Background: With evolving health care industry toward patient centered orientation, inputs from the patients' perspective is valuable. Improved patient satisfaction is associated with increased levels of adherence to treatment processes and recommended prevention, and improved health outcomes. Hence, this study was conducted to assess the current level of patient satisfaction and explore its determinants in the Suva Subdivision health centers, Fiji, 2018.Methods: This was a mixed method cross-sectional study employing both quantitative and qualitative designs. A random sample of 410 participants attending the outpatient services completed the self-administered structured questionnaire. The questionnaire focused on socio-demographic features, waiting time, doctors' communication, and patient trust. Data from 375 questionnaires (response rate of 91%) was analyzed in SPSS where descriptive analysis and univariate and multivariate logistic regression was done at 0.05 level of significance and 95% confidence interval to find the determinants of patient satisfaction. From these 375 participants, 20 participants were purposefully selected for audio recorded interview guided by a semi-structured questionnaire and data was analyzed using thematic analysis.Results: The majority of the patients were generally fully satisfied with their consultation (69.3%). Univariate logistic regression showed that age, gender, education level, waiting time, doctors' communication behavior, and patient trust level were significantly associated with patient satisfaction independently. After controlling for all the variables, gender, number of visits, waiting time, and patient trust were significantly associated with trust. Those who had full trust in the doctors, were more likely to be fully satisfied with their consultation  and those who got seen within 1 h, were more likely to be satisfied with their consultation . Though, the patients voiced that getting a satisfying consultation was worth the wait. The doctors' attitude and way of communication also made a difference to the patient's level of satisfaction.Conclusions: This study showed that patient satisfaction is positively associated with patient trust, doctors' interpersonal skills and communication behavior and negatively associated with waiting time. Hence, doctors upgrading their communication skills and health service managers strategizing ways to improve waiting time can contribute to better patient trust and thus lead to better patient satisfaction and positively influence health outcomes. The health care system has evolved over time with a shift from being a traditional concept of noble profession toward a customer-oriented service industry . ContribPatient satisfaction surveys has been used as a meaningful and essential tool for identifying gaps and developing effective strategies for quality improvements in health care industry . Given tPrice et al. in their literature review showed that improved patient satisfaction was associated with increased levels of adherence to treatment processes and recommended prevention, improved clinical outcomes, better patient safety within hospitals and less health care utilization . Biglu eDespite the increasing importance and research on patient trust, communication and patient satisfaction, there are limited studies done in Pacific Island Countries (PICs) on these subjects. This study was conducted with the purpose to assess the current perceived level of patient satisfaction in resource strained PIC, with Fiji being a representive and the factors associated with patient satisfaction. This study also tries to assess how strongly trust and communication are associated with patient satisfaction.This was a cross-sectional mixed method study employing both quantitative and qualitative designs using the concept of methodological triangulation . The quaFor the quantitative approach, the estimated sample size was calculated using 5% margin error and 95% confidence interval and 50% response distribution. With the use of these figures, the estimated sample size comes to 377. In view of non-response of 10%, the sample size came to 410 participants. To get the total of 410 participants, the number of patients selected from the three-individual health centers depended on the health centre's usual patient load. Participants were selected using systematic random sampling. The patients waiting to be consulted by the doctors in the outpatient department were approached. Every third person waiting to be seen was approached and those who were interested, and after reading the information sheet, those who were still willing to participate and meet the inclusion and exclusion criteria were selected to participate in the studies.Those who were over 18 years, any gender, any ethnic background, self-identified Fijians, and understood either English, Hindi, or Fijian were included in the study, while those not willing to participate or had some form of cognitive disorder were excluded from the study . The selected participants' details were listed down, and this list was used to select participants for the qualitative approach. This list was divided into 6 strata; male, female, I-Taukei, Indo-Fijian, 18–50 years, and more the 50 years of age. From these sub-groups, convenience sampling was used to select the participants for the in-depth interview. The total participants were 20; inclusive of 5 participants representing each sub-group.A structured questionnaire with close-ended questions was used for the quantitative design. The statements in this questionnaire have been already used in previous studies concerning trust, communication skills, and patient satisfaction –34. QuesThe questionnaire contained 4 sections; section 1 contained the socio-demographic information of the participant, section 2 contained 8 close-ended questions which were related to communication skills of the doctors, section 3 contained 10 close-ended questions which were related to patient trust in doctors, and section 4 contained 4 close-ended questions assessing patient satisfaction. Likert 5-point scoring scale was used for answering the questions; strongly agree, agree, not sure, disagree and strongly disagree. Strongly agree is allocated 5 points and regresses down to 1 point for strongly disagree for positive statement such as, “My doctor gave me opportunity to ask questions.” For negative statement such as, “I would prefer to get a second opinion from another doctor,” strongly agree is allocated 1 point and strongly disagree is allocated 5 points. The questionnaire was translated into two other languages; Fijian and Hindi using bilingual translators. Theses translated version were then translated back from Hindi and Fijian to English by different translators to ensure the contents of the original questionnaire matches the translated version .Though, the questionnaire was not tested for reliability before being used for the study, the reliability was tested, and the Cronbach alpha was calculated using this study sample (375 questionnaires). For the whole questionnaire, the Cronbach alpha score for the total of 22 items was 0.91. For section 2, with a total of 8 items, the Cronbach alpha score was 0.76, for section 3 with 10 items was 0.759, and section 4 with 4 items was 0.81. Standardized open-ended audio recorded interview was conducted which was 30–40 min long per interview. The interview was guided by a semi-structured questionnaire that used 8 open-ended questions which focused on participants opinion and feelings about trust in doctors, reasoning behind their trust and satisfaction with the consultation.The quantitative raw data from the questionnaire was entered into excel and after data cleaning, was transferred into IBM SPSS, version 21. Descriptive analysis  was done for the socio demographic variables, waiting time, communication behavior, trust, and patient satisfaction. For inferential analysis, logistic regression was carried out as the variables did not have a linear relationship. Hence, the variables, patient satisfaction, communication behavior, trust, and age were converted into categorical variables whereas the others were already categorical variables. All the statements were scored depending on the participants' choice for sections 2–4.The maximum score of 5 points and minimum score of 1 point. Communication behavior was categorized as “Good communication behavior (32–40 points),” “Fair communication behavior (17–31 points),” and “Poor communication behavior (8–16 points).” Patient Trust was categorized as “Full trust (40–50 points),” “Partial trust (21–39 points),” and “Lack of trust (10–20 points).” Patient satisfaction was categorized as “Full satisfaction” (16–20 points), “Partial satisfaction” (9–15 points), “No satisfaction” (4–8 points). For age, the cutoff was taken at 50 years of age as this was 1 standard deviation from the mean age. For waiting time as well, it was grouped into ≤1 h and more than 1 h . As the facilities in the study are aiming to limit their maximum waiting time of 1 h, the cutoff waiting time was taken at 1 h.p-values. After the completion of the interview, all the audio recorded information was transcribed into a word document. Audio recording was heard three times and transcribed data was corrected accordingly. The final transcribed data were then analyzed using manual thematic analysis. Thematic analysis was guided by a 6 -phase guide framework by Braun and Clarke  and d Clarke . The datAs summarized in As seen in The mean score for patient trust was 38 points (±5). The minimum score was 20 points with highest score of 50 points. Majority of the participants had partial trust in their doctors (61.1%), followed by full trust (38.4%) and lack of trust (0.5%). The mean score for patient satisfaction with their consultation was 16 points (±3). The minimum score was 5 points with maximum score of 20 points. More than two thirds (69.3%) of the participants were fully satisfied with the consultation, 28.3% were partially satisfied, and 2.4% were not satisfied with their consultation.There were 4 statements used to assess patient satisfaction. As For patient satisfaction, 84.7% of those over 50 years were fully satisfied with their consultation as summarized in For inferential analysis, the univariate logistic regression findings are summarized in r = 0.67), hence communication behavior was also removed from the logistic regression. After controlling the variables, only gender, number of visits, waiting time and level of patient trust had significant association with patient satisfaction at 0.05 level of significance. While males and those coming to the health center for first time were less satisfied with their consultation, those who got seen with 1 h and those who had full trust in their doctors were more likely to be satisfied with their consultation.Stepwise backward selection was used to get the final logistic regression, as summarized in p = 0.224) tells us that this model fit well. The ROC curve area was 0.806 and this tells us that this model was accurate in predicting patient satisfaction.This logistic regression equation had Nagelkerke R square of 0.368, hence explained 36.8% of the variance in the data. Hosmer and Lemeshow test . While another 59 years old i-Taukei male said, “I feel comfortable, they are not harsh or rough with you… they do their part.” Some patients appreciated the way they were welcomed by the doctors and their tone when they talk. “The way doctors' approach me…uhm and the way they talk and their tone matters” . “Their first expression… the way they look and greet…I feel happy” . One patient even felt that some doctors go out of their way to make them feel comfortable during the consultation. “I'll say probably he had treated me as a person… he left his level of being a doctor and explained to me as a lay person, cared for me… I was comfortable” . While majority had appreciated the doctor's attitude, few experienced the opposite from their doctors which lead to dissatisfaction with their consultation. The doctor was rude to them and did not talk or explain nicely to them.When talking about their consultation encounter, the doctors' communication behavior was mentioned in either a positive or negative way together with the doctor's attitude and how the doctors treated them. During their consultation, for majority patients, the attitude of the doctors did carry weight. When the doctors were nice to the them, talked in normal tone, their politeness and not sounding harsh or telling off patients, the patients were happier with their consultation. “…the doctor was rude, just saw, wrote the prescription… just sitting and didn't ask” . Patients felt frustrated and dissatisfied when they encounter an arrogant doctor. Those who didn't interact much with the patients and personality stands out as stubborn, were not liked or appreciated by the patients. “Felt angry as doctor didn't explain or examine… couldn't ask because of fear… looked bit stubborn doctor” .“It was a good experience with doctors…I trust the doctor… the way they talk is good, I could ask them, the doctors and nurses are asking things and cared about my need and explained.” Patients indirectly highlighted the importance of communication and trust when it comes to understanding the patients. “I trust the doctors because of how they have treated me…. Doctor says morning to me. The face was welcoming, and I feel free to talk to the doctor” .Majority patients appreciated the fact when the doctors treated them as an individual person rather than some patient with a complain. When doctor put in effort to engage patients into conversation with an attempt to understand the patient, patients seemed to be more satisfied with their consultation. The doctors listened and understood what the patients concern was regarding their health. One of the participants, 48 years old Indo-Fijian male stated, “They respect your opinion… they gave me time to ask the questions and I asked them more questions” . While another participant, 51 years old, i-Taukei female stated, “Yes, they discuss the treatment with me, explained the side effects and asked if I was allergic to any medicine.” Some patients mentioned that they were not involved during the consultation process but would have appreciated if it was done. Sometimes it is difficult for patients to share all information with the nurse which they would rather share with the doctors. “…most questions have been asked by the nurse, not by doctor. Nurse just gives, and doctor reads it. She can read and ask again, it's a follow up questions… sometimes you can say different thing to nurse” as stated by 43 years, i-Taukei male.Patients showed importance to the fact that doctors involve them in the conversation and in the management plan and let patients ask questions as well. “I asked them to give me the medicine from another IV site, but they didn't listen at XXX (name of HC deleted) …my hand got swollen” . Also, in-terms of understanding the patient in context of their financial state, few patients showed disappointment as they were not informed about the medicine and the doctor didn't care to inform them that they had to buy the medicine, as some patients might not afford to buy the medicine. Thirty years old i-Taukei male stated, “The medicine was not here, and I have to buy the medicine. He (the doctor) never ask and told that I need to buy it. I would appreciate if the doctor can ask.”In contrast, when patients were not involved in the treatment plan or their views and opinions were not considered by the doctors, they were some wort disappointed. “The 100% is how they perform when they explain the sickness to you, the right medication and what it can do and the side effects.” Just with proper communication and explaining things well to the patient, it gets rid of their anxiety and frustration. “In the beginning, I am bit scared but when I enter the room and the way the doctor greets me, I can understand that I can be comfortable with this doctor” .Most of the time patients have lot of questions in their mind concerning their sickness and health and only when all this questions and doubts are answered and cleared, then only they have the total satisfaction with their consultation. This was evident from statement by a participant, 59 years i-Taukei male, “…. the way they saw me and explained me and of course they are doctors, I trust that person. My doctor saw me well…” .Together with communication, trust was also linked to them being satisfied with the explanation and consultation. Knowing that medical information is readily available over internet, it can sometimes be a challenge to explain things to patients when they come in with incomplete information on a particular issue in their mind. As highlighted from by this thematic analysis, if the doctor communicates effectively with their patients and are able to gain patients trust, patients are convinced with the explanation provided. A 42 years old Indo-Fijian male stated, “…but at times might not be all the information that I needed. Sometimes the doctors don't explain well, depends on the doctors…” . Also, as mentioned, when the doctors don't engage patients into conversation and provided little or no information concerning their sickness, those patients were neither satisfied with their consultation nor trusted the doctor was giving them the right management. “…the doctor was rude, just saw, wrote the prescription… just sitting and didn't ask anything…I was also afraid to ask. I am not sure whether I should take the medicine or not” .For those who were expecting the doctor to provide them more information concerning their health, they showed disappointment when they were not provided with all the information. “…. Patient get sick with long waiting time…. I would prefer better consultation then shorter waiting time” . Participants were more satisfied when then had a good consultation despite the long wait. A 35 years old i-Taukei male stated, “If the consultation is good, then it is worth waiting…” It was also noted that for some, the long waiting time was a routine, and they did not expect anything better. “…No, the waiting time does not affect me, if your mindset is ok, you can see the big crowd here…you have to be patience” as stated by a 59 years old i-Taukei Male.Participants did point out the fact that the waiting time was long, and they would appreciate if it would be lesser. For majority patients, they would be more satisfied if they had a good consultation and shorter waiting time. Though when asked as to whether they would prefer a shorter waiting time with shorter incomplete consultation or a proper consultation despite waiting bit longer, participants proper consultation was more important than a shorter waiting time. “This study's finding revealed that for a PIC like Fiji, age, gender, education level, waiting time, doctors' communication behavior and patient trust level were significantly associated with patient satisfaction independently. It was also noted that doctors' communication behavior positively affected patient trust as well. After adjusting for all the variables, gender of patient, number of visits to the health center, waiting time and patient trust were significantly associated with patient satisfaction. From all these factors, patient trust and doctors' communication behavior and waiting time were more strongly associated with patient satisfaction independently. Like Jaipul and Rosenthal's study finding which showed that those older age groups till 60 years were more satisfied with their consultation than the younger population, this study also showed the same . This maFemales were more likely to be fully satisfied with their consultation than males This finding differed from the findings of a study carried out by Weisman et al. which showed that there were no major gender differences in satisfaction . Again, Those who visited the HC more than three times were more likely to be fully satisfied than those who came for the first time. A study conducted in South Korea did show that frequency of visit did have a significant effect on patient satisfaction . Though This study also showed that those who waited less than an hour, were more likely to be fully satisfied than those who had to wait longer than 1 h. This finding was similar to previous studies done , 39, 40.Those who had full trust in doctors were more likely to be fully satisfied with their consultation. This finding is similar to previous studies done , 41–43. This may be due to the fact that those who had full trust also had doctors with good communication behavior, hence the patients are likely to have understood about their health problem and management would have been in accord, resulting in a high chance of satisfaction. A study conducted by Platonova et al. also showed that patient trust and good interpersonal relationships with the primary care physician are major predictors of patient satisfaction . InterpeClever et al. conducted a study to find the relationship between physician's communication behavior and patients' overall satisfaction with hospital care showed a significant positive relationship between overall ratings of attendings' communication behaviors and overall satisfaction . SimilarThe present review has several limitations. Though, the patients were selected using random sampling, they were only selected upon their will. Hence, this would have introduced self-selection bias. There might have been a possibility of acquiescence bias as the qualitative questionnaire used both negative and positive statements, as evident from a few of the completed forms. Though, the name of the participants was not revealed, the participants did fill in their name in the questionnaire. Hence, there is a possibility of social desirability bias as well. The quantitative questionnaire did not capture the financial status of the participants and the gender of the doctors and this might have affected the results slightly as studies have shown that socioeconomic status affects patient trust and satisfaction , 45. TheBuilding better trust with proper communication helps in improving patient satisfaction with the consultation and treatment provided and this in turn improves treatment adherence and better health outcomes. This study has shown that currently two thirds of the Suva sub-divisional health center utilizers are fully satisfied with their consultation. There are several factors associated with patient satisfaction individually, such as age, gender, education level, number of visits, waiting time, communication behavior, and interpersonal skills of doctors and patient trust. In concordance with other countries globally, patient trust, waiting time, and communication behavior and interpersonal skills of the doctors had similar relation to patient satisfaction in PIC, Fiji. Some of these are modifiable, such as communication, trust and waiting time, while some are not. Therefore, it would be recommended for health service managers to upgrade their staffs' communication skills and come up with strategies to lessen the waiting time. This study suggest that's patient satisfaction can be used as an indirect measure of health outcomes either subjectively or objectively, though, it would be recommended for further studies to be carried out to better understand the link between patient satisfaction and health outcomes with direct measurement of clinical health outcomes.Ethics approval was granted by the Fiji National University College Health Research Ethics Committee (CHREC) and from the Fiji National Research Ethics Review Committee (FNRERC). Participants were only recruited upon written consent was obtained.All authors took part in the design of the study. SC drafted the manuscript with input from all authors. Research proposal was guided by MM and PW. The data was collected and analyzed by SC and revised by MM and PW. All authors participated in the preparation and approved the final manuscript for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Planctomycetes phylum display “nucleus-like compartmentation” is based on an outdated interpretation of the planctomycetal cell plan (Fuerst and Sagulenko, In the manuscript “Manifold Routes to a Nucleus”, Hendrickson and Poole question the assumption that the evolution of nuclear compartmentalization has been a singular event. They provide interesting observations on jumbophages and newly described archaea. However, their claim that bacteria from the Gemmata obscuriglobus harbors a bacterial “nucleus” (Fuerst and Webb, Planctomycetes were thought to share similarities with bacteria and eukaryotes alike [Planctomycetes was considered to be compartmentalized by an intracytoplasmic membrane (Lindsay et al., Planctomycetes were believed to lack a peptidoglycan sacculus and their outermost membrane was suggested to be the cytoplasmic one and to be surrounded by a proteinaceous cell wall instead (König et al., Planctomycetes are “beyond the bacterium” (Fuerst and Sagulenko, The concept of a nuclear structure outside the eukaryotes was introduced in 1991, when Fuerst and Webb postulated that the planctomycetal species Planctomycetes possess a peptidoglycan cell wall (G. obscuriglobus cell revealed interconnections of all previously suggested compartments, including the nucleus-like structure (Santarella-Mellwig et al., Planctomycetes in a comprehensive study involving mutagenesis and state-of-the-art microscopic techniques and demonstrated that canonical Planctomycetes are a variation of, but not an exception to, the Gram-negative cell plan (Devos, Planctomycetes. However, unusual large pores known as crateriform structures are found in the planctomycetal outer membrane (Planctomycetes (Wiegand et al., However, the concept of the planctomycetal cell plane evolved . Others ell wall  and the n Devos, . Most imn Devos, . Consequmembrane . Such stHowever, we do acknowledge that one aspect of the potential planctomycetal “compartmentalization” requires further investigation: one branch of the phylum, the one of the anammox bacteria, was shown to contain a separated subcellular compartment, the anammoxosome (Neumann et al., Regarding the main aspect of their article “Manifold Routes to a Nucleus,” Hendrickson and Poole unfortunately do not mention most of the above discussed articles (Speth et al., Planctomycetes and the extended PVC superphylum is still a relevant model for endomembrane formation—maybe related to DNA protection—and in any case for cell organization and complexity.Despite the absence of a nucleus-like structure, the phylum All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


VR consists of a three-dimensional, computer-generated environment viewed through a head-mounted display. This medium has provided new possibilities to adapt problematic behaviors that affect mental health. VR is no longer unaffordable for individuals, and with mobile phone technology being able to track movements and project images through mobile head-mounted devices, VR is now a mobile tool that can be used at work, home, or on the move.In line with recent advances in technology, in this review, we aimed to critically assess the current state of research surrounding mental health.We compiled a table of 82 studies that made use of head-mounted devices in their interventions.Our review demonstrated that VR is effective in provoking realistic reactions to feared stimuli, particularly for anxiety; moreover, it proved that the immersive nature of VR is an ideal fit for the management of pain. However, the lack of studies surrounding depression and stress highlight the literature gaps that still exist.Virtual environments that promote positive stimuli combined with health knowledge could prove to be a valuable tool for public health and mental health. The current state of research highlights the importance of the nature and content of VR interventions for improved mental health. While future research should look to incorporate more mobile forms of VR, a more rigorous reporting of VR and computer hardware and software may help us understand the relationship (if any) between increased specifications and the efficacy of treatment. Virtual reality (VR) is emerging as one of the key new technological tools in a digital revolution sweeping across the health care industry. Immersive VR allows users to interact with a computer-generated world, where the users natural sensory perceptions are replaced with a digital three-dimensional 3D) alternative . To creaD alternaEvidently, VR is a rapidly emerging field of research. Since 2016, new HMDs from Oculus, HTC, HP, Acer, Dell, and Sony and the arrival of a range of cheaper mobile phone alternatives have acted as a catalyst for a new wave of VR research. Despite recent investment in Oculus by Facebook, indicating VR is here to stay, its popularity among consumers is unlikely to affect the quantity of research around it. VR research has been continuously expanding in a time where it has not been at the forefront of digital consumerism. Oculus’ chief scientist Michael Abrash has suggested that in the next 5 years, we will see a new generation of VR products, which will operate with 4k screen resolution and with eye tracking that may allow for foveated rendering . This prIn this review, we aim to critically assess the current state of head-mounted VR research in relation to mental health. By doing so, we look to determine which conditions are more susceptible to VR interventions, which conditions need more attention, and in what form VR interventions are most effective. Our secondary aim is to understand more about VR used over the past 5 years and compare it to the new generation of VR in terms of accessibility and specifications. As there are indications that VR HMDs can be used at home as a self-help resource to provide a valuable tool for public health, in this review, we will assess head-mounted VR health research to date to determine whether this has been tested.HMD specifications are categorized into FoV, image resolution, and refresh rate (Hz). FoV refers to the view or surroundings a human can see without any eye movement. The human eye has a rotating FoV of up to 270° ; newer HWe used a useful definition of mental health from a mental health foundation that defined it as:A state of well-being in which the individual realises his or her own abilities, can cope with normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community.The World Health Organization acknowledges that positive mental well-being is rooted within mental health; this state of well-being allows an individual to lead a fulfilling and productive life . In thisHealth care and VR first met in the 1990s as a simulation tool for colonoscopy and upper gastrointestinal tract endoscopy simulation within medical education . VR woulNarrative syntheses were conducted on VR studies that were pertinent to areas of mental health . The litWe set an inclusion timeframe from January 2012 to July 2017. A 5-year period was seen as sufficient enough to reflect the current state of the technology; this would allow us to assess studies that used both the new generation of HMDs and a range of older HMDs that have been in academia for the past decade. In line with this, studies were only included if they used an HMD. This meant excluding studies that used Cave Automatic Virtual Environment, the Computer-Assisted Rehabilitation Environment, and other projector systems without an HMD. As we focused on the systems used, if authors failed to disclose the type of VR used, or stated they used an HMD but provided no further information regarding its model or specifications, the study was excluded. Studies involving the use of two-dimensional (2D) virtual environments such as those seen in Second Life were excluded. Furthermore, augmented reality studies were not included as although augmented images are computer generated, the environment itself is not. Future VR may well feature an augmented experience within it ; howeverMental health conditions were categorized as behavioral conditions that showed the potential to be modified upon intervention. In accordance with the International Statistical Classification of Diseases and Related Health Problems , we wereThe search strategy implemented in this review was conducted in 5 stages.Key reviews in the area were identified; these contained broad mental health VR reviews to more condition-specific reviews.The results and reference lists of these reviews were scanned to make an initial list of suitable studies.Our own searchers were then carried out to identify any missed and more recent studies. The terms searched were: [“Virtual”] AND [“mental health” OR “well-being”]. This was followed with more condition-specific searches: [“Virtual”] AND [“Anxiety” OR “Social Anxiety” OR “Phobia” OR “Agoraphobia” OR “Arachnophobia” OR “Fear” OR “PTSD” OR “Depression” OR “Depress” OR “Stress” OR “Abuse” OR “Addiction” OR “pain” OR “Substance” OR “Eating” OR “Disorder” OR “Sleep” OR “Body Image” OR “Body” OR “sexual” OR “Dysfunction”]. Searches were conducted within “MEDLINE,” “Journal of Medical Internet Research,” “PsychINFO,” “Google Scholar,” and “Science Direct.”Screening was carried out upon the completion of a comprehensive list of studies. At this stage, studies were excluded based on publication date, condition type, and lack of immersive VR.The full texts of remaining articles were then assessed to find further reason for exclusion; at this stage, studies were typically excluded for not using an HMD or failing to disclose the type of VR used.A full list of identified studies can be found in The following findings have been compiled from 81 studies that used HMDs in interventions related to mental health; 18 HMDs appeared across six different areas of mental health. The eMagin z800 (n=34) was the most commonly used form of HMD appearing 34 times . At the in vivo exposure [in vivo exposure, although in some cases, the latter was slightly more effective [VR has been used as a form of exposure treatment (VRET). Its uses include the following conditions: social anxiety disorder -31; PTSDexposure , while oexposure . The conexposure ,33,40. Sexposure  for thosffective . A similffective  finding ffective  found thffective , and it ffective  and diagffective .VR has been used as a distraction tool for pain management. Different forms of VR distractions have been used for burn wound pain -47, phanin vivo TSST. Finally, VR-based mindfulness apps may also prove to have a positive effect on stress [Stress was the primary target and depression the secondary in Shah et al’s VR mood induction procedure study . That stn stress .We identified only one intervention that had depression as the primary target . PatientStudies on eating disorders included those on body image disturbance (BID) ,66, anorHMDs have been used to deliver exposure therapy to help treat tobacco addiction. Four studies investigated tobacco addiction -71; one This review confirms that HMDs have been used to treat mental health in different ways. VRET was one type of intervention that was consistently used across different conditions. VRET interventions with and without CBT content have been implemented for therapy of anxiety, PTSD, stress, eating disorders, and substance addiction. VR excels in its advantage of being able to draw on both audio and interactive visual stimuli, making the fearful stimuli appear as real as possible. In addition, CBT delivered in VR has shown consistent positive results; the accurate adaption of relevant stimuli allows CBT to pinpoint troublesome behaviors. The merging of VR and mobile phones is a timely collaboration, and stress management apps for mobile phones have been described as “incremental acquisitions” to cope with daily-life stresses . The relLindstrom  highlighThe success of VR in the treatment of anorexia- and depression-focused embodiment studies ,36 highlThe state of research suggests that VR cannot be a clinical tool itself and, instead, its success relies on the content it provides a platform for. Complex VR systems backed by PCs with high graphical and processing power to build detailed and adaptable environments allow the content of the intervention to be complemented further. The most common HMD was the eMagin z800, which in the UK is not an accessible product. In public health context, it is imperative that commonly sold HMDs are used with VR apps that can be used for self-help and to promote health. This review points to VR as a useful method of modifying the behavior in an effort to enhance mental health; the challenge now is to apply this to accessible products, which the public can use at home, work, and on the move.The results of this review suggest the potential efficacy of VR to provide a platform for improved mental health. VR has demonstrated some compatibility with proven psychological interventions, but combined, they illustrate a potential for a real positive behavior change for a range of mental health conditions. The current state of research does not illustrate VR’s ability to improve mental health on its own; instead, it highlights the importance of the condition-oriented content within VR interventions.However, the specifications of HMDs and the computers that power them are still important when trying to improve mental health using VR. Although increases in FoV have brought us closer to FoV of the human eye, an improved FPS may decrease the chances of motion sickness for some users. Currently, VR’s strengths are being used for exposure therapy, as successful interventions in the treatment of anxiety, phobias, and PTSD have been demonstrated. In addition, VR-induced distraction has proven to be a remarkable development in pain management. The lack of studies surrounding stress and depression, despite positive initial outcomes, highlights VR’s infancy in some areas of mental health. To help understand more about the relationship between VR systems and its efficacy as a mental health tool, we recommend a thorough reporting of HMD and computer specifications. Finally, there is a need to design interventions that make the most of VR’s increasing mobility, as self-help VR tools could prove to be a valuable asset for mental health services. Thus, researchers must make the most of a rapidly developing medium that is seeing advances in equipment; this will act as a catalyst to develop increasingly detailed and novel interventions that push the boundaries of virtual presence. By achieving this, VR has the potential to radically change the way we modify problematic behaviors that affect our mental health.


The intergenerational transmission of traditional language and culture is at the core of Yolŋu Indigenous knowledge practices. The homeland of Gäwa in remote Arnhem Land, Northern Territory, was established by Warramiri clan kinship networks to provide an appropriate place for this crucial role to continue. Technologies have long played a part in this transmission process, but can databases, websites and other digital storage mediums harmonise with existing Yolŋu epistemological and ontological frameworks? In considering an alternative approach to digital development, we rely on the Yolŋu elements of performative epistemology, multiple perspectives and a fundamental, narrative base. We then apply this approach to the construction of the ‘Warramiri website’ (2011–2015) which houses and structures various resources, outlining its applicability to the current educational practices at Gäwa. From 2011 to 2015, Kathy Guthadjaka and Ben van Gelderen worked collaboratively on creating the ‘Warramiri Website’. Warramiri is the name of one of the ‘clans’ and language groups of the Yolŋu Indigenous people of North-east Arnhem Land, Northern Territory. Although spread out across this area in various townships, around 40–50 Warramiri members now live at Gäwa, a small, very remote homeland at the tip of Elcho Island. Gäwa was established by Kathy Guthadjaka and her kinship network in the 1980s, literally returning to country by cutting a road through the bush, establishing water supplies and houses, running school classes and eventually, permanently settling there. It is a remarkable story of vision, resilience and Indigenous self-determination  and then briefly share the creation of the Warramiri website as a problematised and ongoing application of this theoretical framework.interests and the browsing structure’ ;Cost-effective (given the poverty of many communities);Allowing for diversity of communities and cultural evolution over time;Able to be placed outdoors at the locus of creative practice;Providing community control over contents and over design, development, implementation and maintenance  pastoralists and missionaries . Lastly, a digital resource was felt to be particularly needed at Gäwa for there were many times when neither Kathy Guthadjaka nor any other Warramiri speaker was available for ‘team teaching’ in the senior classroom, so a digital bank of resources which the mainstream, balanda teacher could continue with, at least in some way, was seen as a preferable option than having no Warramiri language and culture input during these times.At Gäwa, there were a few other issues which also led us to think that developing the Warramiri website was appropriate. Firstly, as mentioned, many of the resources were old and were in forms such as audio cassette tapes that were deteriorating and/or were no longer readily utilised. There were scores of hours of audio-recordings of Warramiri elders (mostly passed away), so if those tapes were irreparably damaged the information would be lost forever, and in 10 years time, would there even be cassette players available? Secondly, Kathy Guthadjaka had an array of resources on her trusty Macintosh, but they were filed according to memory only, and though new and amazing resources were consistently conjured up for class use that perfectly suited the unit being studied, in terms of developing a In the Yolngu world it is not so much the case that every reality has an inherent structure, but rather that every structure can be seen to inhere in a whole range of realities…the world in this sense could be seen to be endlessly structurable and humans use language to re-construct what is always a human meaning, using the lines and webs of connectedness and the names created and handed down by the ancestors to render our experiences meaningful in human terms Christie , p. 27.However, Christie also notes a large array of pitfalls in the use of digital technologies. A fundamental notion is that collections of resources require a certain structuring, ordering and prioritising that is inconsistent with Yolŋu epistemology and ontology. Established as an overriding position, the rub of the problem is that:any person at any time.This quote opens up two major issues for consideration. Firstly, by imposing a structure on the website, or database, immediately other structures are precluded, which, in their right time and place are just as valid for Yolŋu knowldege transmission. Furthermore, the process of ordering or using of metadata to identify and recall information under search parameters actually becomes a process of codifying that particular view of reality. As a form of reading-back-reality, or ‘reverse bootstrapping’ Christie , we can represent the world, but ‘talking, singing, crying, dancing and painting all actively participate in the creation of new worlds as they have always done since the ancestors first talked, sang and danced the world into existence’ . It may also mean creating the resource to serve a particular educational purpose or function, not something to be available online ‘forever’. In other words, designers should start with the ‘Christie , p. 10.garma. This term is now well known as the name of the annual Yolŋu conference/festival which attracts considerable artistic and political interest both throughout Australia and internationally. But originally, the term garma was connected to the Yirrkala ‘Bothways’ curriculum of the 1980s, where it was used to define the intercultural interplay between ‘western’ and Yolŋu education systems being developed at the school  linkages among these performances’  space that was the ‘senior’ class, only for them to fall back into her own filing system of multisaved entries (as opposed to categories) to be considered for use in another future knowledge-production instance. Perhaps, if we had read all of the work Christie and others had compiled connected to Warramiri in a specific way, often in the yothu-yindi or märi-gutharra inter-clan kinship relationship  around the seasonal cycle, but students would study deeper (‘inside’) and more literate Warramiri resources as they grew older and were deemed ready by the Elders. In this way, the site could function as a kind of simulacrum of the traditional Indigenous cyclical enculturation process into maturity.As the seasonal approach to the website gathered momentum and we worked on ‘positioning’ various resources into the framework, it became clear that if it were truly to function as the foundation for the school’s curriculum, we also needed a variety of texts, at various literate and visual levels, to accommodate the students ranging from age 5 to 15 who attended school. In a sense then, we put something of a twist on Christie’s criteria of multiple perspectives. Where he had imagined a virtual garma where connected but specific clan (and other) identities were showcased after negotiation, as the Warramiri site was more concerned with older notion of garma; the symbol of the Bothways curriculum of intercultural interplay between Yolŋu and mainstream educational priorities. In 2013, a fine example of this occurred when, using the seasonal template, a combined unit was designed around the Macassan visits to Warramiri land arriving on the ‘Northwind’ with associated stories and information around specific sites, plants, words and ceremonies introduced. But the unit also explicitly linked with the new History: Year 4 component of the Australian Curriculum, where students learn of ‘the diversity of Aboriginal and Torres Strait Islander Peoples, their connection to place… and their contact with other societies’, specifically being referred to ‘the trade between the Macassans and the Yolngu people’ in the Knowledge and Understanding content descriptor ACHASSK086  at the start of the following school year, a connected but more in-depth literate unit involving the ancestral dog Djuranydjura could be studied which also involved Macassan stories, songs and excursions to local ‘sacred’ sites with the potential for ‘inside’ sessions led by elders . Or perhaps the focus could turn to some of the digital audio files which sit under the Mayaltha season that focus on the new growth of plants and fruits and dangers  of the stone fish and stingray in the muddy waters. The ultimate point is that there are a number of resources and layers within each season and decisions on which area to emphasise can be negotiated with Elders and school teachers together. Crucially, through such an ‘overlearning’ cycle, the Warramiri children will progress in ‘language and culture’ as the seasons and years turn  to use the site to learn something of Yolŋu history and culture. However, as the site progressed and a number of sad events also impacted on the Gäwa community, overall trust deteriorated that outsiders would not appropriate the images and video/sound files on the site for their own purposes. In the end, in 2016, a password was added to the site as protection. Indeed, like Christie, we found that ‘processes of exclusion are as important as those of sharing in the work of keeping land and culture strong’ , then they learn the Yolŋu way. It must be there, on their own land. Yes, there, on their own land (Gäwa), not on somebody else’s land. The school is at home, it’s all home. They learn Yolŋu way, the culture at ‘home’. It is all the same, it is home. Home, home, home…The last of Christie’s elements for an alternative Indigenous epistemology regarding digital learning focussed on how the narrative foundation of knowledge production must remain at the fore. His solution was to do away with virtually all the metadata or structure to allow users to create their own connections; to create local, ever-changing, specific narratives. As has been discussed, we instead chose to utilise the seasonal cycle as a structure, attempting to align with the holistic life at Gäwa. However, it soon became apparent that many of the resources did not neatly fit in to any of the season segments. There were many interconnected stories and songs, tracing ancestral movements across land, connecting to significant totemic characters and items. As part of the broader Warramiri website project, we also undertook whole-of-community consultation around ‘two-way’ education at Gäwa, in an attempt to clarify appropriate local pedagogies when it came to Warramiri/Djambarrpuyŋu/English usage as well as learning styles, team teaching, intercultural curriculum, etc.  and thus, naming and knowing land is of utmost importance (van Gelderen Profoundly expressed here, similar place-based, on country sentiments came through in virtually every interview, and community members also spoke about other traditional Warramiri sites on the mainland at Dholtji and Maṯamaṯa and islands through the Wessels. Ben van Gelderen’s notes from later that night were: balanda researcher collaborating with a Yolŋu elder over a number of years, to preserve and document her particular clan languages, history and seasonal life-cycles, all as a legacy for the future generations.However, the season focus was still present and practically within the site, a majority of the visual resources were still housed within these pages. In this sense, the site was akin to the beautifully presented ‘Yan-nhangu Atlas’ which was the culmination of a long-standing project in the homelands of the Crocodile Islands, similar in many ways to our own project; interested The Warramiri website had a long gestation period, but this is something we are proud of. We intentionally wished to ‘work slowly and allow new ideas and practices to emerge here and how, and grow slowly through mutual respect and a history of shared experience’ Christie , p. 32.


Large survey databases for aging-related analysis are often examined to discover key factors that affect a dependent variable of interest. Typically, this analysis is performed with methods assuming linear dependencies between variables. Such assumptions however do not hold in many cases, wherein data are linked by way of non-linear dependencies. This in turn requires applications of analytic methods, which are more accurate in identifying potentially non-linear dependencies. Here, we objectively compared the feature selection performance of several frequently-used linear selection methods and three non-linear selection methods in the context of large survey data. These methods were assessed using both synthetic and real-world datasets, wherein relationships between the features and dependent variables were known in advance. In contrast to linear methods, we found that the non-linear methods offered better overall feature selection performance than linear methods in all usage conditions. Moreover, the performance of the non-linear methods was more stable, being unaffected by the inclusion or exclusion of variables from the datasets. These properties make non-linear feature selection methods a potentially preferable tool for both hypothesis-driven and exploratory analyses for aging-related datasets. Within the field of statistical gerontology, there has been increasing use of large databases to explore relationships between key factorsand some outcome variable(s) of interest (dependent variable(s)). Indeed, several survey initiatives have been set up to track the biological, social and lifestyle factors that affect health and quality of life throughout the lifespan, i.e.Health and Retirement Study , WisconsHowever, the use of these datasets presents some significant challenges if they are to be used optimally to provide us with convincing results, strong evidence, and useful information. For example, it is important that researchers identify and only use variables within a database that are relevant to the outcome in question. Typically, quantitativeanalysiswithin gerontology has used linear methods as a means of simplifying data and identifying relevant variables–8.Howevefeatures). Given their size and complexity, it is not usually practical for researchers to assess how all factors within a database interact to determine an outcome of interest . Instead, researchers will often select a handful of features and assess the predictive ability of these features using a variant of regression such as linear regression. Unfortunately, both of these operations—feature selection and prediction—are potentially problematic for the analysis of many large survey databases. Here, we outline two major issues inherent to this analytic technique and offer an alternative approach, which may be better suited for the analysis of data within these survey databases, when it is reasonable to assume non-linear relationships.It is not uncommon for large survey databases to store dozens or hundreds of different measurements for each person , along with other features that they believe may confound the results (e.g. education level), and ignore all other, presumably irrelevant features.Although this practice is employed frequently , ranks all features on this measure, and rejects features that fall below a cut-off criterion. Filter methods are by far the least computationally demanding method, because they operate on each feature individually and ignore dependencies between them. However, this same approach means that filter methods do not solve the problem of multicollinearity, which can in turn lead to relatively poor performance relative to other techniques. In recognition of this, one of the common application of the filter methods is identifying relevant features for future modelling.Wrapper methods are a category of approaches in which features are selected and assessed, in conjunction with other features, in their ability to account for the variance in the underlying data. An algorithm iteratively learns to select the combination of features that best explains the data. Common approaches to doing this include forward and backwards selection approaches, in which the algorithm starts initially with either none or all of the variables (respectively), and adds/removes variables until the model no longer improves. This approach is vastly employed in both linear and non-linear methods. Given its iterative nature, wrapper methods are relatively expensive computationally, and the typical forward/backward selection methods have both been shown to be potentially experimentally problematic in terms of identifying most relevant subset of features, 19. TheLastly, embedded methods are similar to wrapper methods in that an algorithm iteratively learns to select the features that best contribute to the accuracy of the overall solution. They include interactions between features in generating the model, which typically makes them superior to filter methods for prediction, and less likely to overfit the data than wrapper methods. Although these methods are beyond the scope of the present study, embedded approaches have shown promise in other recent studies that have focused on the analysis of large datasets with multiple variable interactionsThe goal of the present study was to quantitatively compare the performance of different linear  and nonlinear selection methods for the identification of relevant features within the two main survey databases  with applications to non-linear associations in data. To do this, we compared the performance of several linear methods (regression) widely used in gerontology versus non-linear (filter) feature selection methods using two main survey databases  performed under these analysis conditions. Important parameters here include the level of noise obscuring the relationship between variables, the number of samples available for analysis, and the effects of discrete versus continuous variable representations. We therefore assessed performance in two ways. First, we constructed a series of synthetic datasets that mimic the noisy and non-linear nature of many survey datasets. Because the associations between variables were known in advance, we would be able to quantitatively gauge the performance of the different selection methods in identifying relevant features and discarding irrelevant ones . Second, we further gauged the performance of the different selection methods using two representative datasets, the Wisconsin Longitudinal Study, and Hea1 scores, which represents the harmonic average of the precision and sensitivity of each selection method; as selection performance increases the F1 score approaches 1 and as selection performance decreases the F1 score approaches0. To estimate the statistical significance of the difference between F1 scores of different methods, we followed the methodology described in . Sine, cosine and quadratic functions were used to model the relationships between the target and predictor variables. Specifically, we identified the function’s parameters, so that the corresponding predictor variable ranged from zero and Xmax, where Xmax, is a whole number either 4 or 7. We then solved the inverse problem of finding corresponding yi, xi = f−1(yi). Thus, the functional relationships used werexmax. We used the following combinations for {a,xmax} =  for discrete variables, and {a,xmax} = {0.8,7} for continuous variables. p1 and p2 here are random numbers, p1ϵ{0,1},p2ϵ{0,1}.,.To do this, a target variable, xmax. to xmax. The parameters used for the discrete variables were {h,b,c,xmax} = , and the parameters used for the continuous variables were {h,b,c,xmax} = . For datasets containing only discrete variables, the continuous variables were rounded to the nearest whole number.Wealso usedR = 9 variables with a known association with a dependent variable. If more than one solution existed, xi was taken randomly, with equal probability, out of all the outcomes. Finally, we added uniform noise and rounded the resulting value to the closest integer in the corresponding range. We then added K = 80 random features. These random features were defined as follows. First, the range was defined such that each variable was between zero and xmax, where xmax is a random whole number between four and ten, with equal probabilities. Then, the feature was filled with a random whole number, with equal probability, between zero and xmax for discrete random features, and uniformly distributed Altogether, we constructed xϵX was a whole number. In the other set, five variables We made two sets of the experiments. In the first set, we constructed only discrete variables, in which each and every XiϵX is vector of length N. We investigated cases where N = 500, 750, 1000, 1250 and noise equal to .5 and 1.Each XiϵX is related to Y, we can compare different feature selection methods. Thus, for each combination of N and noise we generated 200 synthetic datasets, applied a given method, and then investigated whether each feature was or was not identified as important or unimportant correctly. We then computed F1scores, and checked whether the difference between F1 scores of different methods is significant.Because we have a priori knowledge about whether each feature Note here, that we needed nonlinear relationship without clear trend, and selected relationships fulfill this purpose. At the same time, we are unable to mimic all potential relationships with synthetic dataset, so we used representative database to compare linear and non-linear methods on real data.The goal of our study was to test the selection performance of each method under typical usage conditions, in which researchers would attempt to identify relevant features within in a large dataset. To do this, we used data from two longitudinal studies on aging in USA: Wisconsin Longitudinal Study of Aging database (WLS)  and HealComputer-Assisted Personal Interviewing (CAPI) 2011 wave, Mail: Internet module and Mail: Social and Civic Participation, available at wls_pub_13_04.sas7bdat. The target variable, health change, was computed as the difference in HUIM3 health index, a rating scale targeted at measuring general health, between 2011 and 2004. In total, this representative dataset contained 3,028 respondents with 52 independent variables apiece. We aimed to assess the performance of each method at identifying factors that are already known to influence health in old age. To that end, we identified six variables as potentially relevant to this health indicator based on prior research individuals[education”), alcohol use , tobacco use , and the respondent’s previous health score in 2004 . We excluded 687 respondents who were missing data for any from these previously listed factors. Missing data were imputed with median for all other lifestyle activities; in all cases, this missing/imputed data amounted to less than 15% of the data per activity.We extracted health information along with several life style activities from the WLS, as repodividuals–43: educ“alcohol”, “education”,”tobacco”, “tobacco1”, “tobacco2”, “health”). This analysis was repeated on a smaller, third dataset that did not include the “health” variable. We then compared the performance of each selection method against its own performance on the smaller dataset in order to determine the influence of other variables on the feature selection performance of each method.Data analysis was done on this dataset in three steps. First, we tested each method for feature selection on the complete set of data with all 51 independent variables, which represents analysis conditions wherein researchers do not have strong a priori knowledge to manually reduce a dataset. Second, we again tested each method for feature selection but on a smaller subset of data containing the six variables described above , total alcohol use , smoking , and level of physical activity. We excluded 682 respondents who had missing data for any from these previously listed factors. We than imputed missing data with medians for all other variables; in all cases, this missing/imputed data amounted to less than 20% of the data per variable.In total, our second representative dataset contained information on 900 respondents characterized by 80 independent variables. Similarly to the WLS case, we1 scores were computed for each feature selection method, for two variable types (discrete and continuous), two levels of noise and four samples sizes  and sensitivity.Specifically, p< .001.Left panels in To further assess the classification performance of each selection approach, we analyzed a subset of the Wisconsin Longitudinal Study of Aging (WLS)and a subp values equal to 1 in the table indicate that the corresponding variable was not included into the final model. The same analysis was performed on three data sets: (i) full dataset with 51 variables; (ii) a subset with only six relevant variables ; (iii) a subset with only five relevant variables.As can be seen in alcohol”, and “health”; BLS Cp,, BLS R2 identified “alcohol”, “tobacco 1” and “health”; BLS BIC identified “tobacco 1” and “health”; FLS Cp, and FLS R2 identified “alcohol”, “tobacco 2“, and “health”, and “tobacco1”; and FLS BIC identified “tobacco 2” and “health”. In the smaller dataset, with six relevant variables, OLS identified as important “alcohol”, “education”, and “health”, whereas BLS Cp,, BLS R2, FLS Cp, and FLS R2 identified as important “alcohol”, “education”, “tobacco2” and “health”; BLS BIC and FLS BIC identified “education“, “tobacco 2” and “health”. The exclusion of just one relevant variable, “health”, resulted in no variables being selected as important in the smallest dataset by OLS; one variable, “tobacco 1” selected by BLS Cp, and BLS R2; one variable, “alcohol”, selected by BLS BIC; and only one variable, “tobacco 2” selected by all forward selection methods. LASSO was able to select only “health” in only one dataset with six variables.By comparison, linear methods for variable selection are sensitive to model misspecification, generating inconsistent results depending on the method and on size of the dataset to be analyzed. Specifically, in the largest dataset, OLS identified as important “cognitive health change and one of four relevant variables. Similar to With a small number of relevant variables identified as important, the HRS dataset education” was identified by all the methods. In particular, linear methods were able to identify only this variable. In contrast to linear methods, both Hilbert-Schmidt (HS) and Distance Correlation (DC) identified as significant two out of four relevant variables; although Hoeffding’s test only identified one variable as significant, this was again still at least as good as the number of variables identified by the linear methods.As can be seen, “Linear selection methods have been the main methods of the gerontology field to approach and study two of the main central databases, WLS and HRS. In manyTo do this, we assessed seven linear methods  and three nonlinear methods  under both synthetic and real-world use conditions, in which the associations between variables were known in advance. The objective was to assess the ability of each method to select features and discard irrelevant features, and not to assess the accuracy of the various methods at computing the magnitude of the impact of each feature on the dependent variable, such as when computing a coefficient in a linear model. Within the synthetic datasets the variable associations were deliberately non-linear, as we do not usually expect strong linear relationships in real data. Unsurprisingly, selection performance was much better in these cases, with linear methods offering particularly poor detection sensitivity in these cases. There was a small but consistent performance advantage for Hoeffding’s test bases on F1 statistics in all synthetic dataset analyses, although it bears highlighting that sensitivity remained relatively high for all three non-linear methods, and FDR relatively low even as sample size decreased and noise increased. At the same time sensitivity of linear methods consistently remained much lower compared to non-linear methods, with the only exception of LASSO regression that had comparable sensitivity and much higher FDR. This is in line with previous studies that also corroborate this phenomena , 48Similarly, the selection performance of non-linear methods was more consistent than linear methods in the analysis of real-world health data. Notably, the analyses revealed that the selection performance of the two stepwise regression methods (forward and backward feature selection regression) can vary substantially from one case to another, depending on the variables that are included or excluded from the analysis. Indeed, this was so severe that the removal of just a single variable—in this case, the respondent’s health at the previous assessment—led to substantial differences in the selection of all other features. By comparison, the selection performance of the non-linear algorithms was unaffected by the number of variables in the dataset, which is an important benefit for data-driven analyses in which researchers have weak (or no) a priori hypotheses about the data. Moreover, the selection performance of these non-linear methods was superior to that of linear methods, as evidenced by the number of features identified as significant. Although the poorest-performing method in this analysis, Hoeffding’s test, failed to identify either alcohol consumption or the number of cigarettes smoked per day as significant on health, the number of features it identified as significant (4) was still equal to the best-case selection performance of the linear methods.We should acknowledge, that our work is limited by its inherent assumptions. First, we only investigated datasets where relationships between target variable and features were non-linear. For further understanding of feature selection method's performance, comparison of different methods applied to datasets were underlying dependencies are linear would be quite beneficial. Second, we explored method's applications when target variable was continuous.In reality, however, target variable is often discrete, i.e. presence or absence of a given disease. Understanding performance of different feature selection methods applied to datasets where target variable is non-continuous will also facilitate better choice of feature selection methods.


Generativity—showing concern to establish and guide future generations—has been argued to be a biological adaptation central to cumulative culture and survival, but also, in turn, to be a cultural adaptation dependent on norms. From the perspective of human agency, concern for the future has played a key role in raising agency for generations that follow by creating infrastructure and cultural inheritance. Here, in a population-representative sample of 756 twin-pairs, we present the first test of the genetic and environmental structure of generativity using the Loyola Generativity Scale (short). Genetic analysis of scale sum-scores revealed that shared environmental effects were comparable in magnitude or exceeded effects estimated for genetic differences . At the item level, a well-fitting genetically-informed model suggested 3 factors influencing generativity via a common-pathway structure. The first was tentatively characterized as reflecting a heritable general concern for the future. The second reflected being a valued source of advice and assistance. The third factor showed only unique environment effects and had as its strongest indicator having had a good influence on the lives of others. Replicability of this structure should be tested in the full version of the scale. Work is needed also to validate influences of generativity on vocations such as teaching and on philanthropic activity improving life for subsequent generations. The research topics are broad in scope: from novel models of moral agency  as an environmental moderator  and “Mental cognitive artifacts” such as logic and formal systems of finance. Such are the benefits of such physical and mental cultural infrastructure, that cognitive adaptations specifically to support their creation have been argued to be a key element of human genetic adaptation  has examined the heritability of generativity. In review, we were asked why is a twin study still important? There are several reasons. Generativity theory claims a relatively strong influence of shared environment on generativity Erikson . This woA widely accepted reason to document the magnitude of variance attributable to genetic, family-environment, and unshared environmental influences, not just in a given sample , but in many samples. This impetuous flows from the finding that variance attributable to genes and environment can not only take on different values depending factors such as age or birth cohort  have not been collected. It is of value, then, to collect data on generativity, and to establish whether it has high, relatively modest, or even low levels of heritability, not only to add to the rather sparse database of heritabilities in the domain of attitudes and motives, but to begin to document variation in these traits across cultures and times.A further reason to examine generativity in a genetically informative sample is that in this, as in all areas of social science, concrete estimates of genetic influence not only to test theory that includes such influences, but also motivate other research to include controls for genetics. As was noted in a recent commentary, even longitudinal relationships of parent and offspring behavior are not evidence for effects of parental behavior  of generativity items has not been examined. While the phenotypic null hypothesis , shared or common environmental influences (C) shared by both twins, e.g. place of residence or neighborhood factors, and unique environment (E): environment influences which are not shared, e.g. their unique peer-group , while the scale is designed to be unifactorial, we were open minded as to the factor structure that would be revealed in a genetic analysis. In particular, the multiple components and influences on generativity identified in modern generativity theory  the choice of a baseline model is more complex. While it is common practice to evaluate such models against a multivariate Cholesky ACE model, algebraically, this model is not unbiased Carey . For thiThe data for this study originate from Wave II of the MacArthur Foundation Survey for Midlife Development in the US .We used an abbreviated and modified version of the 20-item Loyala Generativity scale, developed for MIDUS (see Appendix I have done nothing of worth to contribute to others”). The long scale is explicitly focused of effort and success at passing along knowledge (e.g. “I have made a difference to many people”) where the short scale focusses on possessing such knowledge or skills. The long scale also measures the enjoyment of a vocation (such as being a teacher), as opposed to “liking to teach things to people” in the short scale. Some behaviors are absent, for instance volunteering for charity, creative effort, commitment, productivity, neighborhood responsibility. The full version also emphasizes the creation of a legacy that will be remembered beyond a person’s own lifetime.Despite considerable overlap, the long and short scales differ in a number of substantive ways. The items are written in the third-person, and all are positively worded, whereas in the full version, items are in the first-person tense and include negative items  to 4 .To test the hypothesis that familial clustering in generativity is explained by both additive genetic and family environment factors , we fitted univariate biometrical genetic models , we again used the OpenMx package . The remaining proportion of variance was explained by non-shared or stochastic environmental risk factors including measurement error.2 (3) = 1.61, p = 0.657) and an improvement of AIC compared to a model containing these paths (AIC = − 96.00 versus − 91.6 including moderation).In an exploratory modelling phase, we also ran a gene × environment interaction model Purcell  testing We next turned to the item-level data, to test our hypothesis that, under behavior genetic analysis, the items of the scale would be well explained by a single common factor model with significant genetic (A) and shared environment (C) influences . To this end, we computed a 1-factor CPM, and compared this to the direct variance–covariance baseline model (see Table 2 (37) = 136.77, p < 0.001). We then explored sequentially more-complex models. A 1-factor IPM also showed inadequate fit (p < 0.001). We then executed CPM and IPM models with 2 and 3 factors, finding that a 3-factor CPM model fit well (χ2 (21) = 9.85, p < 0.98, see Table 2 (9) = 13.99, p < 0.123) but was not preferred by AIC compared to the 3 common pathway model  was disconfirmed. Instead, the analyses revealed a complex factor structure best accounted for in terms of three psychometric factors in a common pathway model. We discuss these two findings in more detail below.A surprising result of genetic research has been that often Plomin , but notC effects, for all behavior genetic traits, may be premature, not only because of GE covariance in different forms , it would be valuable to repeat the analyses with the full scale, and, preferably, in a larger sample. We are undertaking this task as part of the project this year.It would be of value also to have measures for more of the 7 predicted components of generativity, work that would not require access to a twin sample. Given the importance attributable to education in modern society, it would seem useful to understand better the origins of motivation to teach. Based on low rates of systematic teaching  in pre-industrial society, Lancy  suggestsThe present sample was predominantly middle aged. It would be valuable to study generativity in younger subjects . Also of value would be to measure wider social effects of generativity on important prosocial activities such as institution founding and maintenance.With these limitations, this study is the first step to understanding the genetic and environmental structure of generativity. It demonstrated that, at a scale level, generativity reflects large influences of the environment, including shared environment, while revealing a more complex structure at the item level.


It is an unfortunate—but nevertheless accurate—characteristic of such industrialized societies as ours that the richest areas usually are the dirtiest. The old Yorkshire saying “Where there’s muck, there’s brass” puts it quite succinctly, if smugly. Even today, industrial managers in America sometimes smilingly refer to the acrid stench from their profitable plants as “the smell of money”” [In the Editorial “Air pollution and health” that appeared in Environ. Sci. Technol., 1970, 4 (2), pp. 87–87, Michael Bowen wrote: “50 years passed, but we are now witnesses that something has changed. We are no longer convinced that dirty air is an unavoidable adjunct to a booming economy, and there is evidence that air quality standards adopted can improve air quality in urban areas and workplaces. Industrial pollution does not dominate air quality due to improved emission controls and technology, while at the same time, traffic and residential combustion have increased their role. Thus, in Western countries, the choice between being poor but healthy or rich but unhealthy is overcome.Nevertheless, environmental exposures are still associated with substantial mortality and burden of disease in the developed world (Landrigan et al., 2017 [This Special Issue brings together scientists from multiple disciplines to present their newest results concerning exposures in schools and nurseries, in and from traffic, perceived and observed related health effects, exposures to ultrafine particles, composition of exposures, and differences in toxicity of the exposures by emission sources. Several papers look at exposures in developing countries and most recent scientific epidemiological evidence collected by combining state-of-the-art exposures with observed health data. The way is paved forward, even if a lot of work needs to be done to establish safe and healthy living environments for mankind.


There has been a move towards using mixed method approaches in geospatial research to gain context in understanding health related social patterns and processes. The central premise is that official data is often too reductionist and misses’ nuances that can help explain causality. One example is the geonarrative, a spatially relevant commentary or interview that can be mapped by content and/or location. While there have been several examples of geonarratives being used by researchers, there is no commonly available software that can easily transfer the associated text into spatial data. Having a standardized software platform is vital if these methods are to be used across different disciplines. This paper presents an overview of a solution, Wordmapper (WM), which is a standalone software developed to process geonarratives from a transcription and associated global positioning system (GPS) path. Apart from querying textual narrative data, Wordmapper facilitates qualitative coding which could be used to extract latent contextual information from the narratives. In order to improve interoperability, Wordmapper provides spatialized narrative data in formats, such as ESRI shape files, Keyhole Markup Language (KML), and Comma Separated Values (CSV). A case study based on five different spatial video geonarratives (SVG) collected to assess the human impacts following the 2011 Joplin, Missouri are used for illustration. The recovery process from such events begins with the initial search and rescue, and then extends through multiple years of physical and social rebuilding. Along that continuum, the human toll is immense—from the trauma of the initial experience through various psychopathological manifestation during recovery. These events are spatial, temporal and human. To fully address such dynamic landscapes, we need nuanced data that combines more traditional surveillance with ground-up insights. Indeed, the addition of context into geospatial health research is imperative if researchers are to understand the process, as well as outcome [problem” . Environproblem” ,5,6,7. TThere are many advantages to this form of data collection, especially for challenging environments. While the video provides a visual resource that can be used for digitizing map layers, the simultaneously collected global positioning path (GPS) path anchors each frame to an exact location. Onto these mapped layers, conceptually, are the comments that provide “depth” to the map. Again, each comment is matched to both location and video frame providing a rich understanding of the outcomes and processes at work. This same approach can then be applied across multiple interviews collected for the same time, or across different periods, to gain multiple perspectives of a location, or to see how that location changes. In this way more traditional data, such as overdose locations, can be enriched with an understanding that reaches beyond a point on the map. However, what has been missing to make SVG a truly ubiquitous tool, is an easy means to combine video, narrative and coordinates in such a way that a non-GIScientist can fully utilize this method. In this paper we address this deficiency using a research support tool called Wordmapper.Mobile technologies provide exciting new avenues of spatially focused research across a variety of disciplines. These techniques provide a novel means to capture data for micro spaces of activity ,12,13,14where a hotspot occurs but why? One approach to a more nuanced consideration of spatial data is a qualitative geographic information systems (GIS) approach [Geonarratives” [Health researchers incorporating spatial data have argued that we need to consider-the-local because of its importance in designing effective intervention. Here we mean “local” as a subsection of a neighborhood, along a street, or even around a building. While new geospatial technologies can provide data layers to inform investigations at this scale, an important consideration is the addition of context; not just, approach ,18,19, wapproach , geovisuapproach ,22 and napproach ,23,24. Oratives” , which uratives”  demonstrratives” . Curtis ratives” ,28. In tratives” , with exratives” ,31,32, mratives” , environratives” , urban gratives”  and crimratives” ,36. In tWhile SVG offers an advantage to qualitative researchers with an interest in more explicitly spatial data, for example, why one corner of a city park is associated with violence, an obstacle has been the lack of any easy-to-use software. There are examples of customized software developed for research needs; Kwan and Ding’s  3D-VQGISgeonarrative problem. This means that transcribed text in the form of a narrative and associated GPS data needs to be combined to create a geonarrative dataset where comments and words become spatial objects. By doing this a researcher can generate queries based on textual attributes, such as keywords, and spatial queries based on the geotagged content.To address this research gap for a more ubiquitous use of SVG we have developed a conceptual frame for how narratives can be mapped. This can be seen in To achieve this goal, a working conceptualization model based around six modules was developed. This schema provides the inspiration for Wordmapper. There now follows a more detailed conceptual explanation of these modules while also linking to the practical application as experienced when using Wordmapper.Once a narrative has been collected, it is then transcribed. In order to be able to match the text to a spatial location, the time when each comment or word occurs in the narrative must also be recorded. The preprocessing module accepts a narrative in the form of a text file and GPS data in the form of a Comma Separated Value (CSV) file . The narrative is a text file with each sentence having the timestamp on the audio recording inserted at the beginning. The GPS data is a Comma Separated Value (CSV) file with latitude, longitude, and time in Universal Time Coordinated (UTC) format. The offset time between these two data inputs is the difference between the media time of the audio recording and GPS time. Simply put, if the audio starts at 0:01 seconds, and we know the Greenwich Mean Time (GMT) of the GPS when the first word is spoken, we can sync both data streams together.Apart from accepting these inputs, the preprocessing module should also validate the data inputs, especially out of sync time stamps in the transcribed narrative. We used a custom GPS correction software , developThe combiner module syncs the narratives and GPS data to create geonarratives. To do this all narrative sentences are initially of the tuple form <timestamp, sentence>, which along with offset time is used to match the starting index in the GPS data . The staThe first step in generating spatial words consists of the tokenization of the sentence. Natural Language Toolkit (NLTK) , a PythoX1, Y1) and the last word , the angle of incidence of the path (α) can be calculated using the Point-Slope equation. By assuming a constant speed of travel and an associated known time stamp, the distance between an unknown word and a reference location, z, could be found out using average speed formula. By utilizing the distance (z), and the angle of incidence (α), and a reference word location , the coordinates for the new word  can be calculated using trigonometry  as a CSV file, and the Greenwich Mean Time (GMT) of the video media time that matched the first word of the transcription was used as the offset time for Wordmapper.The preprocessing module in Wordmapper reads in the narrative file, csv file with location, and offset time. The combiner module combines the narrative and location data to create geonarratives, which are added to the Wordmapper geonarrative dataset queue. The dynamic wordcloud generated from the Wordmapper provides an initial comparison of the narratives. The visualization window in In another example  an interIt is also important to go beyond simply mapping text, and instead mine the content, and the structure of the content further. To do this, Wordmapper allows for the creation of different categories, which can then be used to create comment subsets. For example, while these categories could be thematic , they could also be spatial. Here we have created two categories ‘Location Specific’ and ‘Fuzzy Space’ which are used to classify comments that have explicit mention of a location, such as ‘this house’, ‘that church over there’, or comments that have vague place mentions, such as ‘this area’, and ‘that street’. A combined wordcloud  from botAdditional investigative power occurs when these tools are combined, for example a search based on the keyword ‘damage’ and the category ‘Fuzzy Space’ helps to identify locations where mention about ‘damage’ was made. From the example , it seemAnd this whole area, maybe a little wind damage, but that’s it” was classified as ‘Low Damage’ and given the value 1, while a sentence, such as “Moderate to light damage. I know that that particular church for a while was providing shelter to some people.” was classified as ‘Medium Damage’ and given a value of 5, and sentence, such as “Here ? that convenience store there was one of the places that was totally demolished, and I guess there was a recording of a cell phone call that people hiding in the ? people hiding in the freezer. got, uh, widely distributed nationally.” was classified as ‘High Damage’ and was given a value of 10. Kernel Density Estimation, a technique to calculate the density of point and line features, was used to create a density surface with the classified damage values. The map , but it does provide the basis for comparative mapping to see how this approach could be used in areas where no or little data exists. For example, the above heat map could be repeated for emotional content, or mentions of recovery related illnesses or other health conditions. In both examples maps made from more traditional sources are likely to be incomplete.Any spatial data, whether physical (locations of damage), or health (suicide locations) only tell a partial story unless contextualized. One way to capture these insights is through an SVG. Now, using Wordmapper, we also have the means to fully leverage these data. More specifically, Wordmapper allows for the transcribed narrative to be combined with coordinates in an easy to use interface that supports both textual and spatial investigations. These queries are not linear in the sense of a more typical qualitative GIS approach, but rather iterative, supported by images and text. The addition of categories, that can include both content themes and spatial structure, along with supporting visuals, such as maps and wordclouds, encourage the user to evolve their search in a nonlinear way. Wordmapper has been designed for use by non-spatial science, nor computer science savvy users. In this way a local mayor’s office, or a non-profit, or a public health official could benefit from SVG use. This has the additional benefit of also making these groups more willing collaborators as the benefits are tangible.Wordmapper is designed to be standalone software, which both maximizes the security of working with potentially sensitive data ,50, whilDeveloping Wordmapper, however, is only the opening to many other strands of associated research on the technique itself. It has previously been suggested by Curtis and colleagues that comments are either spatially precise (for example “people were injured in this building here”), spatially fuzzy  and spatially inspired (“I’ve heard a lot of people complaining about dust”) . It woulWith advances in the area of Natural Language Processing (NLP), researchers are using approaches like sentiment analysis to identify and extract emotional context from sources, such as microblogs  web-foruSpatial video geonarratives are an exciting new approach for data collection. They can capture institutional knowledge, record a variety of different perspectives for the same space, be used for historical and contemporary investigations, reveal where overdoses are likely to happen, where gang violence may erupt, or provide context to stop an epidemic. This approach is potentially transformative, but two areas currently limiting a more widespread use are, the need for unwieldy data manipulations in a variety of software packages, and a reliance on internet connectivity. Both these deficiencies limit the uptake of the method in non-spatial disciplines, and with partners working in challenging environments. In this paper, we have addressed these needs in the form of Wordmapper, which allows researchers to effectively process and analyze data being generated in various formats, while also having access to a variety of tools suitable for different spatial skill levels. In so doing, we have now opened the way for SVGs to become a more widely used tool to add context into spatial-social research.