Microlearning Environment of Orthodontic Postgraduate Training Programmes in Pakistan: A Multicentre Cross-Sectional Study.

OBJECTIVE: To explore the perception of residents regarding the microlearning environment of orthodontic postgraduate training programmes across Pakistan. STUDY DESIGN: Descriptive, cross-sectional, multicentre study. Place and Duration of the Study: Department of Orthodontics, Dental College, HITEC Institute of Medical Sciences, Taxila, from February to July 2022. METHODOLOGY: This questionnaire-based study was conducted using a pre-validated HEMLEM tool for data collection. QuestionPro survey tool was utilised for data collection and SPSS version 23 was used for data analysis. Independent t-test and one-way ANOVA were performed for comparison of different subgroups. RESULTS: A total of 204 residents participated in this study and collectively showed a mean score of 45.2. Male residents showed significantly higher level of satisfaction than females. Residents below the age of 25 years and those in the first year of training showed maximum level of satisfaction with their learning environments. In general, participants perceived the teaching quality and supervision as more satisfactory than the staff attitude and behaviour. CONCLUSION: Overall, a higher HEMLEM score was recorded, which suggested that Pakistani orthodontic residents felt satisfied with their microlearning environment. Clinical supervisors, curriculum designers, and programme directors could use the findings of this study to further improve the learning environment of their training programmes. KEY WORDS: Learning environment, Microlearning environment, Residents, Clinical training, Supervision, Staff support.

On the snow leopard Trails: Occupancy pattern and implications for management in the Pamir.

The snow leopard (Panthera uncia) inhabits one of the most challenging environments on Earth, referred to as the 'third pole'. Only a fraction of its vast range has been explored thus far, owing to myriad of barriers inflicted by the remote terrain and socio-ecological realities of the landscapes. Understanding distribution patterns of species is essential to devise practical management measures. This study aimed to understand the distribution pattern and factors influencing occupancy of snow leopard in the Pamir Mountain range through sign-based occupancy modelling. Our study confirmed that the Pamir range is a snow leopard stronghold, with occupancy estimated at 0.57 ± 0.02. The topographic features positively influenced the detection probability (p = 0.37 ± 0.005) of snow leopards. Occupancy was influenced by mean annual precipitation (ß = -6.12 ± 1.8), density of roads (ß = -1.61 ± 0.6) and water sources (ß = 0.74 ± 0.4). Our findings underpin that sign-based distribution surveys provide vigorous scientific knowledge about elusive species and merit replication being used for other species. We propose to redefine the protected area boundaries based on ecological knowledge and encourage transboundary cooperation to safeguard snow leopards at a landscape scale.

Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan.

Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan's mountain ungulates.

Psychometric properties of the Urdu version of the Geriatric Oral Health Assessment Index (GOHAI) and oral health-related quality of life in the elder Pakistani population.

OBJECTIVE: The study aimed to translate the English version of the Geriatric Oral Health Assessment Index, assess its reliability and validity, and demonstrate its psychometric properties with regard to OHRQoL in the elder Pakistani population. MATERIAL AND METHODS: In this cross-sectional study, 408 elder people were randomly recruited from three day-care centres. In the translation process, the translated Urdu version was reviewed by a committee of experts, followed by back-translation into English and re-reviewed by the same committee of experts. The questionnaire sought information about socio-demographic characteristics information and self-perception of oral, general health and treatment needs. OHRQoL was examined using GOHAI-U, and intraoral examination recorded the decayed, missing, and filled teeth. Reliability, internal consistency, convergent and discriminant validity of GOHAI-U were examined. RESULTS: The mean GOHAI-U score was 40.2 (SD = 5.7, range = 20-55). The Cronbach's alpha for GOHAI score was 0.71, item-scale correlation coefficients ranged from 0.63 to 0.76, and test-retest correlation ranged from 0.59 to 0.74. Three factors supported the theoretical construction in the component factor analysis of the index. For convergent validity, there was a significant relationship between the GOHAI score and self-perceived oral, general health and treatment needs (P < .05). For discriminant validity, a significant correlation was found between the GOHAI score and clinical measures of dental health status except with the carious teeth. CONCLUSION: The GOHAI-U has sufficient reliability and constructs validity to be used as an efficient measure of oral health-related quality of life in the Pakistani elder population.

Identifying priority landscapes for conservation of snow leopards in Pakistan.

Pakistan's total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime habitat. However, this preliminary demarcation was not always in close agreement with the actual distribution-the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. The current study followed this approach to construct an accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through circuit theory. The probability of habitat suitability, generated from 98 presence points and 11 environmental variables, scored the snow leopard's assumed range in Pakistan, from 0 to 0.97. A large portion of the known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contributions in the MaxEnt model were precipitation during the driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%), and river density (9.2). The model was validated through receiver operating characteristic (ROC) plots and defined thresholds. The average test AUC in Maxent for the replicate runs was 0.933 while the value of AUC by ROC curve calculated at 0.15 threshold was 1.00. These validation tests suggested a good model fit and strong predictive power. The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was connected with the population in India. Based on our findings we propose three model landscapes to be considered under the Global Snow Leopard Ecosystem Protection Program (GSLEP) agenda as regional priority areas, to safeguard the future of the snow leopard in Pakistan and the region. These landscapes fall within mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in the existing protected areas network and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.

Habitat suitability and movement corridors of grey wolf (Canis lupus) in Northern Pakistan.

Habitat suitability models are useful to understand species distribution and to guide management and conservation strategies. The grey wolf (Canis lupus) has been extirpated from most of its historic range in Pakistan primarily due to its impact on livestock and livelihoods. We used non-invasive survey data from camera traps and genetic sampling to develop a habitat suitability model for C. lupus in northern Pakistan and to explore the extent of connectivity among populations. We detected suitable habitat of grey wolf using a maximum entropy approach (Maxent ver. 3.4.0) and identified suitable movement corridors using the Circuitscape 4.0 tool. Our model showed high levels of predictive performances, as seen from the values of area under curve (0.971±0.002) and true skill statistics (0.886±0.021). The main predictors for habitat suitability for C. lupus were distances to road, mean temperature of the wettest quarter and distance to river. The model predicted ca. 23,129 km2 of suitable areas for wolf in Pakistan, with much of suitable habitat in remote and inaccessible areas that appeared to be well connected through vulnerable movement corridors. These movement corridors suggest that potentially the wolf range can expand in Pakistan's Northern Areas. However, managing protected areas with stringent restrictions is challenging in northern Pakistan, in part due to heavy dependence of people on natural resources. The habitat suitability map provided by this study can inform future management strategies by helping authorities to identify key conservation areas.