Somewhere along the way though, I wandered into the world of start-ups. I co-founded AVAtalk Technologies Inc. and have advised a few other early-stage companies. I never woke up thinking, “I’m a business person now.” If anything, it happened almost by accident.

Looking back, I think what pulled me in wasn’t “business” as such, but curiosity and a desire for impact. I’ve always been drawn to research and innovation, but only when they actually make a difference in real people’s lives. That, more than anything, is what connects psychiatry and start-ups for me.

A research mentor who thought like a founder

Before I ever thought of myself as a founder, I was shaped by an extraordinary research mentor: Nancy Mayo. She is disruptive in the best sense of the word and only cares about doing research that is truly transformative.

Her rule was simple:

You don’t start with ideas. You start with people.

She spent a lot of time talking to patients, caregivers, clinicians, anyone affected by the problem she was studying. She wanted to understand their pain points deeply and to involve them throughout the research process. Participants were no longer people she “studied”; they were people who studied with her.

From Nancy, I absorbed a moral compass that still guides me today:

You are privileged. You have skills. Use those skills to make the world better, because you are in a position to do it.

I will always be grateful for that.

What start-ups quietly teach psychiatrists

Being a founder is a grueling process. There is nothing glamorous about working on a product at midnight while not knowing if the next step is the right step and juggling a full clinical load.

But the experience taught me something that loops right back into psychiatry:

An idea or a product has no value if you’re not talking to the people who are supposed to use it.

The whole point of a start-up is to solve a problem. But you can’t solve a problem you don’t understand. And you can’t understand a problem if you don’t spend time listening to the people who live with it every day.

Listening and observing are not “nice to have” qualities in a founder. They are core competencies.

Paul Graham’s founders, and one missing trait

Recently, I reread Paul Graham’s essay, “What We Look for in Founders”. His essays are usually spot on, and I rarely disagree with him. In that piece, he highlights five important traits: determination, flexibility, imagination, naughtiness, and friendship.

I agree with all five.

But I do think he missed one:

Founders need to be exceptional listeners.

Lead with a question, then listen. Listen for pain points. Listen for confusion. Listen for what people don’t say as much as for what they do. Then ask another question. And another. That is how you find the real problem under the surface.

“What brings you in today?”

As a psychiatrist, the single most important question I ask is:

“What brings you in today?”

It is an incredibly simple, open-ended question. After that, my main job is to listen. When you listen long enough, patients will tell you what their pain points are, what truly bothers them, what keeps them up at night, what they are afraid to say out loud.

Sometimes their distress makes it hard for them to explain things clearly. They might feel they “don’t know” what is wrong. But if you listen with patience and curiosity, a theme emerges. From there, you ask more focused questions and gradually clarify the problem together.

That process is not so different from early customer interviews in a start-up.

Even with perfect biomarkers, I’d still ask the same question

I’m a strong believer in the future of mental health care, and I’m excited about neuroscience and biomarkers in psychiatry. Suppose that tomorrow we develop perfect objective tests that can tell us, with high precision, what a person’s diagnosis is.

Even then, in every first encounter, I would still ask:

“What brings you in today?”

Why? Because a diagnosis is not the same thing as understanding someone’s suffering.

A lab result or a brain image may tell me what they have, but not what hurts the most or what they hope will change. To be truly helpful, I still need to understand their subjective experience. That only happens through listening.

The same is true for products. You can have all the analytics, dashboards, and metrics in the world, but if you aren’t actually listening to people, you will miss the point.

Clinicians as founders: you already have what it takes

So why am I writing this?

Because I hear too many clinicians say things like, “I’m not a business person,” or “I could never be a founder.”

I don’t buy that.

Clinicians are trained to do the very thing founders often struggle with: listening deeply and making sense of complex human problems. We spend years learning to build trust, ask good questions, tolerate ambiguity, and lead teams in high-stakes environments.

These are not soft skills. They are exactly the kind of skills that build meaningful, impactful companies.

Innovation in health care often happens without clinicians at the table, which is unfortunate, because our presence is desperately needed. We understand the context, the workflow, and the human cost of bad design.

It is time for the VC world and the start-up ecosystem to recognize the unique value physician-founders bring:

• We are close to the problem

• We are trained listeners

• We are natural leaders in complex systems

Yes, many physicians can’t or won’t go “all in” full-time on a start-up for obvious reasons. But that should not be the main criterion used to judge whether a team can execute. What matters is whether the team as a whole is structured in a way that allows for consistent, reliable execution. A physician founder can be an integral part of that, even if they are not the one writing code at 2 a.m.

If you are a clinician wondering whether you belong in the world of start-ups, here is my view: you probably belong there more than you think.

You already know how to ask, “What brings you in today?”

Now imagine asking your users the same thing and really listening to the answer.

Let’s keep the conversation going. I’m genuinely curious to hear your thoughts in the comments.

Recently, I was at a conference in Atlanta. I have always wanted to visit the city. As a big rap fan, Atlanta has always had a certain mythic status in my mind, so going there for work was even more exciting.

On the way to my hotel, I was struck by something very simple. Looking out the Uber window, every billboard felt unmistakably “Atlanta.” Clothing brands, sports betting apps, financial services, all of them were speaking the local language. Some were referencing rap, some So So Def, some small pieces of local culture you would only really understand if you lived there or followed the music.

It reminded me of something we easily forget when we stay in our own bubble. Good marketing never talks to a generic “consumer.” It talks to a specific person, in a specific place, with a specific history and culture. It takes their world seriously.

As I watched those ads, I realized what they were doing very well. They were not just selling products. They were making people feel something. They were creating a sense of “this is for us.”

Of course, being in Atlanta, I had to visit the Coca Cola museum. That is where the lesson really crystallized. Beyond the famous “secret recipe” story, what struck me most was how skillfully Coca Cola adapts its product to local tastes around the world. The core brand is the same, but the flavor, the campaigns, the positioning are constantly tuned to culture and context.

Medicine, and especially mental health care, often does not work that way.

A large part of being a healer is persuasion. Not in the manipulative sense, but in the sense of helping people see possibilities they did not see before, helping them feel safe enough to try something new. One book that profoundly changed my thinking around this is Persuasion and Healing: A Comparative Study of Psychotherapy by Dr. Jerome Frank. It frames psychotherapy as a kind of meaning-making and persuasive enterprise, grounded in the patient’s world.

That is where I think we, in mental health, still have a lot to learn from marketing. Not about “branding” ourselves, but about taking culture seriously. About understanding that treatment, to be effective, must feel like “this is for me” to the person sitting across from us.

If we truly want to be patient centered, we need to be culture centered. We need to understand people’s stories, their background, their communities, their symbols, their references. Their context is not decoration, it is the soil in which any therapeutic work has to grow.

This becomes even more urgent when we think about what is coming next. There is an entire generation growing up in a digital culture where social media, influencers, meme coins and online communities are not “add-ons,” they are central parts of identity. As a psychiatrist, I know I will increasingly be caring for people whose deepest experiences, stresses and aspirations are intertwined with that digital world.

If we ignore that culture, how can we hope to really reach them?

Now here is the paradox in my own life. People who know me know how strict I am about my relationship with social media. I do not use Facebook, Instagram or Twitter anymore. I used to, but at some point I made a conscious decision to live a more intentional and present life.

The one platform I chose to keep is LinkedIn, because I genuinely enjoy staying connected to my field, learning from colleagues and reading thoughtful perspectives. But stepping away from other platforms also means I am more distant from the front lines of digital culture. That is an interesting tension for me as a clinician who still wants to understand the worlds my patients inhabit.

So I am curious, especially for those of you who practice in mental health or medicine:

How do you intentionally connect with your patients’ culture, including digital culture, in your daily work, and what have you found actually makes a difference in building trust and engagement?

He, H., Sun, X., Doose, J., Faller, J., McIntosh, J. R., Saber, G. T., ... & Sajda, P. (2025). TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study. Brain Stimulation.

Introduction

This study investigates the immediate effects of transcranial magnetic stimulation (TMS) on brain networks and their relationship to treatment outcomes in patients with treatment-resistant depression (TRD). Using a novel, integrative approach that simultaneously combines TMS with functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), the researchers aimed to understand the therapeutic mechanisms of TMS, particularly how the brain's state at the moment of stimulation influences its effects. The work demonstrates that TMS acutely modulates critical brain networks and that these modulations, when timed to a patient's specific brain rhythms, are associated with clinical improvement.

Research Question

While TMS over the left dorsolateral prefrontal cortex (L-DLPFC) is an FDA-approved treatment for depression, its underlying mechanisms are not fully understood. It is hypothesized that the therapeutic effects depend not only on stimulating the correct location but also on the timing of the stimulation relative to the brain's ongoing oscillatory state. This study sought to test this hypothesis by exploring whether synchronizing TMS pulses with a patient's prefrontal alpha-wave oscillations could enhance target engagement and predict treatment response, thereby paving the way for more personalized and effective neuromodulation therapies.

Methodology

This research was a randomized, double-blind clinical trial involving 28 patients with TRD. The methodology can be broken down into three main phases:

Baseline Assessment

Each patient underwent a pre-treatment scan using an integrated fMRI-EEG-TMS (fET) instrument. During this scan, single pulses of TMS were delivered to the L-DLPFC. The concurrent EEG data was used to identify a personalized "optimal phase" of the prefrontal alpha oscillation—the specific point in the brainwave cycle where TMS produced the largest BOLD signal increase in the dorsal anterior cingulate cortex (dACC), a key region in mood regulation.

rTMS Treatment

Patients were randomized into two groups for a six-week treatment protocol.

• SYNC Group (n=15): Received repetitive TMS (rTMS) pulses synchronized to their individually determined optimal alpha phase.

• UNSYNC Group (n=13): Received rTMS pulses at the same frequency but at random phases.

Data Analysis

The researchers analyzed the acute effects of single-pulse TMS from the pre- and post-treatment fET scans. They quantified TMS-evoked BOLD responses across the brain and assessed TMS-induced changes in functional connectivity using a psychophysiological interaction (PPI) analysis. Brain state was defined by the phase of the EEG prefrontal alpha oscillation at the time of each TMS pulse, allowing for state-dependent analysis. Clinical outcomes were measured by the percent change in the Hamilton Rating Scale for Depression (HRSD).

Key Findings

The study yielded several key insights into the mechanisms and predictors of TMS efficacy:

Acute Network Modulation

Single-pulse TMS was found to acutely modulate connectivity within and between large-scale brain networks, particularly by decreasing connectivity involving the default mode network (DMN), cognitive control network (CCN), and limbic networks.

Predicting Treatment Response

For patients in the SYNC group only, the strength of the baseline TMS-evoked BOLD response was a powerful predictor of clinical improvement. Specifically, stronger responses in the bilateral cognitive control network (r ≈ 0.86) and the right limbic network (r ≈ 0.90) were highly correlated with greater symptom reduction. This association was not present in the UNSYNC group.

State-Dependent Effects

The study confirmed that the effects of TMS are brain-state dependent. TMS pulses delivered during a "high-load phase" (the phase that evoked the strongest response at the stimulation site) produced significant downstream network modulation, whereas pulses at a "low-load phase" did not.

Circuit-Specific Changes

The clinical improvement in the SYNC group was strongly associated with longitudinal changes in state-specific functional connectivity. A greater increase in connectivity modulation between the L-DLPFC and the right orbitofrontal cortex (a part of the subgenual cingulate circuit) from pre- to post-treatment was almost perfectly correlated with a better clinical outcome (r = 0.99).

Implications

This study provides compelling evidence for the mechanisms underlying TMS treatment for depression, emphasizing the importance of personalized timing for optimizing target engagement. The findings suggest that EEG-synchronized rTMS may work by systematically engaging a specific and clinically relevant brain circuit connecting the L-DLPFC and the subgenual cingulate cortex.

The ability of baseline TMS-evoked responses to predict outcomes in the SYNC group offers a potential biomarker for identifying patients who would benefit most from this personalized approach. However, the authors acknowledge several limitations, including a small sample size and the absence of a sham control group, which means placebo effects cannot be ruled out. Furthermore, the clinical trial did not find a significant difference in overall efficacy between the SYNC and UNSYNC groups. Despite this, the neuroimaging results strongly support the mechanistic role of state-dependent circuit engagement and are crucial for guiding future research into developing more precise and personalized neuromodulation therapies for TRD.

Carter, B. (2025). Unlocking the Tyranny of Modern Thinking: Keys From Anthropology, Psychology, Neuroscience, and Buddhism. Anthropology of Consciousness, e70023.

Introduction

“Out beyond ideas of wrongdoing and right-doing, There is a field. I’ll meet you there.” So begins a poignant poem by the 13th-century Persian scholar Rumi, a sentiment that resonates deeply with a core challenge of modern existence: our often relentless, self-critical, and distracting inner monologue. In a fascinating essay published in Anthropology of Consciousness, Barbara Carter explores the profound origins of this mental “tyranny” and proposes mindfulness meditation as a powerful antidote, weaving together threads from anthropology, psychology, neuroscience, and Buddhist wisdom.

How We Became Disconnected

Imagine a life where your sense of self isn’t constantly compared, judged, or lost in a flurry of abstract thoughts. Carter invites us to consider “preconquest cultures” – societies untouched by modern colonization – as documented by anthropologist E. Richard Sorenson. These cultures, characterized by constant touch-based caregiving and intuitive rapport, fostered a fluid, embodied consciousness, deeply attuned to the present moment and interconnected with others and nature. Language, for them, was a fluid tool, not a rigid filter or a means of control.

However, contact with the modern world brought a profound shift. The author’s own experience as a Peace Corps Volunteer in the Marshall Islands echoed Sorenson’s observations: a shift from a timeless, consensus-driven, present-centered life to one increasingly fragmented by modern concepts of time, ownership, and abstract rules. This “colonization” of thought, as the essay suggests, led to the emergence of modern health problems like depression, anxiety, and suicide.

The Inner Critic: A Legacy of Trauma and Insecurity

Why do our minds become so prone to self-criticism and judgment? The essay delves into psychology, suggesting that this inner narrative serves a survival function. Psychoanalyst Anna Freud described how young children “introject the aggressor,” internalizing reprimands from caregivers to control themselves. This mechanism of identification with the aggressor leads us to threaten ourselves internally, mirroring how colonized peoples learned to adopt the ways of their invaders.

Attachment theory further illuminates this. Secure attachment, built on consistent, responsive care, fosters trust and self-compassion. In contrast, insecure attachment, often a result of inconsistent or rejecting care, leads to a “fractured self” that represses emotions and distrusts internal signals. Developmental psychologist Darcia Narvaez’s “evolved nest” model posits that optimal psychosocial development historically relied on nurturing childcare, present in an astounding 95% of human history. Our modern deviations from this “evolved nest” may contribute to “trauma-inducing competitive detachment” and profound “ill-being”.

Trauma also plays a crucial role. When overwhelmed, our psychological defenses push painful experiences, along with their somatic and emotional components, into the unconscious. To keep these traumas repressed, we construct a “defensive thinking bubble,” disconnecting from our bodies and direct experience. This creates a “false self” that struggles to confront undesirable internal states.

Narrative vs. Experiential Self

Neuroscience offers a fascinating lens through which to understand this internal struggle. The essay highlights Iain McGilchrist’s work on brain hemispheres: the left hemisphere, dominant in modern culture, tends to see the world in parts, valuing abstraction, reductionism, and control, while the right hemisphere perceives the world as a living, interconnected whole, embracing ambiguity, empathy, and holistic understanding.

Brain imaging studies, widely cited in the paper, reveal that our incessant inner narrative resides primarily in the default mode network (DMN) — a brain network associated with self-referential thinking, rumination, and mind-wandering. This DMN is considered the seat of the ego and defensive, self-critical modes of thought. However, mindfulness meditation has been shown to gradually deactivate or modulate the DMN.

As the DMN quiets, other brain structures become more active: the insula and salience network (SN) — brain structures responsible for attention regulation, interoception, and present-moment perception. This neural shift is crucial because studies referenced in the essay indicate that increased activity in these areas, coupled with reduced DMN dominance, is associated with greater attentional control, emotional awareness, and overall psychological well-being. For instance, long-term meditators have shown less activity in the amygdala—the brain’s fear center—when encountering negative emotional stimuli, suggesting a reduced reactive stress response.

Mindfulness: The Key to Untangling the Mind

Mindfulness meditation is proposed as a direct path to untangle our over-identification with thought and unlock a more direct, embodied experience. It’s not about stopping thoughts, but changing our relationship with them. As one graduate student shared, “This practice helps me recognize when I am stuck in a storyline… With mindfulness, I can step back and see these thoughts for what they are: passing mental events, not ultimate truths”.

By gently anchoring awareness in bodily sensations (like the breath), we learn to observe thoughts and emotions non-judgmentally, returning to the present moment. This practice fosters interoception — the awareness of our internal body sensations — which is profoundly linked to empathy, emotional regulation, and even our connection to nature. Research cited in the essay documents the wide-ranging benefits of mindfulness meditation, including stress reduction, treatment for anxiety and depression, improved cognitive functioning, and enhanced immune function.

The essay highlights that this process is akin to “decolonizing our minds,” not by trying to eradicate difficult thoughts or emotions, but by “co-sensing with radical tenderness”. It’s about accepting what is, allowing it to unfold naturally, and witnessing our internal processes with compassion. This shift from a rigid “narrative self” to a fluid “experiential self” leads to less reactivity, greater self-acceptance, and a profound sense of inner freedom.

Reclaiming Our Interconnectedness

While returning to a “preconquest” era is neither possible nor desirable, the essay offers a compelling vision of reclaiming some of what has been lost. By cultivating mindfulness, we can heal trauma, strengthen secure attachment internally, and rediscover our innate interconnectedness with others and the natural world. This isn’t just an individual journey; it also calls for collective efforts to challenge the structures and incentives of the modern world that perpetuate disconnection and suffering.

In essence, by learning to loosen our grip on the “tyranny of modern thinking,” we can move towards a more peaceful, healthy, and deeply satisfying way of being. As Rumi’s poem suggests, beyond the confines of our concepts and judgments, there is a boundless field of direct experience, waiting for us to arrive.

Andreoli, G., Rafanelli, C., Hofmann, S.G. et al. A Systematic Scoping Review of Fully Idiographic Network Analysis in Mental Health. Cogn Ther Res (2025). https://doi.org/10.1007/s10608-025-10674-2

Introduction

Mental health isn’t a one-size-fits-all equation. We all experience emotions, thoughts, and behaviors uniquely, yet much of traditional psychological research often relies on “nomothetic” or group-level data. This approach, while valuable, can miss the intricate, personalized dynamics of an individual’s mental health. Enter Fully Idiographic Network Analysis (FINA) – a brilliant method that focuses on understanding mental health at the deeply personal, “N=1” level.

A recent scoping review by Andreoli et al. (2025) offers the first comprehensive look at how FINA is being used in mental health research, highlighting its promising potential while also pointing out critical areas for improvement. This deep dive into 43 studies (N=43) published between 2011 and 2025 reveals a vibrant, rapidly evolving field grappling with both innovation and inconsistency.

What is FINA and Why Does it Matter?

Imagine your symptoms – anxiety, low mood, sleep problems – not as isolated issues, but as interconnected nodes in a complex web. FINA helps map these individual symptom networks by collecting intensive longitudinal data from a single person over time. This personalized map can then reveal which symptoms trigger others (a temporal network) or which tend to co-occur intensely (a contemporaneous network). The ultimate goal is to identify unique “drivers” or “hubs” within an individual’s network, offering personalized targets for treatment that couldn’t be seen in group-level data

For instance, in a contemporaneous network, strength centrality (the sum of absolute edge weights connected to a node, indicating how intensely a symptom co-occurs with others) could highlight that for one person, somatic arousal and panic anticipation are tightly linked. In a temporal network, instrength (sum of incoming absolute edge weights, showing how much a symptom is predicted by others) and outstrength (sum of outgoing absolute edge weights, showing how much a symptom predicts others) might reveal that low mood consistently predicts anxiety, suggesting mood as a potential intervention point.

The Landscape of FINA Research: A Snapshot

The review found that FINA research is characterized by considerable heterogeneity across almost all aspects. Here’s what stood out:

• Intensive Data Collection Dominates

  • The majority of studies, 65.1% (n=28), used Ecological Momentary Assessment (EMA) or Experience Sampling Methods (ESM) – where participants report on their experiences multiple times a day, often via electronic devices (96.4%, n=27 of these studies). This intensive approach is crucial for capturing dynamic symptom interplay, with the average completion rate for assessments, when reported, being 84.3%.

• Many Participants, Few True N=1s

  • Despite the “idiographic” (individual-focused) label, only 16.3% (n=7) of studies were true single-subject designs. The mean sample size per FINA analysis was 41.5 (SD=63.8), but surprisingly, FINA results were only actually reported for a maximum of 133 participants (Mean=18.2, SD=33.8) across all studies. This suggests that many studies applying FINA still aggregate data or only present individual results illustratively, potentially limiting deep personalized insights.

• R is King

  • When it comes to analysis, R (93%, n=40 studies) is the overwhelming choice of software, utilizing packages like graphicalVAR and psychonetrics.

• GVAR is the Go-To Model

  • The Graphical Vector Auto-Regressive (GVAR) model (a time-series model capturing both direct and instantaneous effects between variables) was the most frequently employed FINA model, used in 34.9% (n=15) of studies. Other models like Dynamic Time-Warp (DTW) (16.3%, n=7) and Structural Equation Modeling (SEM) variants (14% total, n=5) also emerged as flexible alternatives, especially when data assumptions for GVAR (like stationarity) are violated.

• Assumptions Often Overlooked

  • A significant concern is the infrequent testing of key statistical assumptions. For example, normality (data distributed in a bell-shaped curve) was tested in only 8.8% (n=3) of studies assuming it, and stationarity (statistical properties not changing over time) in only 25% (n=8). This raises questions about the validity of some reported findings. Similarly, topological overlap (when nodes measure overlapping constructs) was assessed in a mere 16.2% (n=6) of applicable studies.

• Stability is Rarely Checked

  • Assessing network stability (robustness to sampling error), usually via bootstrap methods (resampling to estimate statistic distribution), was performed in a meagre 11.6% (n=5) of studies. This is crucial to ensure that the identified networks aren’t just artifacts of a particular data collection period.

• Open Science Practices Are Emerging but Inconsistent

  • While analysis code was shared in 58.1% (n=25) of studies, data sharing was lower (30.2%, n=13), likely due to privacy concerns with sensitive individual-level data. Preregistration (publicly registering study plans before data collection), a cornerstone of transparency, was exceptionally rare, reported in only 7% (n=3) of studies.

Recommendations for More Rigorous FINA

The review authors provide a detailed checklist (Table 2) and recommendations to steer FINA toward greater scientific rigor and clinical utility.

Key suggestions include:

1. Standardize Data Collection

   For reliable edge detection, target at least 75 timepoints for networks with up to 6 nodes. Fixed-interval EMA/ESM is often preferred for models assuming equidistant data points.

2. Test Assumptions Religiously

   Routinely check for normality and stationarity. If assumptions are violated, consider models like DTW or Contingency measure-based Network (ConNEct) that are more robust to such issues. Address overnight lag (the time gap between the last assessment of one day and the first of the next) to maintain time-series integrity.

3. Manage Network Complexity

   Limit the number of nodes (individual symptoms or variables) in a network, with a mean maximum of 12.3 nodes observed in current research, to avoid overfitting (a model fitting too closely to training data, losing generalizability) and enhance interpretability.

4. Prioritize Stability and Comparison

   Implement data-dropping bootstrap or similar methods to assess network stability. Move beyond purely visual comparisons to formal statistical approaches like the Individual Network Invariance Test for comparing networks across or within individuals.

5. Embrace Transparency

   Improve reporting practices by providing detailed participant characteristics and individual-level FINA results. Crucially, promote open science by preregistering studies and sharing de-identified data and analysis code, while maintaining patient privacy.

What This Means for Mental Health Professionals

For clinicians, FINA holds immense promise for personalized care. Understanding a patient’s unique symptom network could lead to highly targeted interventions. However, the review underscores that FINA is still an emerging science.

• Hypothesis Generation

  View FINA-derived insights, like a high strength centrality for a particular symptom, as powerful hypotheses for personalized treatment, rather than definitive causal claims.

• Informed Assessment

  If considering FINA, advocate for robust data collection protocols, such as fixed-interval EMA/ESM with enough data points to reliably build networks.

• Mindful Interpretation

  When interpreting network diagrams, discuss with patients how their individual symptoms interact and how changes in centrality post-treatment might indicate progress.

• Ethical Vigilance

  Ensure stringent data privacy and de-identification, and obtain explicit consent for the intensive data collection required by FINA.

The journey to fully personalized mental health care is complex, but FINA offers a powerful compass. By addressing current methodological gaps and embracing rigorous, transparent practices, researchers can unlock FINA’s full potential to tailor interventions and truly understand the individual labyrinth of mental health.

Flückiger, C., Munder, T., Del Re, A. C., & Solomonov, N. (2023). Strength-based methods – a narrative review and comparative multilevel meta-analysis of positive interventions in clinical settings. Psychotherapy Research, 33(7), 856–872.

Introduction

Imagine a therapy session. What comes to mind? Often, it’s a space dedicated to unraveling problems, dissecting past wounds, and strategizing against distress. And for good reason – psychotherapy is incredibly effective at helping us tackle our deepest struggles. But what if there was a way to make therapy even more effective, not by digging deeper into what’s wrong, but by shining a light on what’s right?

That’s the fascinating question at the heart of a recent paper by Flückiger, Munder, Del Re, and Solomonov (2023) in Psychotherapy Research. They explored the impact of what they call “strength-based methods” (SBMs) – essentially, actively building on a patient’s existing capabilities, resources, and positive qualities, rather than just focusing on deficits. Think of it like a gardener not just weeding, but also nourishing the strongest plants in the garden. These methods aren’t new; they’re woven into many therapy approaches. But their unique contribution to treatment success has been less clear.

This team set out to provide clarity through a two-part investigation: first, a narrative review of studies looking at how these “strength moments” play out during sessions, and second, a robust meta-analysis comparing strength-based therapies to other well-established, or “bona fide,” treatments.

What Does “Strength-Based” Really Mean?

Before we dive into their findings, let’s get clear on SBMs. They’re not about ignoring suffering or forcing a “positive vibes only” mentality. Instead, SBMs are deliberate therapist actions designed to acknowledge, validate, and nurture a client’s inherent strengths, capabilities, and readiness for change. This could look like a therapist highlighting a client’s resilience in the face of adversity, helping them identify times they successfully coped, or building on their existing social support networks. It’s about creating a more complete picture of mental health, encompassing both challenges and the capacities to overcome them.

What Was the Team Trying to Figure Out?

The researchers had two main questions:

1. In-session Impact: When therapists actively use strength-based techniques during a session, how does it immediately affect the client? Does it lead to a more productive session, for example?

2. Overall Treatment Efficacy: Does a therapy approach that systematically integrates SBMs lead to better overall outcomes for clients compared to a similar, yet less strength-focused, bona fide therapy?

How Did They Study It?

For the first question, they conducted a narrative review of eight studies. These studies often used sophisticated video analysis, where trained observers would meticulously code therapist and patient interactions to see how strength-based moments unfolded and what happened next.

For the second, larger question, they performed a “multilevel comparative meta-analysis”. This is a fancy way of saying they pulled together data from nine high-quality clinical trials involving 804 patients, comparing strength-based therapies against other well-regarded treatments. They used advanced statistical methods like three-level random-effects restricted maximum-likelihood models to synthesize the results, which allowed them to account for multiple outcomes reported within a single study. They also assessed overall heterogeneity (how much variation there was between study results) using Q and I² statistics, and checked for any publication bias (where studies with “boring” or non-significant results might not get published) using funnel plots with asymmetry tests and trim and fill analyses.

What Did They Find? A Small but Significant Boost!

The results were compelling and pointed in one clear direction:

1. In-Session Wins: Moments of Strength Matter

The narrative review revealed a consistent pattern: when therapists intentionally engaged in strength-based methods during sessions, it was linked to more favorable immediate outcomes for patients. This means patients often felt more mastery, gained clearer insights, or progressed toward their goals within that very session. One standout finding highlighted that if a therapeutic technique wasn’t initially clicking with a patient, shifting the discussion to their personal skills and abilities dramatically increased the chances of a productive session. This suggests that even when things feel stuck, a strength-based pivot can be incredibly helpful.

2. Long-Term Gains: The Power of a Positive Focus

The meta-analysis, which combined data from hundreds of patients, found a small but statistically significant effect in favor of strength-based psychotherapies. Specifically, these therapies showed an overall weighted average effect size of g = 0.166, meaning they offered a slight edge in effectiveness compared to other solid therapies that didn’t emphasize strengths as much. This wasn’t just a fluke; the analysis had sufficient statistical power (0.86 for 57 effect sizes*)*, and there was no evidence of publication bias, suggesting the finding is reliable.

Intriguingly, the boost was marginally higher for outcomes directly related to a patient’s specific diagnosis (like a depression scale for someone with depression) compared to more general well-being measures. This hints that SBMs can be effective not just for general happiness, but also for targeting the core issues bringing someone to therapy.

Why Does This Matter? Practical Takeaways for Mental Health

These findings aren’t just academic; they have real-world implications for how we approach mental health care:

1. A More Holistic View of Health: This research reinforces the idea that mental health isn’t just the absence of illness. It’s also about the presence of strengths, resilience, and positive functioning. Therapy can (and perhaps should) explicitly foster both.

2. Integrating Strengths into Every Step: For practitioners, this means moving beyond just problem-focused intake assessments. It encourages us to actively assess a client’s strengths from the get-go, discuss them openly, and integrate them into treatment plans. How has this person coped before? What are their personal resources? Who is in their support system?

3. A Flexible, Collaborative Approach: The paper emphasizes the need for therapists to collaborate with clients in identifying and amplifying their strengths. It’s not about the therapist imposing their view but working together to see what feels authentic and valuable to the client. This also means being mindful of cultural contexts, as what one person considers a strength, another might not.

4. Training for the “Positive Lens”: The authors recommend that clinical training programs explicitly teach SBMs as concrete skills, not just a general positive attitude. This could involve deliberate practice, using video feedback to hone the ability to spot and cultivate client strengths, and balancing attention between distress and capabilities.

What We Still Need to Learn

As with any good research, this study also highlighted what we don’t yet know. The narrative review, while positive, was based on a relatively small number of studies, many of which were correlational – meaning we can see associations, but can’t definitively say SBMs caused the immediate session improvements. Also, most of the comparative trials were conducted in Europe, so we need more research from diverse cultural contexts. Future studies should also look at long-term outcomes, potential adverse effects (though none were evident here), and how SBMs specifically contribute to different types of therapeutic goals.

Moving Forward with Hope and Strength

The journey of healing is complex, often requiring us to face uncomfortable truths and difficult emotions. This research doesn’t diminish that. Instead, it offers a powerful reminder: alongside confronting our challenges, actively nurturing our inherent strengths can provide an invaluable boost, making therapy more effective and potentially even more empowering. By weaving a focus on what’s working, what’s strong, and what’s resilient into the fabric of mental health care, we can help people not just alleviate suffering, but truly flourish. It’s an invitation for therapists and clients alike to look beyond the problem and discover the profound potential within.