The result concerns perceptions rather than demonstrated competence. Self-perceived research skills were measured with a 17-item scale covering thinking skills, academic writing and information communication, while academic self-efficacy captured students’ general belief that they could organize and execute actions needed to meet academic goals. All three main constructs were assessed through self-report instruments, making the strong correlation between academic self-efficacy and perceived research ability difficult to disentangle from conceptual overlap, a general tendency to evaluate oneself favorably across domains, or common-method effects. The authors stress that the regression coefficients represent statistical associations, not evidence that confidence or favorable attitudes cause better research performance.

The study used an explanatory–associative, non-experimental design. Data were collected once through a virtual Google Forms survey, with no manipulation of attitudes, self-efficacy or research training. Participants were selected by non-probability convenience sampling from a population of 8,000 undergraduates. The final sample included students from all faculties and academic cycles who voluntarily completed the questionnaires, with incomplete and duplicate records removed before analysis. Of the participants, 52.8% were women and 47.2% men; 56% were under 20, and 46.2% were in their ninth academic semester. Administration was the largest degree program, representing 35.7% of the sample, followed by Environmental Engineering at 14%.

Three validated scales supplied the measurements. The Attitude Toward Scientific Research Scale contained 28 items divided among interest in research, research vocation and evaluation of research, with responses recorded on a five-point strongly disagree–strongly agree scale. The nine-item Academic Self-Efficacy Scale used a four-point never–always format and was treated as a global measure of efficacy beliefs. The Self-Perceived Research Skills Scale included 17 items spanning thinking, writing and information-communication abilities. Confirmatory factor analyses in the present sample supported the instruments’ factorial structures. Chi-square-to-degrees-of-freedom ratios ranged from 1.703 to 1.752, while comparative fit indices ranged from 0.923 to 0.978. RMSEA values were between 0.052 and 0.076, and standardized root mean square residuals ranged from 0.025 to 0.035.

Before interpreting the regression, the researchers evaluated the model’s statistical assumptions. Tolerance and variance inflation factor values were both 0.815 and 1.228, respectively, indicating that multicollinearity was not a serious concern. A Durbin–Watson statistic of 1.96 was close to the expected value of 2, and residual normality was supported by a Shapiro–Wilk result of W = 0.990 with p = 0.081. Residual skewness of −0.22 and kurtosis of 0.48 were within acceptable limits. Visual inspection of residual-versus-predicted plots showed no substantial departures from linearity or homoscedasticity. Maximum Cook’s distance was 0.006 and maximum leverage was 0.007, and standardized residuals ranged from −2.51 to 2.68, so no observations were removed as unduly influential outliers.

The correlations provided a more detailed picture of the relationships. Attitude toward research was moderately associated with academic self-efficacy at r = 0.431 and with self-perceived research skills at r = 0.437; both p-values were below 0.001. Academic self-efficacy and self-perceived research skills had a strong correlation of r = 0.740, also with p < 0.001. Because this latter association was estimated from self-reported measures collected at the same time, it may partly reflect students’ general confidence in their academic capabilities rather than a specific, empirically demonstrated mastery of research tasks. The descriptive means were 100.02 for attitude toward research, 24.92 for academic self-efficacy and 61.27 for self-perceived research skills, with standard deviations of 23.04, 5.63 and 11.18, respectively.

The multiple regression model was statistically significant, with F = 421.016 and p < 0.001. Academic self-efficacy carried by far the greater standardized weight: its coefficient was 0.678, compared with 0.145 for attitude toward research. In unstandardized terms, a one-unit increase in the academic self-efficacy score was associated with a 1.346-unit increase in perceived research skills, while a one-unit increase in the attitude score was associated with a 0.071-unit increase. The model’s R² was 0.565 and adjusted R² was 0.564. These figures describe the model’s statistical explanatory performance for this sample; they do not show what would happen if educators increased either psychological factor or how much of the difference would transfer to a broader student population.

The findings fit a sociocognitive interpretation of university research training, in which efficacy beliefs are related to effort, persistence and willingness to approach difficult academic tasks. They also align with arguments that students who value research may be more inclined to engage in investigative activities. The authors cite research showing that positive attitudes can coexist with methodological weaknesses, including difficulties among Peruvian students in formulating problems and analyzing data with statistical techniques. Academic self-efficacy, attitude toward research and self-perceived research skills are related but distinct constructs: the first concerns general academic capability beliefs, the second captures evaluative and affective orientations toward research, and the third reflects students’ judgments of their own research abilities. Their shared reliance on self-assessment nevertheless makes the especially strong r = 0.740 relationship difficult to interpret independently of measurement effects.

For universities, the results suggest a case for examining psychological conditions alongside technical research instruction. The authors propose gradual, experiential training in which students can observe, practice, analyze and reflect on research procedures, supported by specific feedback, research advising, collaborative groups and access to databases, statistical software, laboratories and repositories. They also point to extracurricular opportunities such as scientific clubs, symposia and institutional journals. These are implications drawn from observed associations, not interventions validated by the present study. The design cannot determine whether mentoring, feedback or improved facilities would raise academic self-efficacy, change attitudes or improve actual research ability. Future work should therefore use longitudinal or intervention-based designs, objective performance measures and assessments of students’ real research competencies.

Several limitations constrain how broadly the results can be applied. Convenience sampling from one university campus limits representativeness, and the uneven distribution of students across degree programs and academic stages may have influenced the scores. Nearly half the sample occupied the ninth semester, so students with more accumulated exposure to research methods may have differed from those in earlier years. The study did not control for academic semester, field of study, age or gender, and the investigators note that these factors should be examined in future models. The single-time-point design also prevents assessment of change over time, while the self-report format introduces potential social-desirability and self-assessment biases. The strongest defensible conclusion is therefore that, among these Peruvian students, greater academic confidence was closely associated with stronger perceived research skills, and favorable attitudes toward research made a smaller but significant contribution. Whether those beliefs correspond to better research outcomes remains a separate question requiring direct performance assessment and experimental or longitudinal evidence.

Subject of Research: Associations between academic self-efficacy, attitudes toward research and self-perceived research skills among Peruvian university students

Article Title: Attitude toward scientific research and academic self-efficacy as statistical predictors of self-perceived research skills in university students in Peru

Article References: Torres Medina, W. E., & Montalvo Apolín, D. E. (2026). Attitude toward scientific research and academic self-efficacy as statistical predictors of self-perceived research skills in university students in Peru. Frontiers in Education, 11, Article 1926983. https://doi.org/10.3389/feduc.2026.1926983

Image Credits: AI Generated

DOI: 10.3389/feduc.2026.1926983

Keywords: academic self-efficacy, research attitudes, research skills, university students, Peru, self-report bias, cross-sectional study, higher education, psychological predictors, regression analysis, Attitude, toward

The review, conducted by Arianna Marci of the University of Genoa and Martina Ragusa and Flavio Manganello of Italy’s National Research Council, followed the PRISMA Extension for Scoping Reviews and searched Scopus and Web of Science for studies published between 2005 and 2025. From 491 deduplicated records, 69 sources met the inclusion criteria: empirical or theoretical work reporting a change in the teaching practices of university teachers following structured faculty development, in any discipline other than medical, dental, nursing, veterinary, or pharmacy education. The authors deliberately excluded health professions education because that field, with its accreditation mandates and routine clinical observation of teaching, has already been synthesized twice and operates under conditions most of higher education does not share. Setting it aside allowed the rest of the field to be described on its own terms for the first time since 2008.

The reviewers charted 498 reported effects across the included sources, organized using the four-level adaptation of Kirkpatrick’s model developed by Stes and colleagues for faculty development in higher education. Level 3, teacher behaviour, is the level most directly tied to what development programs promise: the transfer of learning into actual classroom practice. Of the 498 effects, 217 sat at this behavioural level. And here the review’s central finding emerges. Of those 217 behavioural effects, 150 rested on teacher self-report, either narrative accounts or responses to questionnaires, while only 66 rested on evidence external to the teacher, such as peer or expert observation, student perceptions, or analysis of course artefacts. One effect could not be classified at all.

The direction of effect depended dramatically on who supplied the evidence. Positive effects accounted for 65 percent of self-reported behavioural changes but only 42 percent of externally documented ones, with a quarter of the externally documented effects reporting no change whatsoever. The same asymmetry appeared for measurement design: 65 percent of effects measured without a pre-intervention baseline were positive, against 49 percent of those measured with one. When the two factors were combined, the most demanding configuration, external evidence measured against a baseline, was the only one in which no change was the modal outcome, reported for 14 of its 24 effects. In other words, the predominance of positive findings in this literature is partly an artefact of the methods that produced them.

The methodological weaknesses run deep. Of the 64 empirical studies appraised with the Mixed Methods Appraisal Tool, 29 used non-randomised or purely descriptive quantitative designs, and only a single study employed random assignment. Forty-seven of the 69 sources had no comparison group of any kind. Quantitative and mixed methods studies recurrently showed incomplete outcome data, unaccounted confounding, and undocumented intervention fidelity; in 13 of 23 appraised non-randomised studies, attendance or completion data were absent, leaving the exposure whose effect was being estimated entirely unverified. Only two of those 23 reported complete outcome data. The qualitative work, by contrast, largely met its methodological criteria, though its recurrent weakness was asserting changes in classroom practice on the basis of participants’ self-reports alone.

Perhaps the most striking finding concerns evaluation frameworks. Fifty-three of the 69 sources, more than three quarters, named no evaluation model at all. They described an intervention, chose instruments, and reported results without locating the exercise in any framework. The 16 that did name one did not converge: Kirkpatrick appeared in four, Rogers’ diffusion of innovations and the Community of Inquiry framework in two each, and eight further frameworks in a single source apiece. Notably, the Stes framework designed specifically for faculty development in higher education was used as an evaluation scheme by no source other than the Antwerp papers by its own authors. The field’s apparent theoretical pluralism, the authors observe, rests partly on a category difference that passes unremarked, since outcome taxonomies, theories of individual change, and intervention characterisations are not models of the same thing.

The instrumentation tells a similar story of fragmentation. Only 75 of the 217 behavioural effects rested on a published instrument. The Reformed Teaching Observation Protocol supported 30 of them, more than any other, followed by the Approaches to Teaching Inventory with 15. But 87 behavioural effects rested on instruments the study authors devised themselves, and 55 on no instrument at all. Two thirds of the evidence on what teachers do therefore rests on measures that exist only in the study that used them and cannot be compared across the corpus. The field’s instrumentation is bimodal: a small observational tradition anchored on RTOP and COPUS, and a large body of study-specific self-report measures.

Two sources in the corpus demonstrate the divergence between self-report and observation internally. Ross and colleagues found that the Approaches to Teaching Inventory and the Reformed Teaching Observation Protocol were uncorrelated in the same teachers, with no observed change in RTOP scores while both ATI scales rose significantly. Stes and colleagues found no change in teaching behaviour as perceived by students in the very programme for which an earlier paper had reported an effect on teaching approach. These are not marginal anomalies. They suggest that the field’s principal self-report instrument and its principal observation protocol may not be measuring the same object, and that the choice between them is not a matter of convenience.

The evidence base is also strikingly concentrated. Thirty-six of the 69 sources report on the United States, and 34 of the 39 sources that identify a disciplinary context are in engineering or other STEM fields, chiefly biology. The median study involved just 36 teachers, and 41 of the 69 sources were published between 2020 and 2025, making this a young and geographically narrow literature. What is known about faculty development’s impact on teaching practices, the authors conclude, is largely what is known about STEM teaching in North American universities. Whether the findings transfer to other disciplines and other systems remains an open question the corpus cannot answer.

The authors are careful about what their findings do and do not imply. None of this, they write, means that faculty development fails to change teaching practice. It means the literature, as presently constituted, is not in a position to establish that it does. The remedies they propose are modest and mostly consist of reporting what programs already know about themselves: naming the instruments used, recording attendance and completion, reporting attrition, and collecting a baseline of some kind, however crude. External observation of a sample of teaching, they argue, is not a refinement reserved for research but the only evidence that speaks directly to what teachers actually do, and the RTOP and COPUS tradition demonstrates that it can be organised at the scale of hundreds of sessions. For institutions that fund faculty development, the message is pointed: an evaluation specified as end-of-program participant feedback buys a result it cannot use, because the modal study of that design returns a positive finding almost irrespective of what occurred in the classroom.

Subject of Research: The impact of faculty development programs on teaching practices in higher education, assessed through a scoping review of evaluation methods and evidence quality.

Article Title: Impact of faculty development on teaching practices in higher education: a scoping review

Article References: Marci, A., Ragusa, M., & Manganello, F. (2026). Impact of faculty development on teaching practices in higher education: a scoping review. Frontiers in Education, 11, Article 1947549. https://doi.org/10.3389/feduc.2026.1947549

Image Credits: AI Generated

DOI: 10.3389/feduc.2026.1947549

Keywords: faculty development, higher education, teaching practices, scoping review, Kirkpatrick model, self-report bias, STEM education, classroom observation, RTOP, evaluation methods, teacher behaviour, research methodology

The review, published in eClinicalMedicine by Maria Vedechkina, Prerna Banati, and Valentina Baltag, systematically mapped instruments used to measure adolescent digital technology use across 533 studies published between 2014 and 2025. Conducted under PRISMA-ScR guidelines with a protocol registered on the Open Science Framework, the team searched PubMed, Web of Science, and Scopus using a strategy that combined population terms such as adolescent, teen, and youth with device and media terms and measurement keywords. After removing 711 duplicates from 1,600 records and screening 583 full texts, the authors retained 533 studies spanning more than 20 countries, predominantly in East Asia, North America, and Europe.

The timing matters. Only 120 of the included studies appeared before 2020; the rest were published in the last five years, reflecting the surge of research interest that followed the COVID-19 pandemic, when remote learning and online socialisation deepened adolescents’ reliance on digital platforms. Governments and bodies such as the World Health Organization are increasingly pressed to issue guidance on balancing the risks and benefits of digital engagement, and young people themselves have voiced concerns about technology-facilitated gender-based violence, misinformation, and weak digital safeguards. But sound policy, the authors argue, requires sound measurement first—and that is precisely what is missing.

From the 533 studies, the team identified 135 validated instruments, most of them brief self-report questionnaires of between 4 and 51 items. Just over half of the studies, about 59 percent, used at least one validated instrument, while the remaining 41 percent relied on study-specific, ad hoc questions—often a single item asking how many hours per day an adolescent spends on social media. Strikingly, only two alternative assessment methods were found: passive data collection via a mobile app. Despite the availability of device logs, screen-time tracking, and ecological momentary assessment, the field remains almost entirely dependent on teenagers remembering and honestly reporting their own behaviour, a method known to suffer from recall error and social desirability bias.

What the instruments measure is as revealing as how they measure it. Applying a logic-model framework that distinguishes inputs, processes, outputs, outcomes, and impacts, the reviewers found that duration (79 instruments) and frequency (70) dominated, followed by addiction (47) and problematic use (43). Over two-thirds of the identified tools were explicitly designed to detect pathological or addictive use, borrowing clinical criteria such as withdrawal, tolerance, dependence, and loss of control. Familiar names include the Internet Addiction Test, the Smartphone Addiction Scale, and the Bergen Social Media Addiction Scale. By contrast, fewer than 2 percent of instruments assessed positive dimensions of digital technology use, such as enjoyment, peer bonding, creativity, or skill-building.

The consequences of this risk-heavy orientation are profound. When nearly every tool is built to find dysfunction, the resulting evidence base paints a distorted picture of adolescent digital life—one heavy on deficiency and light on the nuanced middle ground where most use likely falls. Motivations for engagement, such as emotion regulation, identity exploration, or social support, were captured by only about ten instruments. Contextual factors fared worse: parenting practices and family media rules appeared in just four tools, while peer influence and school context were strikingly absent. By overlooking the social and motivational environment, the authors warn, existing measures risk conflating elevated use with harmful use.

Developmental appropriateness emerged as another critical weakness. The reviewers classified most instruments as age-insensitive: they had not been developed or validated specifically for adolescents aged 10 to 19, contained no developmentally specific content such as schoolwork impairment or parental mediation, and lacked age-referenced norms. Only about 12 percent, including the Social Media Disorder Scale, were built and validated specifically for adolescents. Widely used tools such as the Internet Addiction Test were adapted from adult versions with minimal modification, and few incorporated adolescent input during formative work. Generic wording like neglecting responsibilities does little to reflect the realities of teenage life, where peer dynamics, school demands, and family supervision shape how technology is used.

Cross-cultural applicability is similarly thin. Although many instruments have been translated—Chinese, Korean, Spanish, and French were the most common languages—genuine cross-cultural adaptation and validation were rare. Most studies reported translation without content modification or validation across cultural groups, and socioeconomic factors such as device access, digital norms, and urban-rural differences were seldom considered. Roughly 35 percent of the included studies presented data from low- and middle-income countries, but Africa and Latin America were notably underrepresented. The upshot is that instruments are applied globally while remaining tailored to none of the diverse sociocultural settings in which adolescents actually live.

Psychometric quality varied widely. Using an adapted version of the COSMIN guidelines, the team appraised content validity, construct validity, internal consistency, and test-retest reliability. Internal consistency was commonly reported and generally satisfactory, but validity metrics were inconsistent, often limited to exploratory factor analysis or simple correlations. Independent validation studies were scarce, and interpretability and responsiveness were rarely assessed. Only 19 instruments, about 14 percent, earned a strong overall rating, typically through multiple validations and transparent reporting; 14 instruments, about 10 percent, were rated poor, often due to unclear methodology or validation conducted solely by the original developers. The majority, 76 percent, fell in the moderate category.

Perhaps the most fundamental problem is conceptual fragmentation. Definitions of screen time, problematic use, and high usage varied enormously across studies. Some tools defined use as general screen time, others focused on specific platforms, and still others required a clinical threshold on a behavioural scale; some classified adolescents as problematic users based purely on daily hours. Without agreed core constructs or standardised metrics, studies measuring different phenomena under the same label cannot be meaningfully compared or synthesised, stalling cumulative knowledge. The pace of technological change compounds the issue: instruments developed in 2015 contain no questions about TikTok, AI companions, or live-streaming, and almost none captured the commercial dimensions of digital life, such as the ubiquitous targeted advertising of food and beverages to minors.

The review, which forms part of the WHO’s broader effort to inform global policy on adolescent digital health, closes with targeted recommendations. The authors call for holistic instruments co-designed with young people that capture positive, normative, and qualitative dimensions of use, including digital literacy, creativity, and social connection. They urge consensus on core constructs and standardised definitions to enable cross-study comparison, rigorous validation across demographic and cultural groups, and multi-method approaches that combine self-report with passive device logging, wearable sensors, and ecological momentary assessment to reduce recall bias. They also caution researchers against clinging to legacy measures for the sake of comparability at the expense of relevance. Emerging tools such as the Cyber Virtues Scale, the EHealth Literacy Scale, and the Digital Media Use Effects Scales for Adolescents suggest the field may be beginning to broaden, but progress since a 2021 review flagged the same gaps has been minimal. Better measurement, the authors conclude, is not an end in itself but the means to understanding—and ultimately improving—adolescent development in the digital age.

Subject of Research: Measurement instruments for adolescent digital technology use

Article Title: Systematized scoping review of instruments for measuring adolescent digital technology use

Article References: Vedechkina, M., Banati, P., & Baltag, V. (2026). Systematized scoping review of instruments for measuring adolescent digital technology use. eClinicalMedicine, 101, Article 104247. https://doi.org/10.1016/j.eclinm.2026.104247

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104247

Keywords: adolescent health, digital technology use, screen time, measurement instruments, scoping review, psychometrics, internet addiction, WHO, cross-cultural validation, self-report bias, digital wellbeing, eClinicalMedicine

The clinical stakes are considerable. Obstructive sleep apnea affects hundreds of millions of people worldwide and is linked through sleep fragmentation and repeated drops in blood oxygen to cardiovascular disease, metabolic dysfunction, and daytime impairment. Continuous positive airway pressure, or CPAP, remains the gold standard treatment, but between 46 and 83 percent of patients fail to meet the conventional adherence benchmark of more than four hours of use per night. Oral appliances, particularly mandibular advancement devices, are recommended as a first-line option for mild to moderate disease and as an alternative for patients who cannot tolerate CPAP. Earlier studies suggested that patients wear these appliances roughly an hour longer per night than they use CPAP, but much of that evidence rested on self-reports, which are notoriously prone to overestimation.

The study’s technical approach was elegantly simple. The TheraMon sensor, embedded in the posterior buccal side of the mandibular arch tray, was programmed to log temperature readings between 33.5 and 39.5 degrees Celsius. Because the oral cavity sits within that range and room temperature does not, continuous readings within the window were interpreted as periods of actual device use. Participants were not explicitly told that nightly appliance use was being objectively monitored, nor were they informed of the details of the one-year follow-up plan, a deliberate design choice intended to preserve natural patterns of use. At baseline, each participant underwent overnight polysomnography, sleep questionnaires including the Epworth Sleepiness Scale and the Pittsburgh Sleep Quality Index, a five-factor personality assessment, and cone-beam computed tomography to characterize craniofacial morphology.

The therapy itself worked well when the device was actually worn. Mandibular advancement was initially set at 70 percent of each patient’s maximum protrusion and titrated in half-millimeter increments when needed, and the mean apnea-hypopnea index fell from 16.6 events per hour at baseline to 4.16 events per hour with the appliance in place. But the adherence data told a more complicated story. During the first three months, the median nightly use across all nights was just 3.85 hours, below the four-hour threshold used to define adequate adherence. When patients did wear the device, they wore it for a median of 7.05 hours, a full night of sleep. The problem was frequency: patients used the appliance on a median of only 3.7 days per week, and only 55.7 percent of nights met or exceeded the four-hour mark.

The comparison between objective and subjective measures revealed a specific and revealing pattern of bias. Participants were statistically accurate when reporting how long they wore the device on nights they used it, reporting a median of 7.0 hours against an objective 7.05 hours. But they significantly overestimated how often they used it, claiming a median of five days per week when sensors recorded 3.7 days, a difference that was highly significant. Bland-Altman analysis showed that self-reported nightly use across all nights exceeded objective values by a mean of 0.92 hours, and self-reported usage days exceeded objective records by an average of 1.41 days per week. The researchers attribute this to a combination of recall bias and what they describe as white coat adherence: a temporary uptick in device use shortly before scheduled clinic visits, which then dominated patients’ memories of their own behavior.

Even more striking was the divergence in trajectories between adherent and non-adherent users. Of the forty-three participants who completed the three-month follow-up, twenty-one, or 48.8 percent, met the adherence criterion. The adherent group wore the device a median of 6.23 hours per night across all nights and used it on roughly six days per week, with stable, sustained use throughout the observation period. Non-adherent users averaged just 2.38 hours per night on 2.32 days per week, and their weekly use fluctuated, declining when unsupervised and spiking before appointments. Notably, on the nights when both groups actually wore the appliance, the duration of use was statistically indistinguishable, at roughly seven hours. The difference between success and failure was not how long patients slept with the device, but whether they chose to put it in at all.

By the twelve-month follow-up, conducted by telephone with all forty-three completers, the split had hardened. Nineteen participants, or 44.2 percent, remained adherent, and their habits had become exemplary: a median of seven hours per night on seven nights per week. Most non-adherent users, by contrast, had effectively discontinued therapy, with median use of zero hours and zero days per week. Multivariate logistic regression identified two independent predictors of twelve-month adherence: older age, with each additional year raising the odds by about 7 percent, and a smaller mandibular plane angle measured relative to the Frankfort horizontal plane. Patients with hyperdivergent, steeply angled facial skeletons, a craniofacial type already known to be a risk factor for sleep apnea and to require greater mandibular advancement for efficacy, were significantly less likely to keep using the device.

The three-month picture had its own predictors. Older age again emerged as protective, alongside lower baseline Epworth Sleepiness Scale scores, with each point of sleepiness reducing the odds of adherence by roughly 26 percent. Spearman correlations showed that sleepiness scores were negatively associated with every objective adherence measure, including nightly use, weekly frequency, and the percentage of nights exceeding four hours. The authors speculate that patients with excessive daytime sleepiness may initially experience limited symptomatic improvement, only encountering positive feedback later as accumulated use eases their symptoms, and they suggest that greater mandibular advancement combined with enhanced early support might help this subgroup. Personality traits measured by the NEO-FFI, including conscientiousness and neuroticism, showed no significant association with adherence, indicating that behavior was shaped more by clinical and anatomical factors than by stable psychological disposition.

Several caveats frame the findings. Objective sensor data were collected only during the first three months, so the twelve-month comparison relied on self-report, the very measure shown to be unreliable. Side effects and discomfort were not systematically recorded, sleep diaries were not used, and the cohort consisted exclusively of Chinese patients with a mean age of about thirty-nine, limiting generalizability to other populations and to the very elderly. The authors also note that generally shorter sleep duration in the Chinese population may partly explain the relatively low nightly wear time, and that adherence to this particular appliance design should not be assumed to generalize to all oral appliances.

Even so, the study carries a clear practical message. Adherence behavior in oral appliance therapy, as in CPAP therapy, appears to be established early: patients who went on to succeed had already formed stable wearing habits within the first week of treatment. Because the low overall adherence in this cohort was driven primarily by infrequent use rather than short wear sessions, the authors recommend embedding reminders, whether through alarms, mobile applications, or email, into routine care, citing prior evidence that app-based monitoring significantly increases wearing days. They argue for long-term, objective, and individualized adherence monitoring as a standard component of oral appliance management, particularly if these devices are to deliver the cardiovascular benefits that have proven elusive in CPAP trials. For clinicians, the takeaway is that the first three months, and perhaps the first few weeks, offer a critical window to identify struggling patients and intervene before quiet abandonment of therapy becomes permanent.

Subject of Research: Objective versus subjective adherence to oral appliance therapy in adults with obstructive sleep apnea

Article Title: Objective and subjective adherence to oral appliance therapy in adults with obstructive sleep apnea: pilot data from a one-year longitudinal study

Article References: Zhang, W., Yu, M., Gong, X., Dang, W., & Gao, X. (2026). Objective and subjective adherence to oral appliance therapy in adults with obstructive sleep apnea: pilot data from a one-year longitudinal study. Journal of Clinical Sleep Medicine, 22(1), Article 115. https://doi.org/10.1007/s44470-026-00123-6

Image Credits: AI Generated

DOI: 10.1007/s44470-026-00123-6

Keywords: obstructive sleep apnea, oral appliance therapy, mandibular advancement device, adherence, thermal microsensor, objective monitoring, self-report bias, craniofacial morphology, Epworth Sleepiness Scale, CPAP, sleep medicine, longitudinal study