The research, led by Sofia Burmester of Karolinska Institutet and the Stockholm Centre for Dependency Disorders, involved semi-structured interviews with nineteen adults diagnosed with sedative, hypnotic, or anxiolytic use disorder under the DSM-5, all of whom were undergoing or had completed tapering treatment at a publicly funded outpatient addiction clinic in Sweden. The participants—ten men and nine women with a mean age of 53.4 years—had used benzodiazepines for anywhere from two to forty-five years before entering treatment, with an average of 16.6 years of use. More than half had used two or more benzodiazepines or z-drugs simultaneously, with alprazolam being the most common starting medication, frequently combined with zopiclone or zolpidem. Over a third reported obtaining benzodiazepines outside the healthcare sector at some point in their lives, underscoring the depth of dependence in this population.

The treatment they described follows a carefully structured protocol. Patients at the clinic are assigned both a primary nurse and a psychiatrist, undergo a full clinical evaluation including laboratory and drug toxicology testing, and then begin an individualized tapering plan built on shared decision-making. While standard guidance suggests reducing the dose by roughly ten percent every one to two weeks, the actual pace is negotiated between patient and psychiatrist and reviewed regularly. Patients attend weekly or more frequent in-person visits, where a regulated number of tablets are dispensed until the next appointment. Tapering can be paused entirely to allow stabilization if withdrawal symptoms, psychiatric symptoms, or substance use worsen. Doses may be switched to long-acting formulations and distributed evenly across the day to blunt withdrawal. In practice, a patient starting at 100 milligrams of oxazepam daily might follow a sixteen-week schedule, reducing by 10 milligrams per week initially and then slowing to about 5 milligrams per week.

Using reflexive thematic analysis, the researchers identified three overarching themes in how patients experienced this process. The first, ‘Navigating motivation and involvement,’ reveals that motivation is not a fixed prerequisite for treatment but a fluctuating, fragile state that rises and falls with symptoms, circumstances, and clinical relationships. Many participants entered treatment ambivalent, torn between hope for a life without benzodiazepines and dread of the withdrawal ahead. ‘Your motivation, that’s the most important thing, but it’s not so easy,’ one participant said. Others described steely determination from the outset, while some confessed that the fear of feeling unwell made each dose reduction feel like an ordeal requiring them to ‘grit your teeth and steel yourself.’ Crucially, participants reported that empathetic, respectful interactions with healthcare personnel could transform ambivalence into engagement—one credited the staff with helping them ‘see some kind of a life where I don’t need to use benzos.’

Withdrawal symptoms emerged as a powerful force shaping motivation, and their severity varied dramatically. Some participants were pleasantly surprised by how manageable the process felt, with one reporting it was ‘surprisingly little’ and even asking clinicians to speed the taper up. Others described profound suffering: sleeplessness and anxiety so severe that one participant ‘thought I was starting to lose my mind.’ The study found that when patients experienced intense symptoms, their motivation to continue could collapse—unless the treatment structure responded flexibly. Participants praised schedules that allowed them to pause at a difficult dose for a few extra days or to slow the pace when life became overwhelming. Conversely, when they perceived the schedule as rigid and impersonal, the experience could feel coercive. One participant described feeling ‘almost like I’ve been held hostage,’ and others expressed frustration at being left uninformed about treatment goals and expectations, a combination that amplified helplessness and strained communication with staff.

The second theme, ‘Replacing benzodiazepines with new coping strategies,’ captures perhaps the most psychologically profound challenge of tapering: surrendering the one tool that has managed mental illness, often for decades, without knowing what will take its place. Participants described the medication as a crutch that ‘serves a certain function,’ and letting go of it meant relinquishing control over their only coping mechanism. For those whose underlying anxiety or insomnia persisted or worsened during treatment, the final small doses felt almost impossible to release. In moments of distress, some resorted to taking more than prescribed or turned to alcohol, and even after discontinuation, many had to actively resist the urge to resume. ‘There have been a few nights where I’ve thought about it: Maybe I should just take one pill anyways?’ one participant admitted. Relapse was not an abstract risk but a live, immediate fear—one participant said that if the anxiety returned at full force, ‘it feels like there’s really nothing that can stop it from happening.’

Participants largely expected the healthcare system to help them build replacements for the medication, and psychological treatment emerged as the most valued option for addressing the root causes of benzodiazepine use. Those who connected with a psychologist described treatment as being ‘about more than just tapering out,’ a reframing that helped sustain clinic attendance. Yet the study documents a troubling gap between the offer of psychological care and patients’ ability to actually use it. Some declined therapy due to anxiety, time constraints, or past negative experiences. Others encountered delays or poor timing that rendered it ineffective—one participant saw a psychologist while still on a high dose, describing themselves as ‘totally dazed in the head’ and unable to benefit. Fear of relapse also pushed some patients toward other supports, including Narcotics Anonymous or non-addictive medications. Without an effective replacement strategy, participants described lives that remained restricted and symptom-filled, with one saying the future made them feel ‘panicked’ and, after so many years of feeling unwell, ‘meaningless in a way.’

The third theme, ‘Balancing support throughout treatment,’ reveals how finely tuned the therapeutic relationship must be. Participants valued clinicians not only for their expertise—which made them ‘feel safe in some way’—but for their availability and genuine attention. Close relationships with nurses, in particular, allowed patients to laugh, speak openly about missteps such as taking extra doses, and disclose dissatisfaction without fear of losing care. Conversations that normalized their experiences alleviated anxiety; one participant summed it up simply: ‘I’m not crazy.’ But support could also miss the mark in both directions. Brief visits and difficulty reaching staff between appointments left some feeling alone during the worst withdrawal periods, while unfulfilled promises bred helplessness—’we’re helping you and we’re helping you,’ one participant recalled staff saying, ‘but when you leave you’re like: how are they going to help me?’ Others experienced support as intrusive, with unilateral decisions and pressure to engage in unwanted activities adding stress rather than relief.

The study also uncovered a delicate dynamic around dependence on the healthcare system itself. Some participants came to feel like a burden—’it feels like I’m a burden,’ one said—and responded by hiding their struggles or even requesting fewer clinic visits, which paradoxically reduced the support they received. Many appreciated long-term follow-up and the reassurance of being ‘a phone call away,’ while others felt support declined too quickly during recovery. Family members played a complementary and sometimes decisive role, driving patients to appointments, helping manage medications, limiting access to illicit benzodiazepines, and offering encouragement that kept people engaged. One participant was unequivocal: ‘I would never have made it if my family hadn’t helped me… never.’

The authors acknowledge limitations: all participants were recruited from a single specialized outpatient clinic, and because everyone interviewed was undergoing or had completed tapering, the experiences of those who dropped out remain unheard. Still, the study is among the first to examine tapering through the eyes of patients with a formal addiction diagnosis, and the first to do so in a Nordic context. Its central message is striking: successful discontinuation is not simply a pharmacological exercise in lowering doses, but an iterative, emotionally demanding process in which motivation, coping strategies, and support are woven together through everyday clinical interactions. Since patient characteristics like dose, duration of use, and psychiatric history are fixed at treatment entry, the researchers argue, the delivery of care is the variable that clinicians can actually change. Listening to patients—about pacing, about fear, about what support feels like from the inside—may be the difference between a taper that holds and one that fails.

Subject of Research: Patient experiences of benzodiazepine tapering treatment in addiction care

Article Title: Patient experiences of benzodiazepine tapering: a qualitative study of treatment in addiction care

Article References: Burmester, S., Krüger, C., Franck, J., & Westman, J. (2026). Patient experiences of benzodiazepine tapering: a qualitative study of treatment in addiction care. BMC Psychiatry, 26(1), Article 765. https://doi.org/10.1186/s12888-026-08745-z

Image Credits: AI Generated

DOI: 10.1186/s12888-026-08745-z

Keywords: benzodiazepines, addiction, tapering, withdrawal symptoms, qualitative research, patient experiences, substance use disorder, mental health, psychological treatment, therapeutic relationship, healthcare personnel, Karolinska Institutet

The research team set out to address a well-known gap in addiction science. Alcohol use disorder is strongly associated with persistent depressive and anxiety symptoms, and these delayed affective disturbances are thought to play a major role in relapse. Yet vulnerability is strikingly heterogeneous: not everyone who experiences heavy drinking and withdrawal goes on to develop the same long-term emotional consequences. Clinicians currently have no reliable way to identify, during the acute withdrawal window, which patients are most at risk. The Israeli-led team asked whether measurable signs during withdrawal, the so-called withdrawal signature, could predict later behavioral outcomes in a controlled animal model.

To do this, the researchers used a chronic intermittent ethanol exposure protocol in Sprague-Dawley rats of both sexes. Animals received five cycles of a 10 percent ethanol liquid diet, a widely used model that produces dependence-like states without requiring forced injection procedures. Control animals received a pair-fed diet, matched for calories but without alcohol, which allows researchers to separate the effects of alcohol itself from the nutritional disruptions that often accompany heavy drinking. This design is important because malnutrition and caloric imbalance can independently alter behavior and physiology, confounding many alcohol studies.

Acute withdrawal signs were assessed 12 to 24 hours after the final ethanol cycle, a window in which physical withdrawal symptoms typically peak in this model. The team recorded five neurological withdrawal signs along with body temperature and body weight change. Then came the critical part of the design: the animals were left alone for a month, a period roughly analogous to the subacute and protracted withdrawal phase in humans, before undergoing a battery of behavioral tests. These included the sucrose preference test, a standard measure of anhedonia or loss of pleasure; the elevated plus maze, which probes anxiety-like behavior through willingness to explore open, exposed arms; and the open field test, which measures both general locomotor activity and anxiety-related avoidance of open central areas.

The results confirmed that a substantial fraction of alcohol-exposed rats developed lasting behavioral abnormalities. Compared with controls, the alcohol-exposed group showed reduced sucrose preference, indicating depression-like anhedonia; reduced exploration of the open arms of the elevated plus maze, indicating anxiety-like behavior; and reduced total distance and center-zone distance in the open field, reflecting both hypoactivity and anxiety-sensitive avoidance. Depending on the specific measure, between 28.3 percent and 56.7 percent of alcohol-exposed rats met criteria for delayed behavioral abnormalities derived from the control animals’ distributions. That heterogeneity is precisely the point: the damage was real but unevenly distributed, raising the question of what distinguished the vulnerable animals from the resilient ones.

To find out, the researchers turned to principal component analysis, a statistical technique that condenses multiple correlated variables into composite scores. When applied to the five neurological withdrawal signs, the analysis yielded a single composite measure, which the authors call a Neurological Severity Score, that explained 50.4 percent of the variance in withdrawal signs. This gave the team a principled way to ask whether the overall intensity of neurological withdrawal, rather than any single symptom, carried predictive information about later emotional outcomes.

The answer was nuanced. Among the three prespecified withdrawal measures, the Neurological Severity Score, body temperature, and weight change, body temperature emerged as the most consistently informative. It showed associations with multiple delayed outcomes, including depression-like behavior, hypoactivity, and what the authors term sensitive anxiety and sensitive comorbidity, meaning anxiety measures and combined anxiety-depression measures analyzed with thresholds tuned for statistical sensitivity. Temperature-only models showed moderate internal discrimination, with optimism-corrected area under the curve values of 0.773 for sensitive anxiety and 0.735 for hypoactivity. In practical terms, an AUC of roughly 0.75 indicates a model that performs meaningfully better than chance but is far from a definitive diagnostic tool, a level the authors themselves characterize carefully.

By contrast, the composite Neurological Severity Score and body weight change did not show consistent independent associations with the delayed behavioral outcomes. This is an intriguing result, because it suggests that the intensity of overt neurological withdrawal symptoms, such as tremor and abnormal reflexes, may not be the best guide to long-term emotional risk. Body temperature, by contrast, is a systemic physiological readout. Withdrawal-associated hypothermia or temperature dysregulation could reflect deeper disruptions in thermoregulatory circuits, stress hormone systems, or inflammatory signaling that also underlie the delayed emergence of affective disturbances. The authors are appropriately cautious on this point, noting that the association does not establish causality and does not demonstrate clinical predictive value.

Indeed, the study’s limitations are as instructive as its findings. The work was conducted in a single cohort of rats, and the authors explicitly state that independent replication is required before any conclusions can be extended to humans. Behavioral measures in rodents are imperfect proxies for human depression and anxiety, and the statistical thresholds used to define abnormal behavior were derived from control animals rather than from validated clinical criteria. The moderate AUC values, while encouraging for an early-stage study, would need substantial improvement before any translation into bedside risk stratification could be contemplated. The research also received no specific external funding, and the authors declare no competing interests, details that speak to the independence of the work but also to the scale of the effort involved.

Still, the conceptual contribution is significant. The study reframes acute alcohol withdrawal not merely as an acute medical hazard to be managed and forgotten, but as a potential window of biological information about long-term psychiatric vulnerability. If the temperature finding replicates, it would be remarkable for its simplicity: a measurement that requires nothing more than a thermometer, taken during the withdrawal period, could help flag patients who need closer monitoring for post-withdrawal depression and anxiety. In a clinical world where alcohol withdrawal is often treated as a self-limiting event, the idea that its physiological signature might foreshadow the emotional aftermath a month later is a provocative and potentially practice-changing hypothesis. For now, it remains exactly that, a hypothesis awaiting replication, but one grounded in a carefully controlled animal study with both sexes represented, prespecified measures, and appropriately conservative statistical analysis. The next step will be independent cohorts, and eventually, studies in human patients, to determine whether the body’s temperature during withdrawal truly carries a message about the mind’s future.

Subject of Research: Associations between acute alcohol withdrawal measures and delayed affective-like behavioral vulnerability after chronic intermittent ethanol exposure in rats

Article Title: Acute withdrawal signatures are associated with delayed affective-like vulnerability after chronic intermittent ethanol exposure in rats

Article References: Zlotnik, A., Gruenbaum, B. F., Negev, S., Dubilet, M., Perlov, Y., Hertz, N., Grinshpun, J., Benkovich, V., Frenkel, A., & Boyko, M. (2026). Acute withdrawal signatures are associated with delayed affective-like vulnerability after chronic intermittent ethanol exposure in rats. Translational Psychiatry. https://doi.org/10.1038/s41398-026-04503-7

Image Credits: AI Generated

DOI: 10.1038/s41398-026-04503-7

Keywords: alcohol use disorder, ethanol withdrawal, body temperature, depression-like behavior, anxiety-like behavior, rats, chronic intermittent ethanol, anhedonia, sucrose preference, elevated plus maze, open field test, Translational Psychiatry

Latent profile analysis is a form of finite mixture modeling, a family of statistical methods designed to uncover hidden subgroups within a population. Instead of assuming that all smokers come from one homogeneous distribution, the method tests whether the observed pattern of responses across several indicators can be better explained by a small number of underlying groups, each with its own characteristic response pattern. In this study, the indicators were five in number: a measure of psychological dependence on smoking, the number of cigarettes smoked per day, motives for initiating smoking, motives for maintaining the habit, and the severity of withdrawal symptoms. The modeling, conducted in the R statistical environment using Gaussian finite mixture models, compared solutions with increasing numbers of profiles and evaluated them with standard fit criteria, including entropy-based measures of classification quality and likelihood-based information criteria, before settling on a four-profile solution as the best balance of parsimony and explanatory power.

The largest group by far, accounting for 58.9 percent of the sample, was labeled the Moderate Habitual profile. These smokers occupied the statistical middle ground across most indicators: moderate psychological dependence, moderate consumption, moderate motives, and moderate withdrawal. They represent the everyday image of the habitual smoker, someone whose habit is woven into daily routines without reaching the extremes seen elsewhere in the data. The second-largest group, at 18.5 percent, was the Low-Engagement profile. These smokers scored lowest on nearly every indicator, showing weak psychological dependence, low consumption, and mild withdrawal symptoms. Crucially, they also reported the highest intention to quit smoking of any group, a finding that suggests their lighter engagement with the habit is accompanied by a genuine openness to giving it up.

The two smaller profiles are where the study’s most striking insights lie. The Motivation-Driven profile, comprising 16.8 percent of smokers, displayed the highest levels of psychological dependence, the strongest smoking motives, and the most severe withdrawal symptoms of any group. What defines these smokers is not sheer volume of consumption but the intensity of the psychological and motivational machinery behind their habit. They smoke for reasons, and those reasons grip them tightly. By contrast, the Habitual Heavy profile, at just 5.8 percent of the sample, reported the highest number of cigarettes smoked per day, even though their psychological dependence and withdrawal symptoms did not top the scale. For this small group, smoking appears to be primarily a matter of deeply entrenched behavioral volume rather than acute psychological craving.

This dissociation between consumption and psychological dependence is perhaps the study’s most consequential finding. Public health screening and cessation triage have often leaned on cigarette counts as a proxy for how hard it will be for someone to quit. The four-profile solution shows that this proxy can mislead. A Motivation-Driven smoker who consumes a moderate number of cigarettes may, in psychological terms, be more firmly hooked than a Habitual Heavy smoker who burns through far more tobacco. Conversely, the Heavy smoker’s problem may be less about craving and more about the sheer density of smoking cues and routines packed into the day. If these distinctions hold up in future research, they imply that a one-size-fits-all cessation program, or one calibrated only to consumption levels, will fit poorly for at least two of the four profiles.

The study also examined which background characteristics predicted membership in each profile, using auxiliary variable techniques that relate covariates to latent classes without allowing them to distort the underlying classification. Five factors emerged as significantly associated with profile membership: family tobacco use, the presence of a chronic disease, sex, age, and cessation intention. Growing up or living with family members who smoke has long been recognized as a powerful social determinant of tobacco behavior, and here it helped distinguish between profiles, likely reflecting both early exposure to smoking norms and continued environmental reinforcement of the habit. Chronic disease status also differentiated the groups, a reminder that health conditions often intersect with smoking behavior in complex ways, sometimes motivating reduced smoking and sometimes complicating cessation efforts.

The roles of sex and age echo a broader literature on how smoking trajectories unfold across the life course. Smoking patterns established in adolescence and early adulthood tend to persist, and the demographic correlates identified in this study are consistent with the idea that profile membership is not randomly distributed but shaped by developmental and social context. Cessation intention, meanwhile, stood out as both an outcome and a predictor: Low-Engagement smokers, with their weak dependence, expressed the strongest desire to quit, while other profiles, presumably those more deeply entrenched, showed less intention. This gradient suggests that intention to quit is not simply a matter of willpower distributed unevenly across individuals, but is partly a function of the psychological structure of the dependence itself.

The methodological rigor of the study deserves attention. The author followed established guidance for latent profile analysis, including a priori consideration of statistical power for mixture models, careful model comparison across competing numbers of profiles, and the use of three-step approaches for relating auxiliary variables to profile membership, which help avoid the bias that arises when covariates are folded directly into the classification model. Multiple-testing concerns were addressed with false discovery rate control, and continuous variables such as age were handled without arbitrary dichotomization, a practice known to distort odds ratios. Supplementary materials are publicly archived on the Open Science Framework, and the study protocol received institutional ethics approval, with informed consent obtained from all participants. Raw participant-level data remain restricted for privacy reasons but are available on reasonable request.

The context of Türkiye gives the findings particular public health weight. National health survey data indicate that a substantial share of Turkish adults smoke, and tobacco-attributable disease imposes heavy costs on households and the health system. Globally, smoking remains one of the leading preventable causes of death, and cessation interventions, from nicotine replacement therapy to text-message and app-based support programs, have shown measurable but uneven success. The heterogeneity documented in this study offers one plausible explanation for that unevenness: interventions designed for the average smoker may resonate with the Moderate Habitual majority while missing the specific psychological levers that drive Motivation-Driven smokers or the behavioral density that defines Habitual Heavy smokers.

The author is careful to frame the work as a foundation rather than a prescription. The profiles were identified in a cross-sectional sample, so the analysis captures smokers at a moment in time rather than tracking how individuals move between profiles over months and years. Whether a Motivation-Driven smoker gradually becomes a Low-Engagement one, or whether profile membership is stable, is a question for longitudinal designs. Nor can cross-sectional data establish causal direction between profile characteristics and variables such as cessation intention. Still, the study makes a compelling case that the phenotype of smoking is multidimensional, and that the dimensions do not always move together. As cessation science moves toward more personalized approaches, the four profiles identified here, Low-Engagement, Moderate Habitual, Motivation-Driven, and Habitual Heavy, offer a concrete, data-driven vocabulary for thinking about smokers not as points on a single severity scale, but as members of distinct populations with distinct paths out of the habit.

Subject of Research: Latent profile analysis of multidimensional cigarette smoking profiles among adult smokers in Türkiye

Article Title: Multidimensional Smoking Profiles Defined by Psychological Dependence, Smoking Motives, Cigarette Consumption, and Withdrawal Symptoms: A Latent Profile Analysis

Article References: Bulut, A. (2026). Multidimensional Smoking Profiles Defined by Psychological Dependence, Smoking Motives, Cigarette Consumption, and Withdrawal Symptoms: A Latent Profile Analysis. International Journal of Mental Health and Addiction. https://doi.org/10.1007/s11469-026-01738-9

Image Credits: AI Generated

DOI: 10.1007/s11469-026-01738-9

Keywords: smoking, tobacco dependence, latent profile analysis, psychological dependence, smoking motives, withdrawal symptoms, smoking cessation, Türkiye, nicotine, public health, addiction research, Multidimensional