Increasing Value and Reducing Waste of Research on Neurofeedback Effects in Post-traumatic Stress Disorder: A State-of-the-Art-Review.

Post-Traumatic Stress Disorder (PTSD) is often considered challenging to treat due to factors that contribute to its complexity. In the last decade, more attention has been paid to non-pharmacological or non-psychological therapies for PTSD, including neurofeedback (NFB). NFB is a promising non-invasive technique targeting specific brainwave patterns associated with psychiatric symptomatology. By learning to regulate brain activity in a closed-loop paradigm, individuals can improve their functionality while reducing symptom severity. However, owing to its lax regulation and heterogeneous legal status across different countries, the degree to which it has scientific support as a psychiatric treatment remains controversial. In this state-of-the-art review, we searched PubMed, Cochrane Central, Web of Science, Scopus, and MEDLINE and identified meta-analyses and systematic reviews exploring the efficacy of NFB for PTSD. We included seven systematic reviews, out of which three included meta-analyses (32 studies and 669 participants) that targeted NFB as an intervention while addressing a single condition-PTSD. We used the MeaSurement Tool to Assess systematic Reviews (AMSTAR) 2 and the criteria described by Cristea and Naudet (Behav Res Therapy 123:103479, 2019, https://doi.org/10.1016/j.brat.2019.103479 ) to identify sources of research waste and increasing value in biomedical research. The seven assessed reviews had an overall extremely poor quality score (5 critically low, one low, one moderate, and none high) and multiple sources of waste while opening opportunities for increasing value in the NFB literature. Our research shows that it remains unclear whether NFB training is significantly beneficial in treating PTSD. The quality of the investigated literature is low and maintains a persistent uncertainty over numerous points, which are highly important for deciding whether an intervention has clinical efficacy. Just as importantly, none of the reviews we appraised explored the statistical power, referred to open data of the included studies, or adjusted their pooled effect sizes for publication bias and risk of bias. Based on the obtained results, we identified some recurrent sources of waste (such as a lack of research decisions based on sound questions or using an appropriate methodology in a fully transparent, unbiased, and useable manner) and proposed some directions for increasing value (homogeneity and consensus) in designing and reporting research on NFB interventions in PTSD.

Barriers and Considerations in the Design and Implementation of Digital Behavioral Interventions: Qualitative Analysis.

BACKGROUND: Digital behavioral interventions have become increasingly popular for their ability to support patient diagnosis and treatment, chronic disease self-management, behavior change, and adherence to recommended care. However, digital intervention development is impeded by challenges such as limited technical skills, limited access to developers, and cost. The purpose of this study is to elicit in-depth qualitative feedback from intervention developers who have interest in digital behavioral interventions but lack programming skills regarding the barriers they experience and key considerations in the design and implementation of digital interventions. OBJECTIVE: This study aims to understand barriers in the design and implementation of digital behavioral interventions, as well as to identify key considerations for researchers who are developing these interventions. METHODS: We conducted semistructured qualitative interviews with 18 researchers who had experience either designing (but not coding) digital behavioral interventions or running research studies with them. Participants were a convenience sample of users of the Computerized Intervention Authoring System platform, an existing no-code development platform for building digital intervention content, and were recruited through either direct email solicitation or snowball sampling. All interviews were conducted and recorded over videoconference between February and April 2020. Recordings from interviews were transcribed and thematically analyzed by multiple coders. RESULTS: Interviews were completed with 18 participants and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project/study staff. Three key barriers in the development of digital behavior interventions were identified during interviews: lack of cross-disciplinary understanding; variability in recipients' technology access, infrastructure, and literacy; and the idea that evidence-based in-person interactions do not translate directly to digital interactions. Interviewees identified several key considerations that interventionists learned to prioritize, which have the potential to overcome these barriers and lead to successful interventions. CONCLUSIONS: Barriers in the development of digital behavioral interventions are often created by a lack of cross-disciplinary understanding, which can lead to difficulties conceptualizing interventions, unrealistic expectations in terms of cost, and confusion about the development process. Moreover, concerns about research study participant characteristics and access to technology, as well as the translation of in-person interventions to digital, are apparent. Appropriate training in how to work with software development teams may help future digital behavior intervention creators overcome these barriers and may lead to new, exciting innovations in this space.

The Perceived Benefits of Digital Interventions for Behavioral Health: Qualitative Interview Study.

BACKGROUND: Digital interventions have gained momentum in terms of behavioral health. However, owing to lacking standard approaches or tools for creating digital behavioral interventions, clinical researchers follow widely varying conceptions of how best to go about digital intervention development. Researchers also face significant cost-, time-, and expertise-related challenges in digital intervention development. Improving the availability of tools and guidance for researchers will require a thorough understanding of the motivations and needs of researchers seeking to create digital interventions. OBJECTIVE: This study aims to understand the perceptions of behavioral researchers toward digital interventions, and inform the use of these interventions, by documenting the reasons why researchers are increasingly focusing their efforts on digital interventions and their perspectives on the perceived benefits that digital approaches can provide for researchers and intervention recipients. METHODS: We conducted semistructured qualitative interviews with 18 researchers who had experience designing digital behavioral interventions or running studies with them. A convenience sample of interviewees was recruited from among users of the Computerized Intervention Authoring System platform, a web-based tool that facilitates the process of creating and deploying digital interventions in behavioral research. Interviews were conducted over teleconference between February and April 2020. Recordings from the interviews were transcribed and thematically analyzed by multiple coders. RESULTS: Interviews were completed with 18 individuals and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project or study staff. Four major themes came out of the interviews concerning the benefits of digital interventions for behavioral health: convenience and flexibility for interventionists and recipients, support for implementing evidence-based interventions with fidelity, scaling and improving access to interventions, and getting a foot in the door despite stigma and disenfranchisement. CONCLUSIONS: Interviewees described a number of important potential benefits of digital interventions, particularly with respect to scientific rigor, scalability, and overcoming barriers to reaching more people. There are complex considerations with regard to translating behavior change strategies into digital forms of delivery, and interventionists make individual, sometimes unexpected, choices with minimal evidence of their relative effectiveness. Future research should investigate how behavioral researchers can be supported in making these choices toward usability, ease of access, and approachability of digital interventions. Our study underscores the need for authoring platforms that can facilitate the process of creating and deploying digital interventions to reach their full potential for interventionists and recipients alike.

Empowering communities with a smartphone-based response network for opioid overdoses.

In a Philadelphia neighbourhood where opioid overdoses are frequent, neighbors used a smartphone app to request and give help for a victim of suspected overdose. A one-year study demonstrated the feasibility of this approach, which empowered the local community to save lives and even respond to overdoses faster than emergency medical services.

Temporal-Posterior Alpha Power in Resting-State Electroencephalography as a Potential Marker of Complex Childhood Trauma in Institutionalized Adolescents.

The present study explored whether, given the association of temporal alpha with fear circuitry (learning and conditioning), exposure to complex childhood trauma (CCT) is reflected in the temporal-posterior alpha power in resting-state electroencephalography (EEG) in complex trauma-exposed adolescents in a sample of 25 adolescents and similar controls aged 12-17 years. Both trauma and psychopathology were screened or assessed, and resting-state EEG was recorded following a preregistered protocol for data collection. Temporal-posterior alpha power, corresponding to the T5 and T6 electrode locations (international 10-20 system), was extracted from resting-state EEG in both eyes-open and eyes-closed conditions. We found that in the eyes-open condition, temporal-posterior alpha was significantly lower in adolescents exposed to CCT relative to healthy controls, suggesting that childhood trauma exposure may have a measurable impact on alpha oscillatory patterns. Our study highlights the importance of considering potential neural markers, such as temporal-posterior alpha power, to understanding the long-term consequences of CCT exposure in developmental samples, with possible important clinical implications in guiding neuroregulation interventions.

Shared Psychophysiological Electroencephalographic Features in Maltreated Adolescent Siblings and Twins: A Case Report.

This case report presents a comprehensive assessment of four maltreated adolescents, two half-siblings, and two non-identical twins to investigate the effects of complex childhood trauma on brain functioning. The study aimed to identify shared psychophysiological features in the electroencephalographic (EEG) data of these adolescents compared to database norms. Quantitative EEG, event-related potentials (ERPs), and their independent components were analyzed to examine alterations in patterns of electrical activity associated with psychopathology. In the half-sibling pair, enhanced P1 and N1 amplitudes were observed during the cued Go/NoGo task, while reduced N2 amplitude was present in the fraternal twins. The type of trauma also seems to affect EEG spectral distribution and higher-order cognitive processes, such as attention allocation and response inhibition (N2 wave). Specifically, physically abused and bullied adolescents showed reduced N2 amplitudes and lower alpha power in the posterior region. No significant differences were noted in the ERP-independent components for maltreated adolescents compared to norms. The analysis of these cases aimed to provide insights into the neurobiological substrates underlying the overlapping symptoms and syndromes of child maltreatment, which may aid in differential diagnosis and the development of targeted interventions for trauma-related psychopathology in adolescents.

Predictive Dispatch of Volunteer First Responders: Algorithm Development and Validation.

BACKGROUND: Smartphone-based emergency response apps are increasingly being used to identify and dispatch volunteer first responders (VFRs) to medical emergencies to provide faster first aid, which is associated with better prognoses. Volunteers' availability and willingness to respond are uncertain, leading in recent studies to response rates of 17% to 47%. Dispatch algorithms that select volunteers based on their estimated time of arrival (ETA) without considering the likelihood of response may be suboptimal due to a large percentage of alerts wasted on VFRs with shorter ETA but a low likelihood of response, resulting in delays until a volunteer who will actually respond can be dispatched. OBJECTIVE: This study aims to improve the decision-making process of human emergency medical services dispatchers and autonomous dispatch algorithms by presenting a novel approach for predicting whether a VFR will respond to or ignore a given alert. METHODS: We developed and compared 4 analytical models to predict VFRs' response behaviors based on emergency event characteristics, volunteers' demographic data and previous experience, and condition-specific parameters. We tested these 4 models using 4 different algorithms applied on actual demographic and response data from a 12-month study of 112 VFRs who received 993 alerts to respond to 188 opioid overdose emergencies. Model 4 used an additional dynamically updated synthetic dichotomous variable, frequent responder, which reflects the responder's previous behavior. RESULTS: The highest accuracy (260/329, 79.1%) of prediction that a VFR will ignore an alert was achieved by 2 models that used events data, VFRs' demographic data, and their previous response experience, with slightly better overall accuracy (248/329, 75.4%) for model 4, which used the frequent responder indicator. Another model that used events data and VFRs' previous experience but did not use demographic data provided a high-accuracy prediction (277/329, 84.2%) of ignored alerts but a low-accuracy prediction (153/329, 46.5%) of responded alerts. The accuracy of the model that used events data only was unacceptably low. The J48 decision tree algorithm provided the best accuracy. CONCLUSIONS: VFR dispatch has evolved in the last decades, thanks to technological advances and a better understanding of VFR management. The dispatch of substitute responders is a common approach in VFR systems. Predicting the response behavior of candidate responders in advance of dispatch can allow any VFR system to choose the best possible response candidates based not only on ETA but also on the probability of actual response. The integration of the probability to respond into the dispatch algorithm constitutes a new generation of individual dispatch, making this one of the first studies to harness the power of predictive analytics for VFR dispatch. Our findings can help VFR network administrators in their continual efforts to improve the response times of their networks and to save lives.

Cognitive and Behavioral Factors Predicting the Decision to Vaccinate against COVID-19 in Clinical Psychiatric Population-A Cross-Sectional Survey.

The spread of the COVID-19 virus created more than a medical crisis, while it also negatively affected the mental health of the general population. This context increased the vulnerability of the psychiatric population. While research interest highly targeted vaccine hesitancy and acceptance, many studies focused on trust issues-both in vaccine efficacy and in communication with authorities. Less is known about the psychological underpinnings of the COVID vaccination decision, specifically in the high-uncertainty circumstances due to the novelty of the virus. In a cross-sectional study, we investigated the predictive value of several cognitive (perceived risk, vulnerability, uncertainty, and trust in one's decision) and behavioral (previous vaccinations, social media use, and practicing preventive behavior) factors, for the vaccination decision against COVID-19, for 252 psychiatric inpatients (data collected between September 2021 and February 2022). Demographics and diagnostics were also considered. We found a significant relationship between the "Perceived risk of vaccination" and the choice of vaccination (χ2(2, N = 252) = 58.59, p ≤ 0.001), and between the "Trust in own decision to vaccinate" and the decision to vaccinate (χ2(2, N = 252) = 31,5, p ≤ 0.001). The overall regression model was statistically significant (χ2 (9, N = 252) = 97.1, p < 0.001), with between 30% and 45% of the variance in the odds of a positive decision explained by the predictor set. The model coefficients analysis showed that an individual with a psychiatric disorder but with higher confidence in their decision had significant (p < 0.001) increased odds of the decision to vaccinate against COVID-19 by 893%. A former voluntary vaccination did not significantly associate with the decision to vaccinate against COVID-19 (χ2(1, N = 252) = 2.74, p > 0.05) in this special population. No other behavioral factors, diagnosis, or demographics were significant as predictors, for the clinical psychiatric population surveyed, except the educational level. Implications for future vaccination acceptance of this special population are discussed.

Resting-state frontal, frontlateral, and parietal alpha asymmetry:A pilot study examining relations with depressive disorder type and severity.

Introduction: The search for biomarkers has been central to efforts of improving clinical diagnosis and prognosis in psychopathology in the last decades. The main approach has been to validate biomarkers that could accurately discriminate between clinical diagnoses of very prevalent forms of psychopathology. One of the most popular electrophysiological markers proposed for discrimination in depressive disorders is the electroencephalography (EEG)-derived frontal alpha asymmetry. However, the validity, reliability and predictive value of this biomarker have been questioned in recent years, mainly due to conceptual and methodological heterogeneity. Methods: In the current non-experimental, correlational study we investigated relationship of resting-state EEG alpha asymmetry from multiple sites (frontal, frontolateral, and parietal) with different forms of depressive disorders (varying in type or severity), in a clinical sample. Results: Results showed that alpha asymmetry in the parietal (P3-P4) was significantly higher than in the frontal (F3-F4) and frontolateral sites (F7-F8). However, we did not find significant relations between alpha asymmetry indices and our depressive disorder measures, except for a moderate positive association between frontolateral alpha asymmetry (eyes-closed only) and depressive disorder severity (determined through clinical structured interview). We also found no significant differences in alpha asymmetry between participants, depending on their depression type. Discussion: Based on results, we propose the parietal and frontolateral asymmetry indices to form hypotheses that should not be abandoned in the depression markers research, but worth for further experimental research. Methodological and clinical implications of the current findings are discussed.

Health Navigator Perspectives on Implementation of Healthy Michigan Plan Work Requirements.

Importance: In 2020, Michigan Medicaid implemented a new work requirement policy for enrollees in the Healthy Michigan Plan (HMP), the state's expanded Medicaid program. Under the policy, enrollees would be required to report 80 hours of work or other qualifying activities each month or obtain an exemption to maintain health insurance coverage. Objective: To assess the experiences of health navigators (and beneficiaries by proxy) with the implementation of Michigan's Medicaid work requirement. Design Setting and Participants: This qualitative study included health navigators who participated in 11 focus groups from September to December 2020. Focus group questions addressed topics related to implementation and communication of the HMP work requirement policy. A survey was administered to capture background information, assess readiness to assist with navigation, and assess the quality of the state's communication about the policy. Main Outcomes and Measures: The main outcomes were general understanding of policy components, communications about the policy, navigation of the exemption process, navigation of the reporting process, and beneficiaries' ability to comply with the policy. Results: Of 50 health navigators who participated in the focus groups, 44 (88.0%) responded to the survey and 43 provided demographic information (mean [SD] age, 44.0 [10.5] years). All 43 had at least some college or vocational education, with 27 (62.8%) reporting a 4-year degree or higher, and they resided in geographic regions across Michigan. Navigators indicated that they felt prepared to assist HMP enrollees navigate work requirements. Communication to beneficiaries regarding the new policy was viewed as an improvement compared with traditional Medicaid communications. However, the complex policy was potentially difficult for beneficiaries to understand. Limited language options besides English created barriers for some enrollees. Exemptions were confusing for beneficiaries owing to the numerous categories and sometimes vague guidelines. Those who used the online reporting system generally found the platform to be user-friendly. Navigators expressed concern regarding HMP enrollees' ability to report compliance with work requirements owing to barriers with internet access, telephone access, language challenges, and computer literacy. Conclusions and Relevance: In this qualitative analysis of health navigators in Michigan, respondents reported overall positive feedback about many of the implementation and communication strategies, including human-centered design, automatic exemptions, and use of state administrative data to assess whether beneficiaries were in compliance with the policy; however, barriers to reporting remained for enrollees. The findings suggest that state agencies should seek to reduce administrative barriers and apply a human-centered design approach to alleviate risk of unnecessary loss of Medicaid benefits.

Decision-making by laypersons equipped with an emergency response smartphone app for opioid overdose.

BACKGROUND: Targeted naloxone distribution to potential lay responders increases the timeliness of overdose response and reduces mortality. Little is known, however, about the patterns of decision-making among overdose lay responders. This study explored heuristic decision-making among laypersons equipped with an emergency response smartphone app. METHODS: UnityPhilly, a smartphone app that connects lay responders equipped with naloxone to overdose victims, was piloted in Philadelphia from March 2019 to February 2020. Participants used the app to signal overdose alerts to peer app users and emergency medical services, or respond to alerts by arriving at overdose emergency sites. This study utilised in-depth interviews, background information, and app use data from a sample of 18 participants with varying histories of opioid use and levels of app use activity. RESULTS: The sample included 8 people who used opioids non-medically in the past 30 days and 10 people reporting no opioid misuse. Three prevailing, not mutually exclusive, heuristics were identified. The heuristic of unconditional signalling ("Always signal for help or backup") was used by 7 people who valued external assistance and used the app as a replacement for a 911 call; this group had the highest number of signalled alerts and on-scene appearances. Nine people, who expressed confidence in their ability to address an overdose themselves, followed a heuristic of conditional signalling ("Rescue, but only signal if necessary"); these participants had the highest frequency of prior naloxone administrations. Eleven participants used the heuristic of conditional responding ("Assess if I can make a difference"), addressing an alert if they carried naloxone, were nearby, or received a signal before dark hours. CONCLUSION: The deployment of specific heuristics was influenced by prior naloxone use and situational factors. Success of overdose prevention interventions assisted by digital technologies may depend on the involvement of people with diverse overdose rescue backgrounds.

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 12 May 2020. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.c.4878591.v1.

Acceptability of smartphone applications for facilitating layperson naloxone administration during opioid overdoses.

OBJECTIVE: We investigated user requirements for a smartphone application to coordinate layperson administration of naloxone during an opioid overdose. MATERIALS AND METHODS: We conducted interviews and focus groups with 19 nonmedical opioid users and other community members in the Kensington neighborhood of Philadelphia, Pennsylvania, which has one of the highest overdose rates in the country. Data were analyzed using thematic analysis. RESULTS: We found high levels of trust and reliance within one's own social group, especially nonmedical opioid users and members of the neighborhood. Participants distrusted outsiders, including professional responders, whom they perceived as uncaring and prejudiced. Participants expressed some concern over malicious use of a location-based application, such as theft when a victim is unconscious, but overall felt the benefits could outweigh the risks. Participants also trusted community-based organizations providing services such as bystander training and naloxone distribution, and felt that a smartphone application should be integrated into these services. DISCUSSION: Individuals affected by opioid use and overdose reacted positively to the concept for a smartphone application, which they perceived as a useful tool that could help combat the high rate of opioid overdose fatalities in their neighborhood. A sense of unity with others who have shared their experiences could be leveraged to connect willing bystanders with victims of overdose, but risk must be mitigated for layperson responders. CONCLUSION: Based on participant experiences with overdoses, trust-based considerations for the design of smartphone applications to facilitate layperson response will be critical for their adoption and use in real overdose situations.

Layperson reversal of opioid overdose supported by smartphone alert: A prospective observational cohort study.

BACKGROUND: Rapid naloxone administration is crucial in reversing an opioid overdose. We investigated whether equipping community members, including people who use opioids (PWUO), with a smartphone application enabling them to signal and respond to suspected overdose would support naloxone administration in advance of Emrgency Medical Services (EMS). METHODS: This observational cohort study of opioid overdose intervention used a dedicated smartphone app, UnityPhilly, activated by volunteers witnessing an overdose to signal other nearby volunteers in Philadelphia (March 2019 - February 2020). Alerted volunteers chose to respond, or declined to respond, or ignored/missed the alert. Witnessing volunteer was connected to 9-1-1 through a semi-automated telephone call. The primary outcome was layperson-initiated overdose reversal before EMS arrival, and a secondary outcome was hospital transfer. This study is registered with ClinicalTrials.gov, NCT03305497. FINDINGS: 112 volunteers, including 57 PWUO and 55 community members, signaled 291 suspected opioid overdose alerts. 89 (30⸱6%) were false alarms. For 202 true alerts, the rate of layperson initiated naloxone use was 36⸱6% (74/202 cases). Most naloxone-use cases occurred in the street (58⸱11% (43/74)) and some in home settings (22⸱98% (17/74)). The first naloxone dose was provided by a nearby volunteer responding to the alert in 29⸱73% (22/74) of cases and by the signaling volunteer in 70⸱27% (52/74) of cases. Successful reversal was reported in 95⸱9% (71/74) of cases. Layperson intervention preceded EMS by 5 min or more in 59⸱5% of cases. Recovery without hospital transport was reported in 52⸱7% (39/74) of cases. INTERPRETATION: Our findings support the benefits of equipping community members, potentially witnessing suspected opioid overdose, with naloxone and an emergency response community smartphone app, alerting EMS and nearby laypersons to provide additional naloxone. FUNDING: Funding provided by NIH through NIDA, grant number: 5R34DA044758.