The video game market has become increasingly popular among children and adolescents in recent decades. In this research, we investigated the Video Game Addiction Scale (VGAS) for Chinese children and adolescents. We aimed to examine children and adolescents’ prioritization on the VGAS criteria and comparative analysis of the trend of video game addiction among them. A cross-sectional paper questionnaire study was conducted on 1400 Chinese students from grade 3 (9 years old) to grade 12 (18 years old). The respondents had to complete the socio-demographic information and the VGAS test. The VGAS characteristic was prepared in 18 criteria, which was the combination of the Video Game Addiction Test (VAT), Gaming Addiction Scale (GAS), and Revised Chinese Internet Addiction (CIAS-R). Eventually, the VGAS criteria prioritization was ranked methodologically through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for each grade separately. Additionally, the Analytic Hierarchy Process (AHP) weighting technique was utilized to analyze the video game addiction of each grade under the four alternatives, individually. The results indicate that 3rd-grade students with some levels of addiction were the youngest who felt their life would not be fun without video games. Students in 5th grade with some levels of addiction were the youngest students who disclosed that their willingness to play video games is for forgetting their problems or feeling down. Moreover, they played video games more than before, thus, they did not sleep enough. Pupils of grade 6 reported that they played video games more than last semester. In their opinion, it is fair to play video games this much and does not need to reduce playing hours. Not getting enough sleep because of playing video games was seen in 7th graders as their first preference. 10th-grade students were the first to neglect to do their important responsibilities for playing video games. None of the 7th and 12th graders were somehow safe from video game addiction. In conclusion, playing video games can negatively affect studying, sleeplessness, getting far from society, and skipping important responsibilities for school students. Furthermore, the symptoms of video game addiction had seen at younger ages. These data provided insights for decision-makers to target effective measures to prevent children and adolescents’ video game addiction. With the advent of computers, tablets, cell phones, and progressing video games in the market, the willingness of children and adolescents to use those devices and play augmented reality video games have increased quickly. As such, in the last decades, the propensity to watch television has decreased . NowadayIn 2016, research for six European Union countries, from the School Children Mental Health Europe project, implied that 20% of the children play video games for more than 5 h a week . In 2004More than 85% of video games in the market contain some form of violence . In ref.Not all video games have a negative effect on children and adolescents. Mainly as a learning tool, educational games are used to teach subjects such as math or typing using basic game mechanics and thus stand out on most lists of best video games. Research has shown that the effectiveness of mobile video games in learning English language vocabulary can improve the student learning experience . A studyDifferent types of video games and some of their subgenres are briefed in Research on adolescents in Gorakhpur city revealed that 24.50% of adolescents were already addicted to playing video games . A surveAdolescents at their puberty age are very fragile. A punishment or inappropriate behavior from others, violent behavior from a friend even by words, or being cut off from association due to an inability to do something, all can affect the mood of the children. This can persuade them to prefer socializing with people who do not know them and do not judge or condemn them, in order to find peace in their privacy. This isolation can be a flip to turn to computer games. One of the dangers of playing video games for children and adolescents is getting addicted to them. Mainly, parents cannot prevent their kids from playing such games. Therefore, the family will not be informed about their child’s work and their inexperienced child will be harmed in the virtual society. In this research, we investigated the video game addiction criteria in children and adolescents. “Video game addiction” is referred to as “gaming” in the psychopathology and psychiatry areas for mental taxonomies such as the ICD-11 , so in tMulti-decision analysis methods help decision-makers to identify criteria and factors that are related to the subject and weight them based on their significance . One of One of the proven techniques to solve MCDM problems is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, which was introduced by Hwang and Yoon . In the However, many studies have worked on the negative effects of overusing computer games and most of the subjects were relevant to a small range of age. Besides, the detail of gaming tests was not analyzed and was just used to measure the level of the children’s gaming ,32. The To study the extent of video game addiction among Chinese children and adolescents from grade 3 to grade 12.To compare the trend of children and adolescents’ video gaming addiction and understand what reasons lead them to play video games and subsequently get addicted to video games, to take prevention measures.To describe what factors of the VGAS were prioritized by children and adolescents, based on the alternatives they belong to, and conduct a comparative analysis on the trend of their criteria prioritization.To identify the key priorities of VGAS criteria from the point of view of children and adolescents in grades 3–12 to avoid them getting addicted to playing video games.The rest of this study is organized as follows. In Hypothesis 1 (H1).Among the primary school pupils  no cases are already addicted to playing video games.Hypothesis 2 (H2).In Chinese school students, the incidence of getting addicted to playing video games begins from grade 7.Hypothesis 3 (H3).Every 12th grader had some symptoms of addiction or is already addicted to playing video games.Hypothesis 4 (H4).Identifying the level of addiction to playing video games among Chinese students from grade 3 (9 years old) to grade 12 (18 years old).This study addressed the school students from grade 3 in primary school to grade 12 in high school. We have visited different schools in Shantou city of China in downtown and suburbs. Paper questionnaires were given to the students to fill in. The students had been selected randomly from various classes. The questionnaire took almost 20 min to complete. The purpose of the study was explained to the participants, and they had to provide consent to fill in the questionnaires. The poll was anonymous, and the information was confidential. The participants were asked not to consult with each other while they were answering the questionnaire. We conducted the survey in November 2021, and the data were collected for a period of four months. The questionnaire is listed in Students consisting of 1400 cases who had participated in the survey, role as the decision-makers to evaluate the criteria. In this analysis, the VGAS questions are the set of the criteria, This study was approved by the Ethics Committee of Shantou University Medical School (No. SUMC-2022-046). Additionally, the consent of the school’s student affairs office and counsellors were obtained. This study proposed a method to analyze the gaming situation of Chinese children and adolescents. To deal with this, the presented method is classified into four steps. The first step is dedicated to designing a proper survey and identifying the criteria. In the second step, the insufficient and incomplete data were removed. The third step is assigned to sort the criteria according to the decision-makers’ scoring, using the precise TOPSIS method. For getting better results, the criteria weights in the TOPSIS method are calculated by the AHP method. In the fourth step, the criteria are ranked and the results are compared. The proposed method is summarized in Step 1. Designing the questionnaire and criteria. In the present study, participants have been challenged on different scales. We assessed the gaming test for children and adolescents with socio-demographic information and the Video Game Addiction Scale (VGAS). Initially, the socio-demographic information about students such as age, gender, smoking and drinking status, number of friends, and the level of outstanding in class were collected. Subsequently, the students answered the VGAS questions. First, the level of children’s and adolescents’ gaming was measured. As 14-item Video Game Addiction Test (VAT) [st (VAT)  did not st (VAT) , and 19-st (VAT)  with DSMst (VAT) , “never”st (VAT) . A scoreVideo gaming motivation is a complex matter that includes intrinsic and extrinsic motivation components. The extrinsic motivation components are included integrated regulation, identification regulation, introjected regulation, and external regulation. Internal, personal feelings, and environmental forces influence intrinsic motivation. In addition, friends and family can belong to the extrinsic motivation category .Step 2. Reselected the surveyed data. To avoid adding incomplete and insufficient answers to our method, the questionnaire were reviewed. The criteria for removing the unsuitable questionnaire are as follows. Choosing repeated options to all multiple-choice questions, filling the questionnaires very quickly, leaving a question blank in the scoring test, and choosing two answers for single-answer questions.Step 3. The TOPSIS method. The compromise ranking TOPSIS method is adopted as an appropriate method to solve the MCDM problem that is non-commensurable and contradictory criteria. The procedure of the TOPSIS method is presented as follows. In this comparison benchmarking analsis, the set of criteria The TOPSIS method is based on a normalized decision matrix. For normalizing the decision matrix, each typical element of the After calculating the normalizing decision matrix, the weighted normalized decision matrix should compute with Equation (3) as follows: follows :(4)PIS=mNext is to compute the separation distances Eventually, the relative closeness to the ideal solution for each criterion is calculated by Formula (6):Indeed, a higher value of The AHP method. After collecting the data and scaling through the improved questionnaire, the output was inserted into the AHP method with respect to the proper weighting of the TOPSIS model. The first step to weight the criteria through the AHP method is to build the pair-wise comparison matrix. According to the hierarchical structures, the decision-maker can scale the system by scoring the criteria. The positive pair-wise comparison matrix ty scale . The scoAfter that, the summation of the scores is calculated for each criterion. For normalizing the pair-wise comparison matrix, each element of the matrix, The next step is to compute the average for the individual variants. To determine the respective weight values for each criterion, Check for consistency ratio (CR): To make sure that our weighing values are correct, the level of the consistency of the pair-wise comparison matrix must be checked. The consistency index (CI) can be computed as follows:CI = 0 implies that the pair-wise comparison matrix is perfectly consistent. If CI > 0, then the level of inconsistency should be examined by the Saaty scale [CI is the consistency index, and RI is the random consistency index which is proposed by Saaty [ty scale  with theby Saaty  in TableIn the AHP, if the CR is less than 0.1 then the consistency is accepted, otherwise, it will be rejected. The weights that are gained by the AHP method will be used as the weight score that is required for the TOPSIS method.Step 4. Ranking and Analysis. As we have three groups of analysis, this step is discussed in Results and Discussion sections. As mentioned in In this research, we aimed to rank the criteria from the students’ point of view for each grade. In addition, we investigated the top criteria from the point of view of the alternatives per grade. For this purpose, the TOPSIS and AHP methods were utilized. We used the AHP method for weighting criteria because of its accuracy, due to checking the consistency of the variables, to make sure the weights are correct. The TOPSIS method is one of the most well-known and common techniques for solving MCDM problems to rank the alternatives. Therefore, it was reliable for this research and could cover the results adequately for the alternatives.In this study, to get the real answer from the point of view of the children and adolescents, the student’s scores were made into the pair-wise comparison matrix in the AHP method and the decision matrix in the TOPSIS method. The questionnaires were given to the students to score all the questions from 1 to 5, using a 5-point Likert scale. The scores were summed together, and based on that, students were placed in one of the four alternative groups DM1–DM4.AHP method. To make the pair-wise comparison matrix, the total score for each question was calculated and rescaled from 1 to 9 for the Saaty scale. Since the values of the pair-wise comparison matrix are the ratio of each criterion over the other criterion, we obtained these values by dividing them by each other and gained the 18 × 18 pair-wise comparison matrix in Equation (7) with TOPSIS method. We performed two different analyses by ranking alternatives and criteria, which are discussed in In this section, we analyzed the VGAS criteria ranking with the weights of the AHP method based on four alternatives for each grade separately.The AHP method is using for weighting the criteria, and finding the best and the worst values. We aimed to analyze the prioritized criteria that were chosen by children and adolescents from the point of view of the four alternatives, “no symptom of addiction” (DM1), “at risk of getting addicted to video games” (DM2), “have some levels of addiction” (DM3), and “already addicted to video games” (DM4) separately. Here, each alternative works as an independent group. The rows in Grade 3. As we can see in Grade 4. The importance of the criteria from the point of view of 4th-grade students was different. Those who did not have any symptoms of addiction preferred to play video games instead of spending time with others (Q4). Those who were at risk of gaming argued with their family over their time-spending on video games (Q3), while they believed that they should play less video games (Q8). For students with some levels of addiction, others tried to reduce their playing time but failed (Q10).Grade 5. Those 5th graders without symptoms of addiction suggested that they should reduce their video game playing hours (Q8), although they tried several times to reduce their playing time but failed (Q9). Also, at-risk pupils similarly believed in reducing their playing video game hours (Q8). Those students who had some symptoms of gaming addiction stated that they did not sleep enough because of playing video games (Q5), as well as they thought about playing video games all day long (Q6). Additionally, they reported that they were spending more time playing video games than last semester (Q15). They disclosed that their willingness to play video games is due to forgetting their problems or feeling down (Q14).Grade 6. Students with no symptoms of addiction in grade 6 thought that they should play less video games (Q8). From the point of view of at-risk 6th graders, although they knew they should play less (Q8), they argued with others to spend more time playing video games (Q3). For students with some levels of addiction, Q14 preceded other criteria. They disclosed that they play video games when they feel upset or have some problems.Grade 7.Grade 8. As shown in Grade 9. 9th-grade students who did not have any symptoms of addiction agreed that they play more video games than they scheduled (Q2), likewise, they usually play video games because they feel down or have some problems (Q14). For at-risk students to gaming, in addition to Q2 and Q14, they reported some contention with others to play more video games (Q3), although they believed that they should play less (Q8). Those who had some levels of addiction behaved similarly to DM1. For those who were addicted to playing video games in grade 9, we saw some differences in the ranking criteria. They finished their daily responsibilities in a rush to play video games (Q12). However, they thought they played extra video games (Q2), and their attempt to play less video games was unsuccessful (Q9).Grade 10. In grade 10, the gaming criteria trend for those who did not show any symptoms of addiction was new. They reported that they neglected their important activities such as school assignments to play video games (Q13). Moreover, they expressed some arguments with their family about playing more video games (Q3). Students that were at risk of getting addicted prioritized Q2, Q3, Q8, and Q14. They tended to play more video games than their intention (Q2), as well as having discussions with their family about more video gaming hours (Q3). It was a surprise seeing that they believed they should play less video games (Q8). However, they have stated they play video games because of some problems or feeling down (Q14). Students with some levels of addiction in the 10th grade had the same opinion as DM2 in this grade, except that they did not believe they need to cut back on playing video games. Unfortunately, addicts to video games stated that they spend lots of time playing video games (Q2) because it is difficult to stop playing them (Q1). They even preferred playing video games instead of spending time with friends (Q4). Moreover, they reported a lack of sleep due to playing video games (Q5). Furthermore, they did their work in a rush to have more time to play video games (Q12), as well as neglecting their important activities such as homework (Q13). In one word, playing video games is a priority over everything for them.Grade 11. According to Grade 12. Unfortunately, in the 12th grade, all the students had some symptoms of addiction to video games or were at risk of it. For the students at risk of gaming, although they have extra time playing video games (Q2) and argued with others over playing time (Q3), they believed that they should reduce their video game playing hours (Q8). For those who had some levels of addiction, they confessed to extra playing (Q2). Additionally, they discussed with their family to spend more time playing video games (Q3). They even neglected important activities to play video games (Q13). The addicted students reported that they altercated with others for having more time playing video games (Q3). However, they believed that playing video games caused negative effects on their study (Q17), they usually played video games when they feel down or have a problem (Q14). They faced some physical discomforts because of playing video games (Q16). Furthermore, they felt that their life is not happy without playing video games (Q18).In this section, we employed the TOPSIS method to compare the four alternatives (DM1–DM4) against the criteria for each grade separately. For getting a more accurate result, the weights of the TOPSIS method are calculated with the AHP method. In this analysis, the alternatives are ranked based on their proneness to video game addiction. The separation distances, ratio values, and the ranking of the alternatives are classified in For middle school pupils , those who were at risk of gaming (DM2) were the most susceptible pupils to become addicted to video games, and those who had some symptoms of gaming (DM3) stand in the second place, however, they had some differences on 3rd and 4th places.The ranking of the alternatives for high school graders was the same in grades 10, 11, and 12 as DM2 > DM3 > DM4 > DM1. For them, those who were at risk of gaming were the most susceptible students to gaming, and those who had some symptoms of gaming stand in the second rank.As we have seen in We conducted an analysis of the criteria of the VGAS using the TOPSIS method on a total of 18 criteria that are associated with video game addiction. After calculating the weights of the criteria with Equation (9) with the AHP method, the relative closeness criteria to the best ideal solution was computed by Equation (6). As mentioned in Although getting not enough sleep because of playing video games (Q5) is the top factor that was opted by the 7th-grade students, lesser video gaming (Q8), and playing video games because of feeling down (Q14) stand in second and third place of priority, respectively. These values are changed for grade 8 by prioritizing Q9, Q8, and Q3. The 8th-grade students, as the first top criteria, struggled to spend less time playing video games although they failed (Q9). Playing less video games (Q8) was their second target, but they had disputed with family over having more playing hours (Q3). For 9th grade students, Q8, Q3, and Q10 are the top three criteria. Although they were aware that they should reduce their playing hours (Q8), on the other hand, they wanted to have more video gaming (Q3). In addition, others tried to reduce their video gaming hours, but they had not succeeded (Q10).For high school students, the priorities were a bit different. The main goal of all of them was to reduce their video gaming hours. For 10th grade pupils, Q8, Q3 , and Q7 (looking forward to the next video game playing turn) were before other criteria. For grade 11, the trend was similar. Q8, Q3, and Q9 were the 11th-grade students’ priorities. The 12th-grade pupils prioritized Q8 as the top choice. They unsuccessfully tried to spend lesser playing (Q9) which was in second place. Also, they reported less sleep because of playing video games (Q5) as the third choice.The trend of ranking the criteria is almost the same for the 3rd and 4th graders. The sorting of the criteria trend for the students in grades 5 and 6 is not much similar. However, the ranking of the criteria trend for the 5th and 7th graders is nearly the same. The sixth graders, who were about to finish elementary school, behaved differently in the criteria ranking than students in their age group (grades 5 and 7). It implies that they may become too immersed in playing video games. As shown in Although the 7th and 8th-grade pupils had few disagreements on a few criteria, they followed a somewhat similar trend in the ranking criteria. As 7th graders still followed primary students’ demeanor, perhaps it can be derived that the importance of criteria has been changed, as the junior middle school students, when they grow with senior middle school students. The pupils of grades 8 and 9 did not show the same behavior in the ranking criteria, while graders 10, 11, and 12 acted very similarly except in two criteria.The criteria ranking was quite different among middle school students . They seemed to be in a particular conflict over playing video games. Since they are at a risky age, their video game conduct needs to be further explored.All the criteria in the VGAS test with the AHP weighting were included in the TOPSIS method for ranking priorities analysis in Students in grade 3 who found it difficult to stop playing video games (Q1) had Q6, Q18, and Q4 as their last choices. The 4th graders who were given second place to Q2 did not tend to play video games instead of being with their friends (Q4). For them, it was easy to stop playing video games (Q18), as well as the fact that they spent enough time on their daily responsibilities (Q12). For pupils in grade 5, even though they reported playing the extra video games (Q2), they did not take their sleep time for playing video games (Q5). Moreover, they did not count the moments playing video games again (Q6). In addition, they have not reported getting upset or frustrated when they do not have access to video games (Q11). The most insignificant criteria for the 6th graders were quite similar to the 5th graders.Pupils of grade 7 who often did not get enough sleep due to playing video games (Q5), had a higher risk of feeling alone or depression, as Q14 was their third choice. For them, the Q11, Q12, and Q18 criteria were ranked last. They did not get sad or irritated when they could not access video games (Q11), as well as they did not rush in their daily work due to having more time to play video games (Q12). Moreover, the fun of their life was not limited only in playing video games (Q18). Students of grade 8 did not prefer playing video games over being with friends (Q4). Q5 and Q6 were the criteria with the lowest importance for them. The 9th graders had the same choices as the 8th graders on ranking Q5 and Q6. Also, they claimed they can stop playing video games anytime that they like (Q1).For 10th graders who looked forward to playing video games (Q7), no one had tried to help them reduce their playing time (Q10). Students in grades 11 and 12, who had tried to play less video games but did not succeed (Q9), claimed that playing video games did not have a negative effect on their studies (Q17). Students of grade 12 who slept less to have more time playing video games (Q5), reported they did not play more than last semester (Q15).In general, Q8 ranked as the topmost criteria by children and adolescents except for grade 6. Q3 ranked as the second most important criteria and Q6 as the poorest criteria by children and adolescents. Students who thought they should play less video games (Q8) were more likely to argue with others over playing more video games (Q3). Thinking about playing video games all day long (Q6) was their last choice except for grade 7. Middle school students were the most challenging pupils, as they had no similarity in ranking the criteria.Based on the definition of VGAS, 5.63% of the students in grade 12 had suffered from gaming addiction, 22.53% had some levels of addiction, 71.83% were at risk of addiction, and no student had no symptoms of gaming addiction. This is somewhat worrying that almost all the grade 12th students showed a symptom of gaming addiction. For grade 11, these numbers were 2%, 24%, 72%, and 2% for already addicted, have symptoms of addiction, at risk of addiction, and free of gaming addiction, respectively. The gaming rate in grade 10th was 2%, 26%, and 71% for addicted students, have some levels of addiction, and at risk of addiction, respectively. Only 1% of the students did not have any symptoms of addiction.The students of grade 9 had experienced another rate of gaming. Although, the rate of those who did not have any symptoms of gaming was 3%, almost 5% of the students were already addicted to video games. This is more than students in grades 10, 11, and 12. Of the rest of the students, 25% had some symptoms of addiction, and 67% were at risk of gaming. Students in grade 8 showed promising video gaming behavior. Among them, 7.93% did not have any symptoms of gaming addiction, and 79.36% were at risk of addiction. Only 11.11% of them had some symptoms of addiction, and 1.58% were already addicted to playing video games. The rate of gaming addiction results was concerning for grade 7. There was no student who did not have some symptoms of addiction, i.e., all of them were involved in gaming somehow. Almost 89% of them were at risk, 10% had some symptoms of addiction, and 1% of the total were already addicted to playing video games.The highest grade that the students were not getting addicted to playing video games was grade 6. Almost 18% of 6th graders reported that they did not have any symptoms of gaming addiction. A total of 73% reported that they are at risk of addiction, and 9% had some levels of gaming addiction. In the 5th grade, only 6.1% of the students had some levels of addiction, 76.83% were at risk, and 17.07% of the total had no symptoms of gaming addiction. The addiction trend is lower among grade 4 students. A total of 11.32% of them did not have any symptoms of addiction, 67.92% were at risk, and 20.75% had some symptoms of addiction. The level of gaming in grade 3 is at its lowest value. A total of 12.12% of the students had no symptoms of addiction, 75.75% were at risk, and only 12.12% had some symptoms of addiction to video games .In this research, a novel VGAS, the combination of VAT, GAS, and CIAS tests, has been proposed based on four alternatives for different levels of addiction to video games. Firstly, the AHP method was used as the underlying model to weight the criteria and analyze the student’s criteria prioritization under each alternative individually. Then, the TOPSIS method was adopted to rank the criteria. The results implied that among the primary school students  no case of gaming addiction was found. The 6th grade was the only grade that thought it was fair to play video games this much and did not need to reduce their playing hours; they were prone to get addicted to playing video games. The first addicted students were seen in grade 7. They confessed that they played video games longer than they intended. In contrast, no pupils in grade 7 and grade 12 were free of gaming addiction. Moreover, grade 7 as the first grade of middle school, and grade 12 as the last grade of high school, reported not having enough sleep because of playing video games. Furthermore, students with an addiction to video games in grades 7 and 12 were the only students who believed that playing video games negatively affected their studies. It seems that 7th and 12th graders have some similar attitudes towards playing video games.Playing video games because of feeling down or forgetting problems, seriously started in grade 8 students; this needs psychologists to check whether this attitude occurs after students start getting addicted to playing video games in grade 7. Middle school pupils did not have any similarity in prioritizing the criteria. Neglecting important activities was seen poorly just among high school students. Reducing playing time was a top priority for high school graders. The number of students in grades 10 and 11 who did not show any symptoms of gaming was only 1% or 2% of the total. Instead, the number of those who were at risk of gaming was around 72%. Overall, students become more inclined to play video games and subsequently become more addicted to playing video games as they get older. As previous studies have not deeply concentrated on VGAS criteria, thus, these results can help decision-makers to have a better understanding of children and adolescents’ preferences criteria in playing video games and take measures to reduce their video game playing hours.In our future work, we plan to find out the fundamental reasons that encourage children and adolescents to play video games. The causes can be their friends, society, their feeling, or even family.


To promote and ensure coaches' fidelity in delivering an online health coaching program to parents of children with suspected developmental delay, we developed and implemented a novel coaching fidelity rating tool, CO-FIDEL (COaches Fidelity in Intervention DELivery). We aimed to (1) Demonstrate CO-FIDEL's feasibility in evaluating coaches' fidelity and its change over time; and (2) Explore coaches' satisfaction with and usefulness of the tool.n = 4) were assessed using the CO-FIDEL following each coaching session (n = 13–14 sessions/parent-participant) during the pilot phase of a large randomized clinical trial involving eleven (n = 11) parent-participants. Outcome measures included subsections' fidelity measures, overall coaching fidelity, and coaching fidelity changes over time analyzed using descriptive and non-parametric statistics. In addition, using a four-point Likert Scale and open-ended questions, coaches were surveyed on their satisfaction and preference levels, as well as facilitators, barriers, and impacts related to the use of CO-FIDEL. These were analyzed using descriptive statistics and content analysis.In an observational study design, coaches (n = 139) coaching sessions were evaluated with the CO-FIDEL. On average, overall fidelity was high (88.0 ± 6.3 to 99.5 ± 0.8%). Four coaching sessions were needed to achieve and maintain a ≥ 85.0% fidelity in all four sections of the tool. Two coaches showed significant improvements in their coaching skills over time in some of the CO-FIDEL sections , and in overall fidelity . Coaches mainly reported moderate-high satisfaction with and usefulness of the tool, and pointed out areas of improvement .One hundred and thirty-nine (A new tool ascertaining coaches' fidelity was developed, applied, and shown to be feasible. Future research should address the identified challenges and examine the psychometric properties of the CO-FIDEL. FurtherBRIGHT Coaching is a tele-coaching program designed to empower and support caregivers of children with emerging developmental delays who are waiting for services in relation to their child's needs. It is currently being trialed in a nationwide randomized clinical study, across four Canadian provinces, including British Columbia, Manitoba, Quebec, and Nova Scotia  and are comparable among coaches. A fidelity assessment procedure to ensure faithfulness of the coach approach to the program requirements is suggested to be implemented for accurate interpretation of treatment effects in intervention-based research  do not BRIGHT Coaching: CO-FIDEL (COaches Fidelity in Intervention DELivery). In line with the Comprehensive Intervention Fidelity Guide Component 3 – Monitoring Intervention Delivery . Moreover, we sough to explore coaches' satisfaction with and usefulness of the tool (Objective 2).In view of these existing limitations and practice gaps, our team sought to develop and implement a new intervention-specific coaching fidelity rating tool for Delivery , our obj2.2.1.n = 4) experts in the field of family coaching and/or childhood disability research and clinical practice participated to CO-FIDEL development: a Social Worker & Psychotherapist (AB); Researchers ; Developmental Pediatrician (MO)); and a Postdoctoral fellow—Occupational Therapist (TO).CO-FIDEL's development process  includedBRIGHT Coaching, our team conducted and published a systematic review and analysis on existing coaching interventions that are provided to parents of children with or with suspected developmental disabilities  , 23 and . The cover page includes descriptors of the evaluated session and dedicated space for general comments  coaches were involved. All were new to the BRIGHT Coaching program. Coaches had on average 12.8 ± 6.5 years of experience in the field of social work, family functioning, family support, and/or child development. At the time of the trial, for forthcoming real-life generalizability purposes, three of the four coaches were not registered health professionals.Four  who is referred for diagnosis and/or therapeutic interventions due to emerging delay(s) in one or more domains ; having regular access to the Internet using a desktop, laptop, or a mobile device; being comfortable talking and reading in English or in French.All coaches and parent-participants have provided free and informed consent to participate in the study.2.5.2.5.1.BRIGHT Coaching randomized clinical trial's pilot phase, coaches were working with a minimum of one parent-participant, while some coaches had begun to work with several participants. The Lead Coach measured coaches’ fidelity following each coaching session using the CO-FIDEL by listening to the recording of the coaching session. The results were then shared with each coach and reviewed by the Lead Coach before their next scheduled coaching session. Outcomes included the fidelity rating in each of the four sections of CO-FIDEL; the overall fidelity rating; the number of sessions needed to achieve and maintain ≥85% fidelity rating (as per previously established acceptable level (As part of the le level ) in each2.5.2.A self-administered questionnaire consisting of a series of statements to be rated using a four-point Likert-Scale  and open-ended questions was used with the coaches . This qu2.6.2.6.1.(1)Overview: Coach Delivering Content & Attitude: Refers to the coach's ability to guide the participants through the content of each session, respecting the timeline and the related activities of each session, and the overall attitude of the coach during the session . This section was designed to parallel with the basic coaching competencies needed to be measured Global Coach Ratings/Motivational Interviewing Skills Code (MISC): Refers to the coach's motivational interviewing skills . It has five performance factors, where each is also scored on a 7-point scale ranging from 1 - “Low ability” to 7- “High ability”. In addition, examples of “Low ability” and “High ability”  are displayed on the scoring sheet to facilitate the raters' decision-making. An overall percentage score (ranging from 14.3 to 100) is obtained for this section as follows:(3)Behavioral Counts/MISC: Refers to behavioural counts consistent with the MISC  vs. those inconsistent . This section is scored as follows (ranging from 0 to 100):(4)Global Coach Ratings – Solution Focused Interview Skills: Refers to use of solution-focused interview skills . This section contains 7 items, each scored from 1- “Low ability” to 7- “High ability”. An overall percentage score (ranging from 14.2 to 100) is obtained for this section as follows:To obtain the overall fidelity rating, an average of the four sections’ scores was computed.Wilcoxon Signed Rank Test and the Mann-Whitney U Test, respectively. Significance was accepted at p < 0.05.Results were inputted into the Microsoft Excel Software and transferred to the IBM SPSS Statistics 27 for further statistical analyses. Descriptive statistics  were used to outline coaches' individual results per CO-FIDEL's section. Given the small sample size and lack of normal distribution of data, coaches' individual score changes over time in each of the CO-FIDEL's sections and the overall fidelity, as well as the differences between coaches' overall fidelity ratings, were examined using non-parametric tests, the 2.6.2.The four-point Likert Scale responses of the questionnaire were expressed as frequencies in each category: “Not at all”, “Slightly,” “Moderately,” and “Very Much.” Responses to the open-ended questions were analyzed using a directed content-based analysis technique  in the N3.rd, 2018, and April 3rd, 2019, coaches A, B, C, and D completed the entire BRIGHT Coaching program with eleven (n = 11) parent-participants. Coaches A, B, C, and D completed the program with 2, 3, 2, and 4 parent-participants, respectively. In total, 152 coaching sessions were delivered and 139 CO-FIDELs were issued. Thirteen coaching sessions (8.5%) were not assessed using CO-FIDEL secondary to audio recording and/or audio saving malfunctions.Between August 23n = 11; 10 females – mothers; 1 male – father) were caregivers of children aged 3.7 ± 1.4 years old . Some of these children were waiting to receive a diagnosis (n = 6), while others were waiting for services and were diagnosed with autism spectrum disorder (n = 5), global developmental delay (n = 1), intellectual disability (n = 1), learning disability (n = 1), Cohen's syndrome (n = 1), and speech delay (n = 1). On average, parent-participants were aged 37.2 ± 4.6 years old and had various educational levels ranging from master's degree (n = 2), vocational training (n = 5), college credits (n = 2), high school diploma (n = 1), to eighth grade or less (n = 1). Parent-participants' ethnic backgrounds included European ancestry  (n = 8), North American Aboriginal origins  (n = 2), East and South Asian  (n = 1), and Central Asian and Middle Eastern origins  (n = 1). Some worked full-time (n = 4), while others were working part-time (n = 3), were stay-at-home caregivers (n = 2), or were temporarily on a leave . The gross family income of parent-participants ranged between $100,000–$199,999 (n = 4), $75,000–$99,999 (n = 3), $50,000–$74,999 (n = 2), and $35,000–$49,999 (n = 1).Parent-participants . Coach C showed a significant improvement in Section 4 of the CO-FIDEL between the parent-participant_C1 and C2 , and in the overall fidelity between parent-participant_C1 and C2 . For coach A, a significant deterioration was noted for Section 1 of the CO-FIDEL between the parent-participant_A1 and A2 . However, no significant changes in overall fidelity scores were found. For inter-fidelity scores , a significant difference in the overall fidelity rating of the CO-FIDEL was found between coaches C and D for their respective parent-participants_C1 and D1, where coach D demonstrated significantly higher scores than coach C . No other significant between-coaches differences were detected.BRIGHT Coaching session for each coach. We note an overall high and consistent coaching fidelity across coaching topics, ranging from 92.7 ± 6.03 (Topic 1 – Telling your Story) to 97.9 ± 3.78 (Topic 11 – Experience your family). Nonetheless, a higher variability was found for Section 4 of the CO-FIDEL (Solution Focused Interview Skills (SFIS)), as demonstrated by larger standard deviations and lower average coaching fidelity scores across all sessions for two coaches . Coaches’ B and D scores were always above 85% across all coaching topics. Coach A had one instance of ≤85.0% score . However, this did not affect their overall fidelity score for this topic . However, coach C presented with more difficulty as four (n = 4) ≤ 85.0% scores were found for Section 3 , and five (n = 5) ≤ 85.0% scores were found for Section 4 . In addition, coach C had a ≤85.0% overall fidelity score for Topic 8 – Preparing for appointments (82.9 ± 8.2), which was mainly influenced by lower scores on Sections 3  and 4  of that session.3.2.Facilitators or positive impacts  and Barriers or areas of improvement with respect to the CO-FIDEL . Coaches reported more positive impacts related to the use of the CO-FIDEL than challenges . Coaches conveyed that the main benefit of the CO-FIDEL use was that it allowed them to pinpoint specific areas for improvement and highlight progress. For instance, one coach stated: “The CO-FIDEL helps me to notice trends where I could improve and also highlights my progress. It is a great tool to prompt self-reflection.”Responses to the open-ended questions revealed two main themes : Facilit4.COaches Fidelity in Intervention DELivery). In addition to outlining the development procedures of this tool, we sought to demonstrate CO-FIDEL's feasibility in evaluating coaches' fidelity and its change over time during the pilot phase of the BRIGHT Coaching randomized clinical trial; and to appreciate coaches' perspectives in the usefulness and satisfaction with the tool. To our knowledge, this is the first study to examine and present in detail the process of fidelity evaluation of coaches in delivering an online health coaching program in the context of childhood disability.We presented a novel rating tool developed by our team to evaluate the fidelity of coaches in delivering a health coaching intervention to parents of children with or with suspected developmental delays, called CO-FIDEL  and 4 (SFIS) of the CO-FIDEL for certain topics. This was the case for Topic 12 – From Surviving to Thriving and Topic 8 – Preparing for appointments. Sections 3 and 4 of the CO-FIDEL refer to the coach's ability and behavioural counts in using motivational and solution-focused interviewing skills . We speculate that the inherent challenges of the coaching topics may be at play and the novelty of the coaches to the program. More specifically, for Topic 12 – From Surviving to Thriving, the subject discussed can be difficult and sensitive for caregivers in times of uncertainty and vulnerability . For coaches, it could be a challenging session to evoke SFIS such as complimenting or amplifying solution talk, as well as being able to easily balance between manual content and spontaneous counselling. Similarly, for Topic 8 – Preparing for appointments, a coach may tend to use more inconsistent responses such as advice or direct without permission given that the content covered in this session is more didactic in nature. In addition, it should be considered that the coaches were new to the BRIGHT Coaching program and the parent-participants were their first participants. Nonetheless, is encouraging to observe that one of the coaches significantly improved their scores in Section 4 of the CO-FIDEL with their second parent-participant, suggesting that iterative feedback provided via the CO-FIDEL may support coaching skill progression.We showed that it is feasible to use the CO-FIDEL to evaluate the fidelity of coaching skills. Our study determined that the overall coaching fidelity was higher than the 85% threshold for all coaches in their first round of providing the intervention. It remained high for subsequent participants of each coach, and for one coach, it improved considerably from the first to the second participant. Similarly, two coaches showed significant improvements over time in certain sections of the CO-FIDEL. We propose that the iterative nature of the training  and the BRIGHT Coaching program. Nonetheless, reported barriers among others such as the possible ceiling effect, snapshot feature without follow-up/continuity across sessions, and missing elements. In response to those challenges, our team proposes the following solutions. For the possible ceiling effect, where a coach is scored high by the assessor but feels that improvements are still needed, we propose that the CO-FIDEL could be filled out by the coach him/herself and compared in a discussion session with the assessor to evaluate areas of discrepancies. In addition, we could increase the scale  to range from 0 to 10, similarly to a Visual Analogue Scale, which potentially leaves more room for interpretation and scoring. For the lack of continuity across sessions , we propose that scores could be inputted into prepared tables right after the scoring is completed, generating an instant graphical representation of the results. Those could be provided to the coach for reference, where their progress is visible from one session to the next. In addition, CO-FIDEL could be applied to randomly selected sessions coaching sessions post-pilot , to ensure a coach maintains their skills and abilities in providing the intervention. For missing elements, we propose to add items relating to coaching alliance and participant level of enjoyment and engagement in the session into Section 1 of the tool.In gathering coaches' perspectives on the usefulness of and the satisfaction with the CO-FIDEL, it emerged that they highly appreciated this tool in validating and improving their skills as they delivered the BRIGHT Coaching is designed to support and empower caregivers of children with suspected developmental challenges who are waiting for services. In addition, it addresses child-related needs in three coaching topics . Therefore, it is a parent and a child-focused program . Similarly, the Occupational Performance Coaching (OPC)  . Therefore, the CO-FIDEL emerges as one of the several available options for measuring the fidelity of delivering a mixed coaching approach program, where motivational and solution-focused interviewing skills are employed by the coach.Coaching in childhood disability can be parent- and/or child-targeted, depending on the focus of the program and the intended outcomes  . BRIGHT ng (OPC) , a progrt phase) , employst phase) . The usen = 13/152), leading to the loss of data needed to complete the CO-FIDEL for these sessions. However, this is a tolerable extent of missing data, given that 139 sessions were fully and successfully evaluated. Following the pilot phase of the trial, we made a switch to a new online meeting platform, accepting smaller bandwidth, which has shown to be working properly.We recognize the limitations of this study. The main shortcoming is that only the Lead Coach administered the CO-FIDEL. This was also the person who trained and continued to supervise and support the coaches, and therefore, might have been biased. Psychometric properties were not measured in the scope of this study. We also have a small sample size of coaches and pilot participants. We experienced some malfunction of the audio recording equipment/process of the coaching sessions ; Fidelity Check 2- randomly picked session from the second half of the program (Topic 7 to Wrap-up). If the coach reported that they had challenges or needed more guidance and feedback about a particular session, this session is assessed in addition to the randomly picked session. The Lead Coach also has maintained team and individual meetings to allow coaches to report and discuss difficulties and celebrate successes and improvements.To further optimize the validity of the coaching skills during the In conclusion, we aim to emphasize the importance of assessing coaching fidelity, as this plays an important role interpreting the results of an intervention study in terms of the validity of the findings. Its use highlighted coaches' strengths, weaknesses, skills improvement, and maintenance. We strongly encourage future teams conducting projects in health coaching to evaluate and describe processes related to intra- and inter-coach fidelity. In future research, we will focus on fortifying the CO-FIDEL according to the solutions proposed and study its psychometric properties.


Jan Aushadhi) was launched in 2008 and then revamped and rebranded as Pradhan Mantri Bhartiya Jan Ausadhi Pariyojana (PMBJP) in 2015. The current study focuses on the availability, affordability and acceptability aspects of PMBJP essential medicines.In spite of being the ‘pharmacy of the world’, access to essential medicines for a large majority of Indians is constrained by both physical and financial reasons. According to an estimate, medicines account for 69% of household out-of-pocket spending on health care. To make quality generic medicine affordable, India’s People’s Medicine Scheme . The survey was conducted in 11 PMBJP pharmacies in Mumbai and Palghar. Data were gathered on the availability, stock-outs, price and affordability of 35 essential medicines and 2 consumables.Apart from the limited coverage of essential medicines and the significant presence of Fixed dose combinations (FDCs) in the PMBJP medicine list, the availability of surveyed essential drugs was also found to be low (47%) in PMBJP outlets. Across Mumbai and Palghar districts, around 50% and 42% of medicines were found to be out of stock for the period of 3–6 months respectively. The cost of generic medicines of PMBJP outlets for treating various conditions range from 0.01 days’ wages to 0.47 days’ wages for the lowest paid unskilled worker in Maharashtra.The study findings show that PMBJP’s unbranded generics offer great opportunities for substantial cost savings. But, in order to fully realise the potential of this scheme, some policy actions are urgently required. First, the PMBJP drug list must include all essential drugs that feature in NLEM. Second, BPPI should procure only those drugs that pass the bioequivalence test. Third, compulsory de-branding of generics should be done in a phased manner. Fourth, PMBJP’s medicine procurement and distribution policies must be reviewed to address the supply chain issues. Moreover, there is a need for major pharmaceutical policy reforms to promote generic medicines in a big way. Regulations to support mandatory generic prescribing and generic substitution by pharmacists are needed.The online version contains supplementary material available at 10.1186/s12913-022-08022-1. Lack of access to essential medicines is a major health policy concern globally, even more so in the low-and middle-income countries. According to the World Health Organisation, a whopping 2 billion people worldwide are not having access to essential medicines . In otheThe issue of access to medicine is a primary cause of the skewed healthcare utilisation pattern in India. According to National Sample Survey Organisation, public facilities accounted for only 30% of the overall healthcare services in the year 2017–18 . This me-based pricing (MBP) methodology. That apart, for all non-scheduled drugs, the NPPA merely monitors their prices and an annual increase in the maximum retail price of up to 10% is allowed for such medicines.In India, prices of most drugs are fixed by the firms that manufacture or import the drugs into the country. Stated differently, prices of drugs are largely determined by market conditions and market forces. Only those drugs which feature in the National List of Essential Medicines (NLEM) come under price control . As of JA large number of observers branded the NLEM 2011 as irrational and have also been critical of the adoption of MBP approach by DPCO, 2013, abandoning the earlier cost-based pricing mechanism, for fixing the prices of essential drugs, arguing, that the impact of price control would be to make drugs available at reasonable prices but would at best partially address the issue of affordability and access to medicine as MBP has no relation with the cost of medicines –11. It wPradhan Mantri Bhartiya Jan Aushadhi Pariyojna (PMBJP)”, which envisaged making unbranded quality-assured generic medicinesAgainst this backdrop, in September 2015, the union government decided to expand its generic drug scheme called “Jan Aushadhi Scheme (JAS), was initiated by the United Progressive Alliance (UPA) Government in 2008. JAS, as is argued, is an important government intervention in the pharmaceutical market which would make the supply side effective particularly for consumers who are relatively responsive to price changes in making their purchasing decisions of medicines . PMBJP’s stated objective is to gain the confidence of the medical community and consumers in unbranded generics by generating awareness through education and publicity. In this study, we have assessed the acceptability of PMBJP’s unbranded generics It is worth noting that the Indian pharmaceutical market is flooded with irrational or non-essential drugs. For example, majority of fixed dose combinations (FDC) that are marketed in India are therapeutically non-beneficial and unsafe for use , 17. NotWe have used a mixed-methods approach, with the survey-based quantitative component supplemented by a qualitative component consisting of in-depth interviews (IDIs). The survey was undertaken to find out the extent of availability and stock-out of medicines at PMBJP outlets. In-depth interviews were intended to capture the perspectives of physicians and pharmacists on generic medicine in general and PMBJP scheme in particular.The survey was conducted in two districts of Maharashtra, namely Mumbai metropolitan region and Palghar. In terms of per capita income, Maharashtra is one of the richer states in India and Mumbai is its capital city. With a population of more than 20 million, the city is one of the most populous urban centres in the world. It has the distinction of being home to the largest slum population in any city in the world, displaying a high level of income inequality. On the other hand, Palghar is an economically backward district with a population of nearly 3 million and is primarily inhabited by the tribal people.A 3-tiered public healthcare delivery system is catering to the needs of the population of these two districts. At the bottom of the health services pyramid, there are primary health centres (PHC), sub-centres (SC) and health posts (HP), which focus on primary care. The mid-level of the pyramid, which is the secondary care level, includes rural hospitals and municipal general hospitals, and at the top level, tertiary care institutions like medical colleges are there. According to the PBBJP portal, 29 PMBJP pharmacies are currently functional across these two districts. To make the sample representative and consistent with the distribution of PMBJP outlets in Mumbai and Palghar, 11 pharmacies were selected for the study covering all levels of health care delivery system. The PMBJP pharmacies were purposively selected based on their proximity to public health facilities such as medical college (Tertiary level), Municipal General Hospital (Secondary Level) and PHCs and HPs (Primary level). PMBJP pharmacy’s proximity to the public health facilities was assessed using google maps  – 10 with pharmacists and 6 with physicians. Purposeful sampling was used for identifying and selecting the participants for IDIs. Physicians working in public or private sector and practicing in the periphery of PMBJP pharmacies were selected for the study. Only qualified allopathic doctors and the pharmacists registered under the state or central pharmacy council were considered for IDIs. Both quantitative and qualitative data were collected concurrently between January, 2019 and June, 2019.Aside from collecting primary data, secondary data such as the price information of some PMBJP medicines and their leading brand name counterparts (in terms of market share) were gathered from the web portals of PMBJP and MedGuideIndia.com respectively. The latter is a project of Vinod Kumar Memorial Trust. The website provides information on a wide range of drugs available in the Indian pharmaceutical market including their prices. The website is regularly updated by the Trust with assistance from Ministry of Consumer Affairs, Government of India.SPSS version 21.0 and MS Excel were used to analyse the quantitative data to measure theavailability, and affordability of essential medicines of PMBJP. Availability was defined as the proportion of PMBJP pharmacies in which the medicines were available at the time of the survey. We calculated the availability of medicines according to a specific therapeutic category. Hence, the medicines were grouped into therapeutic categories. The formula used for calculating availability is as follows: (n/N) X100, where n is the number of medicines available within a specific therapeutic category in a PMBJP pharmacy on the survey date and N referred to total number of drugs listed in that category as per the survey medicine list. For a PMBJP pharmacy at specific level of care , overall availability of medicine from specific therapeutic category was calculated using the following formula:ni was the number of drugs available within a particular therapeutic category at specific PMBJP pharmacy and P was the number of PMBJP pharmacies at specific level of care  and N was the total number of drugs listed in particular therapeutic category as per the survey medicine list. Hence, N X P gave the total number of drugs in that therapeutic category which were surveyed at all PMBJP pharmacies at PHC level in Palghar. For instance, if availability of 7 (N) antimicrobials medicines in 02 PMBJP pharmacies (P) at PHC level in Palghar was evaluated, then overall 14 units (PXN) would be examined. Against a group of these units, if 03 antimicrobials medicines were available in a PMBJP store and 04 antimicrobials medicines were available in another store, then the overall availability of anti-microbials in PMBJP pharmacies at primary level facilities of Palghar was 50% [((3X1) + (4X1)) X100/14].Here, Total availability of drugs from specific therapeutic category in all PMBJP pharmacies across three levels of health services system in a study area was calculated using the following formula:.i was in the range of 1–3, where 1,2,3 represented three different health care facility levels such as primary , secondary  and tertiary . Here, ni was the number of drugs from a specific therapeutic category available in a PMBJP pharmacy at a particular health care level and Pi was the number of facilities in that particular level of care and Ni was the total number of drugs listed in particular therapeutic category as per the survey medicine list. Similarly, stock-out of medicines was calculated for the reference period of six monthsTo demonstrate the opportunities for potential cost savings associated with the use of unbranded generics, we calculated the costs in treating patients for certain diseases with the PMBJP drugs vis-à-vis their largest selling branded-generic counterparts (popular brands). We chose the latter for comparison as it helps to gauge the potential savings that can be earned by the consumers from substituting branded drugs by the unbranded drugs of PMBJP. As far as the measurement of affordability of essential medicines is concerned, we followed the WHO/HAI methodology. Affordability was estimated by comparing the total cost of a PMBJP medicine for a standard course of treatment for common acute and chronic conditions to the daily wage of the lowest paid unskilled worker, which was supposed to be Rs. 355 in Maharashtra in 2019, as per the state government’s notification on minimum wages [The qualitative data was collected to understand the perception of the doctors and pharmacists on generic medicine as well as their views on PMBJP scheme. Following informed consent, the interviews were audiotaped while the first author also took notes. Recordings were translated from the local languages such as Marathi and Hindi in English, and then transcribed verbatim. We used thematic analysis , which wWe first examined the selected medicine list of PMBJP to assess the extent of coverage of essential medicines. NLEM, 2015 has 376 essential drugs whereas the PMBJP list contains 214 essential medicines. In other words, the overall coverage of essential drugs in PMBJP list is just 57%, when compared to the total number of essential medicines included in NLEM. Moreover, there is significant variation across therapeutic categories  than in Mumbai (51%). The findings suggest that availability of medicines vary significantly, ranging from 8 to 72% in Palghar and from 0 to 83% in Mumbai. Table Table Palghar 5% than inTable Among the medicines unavailable in PMBJP stores at the time of the survey, around 42% were out of stock for the period of 3–6 months, while 11% and 7% of drugs were found to be out of stock for 1–3 months and up to 1 month respectively Assessing the availability and affordability of generic medicine at PMBJP outlets is important, but perhaps it is even more important to know the physicians’ attitude towards generic drugs and PMBJP scheme, as they play a key role in prescribing generic medicines. Most of the physicians argued that generic and branded medicines have the same active substance(s).“Bioavailability of generic medicines is low as compared to branded medicines. Pharmaceutical companies market their brands by branding their bioavailability results. Poor bioavailability makes generic medicine less effective. Hence cost of generic medicines is lower than their branded counterparts.” (PuP3).Nevertheless, they claimed that generic medicines are not as effective as branded medicines. They also believed poor bioavailability is the reason why the price of generic medicines is less than branded medicines.. “Generics are good, but some products are not up to the mark. Some brands of antibiotics are found to be more effective as compared to their generic counterparts. For example, augmentin brand gives effective and quick results as compared to its simple generic amoxicillin clavulanate version. But generic medicines for diabetes and hypertension are very good and cost effective for the patients for chronic illnesses.” (PuP3).Clinicians working in the public sector said that they prescribe 99% medicines in generic form as the government supplies only generic medicines to public health facilities. Further, the healthcare professionals stated that generics do not yield good results while treating for acute conditions like bacterial infections, but they expressed confidence in generic medicines for chronic illnesses“We are ready to prescribe low cost generics, but it becomes difficult for me to convince my patients to take such a low-cost generic medicine. Most of the time patients want relief from pain as quick as possible and thus they are ready to pay even high for medicines. Hence, they question about quality and their effectiveness.” (PrP2).Some physicians reported that they face difficulties in prescribing generics as patients have negative attitudes towards cheaper medicines.“We are ready to prescribe generic only, but there is no mechanism to ensure that private pharmacy shop chemists would dispense right and cost-effective generic medicines. Because there are hundreds of generics with different prices are available in the market, chemists can substitute for prescribed medicine as per their wish and earn high profit margins. There is no proper communication channel between doctors, patients and pharmacists. The loop of three is incomplete.” (PrP3).In fact, the physicians have also cited other reasons for not prescribing generic medicines. The pharmacists, they claimed, will sell noneffective, or highly overpriced drugs once the authority to decide the drug for a given indication is bestowed upon the pharmacists through the policy of compulsory active ingredient prescribing.“We are prescribing generic drugs, but through their brand names. If government wants us to prescribe drug through their molecule names, why do they allow so many brand names and why are there such wide price variations?” (PuP2).Furthermore, the physicians expressed the need for developing a regulatory framework to contain the proliferation of brands by the firms operating in the Indian pharmaceutical market, which, according to them, pose a barrier in prescribing generic medicines. “When we write any generic medicines and if it is not available in hospital pharmacy, patients have to go to other pharmacies to buy it. If these Jan Aushadhi stores are available in Government hospital premises, patient can get those medicines easily.”(PuP2).The physicians, especially those from the rural Palghar district wondered why the generic drug stores are not opened in rural areas where it is needed more. Besides that, the public physicians stressed on the need for establishing the PMBJP outlets within the hospital premises, while private physicians asked for dissemination of information regarding the drugs listed under the PMBJP scheme.“Unless doctors are not getting convinced over quality, I don’t think they are going to routinely write out prescriptions with generic drugs.” (PrP3)Further, the private physicians underlined the need for developing strong regulatory mechanisms to ensure that generic drugs meet high standards of quality.In-depth interviews with pharmacists revealed about the non-supportive attitude of physicians practicing in the periphery of PMBJP stores. Pharmacists expressed their views as follows, “Doctors practicing here are not responding well to generic medicines. Doctors did not seem to be very much confident about the effectiveness of generic medicines. Doctors ask us to ensure efficacy of generic medicines by claiming it in writing.” (P8).“We did Jan Aushadhi scheme awareness campaign twice in the area with the help of Regional Marketing Head of Mumbai region for Jan Aushadhi scheme, we visited doctors practicing in the periphery of our Jan Aushadhi stores. But we didn’t receive cooperation from doctors.” (P10).Further, the functioning of PMBJP scheme is often disrupted by supply chain shortage from causes such as procurement or/and distribution issues.“Now what happens is most of the time we don’t get adequate supply of these Jan Aushadhi products in definite time. Because medicines are coming all the way from Delhi, which takes time. In this case, we have to rely on our own network. Hence, government can increase number of wholesalers, distributors in the scheme to improve availability of medicines at the stores.” (P9).One of the major consequences of supply chain disruptions is reputation impact.“Patients are attracted towards this scheme due to mass media campaign on PMBJP scheme, but most of the time there is lack of supply of medicines.” (P5)Some reported that quality issues are hindering the uptake of unbranded generics, and asked for strong regulatory framework for quality control.“Some generic medicines are not of good quality. In many cases the generic drugs do not produce the desired effect in the expected time which branded ones do. That is why doctors are reluctant to use them. Regulatory authorities need to provide more emphasis on quality control of generic medicines.” (P4).Universal access to medicines, a critical component of Sustainable Development Goals, is intended to ‘ensure access to safe, effective, quality and affordable essential medicines for all . UnfortuWe found that the overall availability of surveyed essential medicines was 47% in PMBJP outlets. Although the extent of availability of medicines seems to have improved at PMBJP stores, studies reported better availability in private sector in India and other LMICs , 26. TheOne of the key findings of our study is that PMBJP list included only 214 essential drugs, implying that it excluded more than 50% of drugs listed under NLEM, 2015. Furthermore, FDC drugs are included in various therapeutic categories in PMBJP list. The inclusion of FDCs of antimicrobials, FDCs for CVDs and other diseases pose a public health concern. It is worth noting that though considerable research showed issues with some antibiotic FDCs, these FDCs still find their way to the Indian market . Almost We found that switching from branded-generic medicine to unbranded generic medicines would lead to substantial cost savings for medicine consumers. Our estimates suggest that unbranded generic substitution would reduce pharmaceutical expenditure by 6–1129% of patient’s spending. Moreover, the unbranded generic medicines are found to be fairly affordable. These results are consistent with evidence from studies in other LMICs –32. HoweMaking medicine accessible at affordable prices to the masses will require more than the somewhat piecemeal approach to generic drug promotion that currently exists in the form of PMBJP scheme. The sale of PMBJP medicines is mainly dependent on the prescription of generic drugs by the physicians. But doctors from private health care facilities hardly mention the generic or chemical names of drugs on the prescription slips and only 60 percent of the prescriptions from public health facilities contain generic names . We founAlthough India’s case is lot more complex than most countries given the dominating presence of ‘branded’ generics in the Indian pharmaceutical market, it is worth learning from countries which achieved reasonable success in promoting the utilisation of generics. USA, the first country to implement a generic drug implementation policy, achieved 89% share of generic drugs in 2016 and this reduced the medical insurance expenditure by US$ 67.7 billion . Japan, Although we reported availability, stock-outs and affordability of medicines in the PMBJP pharmacy outlets, a more comprehensive assessment of the accessibility of essential medicines may have included measurement of medicine prices, prescription pattern and out-of-pocket payments on medicines. In fact, we did carry out prescription audit as part of the overall study, but its findings are not included here. The present study adopted descriptive cross sectional research design to assess the current situation of PMBJP scheme in two districts of Maharashtra. However, to fully understand whether rebranding of JAS as PMBJP improved the accessibility of essential medicines, a pre/post evaluation study would have provided better insights but that could not be performed due to the non-availability of comparable baseline survey data.Further, we did not fully follow WHO-HAI methodology for calculating availability of essential medicines as the list of surveyed medicines was modified to meet the contextual requirements. Besides, we did not compare the prices of unbranded generics with international reference prices as recommended by WHO-HAI methodology since there is already overwhelming evidence showing that generic prices in India are less expensive compared with international standards. Lastly, this study was restricted to two districts of Maharashtra state. Thus, the scope for generalisability of the study findings, especially on availability and affordability of PMBJP medicines is limited.The low availability of medicines at PMBJP outlets reflects the implementation issues faced by the scheme. Nevertheless, the study findings show that PMBJP’s unbranded generics offer great opportunities for substantial cost savings. But, in order to fully realise the potential of this scheme, some policy actions are urgently required. First, the PMBJP drug list must include all essential drugs that feature in NLEM. Second, BPPI should procure only those drugs that pass the bioequivalence test. Third, compulsory de-branding of generics should be done in a phased manner. Fourth, PMBJP’s medicine procurement and distribution policies must be reviewed to address the supply chain issues.Moreover, there is a need for major pharmaceutical policy reforms to promote generic medicines in a big way. Regulations to support mandatory generic prescribing and generic substitution by pharmacists are needed. Besides, CDSO must ensure that generic medicines available in the Indian pharmaceutical market are bioequivalent and those qualifying bioequivalence tests should be listed along with their branded counterparts and price on a public or PMBJP portal.Additional file 1. Data collection tool – Availability and stock out duration of medicines.Additional file 2: Table A2. Profile of Medical practitioners involved in study.Additional file 3: Table A3. Details of Pharmacists.