Prevalence, sociodemographic factors, psychological distress, and coping strategies related to compulsive buyinga cross sectional study in Galicia, Spain

If you feel anxious, you go shopping to feel better. That makes sense — a small reward can provide a brief distraction. If you feel worse afterward and go again anyway, that's still recognizable. But if the buying has become something you can't stop, draining your finances and corroding your relationships, at what point does a habit become a disorder? Otero-López and Villardefrancos went looking for that line in the general population of Galicia, Spain, and they found that seven out of every one hundred people were already on the wrong side of it. That number matters because of how it was produced. Most prior research on compulsive buying leaned on college students or self-selected online respondents, which is part of why prevalence estimates in the literature swing wildly — anywhere from three point six to thirty one point nine percent. Otero-López and Villardefrancos built something more solid: two thousand one hundred fifty-nine adults, recruited door-to-door across all four Galician provinces, and sampled to mirror the two thousand eleven Spanish census. Ages ran from fifteen to sixty five, with a mean of thirty five point four. Participants were screened out if they were already in psychotherapy or on psychopharmacological treatment, keeping the sample clean of people already identified as clinical cases. Compulsive buying itself was measured with the Spanish version of the German Compulsive Buying Scale, a sixteen-item instrument with a Cronbach's alpha of point ninety-one in this sample — that's a high reliability score. Anyone falling two standard deviations above the sample mean, which worked out to a score of forty-five or higher on a scale that ran up to sixty-four, was classified as a compulsive buyer. Seven point one percent of the sample crossed that threshold. That figure lines up with population-based studies from Germany, Denmark, and the United States. It's a real number, not an artifact of a convenience sample. So who are these people? The demographic picture is clear. Women showed higher prevalence than men — eight point three versus five point nine percent — and the mean score on the buying scale for women was nearly thirty compared to just over twenty-seven for men. Age was the other dividing line: compulsive buyers averaged thirty point three years old, while non-compulsive buyers averaged thirty-five point eight. When the researchers broke the data into age bands, the twenty to twenty-nine range held the largest share of compulsive buyers, about a third of all cases, with the fifteen to nineteen bracket not far behind at nearly a quarter. What's equally telling is what didn't predict compulsive buying. Marital status, education level, employment situation, perceived social class — none of these distinguished the groups at statistically significant levels. The demographic signal is concentrated almost entirely in sex and youth. A multivariate logistic regression confirmed that both of these effects held when everything else was accounted for. The full model — which included sociodemographic variables, psychological symptoms, and coping strategies simultaneously — was highly significant and explained about forty-six percent of the variance in who fell into the compulsive buying category. Being female and being younger remained independent risk factors even after psychological distress and coping style were in the model. And now comes the psychological layer, which is where the picture deepens considerably. Otero-López and Villardefrancos assessed symptoms using the Symptom Checklist-90-R, or SCL-90-R, extracting five subscales: anxiety, depression, obsession-compulsion, somatization, and hostility. Compulsive buyers scored significantly higher than non-compulsive buyers on every single one of these dimensions. But the gaps were not equal across symptoms — obsession-compulsion, depression, and anxiety showed the largest differences by far. On obsession-compulsion, compulsive buyers averaged seventeen point sixty versus eight point forty-nine for non-buyers. On depression, nineteen point sixty-nine versus nine point thirty-five. On anxiety, twelve point seventy-five versus five point sixty-nine. Those are not marginal differences. Those are gaps of roughly double across three distinct symptom dimensions. When all predictors competed in the regression model, three psychological symptoms survived: anxiety, depression, and obsession-compulsion each independently predicted compulsive buying status. Somatization and hostility, which had looked significant in simple group comparisons, dropped out once everything was considered together. So the psychological core of the risk profile is that triad — anxiety, depression, and obsessive-compulsive symptoms. The clinical logic is not hard to follow. Buying offers a fast, controllable hit of relief. For someone flooded with anxiety or sinking into depression, that relief is powerful precisely because it's immediate. But here's where the coping data becomes the most important piece. Otero-López and Villardefrancos measured two broad categories of coping strategy. Active, problem-focused coping covered things like problem solving and cognitive restructuring — approaches that engage directly with the source of distress. Passive-avoidance coping covered problem avoidance, wishful thinking, self-criticism, and social withdrawal — approaches that sidestep distress rather than address it. Compulsive buyers scored significantly higher on every passive-avoidance strategy and significantly lower on both active strategies. Think about what that combination looks like in practice. A person is anxious, perhaps depressed, and running obsessive loops of thought. Instead of working through the problem, they avoid it. They tell themselves things will somehow improve without action — wishful thinking. When that doesn't work, they blame themselves — self-criticism — which deepens the distress. And somewhere in that loop, buying becomes the go-to move. It's not solving anything, but it interrupts the loop temporarily. Then the guilt arrives, and the cycle tightens. The regression confirmed that this isn't just correlation within a single snapshot. Problem avoidance, wishful thinking, and self-criticism each independently increased the odds of compulsive buying in the multivariate model. Problem solving and cognitive restructuring, meanwhile, acted as protective factors — people who used them more were less likely to be classified as compulsive buyers. This is the clearest mechanistic signal in the paper. The passive-avoidance strategies don't just accompany compulsive buying; they are part of the predictor profile that distinguishes compulsive buyers from everyone else, even after controlling for demographic factors and symptom severity. Pulling this all together, the risk profile that emerges from Otero-López and Villardefrancos looks like this: female, younger, carrying elevated anxiety, depression, and obsessive-compulsive symptoms, and relying on passive-avoidance coping while underusing active problem-focused strategies. That combination produced a model explaining nearly half the variance in compulsive buying status in a representative population sample. That's a strong result for behavioral research of this kind. There's an important limitation to consider before drawing practical conclusions. This is a cross-sectional study, meaning everyone was measured at one point in time. The causal arrows cannot be determined from the data alone. Does anxiety drive someone toward compulsive buying? Almost certainly, in some cases. Does compulsive buying — with its financial fallout, its secrecy, its shame — generate more depression and anxiety? Probably that too. The relationship likely runs in both directions, reinforcing itself over time. The data here can't untangle that, and Otero-López and Villardefrancos are candid about it. What the data can do is point toward who deserves attention and what might help them. Younger adults and women show elevated risk and would be logical targets for screening. People presenting to clinicians with anxiety, depression, or obsessive-compulsive symptoms — especially if they describe habitually avoiding problems, engaging in wishful thinking, or falling into cycles of self-blame — should perhaps be asked about their buying behavior. Treatment, the findings suggest, might be most effective if it directly targets the coping deficit: building problem-solving capacity and cognitive restructuring skills, while working to reduce the pull of avoidance and wishful thinking. Those are trainable skills. That's a workable intervention target. Seven percent of a general population is not a small number. In a consumer society where purchasing is relentless and frictionless — a tap of a phone and next-day delivery — the conditions for compulsive buying are built into the environment. This study's value is in making the vulnerable population legible: not just a demographic sketch, but a psychological and behavioral profile specific enough to act on. 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