Spaced Retrieval Research Articles

Effectiveness of different memory training programs on improving hyperphagic behaviors of residents with dementia: a longitudinal single-blind study.

BackgroundHyperphagia increases eating-associated risks for people with dementia and distress for caregivers. The purpose of this study was to compare the long-term effectiveness of spaced retrieval (SR) training and SR training combined with Montessori activities (SR + M) for improving hyperphagic behaviors of special care unit residents with dementia.MethodsThe study enrolled patients with dementia suffering from hyperphagia resident in eight institutions and used a cluster-randomized single-blind design, with 46 participants in the SR group, 49 in the SR + M group, and 45 participants in the control group. For these three groups, trained research assistants collected baseline data on hyperphagic behavior, pica, changes in eating habits, short meal frequency, and distress to caregivers. The SR and SR + M groups underwent memory training over a 6-week training period (30 sessions), and a generalized estimating equation was used to compare data of all the three groups of subjects obtained immediately after the training period and at follow-ups 1 month, 3 months, and 6 months later.ResultsResults showed that the hyperphagic and pica behaviors of both the SR and SR + M groups were significantly improved (P<0.001) and that the effect lasted for 3 months after training. The improvement of fast eating was significantly superior in the SR + M group than in the SR group. The improvement in distress to caregivers in both intervention groups lasted only until the posttest. Improvement in changes in eating habits of the two groups was not significantly different from that of the control group.ConclusionSR and SR + M training programs can improve hyperphagic behavior of patients with dementia. The SR + M training program is particularly beneficial for the improvement of rapid eating. Caregivers can choose a suitable memory training program according to the eating problems of their residents.

Card-based design combined with spaced repetition: A new interface for displaying learning elements and improving active recall

This study aims to bring card-based design into education. A mobile application called “English Practice” has been developed wherein a card-based interface named PACARD (Personalize Adaptive CARD-based interface) was implemented. This interface has a flexible design so as to be compatible with various types of mobile devices thus overcoming the small screen challenge. In this study, we use PACARD to evaluate the effectiveness of card-based design on personalized adaptive mobile learning. An empirical study was conducted among 2774 online users for three months to evaluate PACARD's effect on engaging active recall, thus, enhancing memory retention. We also observed how our adaptive mechanism meets user preference. In terms of memory retention and users' preference in PACARD, it results in better retention and it also enabled the learning items to be more appealing to the users as the users related to their own learning progress.

An open learning system for special needs education

The field of special needs education in case of speech and language deficiencies has seen great success, utilizing a number of paper-based systems, to help young children experiencing difficulty in language acquisition and the understanding of languages. These systems employ card and paper-based illustrations, which are combined to create scenarios for children in order to expose them to new vocabulary in context. While this success has encouraged the use of such systems for a long time, problems have been identified that need addressing. This paper presents research toward the application of an Open Learning system for special needs education that aims to provide an evolution in language learning in the context of understanding spoken instruction. Users of this Open Learning system benefit from open content with novel presentation of keywords and associated context. The learning algorithm is derived from the field of applied computing in human biology using the concept of spaced repetition and providing a novel augmentation of the memorization process for special needs education in a global Open Education setting.

Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system

Abstract. This paper introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together with the assimilation of compact phase space retrievals of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination (R2). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of compact phase space retrievals (CPSRs). CPSRs are obtained by preprocessing retrieval data sets with an algorithm that (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ∼ 35 %, while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.

Exploiting Wikipedia API for Hindi-english Cross-language Information Retrieval

The rapidly increasing demographics of the internet population and the abundance of multilingual content on the web increased the communication in multiple languages. Most of the people use their regional languages to express their needs and the language diversity becomes a great barrier. Cross-Language Information Retrieval (CLIR) provides a solution for that language barrier which allows a user to ask a query in the native language and get the relevant documents in the different language. In this paper, we proposed a Wikipedia API based query translation approach. Queries are tokenized and multi-words query terms are created using N-gram technique. Wikipedia title and inter-wiki link features are exploited for query translation. Target language documents are retrieved using vector space retrieval model and BM25 retrieval algorithm. Experiment results shows that the proposed approach achieves better results without exploiting any language resources.

Performance Analysis of Optimized Content Extraction for Cyrillic Mongolian Learning Text Materials in the Database

This paper had developed and tested optimized content extraction algorithm using NLP method, TFIDF method for word of weight, VSM for information search, cosine method for similar quality calculation from learning document at the distance learning system database. This test covered following things: 1) to parse word structure at the distance learning system database documents and Cyrillic Mongolian language documents at the section, to form new documents by algorithm for identifying word stem; 2) to test optimized content extraction from text material based on e-test results (key word, correct answer, base form with affix and new form formed by word stem without affix) at distance learning system, also to search key word by automatically selecting using word extraction algorithm; 3) to test Boolean and probabilistic retrieval method through extended vector space retrieval method. This chapter covers: to process document content extraction retrieval algorithm, to propose recommendations query through word stem, not depending on word position based on Cyrillic Mongolian language documents distinction.

Spaced Retrieval Practice Increases College Students’ Short- and Long-Term Retention of Mathematics Knowledge

A major challenge college students face is retaining the knowledge they acquire in their classes, especially in cumulative disciplines such as engineering, where ultimate success depends on long-term retention of foundational content. Cognitive psychologists have recently recommended various techniques educators might use to increase retention. One technique (spaced retrieval practice) involves extending opportunities to retrieve course content beyond a customarily short temporal window following initial learning. Confirming the technique’s utility requires demonstrating that it increases retention in real classroom settings, with commonly encountered educational content, and that gains endure into subsequent semesters. We manipulated spaced versus massed retrieval practice in a precalculus course for engineering students and followed a subset of students who proceeded into a calculus class the following semester. Spacing versus massing was manipulated within- and between-subjects. Within-subjects, students retained spaced content better than massed content in the precalculus course. Between-subjects, students for whom some retrieval practice was spaced, compared to those for whom all practice was massed, performed better on the final exam in the precalculus class and on exams in the calculus class. These findings suggest that spaced retrieval practice can have a meaningful, long-lasting impact on educational outcomes.

Does GOSAT capture the true seasonal cycle of carbon dioxide?

Abstract. The seasonal cycle accounts for a dominant mode of total column CO2 (XCO2) annual variability and is connected to CO2 uptake and release; it thus represents an important quantity to test the accuracy of the measurements from space. We quantitatively evaluate the XCO2 seasonal cycle of the Greenhouse Gases Observing Satellite (GOSAT) observations from the Atmospheric CO2 Observations from Space (ACOS) retrieval system and compare average regional seasonal cycle features to those directly measured by the Total Carbon Column Observing Network (TCCON). We analyse the mean seasonal cycle amplitude, dates of maximum and minimum XCO2, as well as the regional growth rates in XCO2 through the fitted trend over several years. We find that GOSAT/ACOS captures the seasonal cycle amplitude within 1.0 ppm accuracy compared to TCCON, except in Europe, where the difference exceeds 1.0 ppm at two sites, and the amplitude captured by GOSAT/ACOS is generally shallower compared to TCCON. This bias over Europe is not as large for the other GOSAT retrieval algorithms (NIES v02.21, RemoTeC v2.35, UoL v5.1, and NIES PPDF-S v.02.11), although they have significant biases at other sites. We find that the ACOS bias correction partially explains the shallow amplitude over Europe. The impact of the co-location method and aerosol changes in the ACOS algorithm were also tested and found to be few tenths of a ppm and mostly non-systematic. We find generally good agreement in the date of minimum XCO2 between ACOS and TCCON, but ACOS generally infers a date of maximum XCO2 2–3 weeks later than TCCON. We further analyse the latitudinal dependence of the seasonal cycle amplitude throughout the Northern Hemisphere and compare the dependence to that predicted by current optimized models that assimilate in situ measurements of CO2. In the zonal averages, models are consistent with the GOSAT amplitude to within 1.4 ppm, depending on the model and latitude. We also show that the seasonal cycle of XCO2 depends on longitude especially at the mid-latitudes: the amplitude of GOSAT XCO2 doubles from western USA to East Asia at 45–50° N, which is only partially shown by the models. In general, we find that model-to-model differences can be larger than GOSAT-to-model differences. These results suggest that GOSAT/ACOS retrievals of the XCO2 seasonal cycle may be sufficiently accurate to evaluate land surface models in regions with significant discrepancies between the models.

Student-directed retrieval practice is a predictor of medical licensing examination performance.

IntroductionA large body of evidence indicates that retrieval practice (test-enhanced learning) and spaced repetition increase long-term information retention. Implementation of these strategies in medical curricula is unfortunately limited. However, students may choose to apply them autonomously when preparing for high-stakes, cumulative assessments, such as the United States Medical Licensing Examination Step 1. We examined the prevalence of specific self-directed methods of testing, with or without spaced repetition, among preclinical students and assessed the relationship between these methods and licensing examination performance.MethodsSeventy-two medical students at one institution completed a survey concerning their use of user-generated (Anki) or commercially-available (Firecracker) flashcards intended for spaced repetition and of boards-style multiple-choice questions (MCQs). Other information collected included Step 1 score, past academic performance (Medical College Admission Test [MCAT] score, preclinical grades), and psychological factors that may have affected exam preparation or performance (feelings of depression, burnout, and test anxiety).ResultsAll students reported using practice MCQs (mean 3870, SD 1472). Anki and Firecracker users comprised 31 and 49 % of respondents, respectively. In a multivariate regression model, significant independent predictors of Step 1 score included MCQs completed (unstandardized beta coefficient [B] = 2.2 × 10− 3, p < 0.001), unique Anki flashcards seen (B = 5.9 × 10− 4, p = 0.024), second-year honours (B = 1.198, p = 0.002), and MCAT score (B = 1.078, p = 0.003). Test anxiety was a significant negative predictor (B= − 1.986, p < 0.001). Unique Firecracker flashcards seen did not predict Step 1 score. Each additional 445 boards-style practice questions or 1700 unique Anki flashcards was associated with an additional point on Step 1 when controlling for other academic and psychological factors.ConclusionsMedical students engage extensively in self-initiated retrieval practice, often with spaced repetition. These practices are associated with superior performance on a medical licensing examination and should be considered for formal support by educators.

Can Technology-Assisted Toilets Improve Quality of Life for Rehabilitating Stroke Patients? A Pilot Cohort Study

intraparenchymal hemorrhage. The patient was noted to have impairments in visual perception, memory, language and balance. The patient was diagnosed with Balint’s Syndrome, characterized by simultagnosia, occulomotor apraxia and optic ataxia. The patient required acute inpatient rehabilitation to address this unique set of impairments. Interventions: An interdisciplinary approach was utilized focusing on task-based training to improve his cognitive and physical functioning. The patient benefited from errorless learning techniques, a low stimulation environment, and proprioceptive input to improve balance and coordination. Main Outcome Measure(s): O-LOG, FIM, Berg Balance Test, and a specialized protocol for spaced retrieval of orientation information. Results: The patient demonstrated improvement in orientation (8/30 to 20/30 on O-LOG), balance (0/56 to 17/56 on Berg Balance Test), basic communication skills, and self-care activities over four weeks. Conclusions: These unique interventions led to functional improvement in this patient with Balint’s Syndrome as measured by objective scales. This case report demonstrates the necessity of an interdisciplinary rehabilitation approach for a patient with complex functional impairments. Limited clinical research exists regarding established approaches and additional studies are needed to validate an effective clinical approach for this unique syndrome.

Management of Demented Patients with Urinary Incontinence: A Case Study

Objective: To assess whether a demented patient with urinary incontinence (UI) could learn to use an adapted version of timed voiding (i.e., instead of being led by a caregiver, the patient learns to perform timed voiding by herself). Indeed, UI affects a large number of patients with dementia and creates a substantial burden to the caregiver. UI is the most common complaint at the time of institutionalization and it is often the cause of premature institutionalization. Timed voiding is a promising intervention, but one whose effectiveness remains to be demonstrated. Additionally, timed voiding has the disadvantage of being constraining for caregivers, requiring them to be present to stimulate the patient to urinate at each of the scheduled occasions. Method: The present intervention required the patient to learn (1) to associate an auditory signal from a timer to the action of urination, (2) to reprogram the timer, using the spaced retrieval technique. An ABAB paradigm was used to assess the effectiveness of this program to eliminate urinary accidents. Results: The results of the intervention showed that the use of the timer was effective in helping the patient to reduce her urinary leaks from 1.5 diurnal accidents per week to zero during four months. Conclusion: UI in patients with dementia seems treatable. Such intervention could contribute to delay institutionalization of patients with dementia through maintaining their autonomy and reducing the burden of caregivers.

A Crowdsourcing Approach to Chinese Vocabulary Learning

The fast development of new technology, particularly web-based andmobile technology, has been transforming ways how languages aretaught and learned. The current study examines the use of Memrise, acrowdsourcing spaced repetition program, by college students ofChinese, and its effects on Chinese character learning. The findings ofthe study demonstrate the effectiveness of the program. The study hasalso identified important factors and conditions that should exist inorder for the use of the program to be successful. Based on the findingsof the study, suggestions are made for language teachers in regards tousing Memrise or similar programs in vocabulary teaching. Eventhough the current study focuses on Chinese character learning, thefindings of the study can be applied to any other languages.

Development of a Mobile Device Optimized Cross Platform‐Compatible Oral Pathology and Radiology Spaced Repetition System for Dental Education

Combining active recall testing with spaced repetition increases memory retention. The aim of this study was to evaluate and compare students' perception and utilization of an electronic spaced repetition oral pathology-radiology system in dental hygiene education and predoctoral dental education. The study employed an open-source suite of applications to create electronic "flashcards" that can be individually adjusted for frequency of repetition, depending on a user's assessment of difficulty. Accessible across multiple platforms (iOS, Android, Linux, OSX, Windows) as well as via any web-based browser, this framework was used to develop an oral radiology-oral pathology database of case-based questions. This system was introduced in two courses: sophomore oral pathology for dental students and sophomore radiology for dental hygiene students. Students were provided free software and/or mobile tablet devices as well as a database of 300 electronic question cards. Study participants were surveyed on frequency and extent of use. Perception-based surveys were used to evaluate their attitudes towards this technology. Of the eligible students, 12 of 22 (54.5%) dental hygiene and 49 of 107 (45.8%) dental students responded to the surveys. Adoption rates and student feedback were compared between the two groups. Among the respondents, acceptance of this technology with respect to educational usefulness was similar for the dental and dental hygiene students (median=5 on a five-point scale; dental hygiene interquartile range (IQR)=0; dental IQR=1). Only a minority of the survey respondents (25% dental, 33% dental hygiene) took advantage of one of the main benefits of this technology: automated spaced repetition.

A blended learning scenario to enhance learners’ oral production skills

&lt;span&gt;This paper examines the effectiveness of a mobile assisted blended learning scenario for pronunciation in Korean language. In particular, we analyze how asynchronous oral communication between learners of Korean and native speakers via "kakaotalk" (an open source mobile phone application) may be beneficial to the learner in terms of pronunciation. Our methodological approach is based on task resolution (Ellis, 2003) in peer-to-peer collaborative settings and the spaced repetition concept (Ebbinghaus, 1885, cited by Dempster, 1988). The outcomes of our study show that the learners appreciated the possibility to interact with native speakers but most of them preferred synchronous communication for training their pronunciation skills.&lt;/span&gt;

Comparing simulated atmospheric carbon dioxide concentration with GOSAT retrievals

Satellite observations of atmospheric carbon dioxide (CO2) provide a useful way to improve the understanding of global carbon cycling. In this paper, we present a comparison between simulated CO2 concentrations from an inversion model of the CarbonTracker Data Assimilation System (CTDAS) and satellite-based CO2 measurements of column-averaged dry air mole fraction (denoted XCO2) derived from version 3.3 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing SATellite (ACOS–GOSAT) L2 data products. We examine the differences of CTDAS and GOSAT to provide important guidance for the further investigation of CTDAS in order to quantify the corresponding flux estimates with satellite-based CO2 observations. We find that the mean point-by-point difference (CTDAS–GOSAT) between CTDAS and GOSAT XCO2 is −0.11 ± 1.81ppm, with a high agreement (correlation r = 0.77, P < 0.05) over the studied period. The latitudinal zonal variations of CTDAS and GOSAT are in general agreement with clear seasonal fluctuations. The major exception occurs in the zonal band of 0°–15°N where the difference is approximately 4ppm, indicating that large uncertainty may exist in the assimilated CO2 for the low-latitude region of the Northern Hemisphere (NH). Additionally, we find that the hemispherical/continental differences between CTDAS and GOSAT are typically less than 1ppm, but obvious discrepancies occur in different hemispheres/continents, with high consistency (point-by-point correlation r = 0.79, P < 0.05) in the NH and a weak correlation (point-by-point correlation r = 0.65, P < 0.05) in the Southern Hemisphere. Overall, the difference of CTDAS and GOSAT is small, and the comparison of CTDAS and GOSAT will further instruct the inverse modeling of CO2 fluxes using GOSAT.

Creating Effective Self-Management for Older Adults with Type 2 Diabetes and Cognitive Impairment

The primary objective of the study was to determine whether a distanced-based educational in-tervention would result in positive health outcomes for persons with both DM and cognitive impairment. Older adults with Type 2 diabetes (Diabetes Mellitus—DM) who also have cognitive impairment such as Mild Cognitive Impairment (MCI) or early stage dementia are both challenged and at risk when attempting to live independently. The ability to effectively monitor blood glucose levels and diet and exercise regimens often is severely constrained by the combination of DM and the presence of Mild Cognitive Impairment (MCI) or early stage dementia. We describe an exploratory study funded by the National Institute of Diabetes Digestive and Kidney Diseases (NIDDK) in which Certified Diabetic Educators (CDEs) were linked with 40 older adult with DM and cognitive impairment using iPads and the internet. CDEs presented personalized education sessions to participants, and 18 of the participants also received a cognitive intervention called Spaced Retrieval (SR), which is designed to train the effective use of strategies to enhance medication compliance and reach other goals. Blood glucose and cholesterol measures were assessed at baseline and at 2-, 4-, and 6-month post intervention. Hemoglobin A1c (HbA1c) levels initially declined from baseline after treatment but returned to baseline levels after 6 months. For low-density lipoprotein (LDL) cholesterol, a significant interaction effect was found for the Group × Time interaction. LDL levels increased from baseline after treatment for the control group, but showed decline after baseline in the SR group. Goals that were initially learned were retained, in general, at short-term follow-up, and self-efficacy increased significantly after training. Results show the need for follow-up and support after initial treatment, as well as the need to see if the effects produced by SR can be replicated and sustained with continued contact.

Effects of spaced retrieval training with errorless learning in the rehabilitation of patients with dementia

[Purpose] Among the non-pharmacological interventions for dementia, spaced retrieval training (SRT) is a good method for rehabilitating cognition. The purpose of this study was to examine effects of SRT with errorless learning (EL) in the rehabilitation of patients with dementia. [Subjects and Methods] Twenty-nine participants with vascular dementia (VD) and Alzheimer’s disease (AD) participated in the present study. The Korean version of the Consortium to Establish a Registry for Alzheimer’s disease (CERAD-K) and Modified Barthel Index (MBI) were performed to assess the changes in the neuropsychological performance and the independent activities of daily living after SRT with EL. All tests were administered both before and after SRT with EL. Each SRT with EL intervention was performed for 30 minutes per day for 5 weeks. SPSS for Windows version 18.0 was used for statistical analysis. [Results] All items of the CERAD-K score of the VD group except for constructional praxis increased significantly after the SRT with EL intervention, but no significant differences from the AD group were found. The Korean version of the geriatric depression scale (GDS-K) of the VD group increased significantly after the SRT with EL intervention. The mean MBI scores of each group showed no significant difference after the intervention. [Conclusion] SRT with EL is an effective intervention for memory training of patients with dementia. Future research using sufficient sample sizes will be needed to obtain strong evidence for comparing not only the before and after intervention data but also between the groups.

Spaced Retrieval Training: 26 Years of Growth

Clinicians frequently use spaced retrieval training (SRT) to assist people with memory loss in retention and recall functional information. The body of literature surrounding SRT has made valuable additions, shown flexibility and extended the use of the strategy to other populations. The history and additions of SRT will be reviewed.

Evaluation of Spatio-Temporal Variogram Models for Mapping Xco2Using Satellite Observations: A Case Study in China

Greenhouse Gases Observing Satellite (GOSAT), which measures column-averaged carbon dioxide dry air mole fractions (Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) from space, provides new data sources to improve our understanding of carbon cycle. The available GOSAT data, however, have many gaps and are irregularly positioned, which make it difficult to directly interpret their scientific significance without further data analysis. Spatio-temporal geostatistical prediction approach can be used to fill the gaps for global and regional Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> mapping. It is important to choose a suitable spatio-temporal variogram model since modeling spatio-temporal correlation structure using variogram model is a critical step in the geostatistical prediction. In this study, three different flexible spatio-temporal variogram models, including the product-sum model, Cressie-Huang model, and Gneiting model, are used to model the spatio-temporal correlation structure of Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> over China, using the Atmospheric CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Observations from Space retrievals of the GOSAT (ACOS-GOSAT) Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (v3.3) data products. The three models are compared and evaluated using the weighted mean square errors (WMSE) indicating the fitness between the empirical variogram surface and the theoretical variogram model, cross-validation for quantifying prediction accuracies, and the performance of the three models when used to fill the spatial gaps and generate Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> maps in 3-day temporal interval. The results indicate that 1) the model fitness of the commonly used product-sum model is slightly better than Cressie-Huang model and Gneiting model as indicated from WMSE, and 2) all the three models present similar summary statistics in cross-validation, all with a significantly high correlation coefficient of 0.92, and about 83% of prediction error within 2 ppm and about 53% within 1 ppm, and (3) differences between the mapping results using the three models are generally less than 0.1 ppm, and no significant differences can be identified. As a conclusion from the above results, all the three variogram models can precisely catch the empirical characteristics of the spatio-temporal correlation structure of Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> over China, and the precision and effectiveness of predicting and mapping Xco <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> using the three models are almost the same.

Using Spaced Retrieval Training to Teach People With Dementia to Independently Use Their Walking Aids: Two Case Studies

This article describes two case studies that used spaced retrieval training to teach two aged care facility residents diagnosed with dementia to independently use their walking aids. Each resident received five consecutive 1-hour sessions of spaced retrieval and was observed before and after intervention and at a 1-week follow-up. The results indicate the potential for this memory intervention to improve walker use and highlight several clinical aspects to consider when using this technique with demented people.