A new US phone network for Christians aims to block porn and gender-related content

A new US-wide cell phone network marketed to Christians is set to launch next week. It blocks porn, which experts in network security say marks the first time a US cell plan has used network-level blocking for such content that can’t be turned off even by adult account owners. It’s also rolling out a filter on sexual content aimed at blocking material related to gender and trans issues, which will be optional but turned on by default across all plans.

The network, which is currently being tested ahead of its May 5 launch date, will be run by Radiant Mobile, a newly launched mobile virtual network operator (MVNO). These operators don’t own cell towers but buy bandwidth from the big providers (in this case, T-Mobile) and sell to specific demographics (President Trump announced his own MVNO last year called Trump Mobile; CREDOMobile sends donations to progressive causes). 

“We are going to create—and we think we have every right to do so—an environment that is Jesus-centric, that is void of pornography, void of LGBT, void of trans,” Radiant Mobile’s founder, Paul Fisher, told MIT Technology Review. A representative for T-Mobile did not comment on whether these content blocks violate any of its policies. In a statement, the representative added that T-Mobile does not have a direct relationship with Radiant Mobile but instead works through the MVNO manager CompaxDigital. 

Fisher says he’s recruited a mix of Christian influencers to advertise the plan and has also done outreach to thousands of churches around the country, offering a way to have Radiant donate a portion of congregants’ $30-per-month subscription fee to their church. Fisher has ambitions to market it beyond the US in other countries with significant Christian populations, like South Korea and Mexico.

At least one piece of Radiant’s pitch will sound familiar: the idea that the internet is awash in toxic sludge. It’s powered by content and algorithms that are making us more sad, hateful, and detached. A number of efforts aim to fix that, including contentious age verification laws and a coming wave of lawsuits alleging that social media companies knowingly got young users hooked on their platforms. 

Fisher is pursuing the nuclear option. He says Radiant is working with the Israeli cybersecurity company Allot to block categories of content, such as material about violence or self-harm. Some categories are banned by default and cannot be allowed even for adult users. 

This includes pornography. Chris Klimis, a minister in Orlando who was recruited to be the company’s chief operating officer, says part of the reason he got involved was to offer Christians a real way to “do something” about what he sees as a pornography crisis in the faith. He was appalled by a recent survey showing that 67% of pastors have a “personal history” with porn use. And he worries his six children will come across porn on their devices, even if only inadvertently.

“We’ve got to figure out some way to close the door to the digital space,” he says. “That’s what we’re trying to do.”

The technology to do this blocking is a blunt instrument: Allot groups website domains into more than a hundred categories, which include pornography but also violence, malware, gaming, and in Radiant Mobile’s case “sects,” which includes websites about Satanism. If one of its users tries to visit a website that belongs to a blocked category, the page won’t load. That’s harsher than app-based content blockers like Covenant Eyes, a Christian porn-quitting app that sends notifications to your friends or family if you slip up; those can be worked around or deleted.

“Blocking in the network is certainly not new,” says David Choffnes, a computer science professor and executive director of Northeastern University’s Cybersecurity and Privacy Institute. Such blocking is the backbone of censorship efforts by authoritarian governments, for example. But there are more benign ways it’s used too. US telecoms block particular domains known to be spreading malware and offer optional network-level controls to block adult content on kids’ phones. What is new is a US cell plan instituting network-level blocks that can’t be removed, even by adults.

The trouble is that most websites don’t fit neatly into one category, leaving Fisher with enormous and subjective control over which are allowed or banned. This is most apparent in his effort to block content related to gender identity.

Anthony Re, a sales director at Allot, says the company does not have a category specific to gender but that “LGBT content” tends to fall into its sexuality category, which is described on Radiant Mobile’s website as “sites that provide information on sex, sex and teenagers, and sexual education, without pornographic content.” This category is blocked by default for all phones, a setting that can be changed by adult account owners. 

But if a news site starts hosting enough gender-related content, Fisher might not just label it as “press,” which is allowed, but also “sexuality,” thus blocking the whole domain to any phone with that category blocked. 

Fisher illustrates the subjectivity of such decisions with a recent example involving Yale University. Its general website, www.yale.edu, is categorized by Allot as education. “But they have a subsection of one of their websites that’s totally focused on, you know, trans equality,” Fisher says, referring to lgbtq.yale.edu. Because it’s a distinct domain, Radiant Mobile is able to place it in the sexuality category and block it. 

Yale’s main website remains unblocked, for now. “If we see [the LGBTQ content] on the front pages consistently of Yale University, we’ll block them too,” Fisher says.

Managing website block lists is a professional pivot for Fisher, who spent his career not in telecoms but in fashion; he was an agent for supermodels like Naomi Campbell and members of the Hilton and Getty families, and he later hosted a reality show in which he found people in rehab facilities and homeless shelters and tried to turn them into models. He ultimately left the industry and now says he regrets the role he played in it: “Am I proud that I spent 35 years creating star models or star influencers? Not at all.”

Last year, his friend and fellow fashion mogul Bernt Ullmann suggested he look at what Ryan Reynolds had built with his cell network Mint Mobile: It made buying a cell plan feel less like dealing with a utility and more like choosing a brand, and it had been acquired by T-Mobile in 2023 for $1.3 billion. Fisher liked the business model but didn’t have an audience in mind. Then came a late-night revelation. “God is talking to me,” Fisher recalls. “Do something in the faith-based industry.” He set out to build the first cell network that would let in only content deemed compatible with Christianity.

Fisher says the company has received $17.5 million in investment from Compax Ventures, part of the company serving as the technical middleman between Radiant and T-Mobile. Roger Bringmann, a vice president at Nvidia, is Radiant Mobile’s lead investor and silent partner (Bringmann recently funded a new complex at Austin Christian University in Texas, which bills itself as “the university for Christian entrepreneurs”).

To fill the gap left by all the sites being blocked, the company intends to offer access to a library of religious content, including AI-generated Bible videos. It plans to use characters like Cinderella, Tinker Bell, and others (it has obtained rights from the entertainment and media company Elf Labs, which has been amassing rights to hundreds of children’s characters). “Those characters were originally constructed with a conservative perspective,” Klimis says. They’ll be used in AI-generated content alongside testimonials and devotionals. 

Choffnes has technical doubts that the plan’s firewall will be as effective as promised, not least because “it’s really hard to come up with a list of every website you think is problematic.” But beyond that, he sees the internet, frustrating as it can be, as better open than closed. “I do believe in an open internet,” he says. “I also believe that a lot of the internet is toxic, but I don’t believe that this sledgehammer approach of blocking content is the right answer.”

The Effectiveness and Mechanisms of Action of App-Based Interventions for Improving Mental Health and Workplace Well-Being: Randomized Controlled Trial

Background: Depression is the most common mental health disorder worldwide and frequently leads to workplace absence. As face-to-face treatment can be difficult to access, app-based interventions are a popular solution, although their effectiveness in working populations and their mechanisms of action are unclear. Deficits in executive function may contribute to the onset and maintenance of depression, and executive function training is proposed to improve symptoms by enhancing executive function. Responders to cognitive behavioral therapy (CBT) show improvements in executive function, suggesting that this may be one mechanism of action. Objective: This study investigated the effectiveness of app-based interventions (executive function or CBT-based) for reducing depressive and anxiety symptoms and improving workplace well-being, and assessed whether changes in executive function mediated improvements. Methods: A total of 228 participants (147 female participants) with mild-to-moderate symptoms of depression and anxiety were recruited online and randomly assigned to a waitlist control group, an executive function training group (NeuroNation app, Synaptikon GmbH), or a self-guided CBT group (Moodfit app, Roble Ridge LLC) for a 4-week intervention period. Participants assigned to the active intervention groups were asked to use their apps a minimum of 21 times during the intervention. Participants completed measures of depressive symptoms, anxiety symptoms, and workplace well-being, and a working memory task at baseline, postintervention, and follow-up (12 weeks). Results: Executive function training reduced anxiety (β=−2.79; =.004) and depressive (β=−2.77; =.02) symptoms at follow-up but not at postintervention, and it did not affect workplace well-being. There were no reductions in depressive or anxiety symptoms in the self-guided CBT group, though workplace well-being was improved at postintervention (β=3.72; =.02) and follow-up (β=4.46; =.02). Improvements in executive function did not mediate intervention-related changes in symptoms or workplace well-being. Self-reported adherence rates were high (executive function training: 48/54, 89%; self-guided CBT: 52/54, 96%), although attrition was high at follow-up (58% missing). Conclusions: These results suggest that app-based executive function training may be effective at managing symptoms of anxiety and depression in a working population, while self-guided CBT apps may improve workplace well-being. However, improving executive function did not appear to be a mechanism of action of either intervention. Trial Registration: ISRCTN 12730006; https://www.isrctn.com/ISRCTN12730006
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/97ff2f6a5aa1b4552bcc78ed572308d4" />

Building a Science-Driven Business: How National Institutes of Health Funding Enabled an Evidence-Based Approach to Maternal Mental Health Innovation

The digital mental health (DMH) industry has grown drastically over the last decade; yet, many DMH products have failed to demonstrate meaningful clinical outcomes, in large part due to lack of scientific evidence. This viewpoint paper highlights an example of how early-stage DMH companies can prioritize science as a strategic advantage. We discuss Moment for Parents, an artificial intelligence–driven maternal mental health app built entirely with support from the National Institutes of Health (NIH) Small Business Innovation Research (SBIR) program. We illustrate the advantages and challenges of building a science-backed product with federal funding. Benefits include credible evidence generation, independence in product development, and enhanced market differentiation. We also discuss the challenges of navigating the SBIR ecosystem, including grant writing and administrative demands, and aligning business objectives with federal research priorities. By showcasing both the promise and complexity of SBIR funding, this viewpoint paper offers actionable insights for founders and chief executive officers who aim to prioritize science in the DMH space.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/0353d3d1a7028c09b54629066fd3bca7" />

Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial

Background: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. Objective: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. Methods: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o–based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. Results: Compared to AOC, both the AI therapy group (=−0.47; =.01) and the ChatGPT group (=−0.44; =.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (=−0.37; =.11) and ODSIS depression scores (=−0.25; =.22) and an increase in well-being (=0.12; =.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (=−0.27; =.22) and ODSIS depression scores (=−0.12; =.53) and an increase in well-being (=0.20; =.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: =−0.19; =0.03; =.87; 7-item Generalized Anxiety Disorder Scale: =−0.57; =−0.11; =.62; ODSIS: =−0.59; =−0.13; =.50; and WHO: =−0.38; =−0.07; =.69). Conclusions: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes. Trial Registration: OSF Registries osf.io/r76ef;
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/79f5e531de1d0b2de861e05b715c91f7" />

Effects of an Exercise-Assisting Mobile App (Osteoarthritis-Rehabilitation Assistant [O-RA]) on Rehabilitation Outcomes in Older Adults: Randomized Controlled Parallel Clinical Trial

Background: Mobile apps and biofeedback using motion analysis have both been used separately to increase compliance with exercise programs. We developed a mobile app, Osteoarthritis-Rehabilitation Assistant (O-RA), that uses motion analysis technology in the mobile app to assist older adults with performing a knee exercise program. Objective: This study aimed to evaluate the effects of the O-RA app on the compliance and correctness of the exercise program by older adults. Methods: We conducted an assessor-blind, parallel-design, randomized controlled trial with 40 older adults (aged 60 years or older) who had no symptoms and no diagnosis of knee osteoarthritis. Participants were divided into 2 groups: O-RA app (intervention) group and standard treatment (control) group. Both groups were taught 4 types of exercise programs by a physical therapist for 15 minutes and were instructed to do exercises at home every day for 1 week. The number of exercises, the percentage between observed and prescribed exercises, the correctness of exercises, and overall pain during the program were assessed in both groups. Results: The control group had significantly higher compliance with the exercise program than the intervention group (=3.5044, =.001). There was no statistically significant difference in the correctness of the exercise program between the intervention and control groups. The difficulty of use and satisfaction were 47 and 59, respectively, out of the full score of 100. The main problems were the instability and the difficulty using the app. Conclusions: In older adults without knee osteoarthritis symptoms or diagnosis, the O-RA app was not a facilitator but a barrier to the lower extremity exercise program. An updated version, aiming to increase the stability and make it more user-friendly, should be developed; however, more comprehensive data, including qualitative user feedback and standardized usability metrics, will be needed to effectively guide its design. Trial Registration: Thai Clinical Trial Record TCTR20240923002; https://www.thaiclinicaltrials.org/export/pdf/TCTR20240923002
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/c37817fc3e8476f49e094465f2f45581" />

Peer Mentor Training and Supervision for a Digital Adolescent Depression Treatment in South Africa and Uganda: Mixed Methods Evaluation

Background: Blended digital mental health interventions combining technology with human support are more effective than stand-alone treatments. However, limited research has examined how to train and supervise personnel delivering human support components. The Kuamsha app, a gamified digital intervention for adolescent depression based on behavioral activation, was designed to be paired with low-intensity telephone-based peer support. A structured training and supervision program for peer supporters was codeveloped through workshops with mental health professionals and youth with lived experience of mental health challenges in South Africa and Uganda. To the best of our knowledge, this is the first study to evaluate a structured peer mentor model within a digital mental health intervention in low- and middle-income countries. Objective: This study assessed the feasibility, acceptability, and fidelity of a training and supervision program for peer supporters delivering a digital mental health intervention in South Africa and Uganda. Methods: We conducted a mixed methods evaluation of the peer mentor program. Quantitative metrics assessed the feasibility of recruitment, retention, and attendance among peer mentors (n=13, South Africa; n=4, Uganda), as well as training acceptability. Fidelity, adherence, and competence were scored at the session level and converted to percentages of the maximum possible score. Linear mixed-effects regression models with a random intercept for provider and site estimated adjusted marginal means (95% CI). In-depth interviews and focus group discussions explored program acceptability and implementation factors. Results: The peer mentor training and supervision program was feasible and acceptable in both settings, with high recruitment (South Africa: n=13/19, 68%; Uganda: 4/4, 100%), retention (South Africa: 9/13, 69%; Uganda: 4/4, 100%), and training attendance rates (89%‐92% in South Africa and 100% in Uganda), alongside qualitative reports of high satisfaction. All peer mentors met a minimum posttraining competency threshold (≥50%), with median competency scores of 70.7% (IQR 45.8%‐78.2%) in South Africa and 75.4% (IQR 73.8%‐77.3%) in Uganda. Independent ratings of recorded calls indicated high overall fidelity in South Africa (84.7%, 95% CI 80.3%‐89.0%) and Uganda (87.7%, 95% CI 83.4%‐92.1%). Adherence was higher in Uganda than South Africa (adjusted mean difference [AMD] 13.30 percentage points, 95% CI 8.99‐17.61; <.001), as was competence (AMD 4.88 percentage points, 95% CI 1.23‐8.53; =.009). The AMD in overall fidelity (3.06 percentage points, 95% CI −0.98 to 7.10) was not statistically significant (=.14). The qualitative findings emphasized the value of ongoing supervision and capacity development, interactive training approaches, and blended delivery models. Conclusions: Locally adapted training and supervision models can strengthen peer mentor capabilities to support digital interventions. Adequate supervisory capacity and incentive structures are critical to sustain engagement, retention, and fidelity. In settings with frequent network disruptions, periodic in-person contact between peer mentors and supervisors may enhance fidelity. Future research should examine how peer mentor fidelity influences user engagement and mental health outcomes. Trial Registration: Pan African Clinical Trials Registry PACTR202206574814636; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=23792 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2022-065977

Development of the Healthy Women Intervention to Increase Women’s Engagement in Medication Treatment for Opioid Use Disorder: Mixed Methods, User-Centered Design Approach

Background: Rates of opioid use disorder (OUD) have increased among women over the past 2 decades. Medication treatment for opioid use disorder (MOUD) is effective but underused. Gender-specific treatments for women have been associated with improved substance use outcomes. However, these treatments have not specifically targeted women’s engagement in MOUD, and the impact of existing gender-specific treatments is restricted by in-person delivery. Objective: The aim of this study was to develop a digital intervention to feasibly deliver gender-specific care that addresses the individualized needs of women with OUD to increase engagement in MOUD. Methods: A mixed methods, user-centered design approach was used to inform the development of a digital intervention. In phase 1, qualitative interviews were conducted with women with lived experience of OUD (n=20) and providers who treat women with OUD (n=8). Interviews were recorded, transcribed, and coded for themes. In addition, a larger sample of treatment providers (n=55) completed an online survey to further inform the content of the digital intervention. Phase 2 consisted of designing, beta-testing (n=5), and refining the intervention. Results: The age of women with lived experience ranged from 21 to 59 (mean 38.5, SD 9.4) years; 63% (5/8) of providers interviewed were female participants. The qualitative interview data from women with lived experience and providers were grouped into 6 thematic categories: 3 treatment-related (1) barriers to treatment, (2) facilitators to successful recovery, and (3) important issues to address in treatment, and 3 technology-related (4) positives of using technology as part of treatment, (5) suggested technology features, and (6) barriers to using technology. Across the treatment-related categories, several themes touched on women-specific factors including family responsibilities, abusive partners, stigma, and motivation for treatment (eg, pregnancy). The technology-related categories provided information for designing the features of the intervention, as well as revealing barriers to technology use, which could be helpful in developing implementation strategies. Provider survey participants were primarily female participants (40/55, 73%), with a mean age of 42.5 (SD 12.5) years. Survey data provided additional information on barriers to treatment and suggested technology features. Based on these data and preliminary work, the intervention was created. Minor edits to content and visual design were made in the beta-testing phase. The final version includes a web-based component with 6 topic modules and a mobile component. Topics in the web-based component are presented through infographics, text, videos, and interactive questions. The mobile component includes daily motivational messages, skills practice activities (2/wk), weekly check-ins, and resources (always available). Conclusions: Important themes and suggested features from women with lived experience and providers were incorporated into a digital intervention for women with OUD. Data on feasibility, satisfaction, and engagement with the intervention are currently being collected in phase 3, a pilot randomized controlled trial.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/6b8c4ff957e61601e8e82fd621767c3d" />