How much online pornography is too much? A comparison of two theoretically distinct assessment scales.

BACKGROUND: Online pornography use, an ever more common activity, has raised myriad psychosocial and clinical concerns. While there is a need to screen for and measure its problematic dimension, there is a debate about the adequacy of existing assessment tools. OBJECTIVE: The study compares two instruments for measuring pathological online pornography use (POPU) that are based on different theoretical frameworks-one in line with DSM-5 criteria and the six-component addiction model and one in line with ICD-11 criteria. METHODS: An international sample of 1,823 adults (Mean age = 31.66, SD = 6.74) answered an online questionnaire that included the Short Version of the Problematic Pornography Consumption Scale (PPCS-6) and the Assessment of Criteria for Specific Internet-Use Disorders (ACSID-11). Factorial, correlational, and network analyses were conducted on the data. RESULTS: Both tools adequately screened for online "addictive" behavior, but the ACSID-11 was superior in assessing the degree of clinical risk. CONCLUSION: Depending on the specific aim of the assessment (screening vs. clinical diagnostics), both online pornography measurement tools may be useful.

Online dating: predictors of problematic tinder use.

BACKGROUND: Geolocation apps have radically transformed dating practices around the world, with profound sociocultural implications. Few studies, however, have explored their addictive potential or factors that are associated with their misuse. OBJECTIVE: The present study aimed to assess the level of problematic Tinder use (PTU) in an adult sample, using a machine learning algorithm to determine, among 29 relevant variables, the most important predictors of PTU. METHODS: 1,387 users of Tinder (18-74 years-old; male = 50.3%; female = 49.1%) completed an online questionnaire, and a machine learning tool was used to analyze their responses. RESULTS: On 5-point scale, participants' mean PTU score was 1.91 (SD = 0.70), indicating a relatively low overall level of problematic app use. Among the most important predictors of Problematic use were the use of Tinder for enhancement (reduce boredom and increase positive emotions), coping with psychological problems, and increasing social connectedness. The number of "matches" (when two users show mutual interest), the number of online contacts on Tinder, and the number of resulting offline dates were also among the top predictors of PTU. Depressive mood and loneliness were among the middle-ranked predictors of PTU. CONCLUSION: In accordance with the Interaction of Person-Affect-Cognition-Execution model of problematic internet use, the results suggest that PTU relates to how individual experience on the app interacts with dispositional and situational characteristics. However, variables that seemed to relate to PTU, including lack of self-esteem, negative mood states and loneliness, are not problems that online dating services as currently designed can be expected to resolve. This argues for increased digital services to identify and address potential problems helping drive the popularity of dating apps.

Finding Intimacy Online: A Machine Learning Analysis of Predictors of Success.

While an extensive scientific literature now exists on the use of online dating services, there are very few studies on user satisfaction with dating apps and with the resulting offline dates. This study aimed to assess the level of satisfaction with Tinder use (STU) and the level of satisfaction with Tinder offline dates (STOD) in a sample of adult users of the app. The study also aimed to examine, among 28 variables, those that are the most important in predicting STU and STOD. Overall, 1,387 Tinder users completed an online questionnaire. A machine learning model was used to rank order predictors from most to least important. On a 4-point scale, participants' mean STU score was 2.39, and, on a 5-point scale, mean STOD score was 3.05. The results indicate that satisfaction with dating apps and with resulting offline dates is strongly predicted by participants' age and by their motives for using Tinder (enhancement, emotional coping, socialization, finding "true love," or casual sexual partners), whereas the variables negatively associated with satisfaction were those related to psychopathology. Interestingly, 65.3 percent of app users were married or "in a relationship," and only 50.3 percent of app users were using it to meet someone offline. Generally, participants who engage with the app to cope with personal difficulties seem more likely to report higher levels of dissatisfaction, suggesting that dating apps are a poor coping mechanism and highlighting the need to address underlying problems or pathologies that may be driving their use.

Privacy, bias and the clinical use of facial recognition technology: A survey of genetics professionals.

Facial recognition technology (FRT) has been adopted as a precision medicine tool. The medical genetics field highlights both the clinical potential and privacy risks of this technology, putting the discipline at the forefront of a new digital privacy debate. Investigating how geneticists perceive the privacy concerns surrounding FRT can help shape the evolution and regulation of the field, and provide lessons for medicine and research more broadly. Five hundred and sixty-two genetics clinicians and researchers were approached to fill out a survey, 105 responded, and 80% of these completed. The survey consisted of 48 questions covering demographics, relationship to new technologies, views on privacy, views on FRT, and views on regulation. Genetics professionals generally placed a high value on privacy, although specific views differed, were context-specific, and covaried with demographic factors. Most respondents (88%) agreed that privacy is a basic human right, but only 37% placed greater weight on it than other values such as freedom of speech. Most respondents (80%) supported FRT use in genetics, but not necessarily for broader clinical use. A sizeable percentage (39%) were unaware of FRT's lower accuracy rates in marginalized communities and of the mental health effects of privacy violations (62%), but most (76% and 75%, respectively) expressed concern when informed. Overall, women and those who self-identified as politically progressive were more concerned about the lower accuracy rates in marginalized groups (88% vs. 64% and 83% vs. 63%, respectively). Younger geneticists were more wary than older geneticists about using FRT in genetics (28% compared to 56% "strongly" supported such use). There was an overall preference for more regulation, but respondents had low confidence in governments' or technology companies' ability to accomplish this. Privacy views are nuanced and context-dependent. Support for privacy was high but not absolute, and clear deficits existed in awareness of crucial FRT-related discrimination potential and mental health impacts. Education and professional guidelines may help to evolve views and practices within the field.

Smartphone apps for mental health and wellbeing: A usage survey and machine learning analysis of psychological and behavioral predictors.

Objective: Despite the availability of thousands of mental health applications, the extent to which they are used and the factors associated with their use remain largely unknown. The present study aims to (a) assess in a representative US-based population sample the use of smartphone apps for mental health and wellbeing (SAMHW), (b) determine the variables predicting the use of SAMHW, and (c) explore how a set of variables related to mental health, smartphone use, and smartphone "addiction" may be associated with the use of SAMHW. Methods: Data was collected via online questionnaire from 1989 adults. The data gathered included information on smartphone use behavior, mental health, and the use of SAMHW. Latent class analysis was used to categorize participants. Machine learning and logistic regression analyses were used to determine the most important predictors of SAMHW use and associations between predictors and outcome variables. Results: While two-thirds of participants had a statistically high probability for using SAMHW, nearly twice more had high probability for using them to improve wellbeing compared to using them to address mental health problems (43% vs. 18%). In both groups, these participants were more likely to be female and in the younger adult age bracket than male and in the adult or older adult age bracket. According to the machine learning model, the most important predictors for using the relevant smartphone apps were variables associated with smartphone problematic use, COVID-19 impact, and mental health problems. Conclusion: Findings from the present study confirm that the use of SAMHW is growing, particularly among younger adult and female individuals who are negatively impacted by problematic smartphone use, COVID-19, and mental health problems. These individuals tend to bypass traditional care via psychotherapy or psychopharmacology, relying instead on smartphones to address mental health conditions or improve wellbeing. Advising users of these apps to also seek professional help and promoting efforts to prove the efficacy and safety of SAMHW would seem necessary.

Treatment-resistant OCD: Pharmacotherapies in adults.

Serotonin reuptake inhibitor (SRI) medications are well established as first-line pharmacotherapeutic treatment for Obsessive-Compulsive Disorder (OCD). However, despite the excellent safety profile and demonstrated efficacy of these medications, a substantial proportion of individuals with OCD fail to attain sufficient benefit from SRIs. In this narrative review, we discuss clinical features of OCD that have been associated with poorer response to SRIs, and we present pharmacotherapeutic interventions that have been explored as augmenting or alternative treatments for treatment-resistant OCD. We additionally highlight non-SRI interventions for OCD that are currently under investigation. Pharmacotherapeutic interventions were identified via expert consensus. To assess the evidence base for individual pharmacotherapies, targeted searches for relevant English-language publications were performed on standard biomedical research databases, including MEDLINE. Information relevant to ongoing registered clinical trials in OCD was obtained by search of ClinicalTrials.gov. Pharmacotherapies are grouped for review in accordance with the general principles of Neuroscience-based Nomenclature (NbN). Clinical features of OCD that may suggest poorer response to SRI treatment include early age of onset, severity of illness, duration of untreated illness, and the presence of symmetry/ordering or hoarding-related symptoms. Based on evolving pathophysiologic models of OCD, diverse agents engaging serotonin, dopamine, norepinephrine, glutamate, and anti-inflammatory pathways have been explored as alternative or adjunctive therapies for treatment-resistant OCD and have at least preliminary evidence of efficacy. Medications with dopamine antagonist activity remain the most robustly evidence-based of augmenting interventions, yet dopamine antagonists benefit only a minority of those who try them and carry elevated risks of adverse effects. Interventions targeting glutamatergic and anti-inflammatory pathways are less well evidenced, but may offer more favorable benefit to risk profiles. Ongoing research should explore whether specific interventions may benefit individuals with particular features of treatment-resistant OCD.

Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis.

BACKGROUND: Problematic smartphone use, like problematic internet use, is a condition for which treatment is being sought on the web. In the absence of established treatments, smartphone-provided tools that monitor or control smartphone use have become increasingly popular, and their dissemination has largely occurred without oversight from the mental health field. OBJECTIVE: We aimed to assess the popularity and perceived effectiveness of smartphone tools that track and limit smartphone use. We also aimed to explore how a set of variables related to mental health, smartphone use, and smartphone addiction may influence the use of these tools. METHODS: First, we conducted a web-based survey in a representative sample of 1989 US-based adults using the crowdsourcing platform Prolific. Second, we used machine learning and other statistical tools to identify latent user classes; the association between latent class membership and demographic variables; and any predictors of latent class membership from covariates such as daily average smartphone use, social problems from smartphone use, smartphone addiction, and other psychiatric conditions. RESULTS: Smartphone tools that monitor and control smartphone use were popular among participants, including parents targeting their children; for example, over two-thirds of the participants used sleep-related tools. Among those who tried a tool, the highest rate of perceived effectiveness was 33.1% (58/175). Participants who experienced problematic smartphone use were more likely to be younger and more likely to be female. Finally, 3 latent user classes were uncovered: nonusers, effective users, and ineffective users. Android operating system users were more likely to be nonusers, whereas younger adults and females were more likely to be effective users. The presence of psychiatric symptoms did not discourage smartphone tool use. CONCLUSIONS: If proven effective, tools that monitor and control smartphone use are likely to be broadly embraced. Our results portend well for the acceptability of mobile interventions in the treatment of smartphone-related psychopathologies and, potentially, non-smartphone-related psychopathologies. Better tools, targeted marketing, and inclusive design, as well as formal efficacy trials, are required to realize their potential.

Editorial Perspective: Missing the forest for the trees - how the focus on digital addiction and gaming diverted attention away from wider online risks.

Despite the many ways in which Internet-related technologies can affect psychology, research into the Internet's mental health consequences has disproportionately focussed on the narrow topics of online addiction and the closely related Internet gaming disorder. Over two decades into the online revolution, the Internet is being blamed for dramatic transformations, including a rise in extremism, social polarization and weakened democracies. In trying to understand how these shifts could have happened, or how they might be contained, society looks to mental health experts - after all, it is the interaction between technology and human psychology that is encouraging certain behaviours online and discouraging others. The field, however, has precious little to offer by way of explanations. To no small degree, this is due to the tendency to approach online psychological problems primarily through the addiction framework. The result has been to blind us to other important traits and phenomena that are playing out online and on social media, including impulsivity, aggression, inattention, narcissism and the psychological meaning of living in a postprivacy world. The article covers historical aspects of how the addiction model came to dominate the field; some insufficiently heeded early warning signals about other online ills and the big price society is paying today for this approach. We end with a call for a significant broadening of the focus of research when it comes to online psychopathology.

Case Report: Doubts and Pre-occupations About Being Transgender: Questioning One's Gender Identity or a Case of Obsessive-Compulsive Disorder?

We report the case of a biological female with gender identity-related doubts that were misconstrued as suggesting obsessive-compulsive disorder (OCD). The patient's parent seemed to favor an OCD explanation for the gender-based self-questioning over acceptance of possible transgender identity. We discuss what OCD is and what it is not in the context of gender identity-based doubt; analogy with the better studied sexual orientation-related OCD; cultural flashpoints around sex and gender that can become the object of OCD; how confusion about biological sex, assigned gender and gender identity can lead to clinical harm; and the role of mental health professionals in fighting the stigma faced by gender minorities.

Live psychotherapy by video versus in-person: A meta-analysis of efficacy and its relationship to types and targets of treatment.

In-person psychotherapy (IPP) has a long and storied past, but technology advances have ushered in a new era of video-delivered psychotherapy (VDP). In this meta-analysis, pre-post changes within VDP were evaluated as were outcome differences between VDP versus IPP or other comparison groups. A literature search identified k = 56 within-group studies (N = 1681 participants) and 47 between-group studies (N = 3564). The pre-post effect size of VDP was large and highly significant, g = +0.99 95% CI [0.67-0.31]. VDP was significantly better in outcome than wait list controls (g = 0.77) but negligible in difference from IPP. Within-groups heterogeneity of effect sizes was reduced after subgrouping studies by treatment target, of which anxiety, depression, and posttraumatic stress disorder (PTSD) (each with k > 5) had effect sizes nearing 1.00. Disaggregating within-groups studies by therapy type, the effect size was 1.34 for CBT and 0.66 for non-CBT. Adjusted for possible publication bias, the overall effect size of VDP within groups was g = 0.54. In conclusion, substantial and significant improvement occurs from pre- to post-phases of VDP, this in turn differing negligibly from IPP treatment outcome. The VDP improvement is most pronounced when CBT is used, and when anxiety, depression, or PTSD are targeted, and it remains strong though attenuated by publication bias. Clinically, therapy is no less efficacious when delivered via videoconferencing than in-person, with efficacy being most pronounced in CBT for affective disorders. Live psychotherapy by video emerges not only as a popular and convenient choice but also one that is now upheld by meta-analytic evidence.

Automated syndrome diagnosis by three-dimensional facial imaging.

PURPOSE: Deep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30-40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces. METHODS: We analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images. RESULTS: Unrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative. CONCLUSION: Deep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of "unaffected" relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.

Where Life Coaching Ends and Therapy Begins: Toward a Less Confusing Treatment Landscape.

"Life coaching" is a rapidly expanding profession born out of an unmet need for help effecting change, frustration with traditional models, the stigma attached to seeking care, and the online "Uberization" of many new services. But the distinctions often drawn between life coaching and psychotherapy are increasingly blurry, raise important questions about where coaching ends and therapy begins, and risk confusion between the two helping professions among vulnerable patients. This is potentially serious, in part because life coaching operates in a regulatory vacuum, with no education, training, licensing, or supervision requirements for coaches and no specific legal protections for any harmed clients. Although increased access to new forms of help is a positive development, the risk that mentally ill patients may undergo life coaching rather than receive proven psychotherapy treatments raises concerns about patient safety. It can also trigger fears of professional replacement among mental health providers whose education, preparation, and practice parameters are rigorously defined and closely scrutinized. More research is needed to prove the efficacy and safety of life-coaching modalities, and meaningful action is required at the level of training, oversight, and legislation to help protect patients and clarify roles.

The psychology of "swiping": A cluster analysis of the mobile dating app Tinder.

BACKGROUND AND AIMS: The use of the smartphone dating application Tinder is increasingly popular and has received much media attention. However, no empirical study to date has investigated the psychological characteristics driving its adaptive or problematic use. The aim of this study is to determine whether reliable subtypes of users can be identified via a cluster analysis approach. METHODS: A total of 1,159 Tinder users were recruited. Survey questions investigated user characteristics, including: motives for app use, sexual desire, attachment styles, impulsivity traits, self-esteem, problematic use, depressive mood, and patterns of use. RESULTS: Four reliable clusters were identified: two with low levels of problematic use ("regulated" and "regulated with low sexual desire"), one with an intermediate level of problematic use ("unregulated-avoidants"), and one with a high level of problematic use ("unregulated-highly motivated"). The clusters differed on gender, marital status, depressive mood, and use patterns. CONCLUSION: The findings provide insight into the dynamic relationships among key use-related factors and shed light on the mechanisms underlying the self-regulation difficulties that appear to characterize problematic Tinder use.

Protecting privacy to protect mental health: the new ethical imperative.

Confidentiality is a central bioethical principle governing the provider-patient relationship. Dating back to Hippocrates, new laws have interpreted it for the age of precision medicine and electronic medical records. This is where the discussion of privacy and technology often ends in the scientific health literature when Internet-related technologies have made privacy a much more complex challenge with broad psychological and clinical implications. Beyond the recognised moral duty to protect patients' health information, clinicians should now advocate a basic right to privacy as a means to safeguard psychological health. The article reviews empirical research into the functions of privacy, the implications for psychological development and the resigned sentiment taking hold regarding the ability to control personal data. The article concludes with a call for legislative, educational and research steps to readjust the equilibrium between the individual and 'Big Data'.

From Digital Mental Health Interventions to Digital "Addiction": Where the Two Fields Converge.

Scientific literature from the last two decades indicates that, when it comes to mental health, technology is presented either as panacea or anathema. This is partly because researchers, too frequently, have planted themselves either in the field of digital mental health interventions (variably called "telepsychiatry", "digital therapeutics", "computerized therapy", etc.), or in that of the problems arising from technology, with little cross-fertilization between the two. Yet, a closer look at the two fields reveals unifying themes that underpin both the advantages and dangers of technology in mental health. This article discusses five such themes. First, the breakneck pace of technology evolution keeps digital mental health interventions updated and creates more potentially problematic activities, leaving researchers perennially behind, so new technologies become outdated by the time they are studied. Second, the freedom of creating and using technologies in a regulatory vacuum has led to proliferation and choice, but also to a Wild-West online environment. Third, technology is an open window to access information, but also to compromise privacy, with serious implications for online psychology and digital mental health interventions. Fourth, weak bonds characterize online interactions, including those between therapists and patients, contributing to high attrition from digital interventions. Finally, economic analyses of technology-enabled care may show good value for money, but often fail to capture the true costs of technology, a fact that is mirrored in other online activities. The article ends with a call for collaborations between two interrelated fields that have been-till now-mutually insular.