  More than once I've had someone ask me for an old dataset, only to find it is inaccessible, because it was stored on a floppy disk or an ancient, non-networked computer and so is no longer readable.  Even if you think that you've extracted all you can from a dataset, it may still be worth preserving for potential inclusion in future meta-analyses.

Another value of open data is less often emphasised: when you share data you are forced to ensure it is accurate and properly documented. I enjoy data analysis, but I'm not naturally well-disciplined about keeping everything tidy and well-organised. I've been alarmed on occasion to return to a dataset and find I have no idea what some of the variables are, because I failed to document them properly.  If I know the world at large will see my dataset then I won't want to be embarrassed by it, and so I will take more care to keep it neat and tidy with everything clearly labelled. This can only be good.

But here's the scary thing. data sharing exposes researchers to the risk of being found out to be sloppy or inaccurate. To my horror, shortly before I posted my dataset on the internet yesterday I found I'd made a mistake in the calculation of one of my variables. It was a silly error, caused by basing a computation on the wrong column of data. Fortunately, it did not have a serious effect on my paper, though I did have to go through redoing all the tables and making some changes to the text.  But it seemed like pure chance that I picked up on this error – I could very easily have posted the dataset on the internet with the error still there. And it was an error that would have been detected by anyone eagle-eyed enough to look at the numbers carefully.  Needless to say, I'm nervous that there may well be other errors in there that I did not pick up. But at least it's not as bad as an apocryphal case of a distinguished research group whose dramatic (and published) results arose because someone forgot to designate 9 as a missing value code. When I heard about that I shuddered, as I could see how easily it could happen.

This is why Open Data is both important for science but difficult for scientists. In the past, I've found mistakes in my datasets, but this has been a private experience.  To date, as far as I am aware, no serious errors have got into my published papers – though I did have another close shave last year when I found a wrongly-reported set of means at the proofs stage, and there have been a couple of instances where minor errata have had to be published. But the one thing I've learned as I wiped the egg off my face is that error is inevitable and unavoidable, however careful you try to be. The best way to flush out these errors is to make the data public. This will inevitably lead to some embarrassment when mistakes are found, but at the end of the day, our goal must be to find out what is the case, rather than to save face.

I'm aware that not everyone agrees with me on this. There are concerns that open data sharing could lead to scientists getting scooped, will take up too much time, and could be used to impose ever more draconian regulation on beleaguered scientists: as DrugMonkey memorably put it:  "Data depository obsession gets us a little closer to home because the psychotics are the Open Access Eleventy waccaloons who, presumably, started out as nice, normal, reasonable scientists." But I think this misses the point. Drug Monkey seems to think this is all about imposing regulations to prevent fraud and other dubious practices.  I don't think this is so. The counter-arguments were well articulated in a blogpost by Tal Yarkoni. In brief, it's about moving to a point where it is accepted practice to make data publicly available, to improve scientific transparency, accuracy and collaboration. 

Changing the landscape of psychiatric research:

What will the RDoC initiative by NIMH achieve?

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There's a lot wrong with current psychiatric classification. Every few years, the American Psychiatric Association comes up with a new set of labels and diagnostic criteria, but whereas the Diagnostic and Statistical Manual used to be seen as some kind of Bible for psychiatrists, the latest version, DSM5, has been greeted with hostility and derision. The number of diagnostic categories keeps multiplying without any commensurate increase in the evidence base to validate the categories. It has been argued that vested interests from pharmaceutical companies create pressures to medicalise normality so that everyone will sooner or later have a diagnosis (Frances, 2013). And even excluding such conflict of interest, there are concerns that such well-known categories as schizophrenia and depression lack reliability and validity (Kendell & Jablensky, 2003).

In 2013, Tom Insel, Director of the US funding agency, National Institute of Mental Health (NIMH), created a stir with a blogpost in which he criticised the DSM5 and laid out the vision of a new Research Domain Criteria (RDoC) project. This aimed "to transform diagnosis by incorporating genetics, imaging, cognitive science, and other levels of information to lay the foundation for a new classification system."

He drew parallels with physical medicine, where diagnosis is not made purely on the basis of symptoms, but also uses measures of underlying physiological function that help distinguish between conditions and indicate the most appropriate treatment. This, he argued, should be the goal of psychiatry, to go beyond presenting symptoms to underlying causes, reconceptualising disorders in terms of neural systems.

This has, of course, been a goal for many researchers for several years, but Insel expressed frustration at the lack of progress, noting that at present: "We cannot design a system based on biomarkers or cognitive performance because we lack the data". That being the case, he argued, a priority for NIMH should be to create a framework for collecting relevant data. This would entail casting aside conventional psychiatric diagnoses, working with dimensions rather than categories, and establishing links between genetic, neural and behavioural levels of description.

This represents a massive shift in research funding strategy, and some are uneasy about it. Nobody, as far as I am aware, is keen to defend the status quo, as represented by DSM.  As Insel remarked in his blogpost: "Patients with mental disorders deserve better". The issue is whether RDoC is going to make things any better. I see five big problems.

1. McLaren (2011) is among those querying the assumption that mental illnesses are 'disorders of brain circuits'. The goal of the RDoC program is to fill in a huge matrix with new research findings. The rows of the matrix are not the traditional diagnostic categories: instead they are five research domains: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Systems for Social Processes, Arousal/Regulatory Systems, each of which has subdivisions: e.g. Cognitive Systems is broken down into Attention, Perception, Working memory, Declarative memory, Language behavior and Cognitive (effortful) control. The columns of the matrix are Genes, Molecules, Cells, Circuits, Physiology, Behavior, Self-Reports, and Paradigms. Strikingly absent is anything about experience or environment.

This seems symptomatic of our age. I remember sitting through a conference presentation about a study investigating whether brain measures could predict response to cognitive behaviour therapy in depression.  OK, it's possible that they might, but what surprised me was that no measures of past life events or current social circumstances were included in the study. My intuitions may be wrong, but it would seem that these factors are likely to play a role. My impression is that some of the more successful interventions developed in recent years are based not on neurobiology or genetics, but on a detailed analysis of the phenomenology of mental illness, as illustrated, for example, by the work of my colleagues David Clark and Anke Ehlers. Consideration of such factors is strikingly absent from RDoC.

 2. The goal of the RDoC is ultimately to help patients, but the link with intervention is unclear. Suppose I become increasingly obsessed with checking electrical switches, such that I am unable to function in my job. Thanks to the RDoC program, I'm found to have a dysfunctional neural circuit. Presumably the benefit of this is that I could be given a new pharmacological intervention targeting that circuit, which will make me less obsessive. But how long will I stay on the drug? It's not given me any way to cope with the tendency of checking the unwanted thoughts that obtrude into my consciousness, and they are likely to recur when I come off it.  I'm not opposed to pharmacological interventions in principle, but they tend not to have a 'stop rule'. 

There are psychological interventions that tackle the symptoms and the cognitive processes that underlie them more directly.  Could better knowledge of neurobiological correlates help develop more of these?  I guess it is possible, but my overall sense is that this translational potential is exaggerated – just as with the current hype around 'educational neuroscience'. The RDoC program embodies a mistaken belief that neuroscientific research is inherently better than psychological research because it deals with primary causes, when in fact it cannot capture key clinical phenomena. For instance, the distinction between a compulsive hand-washer and a compulsive checker is unlikely to have a clear brain correlate, yet we need to know about the specific symptoms of the individual to help them overcome them.

3. Those proposing RDoC appear to have a naive view of the potential of genetics to inform psychiatry.  It's worth quoting in detail from their vision of the kinds of study that would be encouraged by NIMH, as stated here:

Recent studies have shown that a number of genes reported to confer risk for schizophrenia, such as DISC1 (“Disrupted in schizophrenia”) and neuregulin, actually appear to be similar in risk for unipolar and bipolar mood disorders. ... Thus, in one potential design, inclusion criteria might simply consist of all patients seen for evaluation at a psychotic disorders treatment unit. The independent variable might comprise two groups of patients: One group would be positive and the other negative for one or more risk gene configurations (SNP or CNV), with the groups matched on demographics such as age, sex, and education. Dependent variables could be responses to a set of cognitive paradigms, and clinical status on a variety of symptom measures. Analyses would be conducted to compare the pattern of differences in responses to the cognitive or emotional tasks in patients who are positive and negative for the risk configurations.

This sounds to me like a recipe for wasting a huge amount of research funding. The effect sizes of most behavioural/cognitive genetic associations are tiny and so one would need an enormous sample size to see differences related to genotype. Coupled with an open-ended search for differences between genotypes on a battery of cognitive measures, this would undoubtedly generate some 'significant' results which could go on to mislead the field for some time before a failure to replicate was achieved (cf. Munafò, & Gage, 2013).

The NIMH website notes that "the current diagnostic system is not informed by recent breakthroughs in genetics". There is good reason for that: to date, the genetic findings have been disappointing. Such associations as are found either indicate extremely rare and heterogeneous mutations of large effect and/or involve common genetic variants whose small effects are not of clinical significance. We cannot know what the future holds, but to date talk of 'breakthroughs' is misleading.

4. Some of the entries in the RDoC matrix also suggest a lack of appreciation of the difference between studying individual differences versus group effects.  The RDoC program is focused on understanding individual differences. That requires particularly stringent criteria for measures, which need to be adequately reliable, valid and sensitive to pick up differences between people.  I appreciate that the published RDoC matrices are seen as a starting-point and not as definitive, but I would recommend that more thought goes into establishing the psychometric credibility of measures before embarking on expensive studies looking for correlations between genes, brains and behaviour. If the rank ordering of a group of people on a measure is not the same from one occasion to another, or if there are substantial floor or ceiling effects, that measure is not going to be much use as an indicator of an underlying construct. Furthermore, if different versions of a task that are supposed to tap into a single construct give different patterns of results, then we need a rethink – see e.g. Foti et al, 2013; Shilling et al, 2013, for examples.  Such considerations are often ignored by those attempting to move experimental work into a translational phase. If we are really to achieve 'precision medicine' we need precise measures.

5. The matrix as it stands does not give much confidence that the RDoC approach will give clearer gene-brain-behaviour links than traditional psychiatric categories.

For instance, BDNF appears in the Gene column of the matrix for the constructs of acute threat, auditory perception, declarative memory, goal selection, and response selection. COMT appears with threat, loss, frustrative nonreward, reward learning, goal selection, response selection and reception of facial communication. Of course, it's early days. The whole purpose of the enterprise is to flesh out the matrix with more detailed and accurate information. Nevertheless, the attempts at summarising what is known to date do not inspire confidence that this goal will be achieved.

After such a list of objections to RDoC, I do have one good thing to say about it, which is that it appears to be encouraging and embracing data-sharing and open science. This will be an important advance that may help us find out more quickly which avenues are worth exploring and which are cul-de-sacs. I suspect we will find out some useful things from the RDoC project: I just have reservations as to whether they will be of any benefit to psychiatry, or more importantly, to psychiatric patients.

References
Foti, D., Kotov, R., & Hajcak, G. (2013). Psychometric considerations in using error-related brain activity as a biomarker in psychotic disorders. Journal of Abnormal Psychology, 122(2), 520-531. doi: 10.1037/a0032618

Frances, A. (2013). Saving normal: An insider's revolt against out-of-control psychiatric diagnosis, DSM-5, big pharma, and the medicalization of ordinary life. New York: HarperCollins.

Kendell, R., & Jablensky, A. (2003). Distinguishing between the validity and utility of psychiatric diagnoses. American Journal of Psychiatry, 160, 4-12.

McLaren, N. (2011). Cells, Circuits, and Syndromes: A Critical Commentary on the NIMH Research Domain Criteria Project Ethical Human Psychology and Psychiatry, 13 (3), 229-236 DOI: 10.1891/1559-4343.13.3.229

Munafò, M. R., & Gage, S. H. (2013). Improving the reliability and reporting of genetic association studies. Drug and Alcohol Dependence(0). doi: http://dx.doi.org/10.1016/j.drugalcdep.2013.03.023

Shilling, V. M., Chetwynd, A., & Rabbitt, P. M. A. (2002). Individual inconsistency across measures of inhibition: an investigation of the construct validity of inhibition in older adults. Neuropsychologia, 40, 605-619.


This article (Figshare version) can be cited as:
 Bishop, Dorothy V M (2014): Changing the landscape of psychiatric research: What will the RDoC initiative by NIMH achieve?. figshare. http://dx.doi.org/10.6084/m9.figshare.1030210  


P.S.8th October 2015. 
RDoC is in the news again, leading Jon Roiser to send me a tweet asking whether my views expressed re social factors were just intuitions or evidence-based. That's a good question, given the importance I attach to evidence. So is there any evidence that past life events or current social situation predict response to intervention in depression? 
I have to confess I am not an expert in this area. My views are largely formed from what I learned years ago when training as a clinical psychologist, when research by Brown and Harris showed life events were potent predictors of depression:

Brown, G.W. & Harris, T.O. (1978). Social origins of depression: A study of psychiatric disorder in women. London: Tavistock. 

These studies were not on intervention, but it does seem plausible that the same factors that are associated with initial onset will also influence response to intervention. Thus it seems reasonable that it would be harder to treat someone's depression if they are still experiencing the factors that led to the initial depression, e.g. living in an abusive relationship, coping with the death of a loved one, or experiencing financial stress.
In response to Jon's query, I did a small trawl through recent articles in Web of Science; I have only looked at abstracts for these, so don't know how good quality the evidence is, but the general impression is that social factors and life events are still regarded as important factors in the etiology of depression - and therefore might also be expected to influence response to intervention. Here's a handful of papers:

Colman, I., Zeng, Y., McMartin, S. E., Naicker, K., Ataullahjan, A., Weeks, M., . . . Galambos, N. L. (2014). Protective factors against depression during the transition from adolescence to adulthood: Findings from a national Canadian cohort. Preventive Medicine, 65, 28-32. doi: 10.1016/j.ypmed.2014.04.008

Cwik, M., Barlow, A., Tingey, L., Goklish, N., Larzelere-Hinton, F., Craig, M., & Walkup, J. T. (2015). Exploring Risk and Protective Factors with a Community Sample of American Indian Adolescents Who Attempted Suicide. Archives of Suicide Research, 19(2), 172-189. doi: 10.1080/13811118.2015.1004472

Dour, H. J., Wiley, J. F., Roy-Byrne, P., Stein, M. B., Sullivan, G., Sherbourne, C. D., . . . Craske, M. G. (2014). Perceived social support mediates anxiety and depressive symptom changes following primary care intervention. Depression and Anxiety, 31(5), 436-442. doi: 10.1002/da.22216

Kemner, S. M., Mesman, E., Nolen, W. A., Eijckemans, M. J. C., & Hillegers, M. H. J. (2015). The role of life events and psychological factors in the onset of first and recurrent mood episodes in bipolar offspring: results from the Dutch Bipolar Offspring Study. Psychological Medicine, 45(12), 2571-2581. doi: 10.1017/s0033291715000495

Sheidow, A. J., Henry, D. B., Tolan, P. H., & Strachan, M. K. (2014). The Role of Stress Exposure and Family Functioning in Internalizing Outcomes of Urban Families. Journal of Child and Family Studies, 23(8), 1351-1365. doi: 10.1007/s10826-013-9793-3

I'd be happy to consider alternative evidence, but my view is that if we want to look at brain or gene predictors, we'd do well to also assess life events and social factors - things that are relatively easy to measure, might explain a significant proportion of variance, and could also possibly provide a mechanism to account for neurobiological findings.