People exhibit a strong attachment to possessions, observed in behavioral economics through loss aversion using new items in the Endowment or IKEA effects and in clinical psychology through pathological trouble discarding domestic items in Hoarding Disorder. These fields rarely intersect, but both document a reticence to relinquish a possessed item, even at a cost, which is associated with feelings of loss but can include enhanced positive states as well.To demonstrate the shared properties of these loss-related ownership effects, we developed the Pretzel Decorating Task (PDT), which concurrently measures overvaluation of one’s own over others’ items and feelings of loss associated with losing a possession, alongside enhanced positive appraisals of one’s items and an effort to save them. The PDT was piloted with 31 participants who decorated pretzels and responded to their own or others’ items during functional neuroimaging (fMRI). Participants observed one item per trial (self or other) and could work to save it (high or low probability loss) before learning the fate of the item (trashed or saved). Finally, participants rated items and completed hoarding tendency scales.The hypotheses were supported, as even non-clinical participants overvalued, viewed as nicer, feared losing, and worked harder to save their items over others’—a response that correlated with hoarding tendencies and motor-motivational brain activation. Our region of interest in the nucleus accumbens (NAcc) was engaged when viewing one’s own items to the extent that people worked harder to save them and was more active when their items were saved when they felt emotionally attached to possessions in real life. When their items were trashed, NAcc activity negatively correlated with trouble discarding and emotional attachments to possessions. Right anterior insula was more active when working to save one’s own over others’ items. Extensive motor-motivational areas were engaged when working to save one’s own over others’ items, including cerebellum, primary motor and somatosensory regions, and retrosplenial/parahippocampal regions—even after controlling for tapping.Our attachments to items are emotional, continuous across typical and pathological populations, and drive us to save possessions that we value. Individuals spend significant time working for, buying, organizing, and discarding possessions. People vary widely, however, in the degree that they express this motivation to acquire and keep goods—from the most spartan among us, who keep few things and enjoy an uncluttered space to those suffering from pathological Hoarding Disorder (HD). Some have suggested that HD is an extreme form of people’s typical tendency to become attached to possessions and to want to hold on to them, even at a cost, but research linking these processes is limited and current findings are mixed. The primary goal of the present study was to directly test the relationship between typical endowment-like processes and continuous hoarding tendencies in non-patients using a novel fMRI task.In behavioral economics, people often exhibit a strong or irrational attachment to possessions through the “endowment” or the “IKEA” effects. In the endowment effect, participants financially overvalue a new item like a mug that was just given to them by the experimenter, demonstrated when they require more money to sell the item than others are willing to pay for it  , 1991. IThere are clear similarities in the psychological and neural processes that underserve endowment and HD processes, which require further examination  in which participants decorated a pretzel ahead of time and then, during functional neuroimaging (fMRI), viewed their own and others’ items, one at a time, could the work to save the item from the trash (high or low probability loss), and then learned the fate of the item (saved or trashed). People were expected to be willing to pay more for their items over others (as in endowment processes) and to rate the sense of loss as worse if they were to lose them, while also appraising them as nicer and being more willing to work to save them . This overvaluation was also expected to correlate with hoarding tendencies, even in our non-clinical sample using an HD symptom scale. We expected to replicate the link between expected loss and activation in the anterior insula observed in endowment effect  and HD dThe PDT was expected to work because it resembled prior endowment and IKEA effect tasks that generally have large effect sizes. Moreover hoarding-related phenomena have been observed in non-patients previously and exist on a continuum. In addition, the use of a food item was expected to work because individual differences in hoarding tendencies previously correlated with intertemporal discounting for snack foods, even when identical items were offered to participants in large quantities . Food alIf we understand the underlying psychological, behavioral, emotional, and neural processes that cause people to overvalue possessions, we are in a better position to help people avoid maladaptive situations that can undermine financial security, well-being, and the health of the planet.via flyers posted around campus and the community. The sample size was deemed adequate because fMRI results and relationships to hoarding had been established before using a similar task with a much smaller non-clinical sample , right-handed, and without a history of neurological or psychiatric illness. All procedures were approved by the university Institutional Review Board, and written consent was obtained for each participant.Thirty-one participants  from the local community were recruited for a two-session study  N = 20; . We incr N = 20; . ParticiA task that accesses both endowment and hoarding processes required real possessions that participants would value and want to save or fear losing, but still consent to lose. The items also had to be meaningful to owners and non-owners, and to be meaningful when presented in the multiples that were needed for fMRI. fMRI items also needed to be visually similar, to avoid visual confounds on brain activation. We also needed to measure feelings of loss along with positive appraisals and motivation toward items. An IKEA-like task suited these constraints . People One to two days before fMRI scans, participants consented and decorated 28 pretzel rods in the laboratory, by dipping them in melted white or milk chocolate and covering them with their preferred combination of crushed nuts, sprinkles, or miniature M&Ms. Pretzels were photographed individually with a Nikon Coolpix camera in a 4:3 size ratio, on the same gray surface, with the chocolate covered end facing the bottom right corner of the frame, going diagonally toward the top left, at approximately a 30° angle. Each participant’s items were slotted into their scanner trials, so personal items would appear in the same ratio for all participants. Others’ items were taken from a set created during a pilot pretzel-making session, to cover the range of quality observed by pilot participants. That is, pilot participants made a large set of pretzels and rated their quality from low to high, in terms of the subjectively perceived outcome of the decorating process. We then selected items for the other condition of low, medium, and high quality to match the range in future fMRI participants’ creations, based on the range in pilot participant creations. Using the same pilot items for the others’ pretzels across participants  was beneficial because we could institute the same delay between making the items and the fMRI visit for all participants see . The oneTask stimuli were presented using E-Prime 2.0 software projected onto a screen at the back of the magnet, viewed through a mirror. Pretzel stimuli varied on two orthogonal dimensions: creator (self-versus other) and loss probability (the likelihood that the pretzel would be thrown away at the end: high versus low). On each trial, subjects viewed one pretzel for 2000 ms, made by themselves or someone else, indicated with black text above and to the left of the image (“YOURS” or “OTHERS”). The top right displayed loss probability (“TRASH LIKELY” in olive text or “SAVE LIKELY” in blue). This was followed by a green jittered fixation cross on a white background for 5,000–6,000 ms.For full trials, the next slide said “WORK” with “Tap fast to save pretzel!” underneath. Participants were instructed to tap faster during this 2000 ms period to the extent that they wanted to save the pretzel, to increase the likelihood that it would be saved. In reality, the number of trashed versus saved outcomes was predetermined (80% for the stated likelihood and 20% for the opposite) and participants could only take home their items because others’ items were the same for all participants. After tapping, a black jittered fixation cross appeared on a white screen for 4,000–5,000 ms to indicate the end of that period. Next the outcome slide presented that pretzel for 1,500 ms, surrounded by an olive border with the text “TRASHED” or a blue border with the text “SAVED!” above the image. Trials were separated by a black fixation cross on a white background that changed to green for the 500 ms before trial onset. No participants reported noticing that the outcomes were fixed.M = 1,640 ms, sampled from an exponential distribution). This allowed us to separately measure people’s response to observing their own or another’s item, aesthetic appeal, effects of loss probability, effort to save items, and the response to it being trashed or saved.The task intermixed view-only trials (~30%) and full trials that included work and outcome phases (~70%) to dissociate BOLD activity from viewing pretzels versus preparing to save them after ,b. View-Participants completed a motor-tapping localizer after the Pretzel Decorating Task, to identify regions associated with simple tapping, to later subtract from activation during our Work period . During three tapping blocks, participants saw a cursor blinking at 0.5 Hz, 2 Hz, or 4 Hz for 20 s and were asked to tap along with the cursor (randomized order). During rest periods between these blocks, participants relaxed for 20 s. The tapping localizer was followed by a motor reaching imagery localizer, in which participants imagined, in a 2 × 2 design, pulling a person or object back toward themselves, to rescue the item or for a more mundane reason. No brain areas were significantly more active for any contrast in this imagery localizer, which was included for a separate study on altruistic rescues and is not discussed further  “Niceness”: how nice the pretzel looked  signal for each participant in the main task, we acquired 1,060 functional T2* weighted spiral out volumes  divided evenly across four runs. Localizer tasks for motor tapping and motor reaching visualization were acquired with the same parameters but with 70 and 82 volumes, respectively. Trials were not initiated until after the first 5 functional images. Structural images for data presentation and co-registration were acquired in the same slice locations using a T1-weighted fast gradient echo pulse sequence , and high-resolution structural images (voxel size 1 × 1 × 1 mm) were collected using a T1-weighted, spoiled 3D GRE acquisition.Behavioral analysis consisted of six mixed models. We first compared participants’ ratings for each pretzel as the dependent measures in three separate linear mixed models: niceness, willingness to pay, discard distress. Participant was included as a random factor and pretzel creator as a fixed factor (self > other).Next, in three similar linear mixed models we predicted participants’ behavioral tapping effect, that is, their greater effort to save one’s own over others’ pretzels in the 2 × 2 model with participant as a random effect. The number of taps were predicted in a linear mixed model with fixed factors for self > other and high > low loss probability (modeling each main effect and their interaction), including one covariate per model  and modeling the main effect of each rating and their interactions with self > other and high > low loss probability.Hoarding tendencies were also modeled with a series of linear mixed models using the 2 × 2 model  with participant identity as a random effect, to predict the number of taps to save a pretzel as the dependent variable, with each hoarding tendency entered as a covariate. There was one model for each total score and for each subscale score, so the results were Bonferroni corrected for 21 comparisons . We report the main effect for each individual-difference tendency, their interaction with each main effect, and the three-way interaction . Thresholding results of the 2 × 2 models first involved two-sided, one-sample resholds .a priori regions of interest (ROIs), we predicted NAcc and right anterior insula to be more active for self > other items, based on a neuroimaging study of the endowment effect . Afterwards we extracted average brain activation within the ROI from the 2 × 2 model using MarsBaR , thresholded at The Outcome period permitted many possible contrasts, which we simplified by only performing those that reflected the psychology of losing or saving a possession in the ROI. We compared activation when one’s own items were discarded compared to all other possibilities  and when one’s own items were saved versus trashed (self saved > self trashed) and correlated these effects with the three retention-related hoarding tendencies.a priori ROIs missed key areas of interest, producing multiple null results. Thus, ROI analyses were followed with exploratory whole-brain (WB) analyses, summarized below and detailed in the p < 0.1, FWE TFCE, k > = 0. Because people responded more to nicer looking pretzels in the behavioral results, we also explored null effects by adding a regressor for pretzel niceness to the 2 × 2 model in the WB. We report below the more stringent threshold of p < 0.05, FWE TFCE, k > = 0, but also include results in the supplement at the p < 0.10 level, FWE TFCE, k > = 0 (noting that this is still a more stringent threshold than uncorrected results). Null results were also explored by recalculating the 2 × 2 analyses in the whole brain for Viewing and Work with an alternative functional ROI from task > baseline  = 12.31, p < 0.001, they were willing to pay more for them, F = 22.78, p < 0.001, and they reported greater distress when imagining that they were discarded, F = 42.98, p < 0.001 self = 5.74 (0.31); M (SD)other = 3.72 (0.31), F = 297.59, p < 0.001. Across conditions, participants also worked harder for nicer pretzels, F = 274.741, p < 0.001, would pay more for them, F = 115.90, p < 0.001, and reported being more distressed about imagining losing them, F = 317.19, p < 0.001. Note that this shows that participants not only prefer their pretzels because they decorated them to their own preferences, but that participants also agreed upon which were items were “nicer” and worked harder for all nicer ones, regardless of creator. Participants worked particularly hard for their pretzels to the degree that they would pay more for them, creator x WTP interaction: F = 10.08, p = 0.002. Effort to save was not influenced by whether the loss probability was high or low, F < 0.1, p > 0.1, and loss probability did not interact with any other effects across models, Fs < 2.3, ps > 0.10.Participants’ preference for self over other items was also reflected in how hard they worked to save them in the scanner . ParticiAs predicted, the behavioral tapping effect, to work harder to save one’s own over others’ items, also increased with multiple hoarding tendencies. The behavioral tapping effect was still significant after correcting for each hoarding tendency (except it did not survive correction after adding SIR-Acquisition), indicating that the impact of ownership does not just reflect the actions of unusual or disordered participants in our sample. Moreover, the behavioral tapping effect increased with continuous hoarding tendencies: SIR total scores, the SIR subscale for trouble with excess clutter in the home, and the SCI need for control over possessions , and right parahippocampal gyrus including retrosplenial cortex . After mDuring the Outcome period, within the ROI, no regions were significantly more active when one’s own pretzels were trashed compared to all other possibilities, but there were significant negative correlations in left and right NAcc with hoarding tendencies for trouble discarding and emotional attachments to possessions . When onPeople are often surrounded by things that they value and retain for a variety of reasons, beyond market value and simple utility, including personal attachments, associations with past memories, and representations of one’s identity . Much ofWe hypothesized that endowment and hoarding tendencies share an underlying mechanism, which includes the fear of losing a valued possession alongside a strong, positive appraisal of valued items that also motivates us to want to save them. To demonstrate a relationship between endowment and hoarding, while measuring both the negative and positive associations, we developed a novel Pretzel Decorating Task (PDT). This task combines the benefits of endowment and HD tasks because it uses items that people considered to be “theirs” and that they became attached, which are also be relevant to other people, even when offered in multiples. The task was supplemented with ratings to document people’s monetary valuation of their own and others’ items, negative feelings about potentially losing the items and their positive appraisals of them. Moreover, the task uniquely measures people’s behavioral effort to try to save their items from loss. Finally, all of these measures could be associated with non-clinical, individual differences in hoarding tendencies.The task was also practical because it permitted multiple, repeated trials of saving and loss using visually similar items, as is required for fMRI. The fMRI design also allowed us to segregate activation associated with distinct phases of ownership including appraisal, effort to save the item, and the response to losing or saving it . BecauseThis pilot study of the novel PDT was successful. Most importantly, it produced a strong endowment-like effect and clearly demonstrated people’s reticence to give up an item that they considered to be their own. Participants’ ratings also demonstrated, like in endowment tasks, that people monetarily overvalued their items over others’ and anticipated greater distress associated with their potential loss. In addition, we documented positive motor-motivational processes, as participants rated their items as nicer and physically worked harder in the scanner to try to save them from the trash. Finally, we were able to demonstrate the relationship between these forms of valuation and hoarding tendencies, across participant ratings, behavior, and in the brain. Taken together, the PDT has value as an ecologically-valid way to measure ownership that is amenable to testing in typical and pathological populations.Our brain activation data were often null, in small regions, or in areas that we did not specify in our ROI. Generally, activation within our ROI (NAcc and insula) depended upon participant engagement and hoarding tendencies, in which case, effects may have been stronger with diagnosed HD patients. It is possible that participants were not motivated enough by the desert pretzels to engage these regions. For example, people vary in reward sensitivity and mesolimbocortical engagement increases to appetizing foods with participant individual differences in behavioral activation system (BAS) drive . Rather, preferences were largely similar across participants—demonstrating that the appraisals were not particularly idiosyncratic. Moreover, because effort was still always higher for one’s own items, the effect implicates ownership and the impacts of creation.People did value nicer looking items more—both their own and others’—but efforts to save items remained higher for one’s own over others’ items across the spectrum of item quality, from least to most desired items. This demonstrates a role for positively appraising our own items during endowment and hoarding processes. Participants agreed upon which pretzels looked nicer and were willing to work harder for nicer ones whether they made them or not. This means that the overvaluation cannot just reflect the fact that one’s own items were catered to their idiosyncratic preferences  . ImportaIn addition to sensorimotor processes, regions that support visual processes, episodic memory, and object associations were involved in our task—which have been previously implicated in HD. In this study, a small region in parahippocampal gyrus and retrosplenial cortex was more active when participants worked for their items over others’ and for nicer items. In HD, this region was also more active in HD than healthy control participants when deciding whether to discard their junk mail or not  and paraThere are some limitations to our study, which is natural given that this was a pilot demonstration of a task using a moderate number of participants. Researchers have suggested larger sample sizes for a robust test of individual differences . We also intentionally used a food item because it easily allowed us to quickly attach people to items that would be considered theirs but that they would still consent to losing, and that could exist in replicates without diminishing returns . We expect this response to generalize to material goods e.g., , but thiIn addition to the initial goal of using the Pretzel Decorating Task to study endowment effects and hoarding tendencies, the PDT is also well-suited to interrogate mesolimbocortical reward process more broadly, including in healthy control individuals and patients with a variety of conditions. For example, the PDT can be used to study disorders that involve anhedonia, trouble anticipating pleasure, low motivation, or trouble incorporating positive and negative feedback from impairment in the frontostriatal circuit, such as in depression, schizophrenia, Parkinson’s Disease (PD), substance abuse disorder, and subsequent to damage to the frontal lobe or striatum e.g., . For exaThis research should be extended to other socioeconomic groups or cultures, as this was a Western, American sample, taken from a population with relatively high wealth and education. It is likely that edible items that people create and their possessions more generally are valued in other cultures and contexts; however, more collectivistic or less materialistic cultures may not be as susceptible to effects of excessive acquisition, materialism, ownership, and personalization see .There are a few effects that often occur in the lab or in the brain that we did not find. There were no effects of loss probability across our ratings or behavioral measures. One might suspect that this was not implicated because our actual outcomes were fixed, but this seems unlikely given that people did work harder for their items throughout the task, and it would be difficult to discern the disparity between reality and our largely accurate but fixed outcomes. This null effect might follow from the general tenant that loss aversion only holds for risks with an equal probability to win or lose , but futThis study contributes to the literature by highlighting the degree that endowment and hoarding processes share attributes, involving both negative feelings of potential loss as well as positive, motor-motivational processes. These results cast ownership as more of a dynamic feedback loop, wherein the motivation to acquire something—and our attachment to it—fuel our effort to retain it and our reticence to let it go. This is a personal and relational process that is not purely “irrational” or “disordered,” and should not only be studied with money or in pathological cases. This is a normative process that is adaptive and that likely emerged from organisms’ important need to save resources and one another . These tThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by University of Michigan IRB. The patients/participants provided their written informed consent to participate in this study.TL was responsible for final data analysis and manuscript preparation. BV, RS, and SP contributed to study design and analysis plan. BV completed participant testing and initial data analysis and manuscript drafting. SP was responsible for funding, project supervision, and final manuscript preparation. All authors contributed to the article and approved the submitted version.This research was supported by a grant from the Templeton Foundation to SP and from the University of Michigan to SP; the funders were not involved in the study design, preparation, or submission.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Common Misconceptions about the Phonological Deficit Theory of Dyslexia” and described this theory as “a model of true scientific progress” and a clear “success story”. In this note, I argue that at least part of the success of this theory is due to the lack of explicit predictions which make it very difficult (if possible) to test its predictions, and, possibly, falsify the theory. Some areas of pertinent research, including categorical phoneme perception, picture naming, and phonological awareness are summarized. Furthermore, two lines of research in which groups of researchers have attempted to formulate more explicit predictions are briefly outlined. It is concluded that, although much research has variously referred to the phonological deficit theory of dyslexia, the resulting large body of evidence presents a complex pattern of results which, in the absence of an explicit formulation of the theory, is extremely difficult to frame within a unitary interpretation. Overall, what seems needed is a theoretical formulation that, on the one hand, can account for the complex pattern of available evidence and, on the other hand, provide testable predictions for future research.In a recent paper, Share discussed four different “ Neurobiological Basis of Developmental Dyslexia”, Share [Common Misconceptions about the Phonological Deficit Theory of Dyslexia”. In general, Share described the phonological theory as “a model of true scientific progress” and a clear “success story”. It is true that this proposal has gained a large consensus among the scientific and clinical community. Indeed, even some definitions of dyslexia variously refer to the role of deficits in phonological processing, potentially biasing the selection of participants . Howeveion, see , e.g., a skills” .Phonological Deficit Theory of Dyslexia” is due to the lack of explicit predictions which make it very difficult (if possible) to test, and, possibly, falsify the theory.In this brief opinion paper, I argue that success is not the entire story for a scientific theory; rather, the critical factor for a model/hypothesis/theory is to provide explicit predictions that can be tested in experimental research by the scientific community. In other words, what seems important in the evaluation of a scientific proposal is the possibility to falsify its statements through empirical research. The argument I will briefly develop here is that at least part of the success of the “theory”; later in the paper, he referred to this idea as a “hypothesis”. Indeed, if one looks at the very large literature on the topic, this ambiguity is not occasional. Researchers referred to the idea that dyslexia is due to a phonological deficiency as a “core deficit hypothesis”, a model, or a theory. The term “theory” is more demanding as it should refer to a set of explicit and inter-related statements on the relationship between a set of phenomena. Is this the case for the phonological deficit theory of dyslexia? Despite the very large literature on the topic, there is no formulation of the theory that is sufficiently explicit to be directly testable. For example, Ramus and Ahissar [The general consensus is that dyslexic individuals’ phonological representations are degraded ”. What does it mean that phonological representations are degraded? In their quote, Ramus and Ahissar [This is a difficult question to answer, because such representations can never be directly observed. Rather, their properties have to be inferred from patterns of behavior on phonological tasks. A reasonable assumption, however, is that a person lacking phonemically structured phonological representations would find phoneme awareness tasks difficult or impossible to perform”. Thus, in this perspective, phoneme awareness (PA) tasks are considered critical measures of the phonological deficit. It is well known that as a group, children with dyslexia are impaired in phonological awareness tasks, such as deleting or adding a phoneme to a word or a pseudoword [A first point that, in my opinion, needs to be considered is that there seems to be no clear and explicit description of the proposal that dyslexia is caused by a phonological deficit. In his title, Share referred to this as a “ Ahissar  said tha Ahissar  pointed  Ahissar  acknowleeudoword . The criI argue that PA is only the “tip of the phonological iceberg” and that “deeper” spoken-language phonological impairments among dyslexics appear well before the onset of reading and even at birth.” Elsewhere: “Together with phonological awareness, this phonological ensemble was collectively labeled “phonological processing”. In general, Share [The torrent of converging research findings came to the boil in the final decade of the twentieth century with numerous independent reviews and meta-analyses of the research literature …, spilling over into the early years of the 21st century”. Furthermore, Share noticed that the popularization of the theory “well beyond the bounds of the research community” produced “inevitable misunderstandings and misconceptions”, the focus of his presentation.Share  himself l, Share  seemed tensemble”, “iceberg”, or “torrent” represents an effective communicative means. However, it seems clear that this does not substitute for an explicit formulation of the theory. Below, I will provide a few examples of areas in which the lack of explicit predictions impedes a thorough evaluation of the theory. Accordingly, the goal of the present brief note is not that of a comprehensive evaluation of the theory . Rather, I will focus on some critical research areas to highlight the interpretive difficulties that arise from the fact that the theory is under-specified.Using metaphoric expressions such as “a steady accumulation of convergent findings pointed to subtle sub-clinical abnormalities in preliterate spoken language among dyslexics.” On the one hand, the idea that these sub-clinical abnormalities precede the literacy disturbance appears important in that it places the reading disturbance within a broader linguistic perspective; on the other hand, the fact that the supposed deficits are “subtle” and “sub-clinical” makes it difficult to exactly predict which deficits are expected under which conditions, and which failures to detect deficits would run against the theory. In other words, there is a risk of circularity such that subtle deficits may be present, thus confirming the theory, but they may also be difficult to detect (because of their subtlety) so that their absence does not actually disconfirm the theory. Share quoted a number of signs, including “word-finding and word-retrieval problems, difficulties recalling addresses, telephone numbers, the days of the week or months of the year, foreign names and places, early speech production and later articulation difficulties especially with phonologically challenging material such as tongue-twisters.” Clearly, these are descriptive examples impinging on very different linguistic processes and do not represent explicit predictions. It would be hard to imagine that the theory is disconfirmed by the failure to find any of these putative deficits.The phonological theory of dyslexia seems to rest on the idea that a number of phonological defects actually precede the difficulty encountered by the children when learning to read. In Share’s words: “positive” findings, there are also “negative” findings. In a systematic review, Ramus and Ahissar [the most obvious prediction of the degraded phonological representations hypothesis should be that dyslexic individuals speak differently. However, there is very little evidence for that.” Below, I briefly critically examine some research themes considered critical in the evaluation of the phonological deficit theory of dyslexia.As stated above, the literature on linguistic correlates (or antecedents) of dyslexia is very large and a systematic summary of this body of research goes beyond the scope of the present note. However, it seems clear that along with “ Ahissar  emphasizthe degraded phonological representations hypothesis should predict wide-spread disruption of the categorical perception of phonemes”. By contrast, the evidence reviewed by these authors indicates that results are very variable, with studies reporting deficits in phoneme perception only in a sub-group of children or in some specific conditions and others finding no actual group difference. A similar pattern emerges when the results refer to the detection of phonemes under noise (a condition expected to enhance the sensitivity of the task); again, the results are mixed with different outcomes. Ramus and Ahissar [In their review, Ramus and Ahissar  stated t Ahissar  conclude Ahissar ,8 report Ahissar  are not post hoc interpretation. Overall, it seems over-reaching to include, without further qualifications, picture naming among the tasks which reliably confirm the phonological deficit theory of dyslexia as done by Share [Another research area generating a host of mixed results is that concerning picture naming. Share  listed cby Share .A closely related but distinct line of research is that which goes under the name of rapid automatized naming  tasks and vice versa, an observation which is at the base of the double-deficit hypothesis of dyslexia . This paOverall, data on multiple-display RAN tasks indicate a consistent impairment in children with dyslexia. However, due to the absence of impairment with single display presentations, the nature of the disturbance does not appear consistent with a phonological interpretation but requires the contribution of other factors . More gOver the years, phonological awareness (PA) has been an area of great debate. Furthermore, misconceptions 1  is just about deficits in phonemic awareness (PA) and, consequently, is merely a circular “pseudo-explanation” or epiphenomenon of reading difficulties”) and 2 (“Deficits in PA (and other reading-specific skills such as pseudoword naming) are circular or pseudo-explanations of reading difficulties”) described by Share ). Howevephonemic awareness is not a universal and emergent linguistic capability but is best categorized as a reading subskill.” How does one avoid then the risk of possible circularity connected with the interpretation of performance in PA tasks? The critical point in Share’s analysis is the proposal that PA must be seen as a proximal precursor (or risk factor) of reading not as a  cause. The distinction between proximal and distal causes has been important in the genesis of cognitive neuropsychology. In general, cognitive modeling has been concerned with developing architectures that describe how some proximal factors and their interactions may account for a given target behavior [distal” if they affect behavior only indirectly by influencing the proximal factors in the model. Notably, cognitive skills are neither proximal nor distal as such; rather, this distinction refers to the way in which one looks at a given cognitive factor .the present meta-analyses are consistent with the claim that the development of phonemically structured phonological representations is one critical foundation for learning to read successfully in an alphabetic script … and that a failure to develop such phonemically structured phonological representations is a principal cause of the difficulties in learning to read experienced by children with dyslexia …” [Personally, I think that framing PA performances in proximal terms is an interesting proposal with potential intriguing implications and developments. Still, it should be observed that this can hardly be seen as a clarification of a common misconception about the role of PA. Indeed, the up-to-date most extensive review of the literature on PA  concluded that “lexia …” . Thus, tlexia …” , is not together with phonological awareness, this phonological ensemble was collectively labeled “phonological processing“. Yet, the “ensemble” term points to the collective and unstructured nature of this set of predictors. Thus, seeing PA in proximal terms has the direct implication that one expects the nature of the relationship with reading to be spelled out more clearly as part of a structured cognitive architecture. It appears that this enterprise still needs to be fulfilled.I think it is important to spell out the implications of PA when seen in a proximal perspective. Proximal factors come to life within cognitive architectures of a given behavior. Particularly, one expects that a cognitive architecture makes explicit the nature of the relationship between the predictors and the target behavior. A few authors have proposed descriptive sketches of the processes involved in reading  which cdistal” predictors. On the one hand, the actual relationship why a failure in a task such as balancing a rod (or detecting the movement of a grating) should impair reading is not explicitly spelled out ; however, on the other hand, they do not suffer from the close circular relationship with reading which affects PA tasks. Thus, it is hard to see how learning to read influences the acquisition of skills such as balancing a rod or detecting the presence of movement.A second implication of seeing PA in proximal terms is that PA measures can be examined along with other proximal predictors although they should not be directly compared with measures aimed to capture long-range  relationships with reading. There is a very rich tradition in the research on dyslexia as to examine possible mechanisms which represent the basis for the reading disturbance . For example, studies have examined the possible contribution of impairments in magnocellular processing , in tempAn implication of this reasoning is that in predicting dyslexia, proximal and distal predictors serve different purposes and should not be mixed in a direct comparison. However, in various studies, PA tasks have been used along with measures aimed to capture underlying basic mechanisms. For example, Ramus et al.  comparedIn a different study, Saksida et al.  aimed toA third implication of seeing PA tasks as proximal predictors is that one may want to consider whether deficits in basic sensory mechanisms underlie the observed impaired performance in PA tasks, hence providing a comprehensive theoretical proposal of the phonological hypothesis. Some authors have taken this perspective. For example, Tallal  has propTo summarize, seeing PA tasks as proximal predictors may avoid circularity in the causal interpretation of the disturbance, as proposed by Share . HoweverFinally, it should be added that these comments apply to the population of children with dyslexia as a group and this is certainly an over-simplification. It is well established that there are large individual differences in PA tasks, with several children behaving well within normal limits . A compAs described above, several authors have framed their results within the phonological deficit theory of dyslexia even in the absence of explicit predictions. However, in a limited number of instances, groups of researchers have attempted to formulate more explicit predictions derived from their understanding of the theory. Considering these approaches and the related findings is interesting and informative for an evaluation of the phonological deficit theory of dyslexia. Two such lines of research will be briefly outlined below.In a series of papers, Berent et al. ,8,43 disIn studies on individuals with dyslexia speaking either Hebrew ,43 or EnOverall, the studies carried out by Berent et al. ,8,43 indAnother significant line of research aimed to characterize the nature of the putative phonological impairment in dyslexia has been developed in a series of studies by Ramus, Szenkovits, and colleagues ,45,46. TThe first set of experiments was exploratory in nature ,45. Theythese results fail to confirm the predictions of the “degraded phonological representations” hypothesis” [Second, Ramus and Szenkovits  examinedothesis” .this runs against any variant of the degraded phonological representations hypothesis that involves a degradation of voicing or place features.” Furthermore, they stated that “the results we obtained here suggest that dyslexic individuals have both intact phonological representations and a normal phonological grammar, or that if their phonological representations or grammar are affected, they are so subtly affected as to seriously diminish the plausibility of such degradation significantly affecting reading acquisition” [Finally, Szenkovits et al.  also tesisition” .Overall, these two groups of researchers have tried to derive explicit and testable hypotheses to support or disconfirm the phonological deficit theory of dyslexia. Both investigated the question of phonological grammar although from a partly different perspective. Berent et al. ,8,43 focNote that even negative results may not necessarily lead to a rejection of the theory. For example, Ramus and Szenkovits  made theAs stated by Share , in the If one wants to make a scientific advancement, what really seems needed is an attempt to make a theoretical formulation that, on the one hand, can account for the complex pattern of available evidence and, on the other hand, provide testable predictions for future research. It is my hope that this note may contribute to foster this process.


The COVID-19 pandemic highlighted significant structural barriers that exacerbated health inequities among people at-risk for overdose. Digital health technologies have the potential to overcome some of these barriers; however, development of these technologies often fails to include people who use drugs and community key stakeholders in the development and dissemination process. Consequently, this may exacerbate health inequities and the digital divide among underserved, highly vulnerable people who use drugs.N = 74 key stakeholders  to inform initial design and development.The current study employed community-engaged research methods to develop and implement a digital platform to improve overdose surveillance among harm reductionists in Texas. We used a co-design process with four community advisory boards (CABs) and conducted qualitative interviews among Several key themes emerged through the qualitative data pertaining to technical features and human factors applications. In regards to technical features, participants highlighted the importance of developing a unified system of overdose reporting and data sharing among community organizations within a county or region to better inform overdose surveillance and community outreach efforts. This system should include flexible data entry methods, have offline usage capability, be user friendly, and allow for tracking of overdose-related supply distribution. Key human factor themes included the need to use person-centered language, to preserve the established trust of the community organizations among people who use drugs, to be tailored to specific target user groups , and maintain transparency of data usage. Further, participants noted the importance of developing a platform that will facilitate client conversations about overdose when doing outreach in the field. These themes were reviewed by our CABs, academic, and industry partners to design an overdose digital platform uniquely tailored to community-based organizations providing harm reduction and overdose response efforts.Community engagement throughout the development process is critical toward developing digital health tools for underserved people who use drugs. Dismantling the power structure among academic and industry partners is critical toward creating equity in engagement of community-based partners, particularly among persons with lived experience in addiction, a history of incarceration, or financial challenges. Our study highlights a multisectoral co-design process across community-academic-industry partners to develop a digital health tool tailored to the unique needs of community-based harm reduction organizations serving highly vulnerable people who use drugs. These partnerships are essential toward creating impact and reducing health disparities among highly vulnerable people who use drugs. Overdoses involving opioids and other substances were declared a public health emergency in the United States in 2017 and have reached historically devastating numbers during 2021 . It is cThese data are often housed in disparate systems which limit opportunity for integration and systematic analysis . ImportaDifferent approaches need to be considered in digital health technology development targeting PWUD, particularly among doubly vulnerable minority populations. Employing community engaged research methods through co-collaboration with PWUD throughout technology design and development works to mitigate exclusion of the very population it is meant to serve . When inCommunity based participatory research (CBPR) is a co-collaborative model that re-aligns traditional “researcher-subject” hierarchies to promote partnership and respond to community priorities . The comTexans Connecting Overdose Prevention Efforts (TxCOPE) is a digital health ecosystem developed through employment of CBPR, a community engaged research approach. Similar to other states in the United States, Texas currently does not have a unified, comprehensive digital system in place for fatal and non-fatal overdose reporting and tracking, contributing to the gap in comprehensive, real-time collection, dissemination, and analysis of overdose data . TxCOPE We employed principles from community-engaged research and user-centered design to inform our co-design process and formative research approach. Community-engaged research re-aligns typical researcher-subject hierarchies to involve communities, elevate their perspective within the research and solutioning process, and dismantle existing power structures , 10. UseOur pre-design process consisted of three steps: establishing community advisory boards, conducting formative research, and preparing for the co-design sessions.One method in community-engaged research is the development of community coalitions of key stakeholders and individuals with lived experience . In thisN = 74 key stakeholders and people with lived experience  across the four pilot counties in Texas to inform initial design and development. These interviews were between 60 and 90 min in duration and participants received compensation in the amount of $30 for their time. The following research questions were addressed in interview: (1) How do stakeholders engage in the field of drug overdose perceive existing overdose and naloxone data in the State of Texas?; (2) How do stakeholders engaged in the field of drug overdose currently report opioid-related data? ; (3) What are the perceived problems or negative outcomes associated with underreporting overdoses in Texas?; (4) What are stakeholders engaged in the field of drug overdose perspectives on other existing data reporting programs?; (5) What are perceived solutions to improve the tracking of overdose-related variables?; and (6) What methods should be used to implement this system to promote widespread adoption and sustainability?Activities during this step included conducting a scoping review, series of field observations among harm reduction organizations and street outreach teams, and qualitative interviews with key stakeholders. These data were triangulated to understand existing overdose surveillance methods, gaps in data collection and reporting, and perceived solutions to improve overdose data to inform community response efforts. Qualitative interviews were conducted among a series of In interviews with PWUD, the research questions addressed varied slightly and reflected the following: (1) Do people who use drugs currently report overdose-related data? If yes, among this population who is more likely to report and why? If no, what are the reasons this population does not report and how often do they think overdoses occur and are not reported?; (2) What methods will increase the likelihood that people who use drugs will report overdose-related data ?; and (3) What methods should be used to increase adoption and sustainability of an overdose reporting system among people who use drugs? Semi-structured interview guides and debriefing guides were created for each interview group. The interview guides were composed of structured, open-ended question, and provided flexibility for the interviewers to adapt and clarify questions as needed. Methods and results for the qualitative interviews are described below.During the Co-Design Phase, our academic team lead coordination of all aspects of the project and facilitated meetings with our technology team, Maven Wave an Atos company, and our community partners. This included multisectoral meetings focused on framing the problem, conducting generative design work, sharing ideas for technology design and development, reviewing wireframes and low-fidelity prototypes, and iterative testing and refinement. We completed preliminary data analysis throughout this phase using the framework matrix method for efficiency.The Post-Design Phase consisted of a pilot test across participating harm reduction organizations to assess feasibility and refine the technology. Data were formally analyzed during this phase using Applied Thematic Analysis. Finally, we developed a plan for scaling and implementation. This included hiring a local street artist to develop promotional materials and artwork. The inclusion criteria for qualitative interviews with medical examiners, justices of the peace, harm reductionists, and other key stakeholder representatives included: (1) eighteen years or older, (2) employed in one of the target counties  or have relevant experience that will inform statewide efforts; and (3) ability to read and speak in English. The inclusion criteria for people who use drugs (PWUD) included: (1) eighteen years or older, (2) reported misuse of opioids or stimulants in the past 3 months, (3) resides in Texas, and (4) ability to read and speak in English and/or Spanish. The exclusion criteria for all participants included: the inability or unwillingness to provide consent, being actively suicidal, or psychotic.Screening for prospective participants consisted of a short (5–10 min) screening survey conducted over the phone or through email and was coordinated by the research team. When the inclusion criteria were met, the research team would then provide and obtain informed consent. During the consent process, participants were informed about the purpose of the study and all procedures. Participants were told that the interview would be audio-recorded and then transcribed verbatim. The transcripts would be cleaned and all identifying information would be removed then audio-recordings would be deleted. Participants were given time to review the consent form in-depth and ask questions. Participants were given a copy of the consent form for their records. Participants protected health information were removed and had a unique ID number assigned to them. Recruitment methods were comprised of in-person (when permitted), flyers, e-mails, telephone, snowball sampling, social media advertising, web-posting, word of mouth, and using CABs in each pilot county to assist with recruiting. In total, we recruited and interviewed 24 people who use drugs, 20 harm reductionist, 20 first responders, and 10 overdose prevention and response experts before reaching data saturation.Qualitative interviews were conducted by videoconference and in-person, when permitted, with two trained researcher staff. One researcher conducted and led the interview while the other co-facilitated and took notes. After the interview was completed, the audio recordings were transcribed verbatim by a confidential professional transcription agency. Transcripts were then cleaned and scrubbed of all personal identifying information. Once returned, the cleaned transcripts and the debriefing guides were used for analysis.Qualitative interview data were analyzed using applied thematic analysis and triangulated to inform development of the TxCOPE digital ecosystem. Data from the qualitative interviews were analyzed using applied thematic analysis which was selected for its flexibility and systematic approach in analyzing text-based qualitative data while planning as well as preparing for the data collection . The resData analysis was conducted by six trained coders  using a reflexive analysis approach. The process involved assigning two team members per transcript to be coded independently using the corresponding codebook. Once independent coding was completed the two coders met to resolve discrepancies in the coding using the reflexive team approach to resolve any discrepancies. Once a consensus was met the coders finalized the coded transcript. During coding additional relevant data and themes emerged resulting in multiple revisions of the codebook. In order to organize the data collected during interviews, framework matrices were developed. The debriefing guides and cleaned transcripts were used to identify emerging themes and house direct quotations from the interviews. Once the data reached saturation, the emergent themes were collected from the coded transcripts and framework matrices. Data saturation was determined to be achieved when no new information was obtained in new interviews on key research questions . Severaln = 24 people who use drugs; n = 20 first responders, n = 20 harm reductionists, n = 10 overdose prevention and response experts) were conducted. Participants included: emergency department and hospital employees (11.1%), EMS (22.2%), epidemiologists (3.7%), fire department (12.9%), harm reductionist (35.1%), law enforcement (1.9%), poison control (1.9%), substance use treatment providers (5.6%) and other key stakeholders  (5.6%). See Qualitative interviews with 74 key community stakeholders .The advisory boards and harm reduction organizations viewed obtaining data from this population as key to be able to have real-time, meaningful data that will inform community overdose prevention and response efforts. “I do think a more comprehensive app and website would be useful, but then like, more trust would have to be established and that there would also have to be ways to…ensure that people without access to technology would, maybe even like, maybe if there is like, an incentive for people to like, report an overdose, but I think that would definitely have to be carried out by a harm reduction organization because I just feel like that's where most trust is placed in the community” .In regards to technical features, participants commented on the need for ease of use, discussed the complexity of location documentation, and identified several features for the digital platform.In terms of technological features, participants highlighted a need for flexible data entry methods, offline usage capability, and for simplicity and ease. First responders requested simplicity but also repeatedly noted compliance might be poor and that pulling data from the existing system would be better because they already have systems in place. One first responder stated “don't make something complicated and I think it will piss people off if they are like, ‘I already entered this”' . Harm reduction workers and PWUD commented on both apps and website portals. Participants highlighted the importance of accessibility as it relates to equity in adoption and data reliability: “if different people are going to be using it you have to make it really easy to understand because then you get misclassification of information.” . Another participant noted, “It should be very practical and easy to use, uh, where they are not able—where they're able to just, um, like a one-, two-, three-step—not make it more than that because, uh, they might get fatigued, as it is, they're already using [drugs], you know—-so their patience is not too good, you know, so I think we have to keep that app very practical” .The ability to download an app in the iTunes and Google Play stores was often mentioned but responses included those who preferred to log into a web portal because some participants expressed privacy concerns regarding a mobile application: “I think that most people have phones, right? Um, even folks that are homeless out in the community have phones. So I think that, if there was a really easy, free, downloadable app that people could use to report these, I think that they would report “em”” . One PWUD felt an app would be fine for their peer group but would not work for everyone because of phone access issues: “For my cohort of people, an app would be very effective. But for people that don't have or use apps, that's not gonna help them” . Another PWUD commented on concerns about privacy with an app: “Not something that, like, a lot of things that you gotta sign up and put your name and put your email and create a username and a password and all that, like, no” . This was echoed by other PWUD, “I don't trust the phones” .Regarding simplicity and ease of use, one EMS worker said “Yeah, I think you're gonna get a lot more use if it's kind of binary, in the sense that it's—you know, you can just—you can click through options. You know, the less that someone has to freeform an answer, and I hate to say it, but like the less somebody has to write a narrative, the more likely it is that they'll use it consistently because it's easy” .Many participants ranging from harm reduction workers to PWUD highlighted a desire to use the platform quickly and many brought up drop down options. One law enforcement officer highlighted utility of drop downs: “I mean, guess ease of use, right. Drop-down menus are super easy. You just click-click check boxes or whatever” . For EMS workers, integration with current systems was a highly desired technical feature. One EMS worker felt this was critical to utility: “So, having it integrated into my EPCR and makin' it to where I can't close it without doing it would be the only way to get the 100 percent compliance” .Preferences on overdose incident location documentation varied between those who valued granularity down to the zip code or community/neighborhood level. Harm reduction workers noted that more precise location data would allow them to make data-driven decisions for community outreach strategy. First responders noted zip codes would be helpful whereas PWUD noted areas of town or general neighborhoods where the overdose occurred, and more importantly to them, where the drugs were purchased. Taken together, there seemed to be perceived value in documentation of location of overdose, but groups viewed locations somewhat differently.For example, one first responder  said “Oh, man. Well, if it's going up to the state, I would think some sort of, you know, uh, well, the state employees should be able to have access to it so that maybe they can see if they're having, like, a spike in, say, zip codes or that kind of thing. You know what I mean? That way they could, like, maybe have better, uh, communication with the local municipalities as far as, you know, “We've been tracking numbers and we show that in your zip code that it spiked, like, 20 percent,” or whatever. You know? That kind of thing...Yeah. I think it should be local and state should have access to it. Definitely.”One harm reduction worker in an urban area said “I think at least being able to see if there are neighborhood clusters. Or a particular area. I mean that would be incredibly helpful for our services. I mean, if we could see that a bunch of people overdosed even if we didn't know from what, if there is like a spike in the map. And we–and other organizations–could figure out what's going on in that community” . Another harm reduction worker highlighted the need to document where the drugs were from, not just where the overdose occurred. “if I'm still using drugs part of what I wanna know is where did the drugs come from. People get drugs from different places, so one of them is like a hotspot for someone who deals drugs that are knowingly filled with fentanyl” . This was echoed by PWUD “...and they can also report whether an emergency call was made, whether Narcan was used or not used, what substance it was, just a general part of town” .Features desired included components such as documentation of overdose context, polysubstance use, interventions administered such as reversals or rescue breathing, and location of the overdose incident. A popular feature among harm reduction workers was the ability to track resources such as naloxone. For example, one harm reduction worker had the idea that this could facilitate resource sharing: “sometimes, um, I ran-I ran out of testing strips or I ran out of Narcan and then, um, usually I just ask other agencies in the area, ‘Hey do you—can I have some testing strips or Narcan?’ And they usually have a bunch that they didn't use. So maybe a button or a link to ordering more” . This was echoed by an EMS worker: “Um, I think if-if Narcan was available in the community, that would be helpful to be able to know, like, where you could get it, how you could get it. That sort of thing. And then, if you did have it and you administered it, then it would be nice, like you said, to have an app or some sort of software or internet access to where you could document like, “Yes, I did use this community, uh, resource, and it was effective.” You know what I mean?” .PWUD added additional features related to the desire for the website to include resources such tutorials on vein care or naloxone, or where to get treatment. One PWUD noted, “like some of these, um-some of these, uh, website or, um, mobile apps, um, they have, uh-they have a option on there where you can either, you know, go into like a frequently asked questions section— or you can type in, um, you know, a keyword like “help” or, um, uh, you know, “information” or “info” or something. And then you can have some kind of bot respond back to you, you know, about giving you options about what you, you know, want information on, or what you want help with. You know, and you can get all kinds of resources like that, you know, if - if you're looking to get some kind of, uh, um, recovery services or, um, emergency services, you know, poison control numbers. Yeah. Yeah, anything like that, um, I - I - I think that's definitely something that either already exists or should exist by now, but, um, yeah, that's definitely a—I think it's a good idea.” .One harm reduction worker added that including treatment resources may require tailoring to each community: “Here are our services. Here are different organizations,” and that kinda, like, for example—but then the problem with that is you're gonna have to regionalize it. “Cause, like, somebody in, uh, Dallas has no benefit from knowing that [harm reduction organization] does HIV testing from one through five” .Participants were provided the opportunity to reflect on how overdose reporting could be improved. Themes from these questions included data accessibility, data integration, and privacy concerns.Regarding the technology, harm reductionists and the SUD treatment providers endorsed accessibility of the surveillance data. Some harm reductionists were excited about the idea of unified data across the state, and having “Just one system where everyone could go to one place” . One PWUD suggested that alerts could be used to notify users when overdose rates increase in their area . Several EMS/Fire respondents noted that they already record overdose data, and so an efficient system would pull data from their records: “the system that we have right now is pretty good. I'm happy with it, and, like, it has all that stuff you need as far as drugs and-and overdose tracking” . Several EMS/Fire respondents suggested that state-mandated reporting would be helpful: “I think that if the state were to mandate collection of the data, then I could see administration either mandating us to go and fill out those forms and referrals, or just designating somebody to collect that data” .Harm reductionists, EMS/Fire, and poison control respondents highlighted the importance of combining data sources: “there's so many different systems that trying to make sure that it isn't a duplicate or that we're not missing something or, you know, whatever it is, um, that's probably, one of the harder things” . Another participant highlighted challenges with obtaining real-time overdose data and the need for data aggregation across systems: “I don't think you can create anything that's gonna give you all the information in real time that is experiencing overdose. I don't. You're gonna need a combination of reporting” .Some harm reductionists suggested that shared data could create opportunities for collaboration across harm reduction organizations, while others suggested broader impacts of reporting for PWUD: “I feel like that should be the goal, to empower our [clients] to be able to report that information when needed and as they feel comfortable” . Another harm reductionist highlighted how this might facilitate empowerment among PWUD: “That would empower them, that would make them feel like they are worthy of being cared for and better” . Another harm reductionist noted, “The idea is empowering people in their own health because there is a lot of things in their life that they can't control” . Similarly, one PWUD suggested that more reporting data might help people realize how much more common overdoses are, and this would allow for increased funding .When asked about their open-ended goals, harm reductionists commonly cited the need for changes to public policies in Texas: “I think it would be great if there was buy-in from all of our counties across the state…. I think you could create an amazing infrastructure and website, and then if you don't have the political will to get people to use it, then it will be similar to some of the stuff we already have ” . Another participant noted, “I would first have to change state policy where programs have to collect this information or are allowed to work with this population without fear of losing their funding. So I would include state policy to include harm reduction services” .PWUD were very concerned with anonymity. Their primary concern was ensuring that law enforcement cannot access their personal information. “People don't report it because they are afraid. Because of an underlying mistrust” . This mistrust was reflected in their suggestions for policy-related improvements. PWUD indicated that their peers were unlikely to report overdoses through existing channels due to mistrust, and enhancing trust would be an effective path to improved reporting: “If people started having more positive experiences when they did report it, then, you know, word would get around what really happens when you report it” . This same participant then noted: “Like, that's how it happens when you report an overdose. Like, they don't frisk everybody there and threaten to throw them in jail” . Notably, EMS/Fire respondents recognized this perception, but felt it was not accurate: “The perception is that if law enforcement's gonna get involved, you know, I'm gonna go to jail, or my friend's gonna go to jail. And [we need] some kind of massive public education campaign that explains to people that, you know, hey, this is not a criminal activity” .Emerging research estimates that 50–70% of overdoses in Texas go uncounted as a result of the punitive and stigmatizing nature of policies and the fact that only 15 of the 254 counties in Texas have a medical examiner to diagnose overdose as a cause of death . Many PWThis study highlighted the importance of using a co-design process in the development of an overdose surveillance digital platform to facilitate equity across multisectoral partners including harm reduction workers, first responders, and people who use drugs. Community engagement throughout the development process is critical toward developing digital health tools for underserved people who use drugs. We combined community-engaged research and user-centered design methods to serve as the foundation of the co-design process with our community, academic, and industry partners , 10, 11.www.txcope.org/harmreduction). Priorities of the community included HIPAA-compliant, secure, and anonymous reporting form. The overdose report form was designed by the community advisory board (CAB) members with detailed attention to language used throughout the report form. The community wanted to ensure data will be collected for marginalized populations with a priority among trans-people and racial/ethnic populations  grant award number 1H79TI081729. KC effort was supported, in part, by NIDA K23DA039037. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation of the manuscript.The content of this study does not represent the official view of SAMHSA, NIDA, or the Texas Health and Human Services Commission.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.