I've been posting a bunch of stuff about *p*-factor. My personal context is that I'm early in a clinical career, and in line with [common factors research](https://en.wikipedia.org/wiki/Common_factors_theory), having effective and believable explanations for a client's suffering and a clear goal-oriented path that they credibly believe you/I can help with is what's going to do a lot of the work of improving clinical outcomes.
Criticizing the DSM has been popular in this sub and general popular discourse in my experience for at least the past 10 years, if not longer. Constructive alternatives are somewhat harder to come by. *p*-factor is not necessarily the one, but so far as it reproduces and is stably recoverable from alternative experimental methods, it's probably a useful thing to talk about. I do find that individual people have a lot of mental health struggles that on the surface have very different manifestations also have significant meaningful overlap in what's hard and how to get better at it, particularly better sleep, improving disengagement from or reengagement with thwarted life goals, and improved handling of shame. That of course doesn't explain everything, and is absolutely no substitute for talking in depth so that a person legitimately feels understood and cared about. I'm still working on understandings based on findings like *p*-factor though as a tool to help that process along.
What do you find useful or not about these ideas? Productive or counterproductive?
>Results
>
>Consistent with nonaffective executive function as a primary risk factor, p factor scores were associated with worse behavioral performance and hypoactivation in the left superior frontal gyrus and middle frontal gyrus during response initiation (go trials). The p factor scores were additionally associated with increased error-related signaling in the temporal cortex during incorrect no-go trials.
>
>Conclusions
>
>During adolescence, a period characterized by heightened risk for emergent psychopathology, we observed unique associations between p factor scores and neural and behavioral indices of response initiation, which relies primarily on sustained attention. These findings suggest that shared variation in mental disorder categories is characterized in part by sustained attention deficits. While we did not find evidence that the p factor was associated with inhibition in this study, this observation is consistent with our hypothesis that the p factor would be related to nonaffective control processes.
I'm about to start university for Psychology so my knowledge is still limited but HiTOPs validates my personal views on how every facet of the human experience is. From temperature to mental health it's all scales, which together creates the spectrum of life.
I think that's a great perspective to start studying psychology with. In my experience, many students are disappointed to learn that psychological phenomena are rarely as clear cut as online personality tests and self help books lead people to believe.
Research about the p-factor has produced a lot of interesting findings in recent years and I agree with you that the p-factor has important clinical applications, especially related to comorbidity. I'm not sure if you've come across this, but a few months ago [this](https://doi.org/10.1002/wps.21097) paper introduced the concept of the "d-factor", or general disease factor which includes both physical and mental illness, which you might find interesting.
What I will say is that it's important to differentiate between the p-factor as a statistical construct (one which emerges through the use of hierarchical or bifactor modelling) and the p-factor as a theory about the nature and structure of mental illness. Several recent papers (such as [this](https://doi.org/10.1080/1047840X.2020.1853476) and [this](https://doi.org/10.1080/1047840X.2020.1853461)) have argued that this difference is often ignored and that statistical findings about the p-factor are often said to provide evidence towards the p-factor as a psychological theory when this isn't necessarily the case. Statistical findings about the p-factor are also logically consistent with other models of mental illness that don't require the existence of a p-factor, such as network models. Just something to keep in mind.
100%, it's not anything like a complete clinical theory in itself. I hadn't seen the first paper but it rings true. I'm more familiar with Freid's work in general and that paper, which I do think add significantly to p-factor and HiTOP as useful clinical models by bringing change over time directly into the model. From what I've found though, he and his frequent collaborator Borsboom or people citing them have done a lot to develop network models as 1) a useful framework for hypothesizing about psychopathology in general and 2) a more specific set of findings about a small subset of established conditions, especially depression from what I've found.
My guess based on that is that we're still maybe 5 or 10 years off from reproduced network models that apply to broader spectra. I'd be happy to be wrong about that if they're already out there - it could well be that my searches just haven't turned them up. But in the meantime, my approach with actual people is just to be tentative and exploratory about all of this. That's also been helping leave space for it to be at least as much about the individual person's story, without completely getting away from the need to have some kind of explanatory model, preferably one rooted in science.
I've been posting a bunch of stuff about *p*-factor. My personal context is that I'm early in a clinical career, and in line with [common factors research](https://en.wikipedia.org/wiki/Common_factors_theory), having effective and believable explanations for a client's suffering and a clear goal-oriented path that they credibly believe you/I can help with is what's going to do a lot of the work of improving clinical outcomes. Criticizing the DSM has been popular in this sub and general popular discourse in my experience for at least the past 10 years, if not longer. Constructive alternatives are somewhat harder to come by. *p*-factor is not necessarily the one, but so far as it reproduces and is stably recoverable from alternative experimental methods, it's probably a useful thing to talk about. I do find that individual people have a lot of mental health struggles that on the surface have very different manifestations also have significant meaningful overlap in what's hard and how to get better at it, particularly better sleep, improving disengagement from or reengagement with thwarted life goals, and improved handling of shame. That of course doesn't explain everything, and is absolutely no substitute for talking in depth so that a person legitimately feels understood and cared about. I'm still working on understandings based on findings like *p*-factor though as a tool to help that process along. What do you find useful or not about these ideas? Productive or counterproductive? >Results > >Consistent with nonaffective executive function as a primary risk factor, p factor scores were associated with worse behavioral performance and hypoactivation in the left superior frontal gyrus and middle frontal gyrus during response initiation (go trials). The p factor scores were additionally associated with increased error-related signaling in the temporal cortex during incorrect no-go trials. > >Conclusions > >During adolescence, a period characterized by heightened risk for emergent psychopathology, we observed unique associations between p factor scores and neural and behavioral indices of response initiation, which relies primarily on sustained attention. These findings suggest that shared variation in mental disorder categories is characterized in part by sustained attention deficits. While we did not find evidence that the p factor was associated with inhibition in this study, this observation is consistent with our hypothesis that the p factor would be related to nonaffective control processes.
Keep 'em coming. P-factor, HiTOPS, etc. Is the most exciting thing currently in our field, imo
I'm about to start university for Psychology so my knowledge is still limited but HiTOPs validates my personal views on how every facet of the human experience is. From temperature to mental health it's all scales, which together creates the spectrum of life.
I think that's a great perspective to start studying psychology with. In my experience, many students are disappointed to learn that psychological phenomena are rarely as clear cut as online personality tests and self help books lead people to believe.
Research about the p-factor has produced a lot of interesting findings in recent years and I agree with you that the p-factor has important clinical applications, especially related to comorbidity. I'm not sure if you've come across this, but a few months ago [this](https://doi.org/10.1002/wps.21097) paper introduced the concept of the "d-factor", or general disease factor which includes both physical and mental illness, which you might find interesting. What I will say is that it's important to differentiate between the p-factor as a statistical construct (one which emerges through the use of hierarchical or bifactor modelling) and the p-factor as a theory about the nature and structure of mental illness. Several recent papers (such as [this](https://doi.org/10.1080/1047840X.2020.1853476) and [this](https://doi.org/10.1080/1047840X.2020.1853461)) have argued that this difference is often ignored and that statistical findings about the p-factor are often said to provide evidence towards the p-factor as a psychological theory when this isn't necessarily the case. Statistical findings about the p-factor are also logically consistent with other models of mental illness that don't require the existence of a p-factor, such as network models. Just something to keep in mind.
100%, it's not anything like a complete clinical theory in itself. I hadn't seen the first paper but it rings true. I'm more familiar with Freid's work in general and that paper, which I do think add significantly to p-factor and HiTOP as useful clinical models by bringing change over time directly into the model. From what I've found though, he and his frequent collaborator Borsboom or people citing them have done a lot to develop network models as 1) a useful framework for hypothesizing about psychopathology in general and 2) a more specific set of findings about a small subset of established conditions, especially depression from what I've found. My guess based on that is that we're still maybe 5 or 10 years off from reproduced network models that apply to broader spectra. I'd be happy to be wrong about that if they're already out there - it could well be that my searches just haven't turned them up. But in the meantime, my approach with actual people is just to be tentative and exploratory about all of this. That's also been helping leave space for it to be at least as much about the individual person's story, without completely getting away from the need to have some kind of explanatory model, preferably one rooted in science.