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Effects of timing of initiation and planning on smoking cessation outcomes: study protocol for a randomised controlled trial
Ron Borland1,
James Balmford1 &
Elena Swift1
Recent theoretical and empirical work has led to debate over the benefit of delaying the implementation of a decision to quit smoking in order to plan the attempt. These two need not be linked, planning can occur before a commitment to quit is made, or after it is implemented, as well as in between. This study will test whether there are independent benefits for encouraging smokers to act immediately on a definite decision to quit smoking, and to engage in structured planning.
A complex randomised controlled trial with a factorial design, testing the presence of a recommendation to quit immediately (or not) and encouragement to structured planning (or not) as additions to standard care, a web-based automated tailored advice program (QuitCoach). Participants are recruited from users of the QuitCoach who reside in Australia, do not report a mental health condition for which they are taking medication, are adult daily smokers, and at least open to the possibility of quitting. For the Immediate arm they could not have committed to quit within 2 days, while the Planning arm included all these and those quit within the last 4 days. This creates 6 groups: 2 × 3, with 2 × 2 fully randomised, and 2 only randomised for the planning arm. Follow-up assessments are conducted around 1 month (targeting two weeks after the quit attempt started), and 6 months later. The primary outcome is 6-month sustained abstinence at 6 months. Secondary outcomes include point-prevalence abstinence at both follow-ups, and making quit attempts during the intervention period. We will also explore differences in actual behaviour (timing and planning) by intervention, and relate this to outcomes.
This study will result in a better understanding of the roles of planning and delay in influencing the success of quit attempts.
Australian New Zealand Clinical Trials Registry http://ACTRN12612000613808
Most attempts to quit smoking fail. Borland et al. [1] recently estimated that the average smoker makes around 1 unsuccessful quit attempt per year, defining attempts as quitting for at least a day. They found around 40% reporting attempts (average around 2 each), but that at least 20% of attempts are forgotten within the year. Smokers also report a similar number of aborted attempts (plans to quit that did not achieve 1 day of abstinence). This represents a lot of failed effort. Other researchers have estimated that only 3-5% of smokers are able to achieve prolonged abstinence for 6–12 months after a given unassisted quit attempt [2], an estimate consistent with the high levels of failure. Relapse is most common within the first week [2]. Good quality structured support and advice increases smoking cessation rates over those achieved in self-managed attempts, independent of any effect attributable to use of pharmacotherapy [3], but effects of both kinds of intervention are modest. However, evidence suggests little or no success in reducing relapse beyond the early days of an attempt [4, 5]. There is a need for better strategies to reduce relapse.
It is widely believed that planning for a difficult task like quitting smoking should result in increased success. The importance of planning is emphasized in stage-based models of behaviour change [6], and is implicit in models that specify the factors leading to the formation of a behavioural intention, such as the Theory of Planned Behaviour [7]. Smoking cessation guidelines for health professionals e.g., [8–10] typically recommend that smokers be encouraged to set a quit date in the future (usually 1–2 weeks later), and to prepare for this date using a range of strategies including dealing with perceived barriers to quitting, seeking social support, considering the use of pharmacotherapy or behavioural assistance, keeping a smoking diary to better understand triggers to smoke, and developing coping strategies to deal with them.
Recently, theoretical and empirical developments have led to a questioning of the primary importance of planning for quit success. PRIME theory, a comprehensive theory of addiction proposed by West [11], has drawn attention to the instability of motivation [see also [12]; Borland, forthcoming] and to the primacy of impulses and emotions in the motivational system. According to the theory, smokers may experience 'tension' or dissonance about their smoking over a period of time without being moved to action, until a precipitating event occurs that triggers action. When a quit effort is triggered by such an 'epiphany', it may be launched with a motivational momentum that increases the likelihood of success. Delaying a quit attempt following such an event in order to plan for it may be detrimental, as it can lead to a decline in motivation over the planning period, thus resulting in the attempt being made on average during a period of reduced motivation. Related to this several recent studies, using retrospective reports, have found that those who successfully quit (typically stopped for more than 6 months) have been more likely to report that their quit attempt was spontaneous, i.e. occurred as soon as the decision was made, rather than allowing a period for planning, than those who reported a failed attempt [13–17]. A study of ours found much more complex patterns with some evidence of shorter planning periods associated with less success, but no effect for longer delays [18]. Population-based retrospective studies of cutting down to quit (a form of preparatory planning and something that precludes spontaneous quitting completely) find it also results in less success than abrupt cessation, even among attempts that result in a period of cessation [19].
At this point, it is premature to conclude that delay is detrimental. The Murray et al. [15] paper provided some evidence that at least some of the effects are due to differential forgetting. Forgetting could be because a lead-in period increases the duration and thus potential salience of the event for any given length of time quit, and does this proportionately more for short attempts. Alternatively, pre-quit periods might be disproportionately likely to be forgotten with time quit as they form a smaller part of the total event. However, if the effects are real, it suggests that some forms of preparatory activity are counterproductive. Borland's (forthcoming) dual process theory of behaviour emphasises the continually changing, environmentally cued, reactive tendency to smoke, and argues that self-regulatory functions need to be able to sustain a level of motivation for change sufficiently long for both a quit attempt to be initiated and for it to become a stable new behaviour pattern. This requires effort, which is prone to be exhausted [20, 21]. As effort is required in the preparatory stages, delay will bring forward the point of exhaustion, all other things being equal. So unless preparatory activity actually leads to the task becoming easier at a faster rate than the effort involved leads to exhaustion, relapse will be more likely under conditions of delay.
Up to around half of quit attempts are reported to start immediately the decision is made [13–18]. Cooper et al. [18] also found that a minority of attempts begin after a period of abstinence for other reasons (e.g. being too ill to smoke), with only around half delaying implementation. Qualitative research [15], an in-depth empirical study following smokers on a day by day basis [12], and our own work all point to greater complexity regarding what is meant by both spontaneity and planning. First, implicit in West's model is that spontaneity relates to peaks in fluctuating levels of longer-term concern; that is, that 'spontaneous' quit attempts are typically preceded by periods of deliberation that are not strong enough to trigger action, rather than occurring completely out of the blue. Certainly, a lot more smokers report thoughts of quitting than go on to try in any given period of time [1]. Second, planning may be able to be carried forward from previous, especially recent attempts. Third, our work has found that a proportion of those reporting spontaneous quits also report cutting down to quit and/or using medications (e.g., Varenicline) that require a period of use prior to stopping smoking (unpublished data). Clearly these do not represent cases of spontaneously fully implementing a quit attempt.
There is clearly ambiguity as to what constitutes a spontaneous attempt and how that relates to planning. First, what has been caught up under ideas of spontaneity really covers two quite distinct concepts: the spontaneity of the decision to quit (i.e., whether it is made without any preparatory thought or related activity); and the immediacy of implementation (i.e., whether implementation occurs immediately the decision to quit is made or with some delay). Implementation can also either refer to stopping completely (full implementation), or beginning a process that will lead to full implementation; e.g., arranging for a doctor's appointment to get prescription medication, beginning a period of preloading with medication, or starting a cut-down schedule. Where implementation is staged, the actual quit date might not be set until reaching the target window for quitting (e.g., for Varenicline from 1–2 weeks after initiating use), and implementation could then be 'immediate' or sometime in the future (delayed). This analysis suggests that it may be useful to distinguish four key concepts, defining a spontaneous attempt as one where the decision or process of deciding is initiated without any prior forethought (at least recent); delay in initiation as a gap between the decision to act and the initiation of the attempt; initiation of implementation as beginning to perform any action necessary to the chosen approach (e.g. obtaining medication); and full implementation as actually stopping smoking completely.
We now turn to a similar analysis of planning, or more correctly, pre-planning, as we are not considering on-the-spot planning to deal with actual challenges. The term 'planning' can refer to a wide range of possible activities from simply forming some intention to act (I am planning to quit), through to various forms of preparatory activity. The research referred to above has tended to assume that planning must occur before action, and that spontaneous attempts preclude the possibility of planning. It is true, where a spontaneous decision is fully implemented immediately, that there is no opportunity to pre-plan a quit attempt. Otherwise, there is the possibility of conditional planning (i.e. before deciding to quit) or of engaging in planning between making the decision and full implementation. However, while delay provides the opportunity to plan, it does not mean it will happen.
There are some aspects of planning that must by necessity occur before full implementation, such as deciding on how to quit (abruptly or by cutting down), whether to use help such as Varenicline that should start before actually quitting, and planning activities like keeping diaries of cigarettes smoked. However, many aspects of planning can equally occur before or after quitting, such as planning for high-risk situations and seeking social supports. Anticipating and forming strategies to deal with events that may precipitate relapse can occur after a quit attempt has started, though situations that will be encountered early on, such as dealing with strong situational cravings, would have to be prioritized. Assuming the person is not already craving a cigarette when they make the decision to quit, they should have some time to plan before any serious cravings occur, and except for the minority who experience almost continual cravings, should have time between bouts of craving to plan for future instances, even if they have to deal spontaneously with a couple of unplanned-for episodes of craving before their planning is complete. Certainly, the notion that the sequence must be to decide, plan, then implement is by no means a necessity, and what limited data we have suggests it is by no means the norm. There is also no good evidence as to whether the timing of these activities has any effect on their utility.
It is also plausible that the quality of planning is at least as important as its presence. Recent research has shown that a form of planning called an implementation intention can improve outcomes [22]. An implementation intention is a self-statement of the form when or if some specified event occurs, I will engage in some specified protective action; e.g., 'when I get a craving to smoke while with my friend Jim, I will remind him that he has agreed to help me stay quit'. A meta-analysis of 94 studies found forming implementation intentions to have a medium-to-large effect on goal attainment, over and above the impact of forming relevant goal intentions [23]. More recently implementation intentions have been shown to facilitate ongoing goal striving (relapse prevention), protecting individuals from the influence of potentially disruptive inner states such as cravings [24]. It appears to be a new and important strategy for getting people to implement plans at the appropriate time. That said, all of the studies to date have either been of relatively straight-forward behaviours, or have only considered short term outcomes for more complex ones like smoking.
This study is designed to test (a) the potential benefit of structured support for planning, and (b) the potential benefit of recommending an immediate start to the implementation of a quit attempt.
Conducting RCTs of events where choice is under the control of smokers rather than researchers/clinicians is always complicated and often requires compromise. It is particularly problematic when smokers' spontaneous choices might contribute to the therapeutic effect. We cannot randomize spontaneity, but independent of whatever pre-decisional planning smokers have engaged in, we can randomize to encouragement to quit at one time or another, and to the provision of structured help to facilitate planning, but are limited in our ability to constrain the timing of the planning that is undertaken.
Advising people to stop smoking immediately is unlikely to be a sensible intervention strategy because it precludes use of the forms of help that require a period of pre-quit use (e.g. Varenicline). Immediate implementation is defined here as immediately taking whichever 'next step' is required to ensure that the quit attempt takes place without avoidable delay, and only for some will this be stopping immediately. We will record instances of unavoidable delay, to see if this makes a difference.
In this study, we will recruit a group of smokers at a time when their motivation to quit is high, and at the point at which they seek cessation assistance, but who are not sufficiently advanced in their progress towards becoming an ex-smoker to preclude the provision of either or both interventions. The use of web-based cessation help is an ideal setting, as smokers can access it when considering quitting and there need be no delay. While some smokers access this form of help after quitting, most do so before, including many who have not yet committed to an attempt [25]. The QuitCoach [26], a demonstrably effective Internet-based automated tailored advice program developed by the authors [27], is designed to assess a smoker's situation and provide immediate assistance. Users complete a 10-minute online assessment and receive tailored advice based on their answers, which can either be read on screen or downloaded as a PDF document. The program is designed to be used on multiple occasions, with return to the site recommended after a significant change has taken place, such as actually initiating a quit attempt, or to prevent relapse.
The primary hypotheses are that among smokers who seek help from QuitCoach, 6 month sustained abstinence will be greater among:
those encouraged to begin to implement a quit attempt immediately as compared with those supported to quit to their own timetable); and
those who are provided with a structured planning program with prompts to engage in planning activities and encouragement and supported to form implementation intentions as compared with those only provided motivational messages and general encouragement to plan.
Secondary aims are to:
test for any interaction between the two interventions, particularly to see if the two add value when combined;
test the hypothesis of a dose–response relationship for actual use of the planning resources and with other planning activity;
test whether more dependent smokers will be more likely to benefit from the planning intervention;
test whether smokers with a recent history of quit attempts and those who report at baseline that they have already engaged in planning will be less likely to benefit from the planning intervention; and
explore the relative benefits of the timing of planning (e.g., more before vs more after) on success.
This trial has two levels of randomisation: first into the provision of structured planning tools (YES/NO), and then among that proportion of the sample who have not committed to an imminent attempt or already quit, randomisation into encouragement to quit as soon as possible (YES/NO) (see Table 1).
Table 1 Study design
Eligibility for the Immediate arm is limited to those without a fixed quit date, or with a quit date two or more days away. The Structured Planning arm is open to all current smokers regardless of quit date, and also includes those quit for less than 4 days. The 2 × 2 design allows a test for interaction effects between the two aspects of each arm. The addition of the two supplementary conditions allows for a randomised test of the utility of structured planning on a broader sample, and non-randomised comparisons of the differential success rate of the QuitCoach as a function of participants' progress toward quitting at recruitment (no quit date, quit dates of various times in the future, or already quit).
Participant recruitment
Participants will be recruited from QuitCoach users. Eligibility will be limited to those who are over 18 years of age, who reside in Australia, do not report a condition that would require referral to an in-person service (i.e. medicated for a mental health condition), and are interested in quitting smoking. For the Immediate arm it excludes those committed to an attempt within the next 2 days, but these are included along with those quit for up to 3 days in the Structured Planning arm. Interest in quitting is assessed by: "Which of the following best describes your current thinking about quitting? (a) I am planning to quit; (b) I am just open to the possibility (both eligible); (c) I am not interested in quitting in the near future (not eligible)". QuitCoach users who do not consent to participate in the research receive the standard program.
Following the questions to establish eligibility (all part of the standard QuitCoach assessment), eligible participants are invited into a study "to find out whether the way people use the QuitCoach affects their chances of successfully quitting". They are also told the study involves completing two short follow-up surveys, and that they might get access to some added functionality of the QuitCoach which are not yet available to everybody. They are also told: "We ask you to consider whatever recommendation the QuitCoach makes carefully and to follow the advice, unless you have good reasons not to." Those consenting are sent an email welcoming them to the study and the brief research description.
We will use anonymous group data to assess whether those who agree to participate in the research differ from other users of the QuitCoach who meet the eligibility criteria.
Randomisation and allocation concealment
Randomisation is via a hidden binary number generator in the on-line recruitment survey which is activated after the person consents, allocating a code of 0 or 1 for each arm of the study (i.e., 0,0 = neither immediate implementation nor structured planning; 0,1 = no immediate implementation, receiving structured planning; 1,0 = receiving recommendation to quit immediately but no structured planning; 1,1 = receiving both interventions). Participants know what they are receiving (as blinding of participants is impossible in trials of behavioural interventions), but they are not told about the alternative arms, so are blind to differences between what they and others are receiving.
Base condition This is the standard QuitCoach (the CC arm in Table 1). The QuitCoach consists of an assessment phase where users are asked a range of questions tailored to their progress towards quitting. No advice is provided during the assessment, except to a subgroup not eligible for this trial who report a mental health condition for which they are taking medication, who are recommended early in the assessment to seek medical advice in conjunction with use. On completion of the assessment users are provided with a tailored letter that provides a mix of personalised advice and encouragement tailored to their quit progress, level of addiction, self-efficacy, smoking-related beliefs, social supports, base levels of positive and negative affect, and identified challenges in dealing with temptations to smoke. Users are encouraged to quit when they are ready. The advice provides suggestions about the use of planning strategies, but they are not particularly highlighted, nor is any direction as to how to implement them provided in the letter. Third, there is provision of a range of untailored resources, which the tailored letter refers to where relevant, and those referred to are highlighted as being of potential use. Users are encouraged to use the program multiple times, and on second and subsequent times, feedback is provided not only on reported states at that time, but on progress from the previous assessment. Email reminders are sent to encourage return. Based on the evaluation of an earlier version of the program, only around one quarter (27%) return for a second assessment [25], even though multiple visits is associated with better outcomes [27].
More information about QuitCoach is available in the supplementary materials accompanying Borland, Balmford and Benda [28]. Readers who would like to see how the QuitCoach differs for each study condition can do so at http://historical.quitcoach.org.au (instructions for accessing the content of each condition are provided on the site).
The immediate implementation arm (IC and IP groups) This involves a modified version of the standard QuitCoach with key elements of the intervention delivered during the assessment stage. Those in this arm are encouraged (recommended) to quit immediately, or as soon as practically possible, during their initial QuitCoach assessment (and any subsequent assessments, if they have not already quit) ('We suggest you think about setting a quit date right now. There is nothing to be gained by delaying it'). They are provided with a brief explanation of the reasons for doing so: that some recent research suggests that quitting as soon as you decide may increase the likelihood of success over delaying implementation. Those who have already set a quit date are encouraged to bring their quit date forward ('We suggest you bring your quit date forward, as there is nothing to be gained by delaying it. Choose the earliest time you can'), ideally quitting immediately, later today or first thing tomorrow morning. Others are encouraged to take the next step toward quitting as soon as possible (e.g. for those planning to take prescription medication 'We recommend you call the doctor to make an appointment immediately'), implement their quit attempt immediately they have done all they need to do, and to do this preliminary work in as short a period as possible (e.g. for those planning to cut down, 'if you want to cut down, take no more than 4 more days to quit completely'). This is all done during the assessment phase. In addition, any commitment to immediate implementation is reinforced in the advice letter, and for those not taking up the suggestion during the assessment, they are encouraged to implement as soon as they feel ready to commit.
The structured planning intervention The structured planning augmentation of the QuitCoach (the IP, CP and XP arms of the study) consists of additional highly prescriptive instructions for planning a quit attempt, organised around two main tools; a To Do List (TDL) and a Problem Planner (PP). The To Do List operates something like the Task function in some computer diaries. It prompts the user by listing the most important things they need to do to increase their chances of quitting smoking successfully, with an indication of when they need to be done. The Problem Planner provides a template for the development of implementation intentions to survive identified problem situations.
Figure 1 shows a screenshot of the TDL for a study participant, displayed upon their return to the QuitCoach. The content of the TDL is dynamic, based primarily on smoking status/intention to quit, but also on other responses to the QuitCoach assessment including static variables such as age and gender, as well as things like levels of temptations and urges to smoke.
Example screenshot of the to do list. A screenshot of the TDL for a study participant, displayed upon their return to the QuitCoach.
A maximum of 3 tasks are displayed on an individual's TDL at any one time, with the list tailored both in terms of the tasks that appear on it, and the order in which they appear. The limit is to prevent the task seeming too overwhelming, and to maximise the completion of the tasks we consider most likely to be helpful. Each task is accompanied by a priority rating (highest, high or medium). Tasks potentially listed for inclusion on the TDL include: (a) finding out more about the health effects of smoking; (a) making or reviewing a list of your reasons for quitting; (b) deciding on a plan for how to quit, e.g. cold turkey or by systematically reducing consumption; (c) deciding on and, if relevant, implementing a plan for use of medication; (d) developing and documenting both cognitive and behavioural plans for coping in high-risk situations, using the Problem Planner; (e) making plans to ensure that friends and family are on-side to provide social support; (f) planning a schedule of rewards for achieving abstinence goals; (g) making your home smoke-free; (h) writing a list of things you will miss when you quit, and considering how these things can be achieved in other ways; (i) learning simple stress management techniques; (j) reviewing what went wrong on the previous quit attempt; (k) creating a smoking diary to better understand your smoking, and (l) if quit, spending a few minutes preparing for the day ahead. Many of these tasks refer participants to resources available on the QuitCoach site. These resources are available to all QuitCoach users, but only those in the structured planning arm will be directed to them in a systematic way. Participants may also add their own tasks to their TDL, but these do not displace existing tasks on the list.
Participants are encouraged to form implementation intentions for each listed task to help ensure each behavioural proscription or self-identified strategy for dealing with tempting situations is carried out. The instruction to do so is worded: 'In the box below, write when you will do this, and anything else you want to add that will help you'. Tasks on the TDL are able to be marked as completed (at which point they are removed from the list and added to a 'completed tasks' list) or if the person decides not to do it, rejected (and added to a 'rejected tasks' list). Tasks marked as completed or rejected are replaced on the TDL by the next-highest priority task, if one exists.
The Problem Planner (PP) is a dynamically-generated form, presented in the form of a 'wizard' across several screens, into which participants can enter strategies for dealing with the situational temptations to smoke they identified during the QuitCoach assessment as likely to be difficult for them. For each identified strategy, participants are encouraged to form an implementation intention to help ensure that the strategy is remembered and implemented when needed (for example, 'If I am at the pub and my friends go outside to smoke, then I will stay indoors and think about how much better it is not to smell of secondhand smoke). The PP wizard is structured into seven categories of tempting situations, of which five are presented to any one user. Three of them are mandatory (dealing with crises, strategies for slipups and other situations (those not covered earlier)). Two are chosen from the other four (coping with stress, social situations, first cigarette of the day, and filling in time), based on responses to the QuitCoach assessment. Under each category of situation, participants can create as many 'if-then' statements as they wish. Upon completion of the wizard, the PP is compiled into a form that can be viewed on screen and printed as a PDF document. On subsequent visits to the site this form can be edited, should the participant wish to add or delete problem statements. The planning intervention is designed to support those receiving it, and thus we would expect those users to return more often to the QuitCoach than other participants, although nothing mandates this.
Integration of the two interventions (IP group) Because the Structured Planning intervention is tailored to any level of immediacy in quitting, there is nothing unique about this group except that more will be doing their planning after the initiation of their quit attempt and more after full implementation (as will the XP group).
Common elements Frequency of use of the QuitCoach is at the participant's discretion, regardless of which of the four possible study arms they have been randomised to. Thus, there is no set endpoint for delivery of the intervention. All participants will be reminded to return to the site via emails sent periodically over several weeks, scheduled according to their readiness to quit.
We collect research information at three points: 1) at baseline, incorporated into the QuitCoach assessment (nearly all questions used are part of the standard assessment); 2) a first follow-up two weeks after the estimated quit date for each participant, or where the quit date is unknown or a quit date has not been set, a month after recruitment; and 3) A final follow-up 6 months after the identified quit date for each participant, or a comparable time after recruitment if no quit attempt was reported at the initial follow-up. Follow-up assessments will be conducted over the Internet, using email invitations including a web link to prime respondents to do the surveys online, or for those failing to respond to this, by telephone interview (the emailed invitation includes a notification that those failing to respond will be called).
The QuitCoach assessment, used as the baseline survey, includes validated measures of sociodemographics, quitting history, intention to quit [29], self-efficacy to quit [29], nicotine dependence [30], pros and cons of smoking and temptations to smoke [31], determination to quit [32] and a 5-item measure of positive and negative affect. All of these are used in the advice tailoring algorithms. To this we have added measures of rated quality of life, health status, perceived usefulness of planning, and the extent to which planning has already taken place on the current quit attempt (prior to recruitment). The base assessment will also ask for residential details (i.e., postcode) with which to determine socio-economic status as measured by SEIFA levels of area disadvantage [33].
At the first follow-up, we will assess smoking status, including implementation of the suggested quit date and actual quit date. We will ask about the extent of any planning undertaken since the baseline survey both pre- and post-full implementation of quit attempts (as relevant). We will measure use of other cessation support and use of pharmacotherapy (both pre-and post-implementation). The questions on affect will be re-asked in order to assess stability of mood. Finally, among those quit, we will measure self-efficacy to stay quit, extent of cravings [34], and determination to stay quit [32].
The final (6-month) follow-up will be restricted to measuring outcomes; smoking status, duration of time quit, and any lapses.
Engagement with the intervention will also be measured using naturally collected unobtrusive objective measures of program use [35], using web server log files and session identifiers linked to individual login names. Data collected will include the number of QuitCoach assessments completed and partially completed, number of log-ins to the site, number of openings of the advice page, To Do List and Problem Planner, number of edits of the To Do List, and number of times the additional resources page is viewed.
Sample size calculation
As noted earlier, we expect that a minority of participants will not comply with the recommendations to which they had been randomised. Based on levels of intervention usage achieved in a previous study in which participants were offered use of QuitCoach, a text messaging program or a combination [36], we anticipate at least 50% of those offered a program of structured planning will undertake a criterion level of planning (defined as one or more of seeking social support, practicing replacement strategies, or forming plans for coping with challenges, as reported at the first follow-up), whereas less than 5% of those in the IC and CC conditions will do so. We expect around 60% acceptance of the immediate implementation recommendation. This effectively means that the real effect of the intervention will be around twice the observed difference, which must be taken into account in power calculations.
We consider a 5% difference in absolute success rates (6 month sustained abstinence) to be highly significant. The expected base cessation rate for the control group (CC) is 18%, based on a comparable group from [28]. We propose a sample size of 600 per group (1200 per main effect comparison), which will provide 86% power to find a 5% increase in the success rate (23%) in the IC and CP conditions. We will have 98% power to find a 10% increase in the success rate (28%) in the IP condition over the CC condition, assuming no interaction. We have 80% power to find a difference of 6.6% between the IP and CC conditions [37]. A total sample size of 2400 across the 6 groups (i.e., with 800 per main effect comparison, with 800 in the XP and XC conditions combined) provides 68% power to find a 5% increase in the success rate in the IC and CP conditions.
Outcomes and data analysis
The primary outcome measure will be the percentage of smokers reporting 6-month sustained abstinence at the final follow-up, with supplementary analyses of the percent making a quit attempt assessed at 2-week post-implementation date, and point-prevalence abstinence at each follow-up point. The primary analyses will use intention to treat analysis with various strategies for dealing with missing data (all will be followed up regardless of engagement with the interventions). Some analyses will be conducted using only reported outcomes, especially those that involve possible mediators or moderators of effect, which will include logistic regressions. Biochemical validation of cessation outcome is considered unnecessary in larger population-based studies (particularly where there are low demands on the participants and no face-to-face therapist contact) as levels of misrepresentation are generally low and unsystematic [38]. This is an effectiveness trial where randomisation is to a set of recommendations which we know a significant proportion of participants will not follow. We will monitor both the choices smokers make around timing of implementation and the extent to which they comply with exercises and advice around structured planning as these should mediate outcomes see [39]. In doing so we will ask about any pre-decisional planning and prior quit experience. Nonetheless, the primary analysis will explore condition by outcome, independent of intervention compliance. Important secondary outcomes are whether the proportion of smokers who accept the offer to schedule their quit attempt and/or implement criterion levels of planning differs by condition, and the prospective relationship between those actions and success. We will also assess the impacts of the interventions and the outcomes on measures of quality of life, affect (particularly signs of depression), and overall health. This will be done both as a function of allocated condition and by achieved outcome.
The study protocol was approved by the Cancer Council Victoria Human Research Ethics Committee (HREC No. 1108).
This study will result in a better understanding of the roles of planning and delay in influencing quit attempts. It is the first large-scale population test of the utility of implementation intentions and if it shows they convey real benefits, should lead to their widespread adoption in cognitive behavioural interventions generally. It will also lead to advances in our understanding of how hard-to-change behaviours can be modified. This will allow us to provide advice both to smokers thinking of quitting, and to smoking cessation services, of the optimal way to configure quit attempts. We are also likely to have enhanced the capacity of QuitCoach in terms of increased efficacy and participation, thus increasing the potential impact of one component of Australia's current suite of services for smoking cessation.
If smokers should be encouraged to quit spontaneously rather than delaying in order to plan, it has profound implications for the delivery of all cessation services. It would demand that help programs have the capacity to respond rapidly, rather than place people in queues to be managed on the service's timeline.
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Zwar N, Richmond R, Borland R, Stillman S, Cunningham M, Litt J: Smoking cessation guidelines for Australian general practice. Australian Family Physician. 2005, 34 (6): 461-466.
West R: Theory of addiction. 2006, Oxford, UK: Blackwells
Ferguson SG, Shiffman S, Gitchell JG, Sembower MA, West R: Unplanned quit attempts--results from a U.S. sample of smokers and ex-smokers. Nicotine Tobacco Res. 2009, 11 (7): 827-832. 10.1093/ntr/ntp072.
Murray RL, Lewis SA, Coleman T, Britton J, McNeill A: Unplanned attempts to quit smoking: missed opportunities for health promotion?. Addiction. 2009, 104 (11): 1901-1909. 10.1111/j.1360-0443.2009.02647.x.
Sendzik T, McDonald PW, Brown KS, Hammond D, Ferrence R: Planned quit attempts among Ontario smokers: impact on abstinence. Addiction. 2011, 106 (11): 2005-2013. 10.1111/j.1360-0443.2011.03498.x.
West R, Sohal T: "Catastrophic" pathways to smoking cessation: findings from national survey. British Med J. 2006, 332 (7539): 458-460. 10.1136/bmj.38723.573866.AE.
Cooper J, Borland R, Yong H-H, McNeill A, Murray RL, O'Connor RJ, Cummings KM: To what extent do smokers make spontaneous quit attempts and what are the implications for smoking cessation maintenance? Findings from the international tobacco control four country survey. Nicotine Tobacco Res. 2010, 12 (Suppl): 51-57. 10.1093/ntr/ntq052.
Cheong Y, Yong H-H, Borland R: Does how you quit affect success? a comparison between abrupt and gradual methods using data from the international tobacco control policy evaluation study. Nicotine Tobacco Res. 2007, 9 (8): 801-810. 10.1080/14622200701484961.
Baumeister RF, Vohs KD, Tice DM: Strength model of self-control. Curr Dir Psychol Sci. 2007, 16: 351-355. 10.1111/j.1467-8721.2007.00534.x.
Vohs KD, Baumeister RF, Schmeichel BJ, Twenge JM, Nelson NM, Tice DM: Making choices impairs subsequent self-control: a limited-resource account of decision making, self-regulation, and active initiative. J Personal Soc Psychol. 2008, 94 (5): 883-898.
Gollwitzer P: Implementation intentions: strong effects of simple plans. Am Psychol. 1999, 54: 493-503.
Gollwitzer PM, Sheeran P: Implementation intentions and goal achievement: a meta-analysis of effects and processes. Adv Exp Soc Psychol. 2006, 38: 69-120.
Achtziger A, Gollwitzer PM, Sheeran P: Implementation intentions and shielding goal striving from unwanted thoughts and feelings. Personal Social Psychol Bull. 2008, 34 (3): 381-393. 10.1177/0146167207311201.
Balmford J, Borland R, Benda P: Patterns of use of an automated interactive personalized coaching program for smoking cessation. J Med Inter Res. 2008, 10 (5): e54-10.2196/jmir.1016.
QuitCoach: http://www.quitcoach.org.au,
Borland R, Balmford J, Hunt D: The effectiveness of personally tailored computer-generated advice letters for smoking cessation. Addiction. 2004, 99 (3): 369-377. 10.1111/j.1360-0443.2003.00623.x.
Borland R, Balmford J, Benda P: Population-level effects of automated smoking cessation help programs: a randomised controlled trial. Addiction. 2012, Epub ahead of print
Hyland A, Borland R, Li Q, Yong HH, McNeill A, Fong GT, O'Connor RJ, Cummings KM: Individual-level predictors of cessation behaviours among participants in the international tobacco control (ITC) four country survey. Tob Control. 2006, 15 (Suppl 3): 83-94.
Borland R, Yong HH, O'Connor RJ, Hyland A, Thompson ME: The reliability and predictive validity of the heaviness of smoking index and its two components: findings from the international tobacco control four country study. Nicotine Tobacco Res. 2010, 12 (Suppl 1): 45-50.
Borland R, Segan C, Velicer WF: Testing the transtheoretical model for smoking change: Victorian data. Aust J Psychol. 2000, 52: 83-88. 10.1080/00049530008255372.
Segan CJ, Borland R, Greenwood KM: Do transtheoretical model measures predict the transition from preparation to action in smoking cessation?. Psychol Heal. 2002, 17: 417-435. 10.1080/0887044022000004911.
Australian Bureau of Statistics: 2039.0 - Information paper: an introduction to socio-economic indexes for areas (SEIFA). 2006, Canberra: Ausralian Bureau of Statistics
Herd N, Borland R, Hyland A: Predictors of smoking relapse by duration of abstinence: findings from the international tobacco control (ITC) four country survey. Addiction. 2009, 104 (12): 2088-2099. 10.1111/j.1360-0443.2009.02732.x.
Danaher BG, Boles SM, Akers L, Gordon JS, Severson HH: Defining participant exposure measures in Web-based health behavior change programs. J Med Inter Res. 2006, 8 (3): e15-10.2196/jmir.8.3.e15.
Balmford J, Borland R, Benda P, Howard S: Factors associated with use of automated smoking cessation interventions: findings from the eQuit study. Heal Educ Res. 2012, Epub ahead of print
Lenth RV: Java applets for power and sample size [computer software]. 2006, http://www.stat.uiowa.edu/~rlenth/Power
SRNT Subcommittee on Biochemical Validation: Biochemical validation of tobacco use and cessation. Nicotine Tobacco Res. 2002, 4: 149-159. 10.1080/14622200210123581.
IARC: IARC handbooks Of cancer prevention. Methods for evaluating tobacco control policies. 2008, Lyon, France: International Agency for Research on Cancer Prevention, World Health Organization, Vol 12
The study is funded by the National Health and Medical Research Council (Australia), Project Grant 1009767.
VicHealth Centre for Tobacco Control, The Cancer Council Victoria, 1 Rathdowne St Carlton, Melbourne, VIC, 3053, Australia
Ron Borland, James Balmford & Elena Swift
Ron Borland
James Balmford
Elena Swift
Correspondence to Ron Borland.
RB and JB conceived of the study and drafted the manuscript. ES contributed to the implementation of the study and the drafting of the manuscript. All authors read and approved the final manuscript.
Borland, R., Balmford, J. & Swift, E. Effects of timing of initiation and planning on smoking cessation outcomes: study protocol for a randomised controlled trial. BMC Public Health 13, 235 (2013). https://doi.org/10.1186/1471-2458-13-235
Randomised controlled trial


text:
Q: Documentation for the webkit developer tools' `window.console._commandLineAPI` I discovered that if I step out of a function invoked in the chrome dev console, I end up in this source code:
with ((window && window.console && window.console._commandLineAPI) || {}) {
myFunction()
}

There are a few questions related to this describing some strange quirks in the console, but they're not relevant here.
If I type window.console._commandLineAPI into the console, I get a whole bunch of member names, some of which are more helpful than others:
$$: function () { [native code] }
$_: undefined
$x: function () { [native code] }
clear: function () { [native code] }
copy: function () { [native code] }
dir: function () { [native code] }
dirxml: function () { [native code] }
get $0: function () { [native code] }
get $1: function () { [native code] }
get $2: function () { [native code] }
get $3: function () { [native code] }
get $4: function () { [native code] }
getEventListeners: function () { [native code] }
inspect: function () { [native code] }
keys: function () { [native code] }
monitorEvents: function () { [native code] }
profile: function () { [native code] }
profileEnd: function () { [native code] }
set $0: undefined
set $1: undefined
set $2: undefined
set $3: undefined
set $4: undefined
unmonitorEvents: function () { [native code] }
values: function () { [native code] }
__proto__: CommandLineAPI

Is there any documentation anywhere on what these functions do?

A: This sounds like the FireBug command line API.

A: You can find the documentation here

redpajama_set_name: RedPajamaStackExchange


text:
James Connors may refer to:

James Connors (Kiltullagh) (died 1881), Irish tenant farmer, murdered in May 1881
James Connors (Medal of Honor) (1838–?), Irish born Union Army soldier during the American Civil War
James H. Connors (died 1941), American horse racing executive and businessman
Jim Connors, mayor of Scranton, Pennsylvania
Jimmy Connors (born 1952), American tennis player
Jimmy Connors, American welterweight boxer and brother of mobster Edward G. Connors

See also
James Connor (disambiguation)

redpajama_set_name: RedPajamaWikipedia


text:
Q: Is it possible to use the M.2 interface for other PCIe devices? Since there are adapters to adapt M.2 to PCIe x4, I was wondering if such an adapter can be used to connect other PCIe devices like network interfaces or USB controllers to the system?
Are there any special features that need to be supported by the motherboard for this to work (besides having a M.2 connector that is hooked up to PCIe of course).

A: An M.2 slot basically has 4x PCIe V3.0 and a regular SATA port in 1 connector.
Those adapters break out the PCIe lanes and feed them into a normal PCIe 4x connector which should be able to take any PCIe 1x and 4x card (provided you can physically fit that somehow it in your PC case).
Whether it will actually work properly??? Maybe...
The PCIe lanes are a very high-speed bus. Adding more wiring length (which this converter does) to that might cause problems with electrical interference.
Some PCI-e cards may be fine with it. Others may not. Trail and error is the only way to say for sure.
If I were to guess: The faster the PCIe device put in such a converter the more potential for trouble.
A PCIe 1x serial adapter is probably fine. A 10 Gb/s network card probably not.


text:
Parent Section N/A
Pharmaceutical Quality Control Labs (7/93)
GUIDE TO INSPECTIONS OF PHARMACEUTICAL QUALITY CONTROL LABORATORIES
Note: This document is reference material for investigators and other FDA personnel. The document does not bind FDA, and does no confer any rights, privileges, benefits, or immunities for or on any person(s).
The pharmaceutical quality control laboratory serves one of the most important functions in pharmaceutical production and control. A significant portion of the CGMP regulations (21 CFR 211) pertain to the quality control laboratory and product testing. Similar concepts apply to bulk drugs.
This inspection guide supplements other inspectional information contained in other agency inspectional guidance documents. For example, Compliance Program 7346.832 requiring pre-approval NDA/ANDA inspections contains general instructions to conduct product specific NDA/ANDA inspection audits to measure compliance with the applications and CGMP requirements. This includes pharmaceutical laboratories used for in-process and finished product testing.
2. OBJECTIVE
The specific objective will be spelled out prior to the inspection. The laboratory inspection may be limited to specific issues, or the inspection may encompass a comprehensive evaluation of the laboratory's compliance with CGMP's. As a minimum, each pharmaceutical quality control laboratory should receive a comprehensive GMP evaluation each two years as part of the statutory inspection obligation.
In general these inspections may include
- the specific methodology which will be used to test a new product
- a complete assessment of laboratory's conformance with GMP's
- a specific aspect of laboratory operations
3. INSPECTION PREPARATION
FDA Inspection Guides are based on the team inspection approach and our inspection of a laboratory is consistent with this concept. As part of our effort to achieve uniformity and consistency in laboratory inspections, we expect that complex, highly technical and specialized testing equipment, procedures and data manipulations, as well as scientific laboratory operations will be evaluated by an experienced laboratory analyst with specialized knowledge in such matters.
District management makes the final decision regarding the assignment of personnel to inspections. Nevertheless, we expect investigators, analysts and others to work as teams and to advise management when additional expertise is required to complete a meaningful inspection.
Team members participating in a pre-approval inspection must read and be familiar with Compliance Program 7346.832, Pre-Approval Inspections/Investigations. Relevant sections of the NDA or ANDA should be reviewed prior to the inspection; but if the application is not available from any other source, this review will have to be conducted using the company's copy of the application.
Team members should meet, if possible, prior to the inspection to discuss the approach to the inspection, to define the roles of the team members, and to establish goals for completion of the assignment. Responsibilities for development of all reports should also be established prior to the inspection. This includes the preparation of the FDA 483.
The Center for Drug Evaluation and Research (CDER) may have issued deficiency letters listing problems that the sponsor must correct prior to the approval of NDA/ANDA's and supplements. The inspection team is expected to review such letters on file at the district office, and they are expected to ask the plant for access to such letters. The team should evaluate the replies to these letters to assure that the data are accurate and authentic. Complete the inspection even though there has been no response to these letters or when the response is judged inadequate.
4. INSPECTION APPROACH
In addition to the general approach utilized in a drug CGMP inspection, the inspection of a laboratory requires the use of observations of the laboratory in operation and of the raw laboratory data to evaluate compliance with CGMP's and to specifically carry out the commitments in an application or DMF. When conducting a comprehensive inspection of a laboratory, all aspects of the laboratory operations will be evaluated.
Laboratory records and logs represent a vital source of information that allows a complete overview of the technical ability of the staff and of overall quality control procedures. SOPs should be complete and adequate and the operations of the laboratories should conform to the written procedures. Specifications and analytical procedures should be suitable and, as applicable, in conformance with application commitments and compendial requirements.
Evaluate raw laboratory data, laboratory procedures and methods, laboratory equipment,including maintenance and calibration, and methods validation data to determine the overall quality of the laboratory operation and the ability to comply with CGMP regulations.
Examine chromatograms and spectra for evidence of impurities, poor technique, or lack of instrument calibration.
Most manufacturers use systems that provide for the investigation of laboratory test failures. These are generally recorded in some type of log. Ask to see results of analyses for lots of product that have failed to meet specifications and review the analysis of lots that have been retested, rejected, or reworked. Evaluate the decision to release lots of product when the laboratory results indicate that the lot failed to meet specifications and determine who released them.
B. Pre-Approval
Documents relating to the formulation of the product, synthesis of the bulk drug substance, product specifications, analysis of the product, and others are examined during the review process in headquarters. However, these reviews and evaluations depend on accurate and authentic data that truly represents the product.
Pre-approval inspections are designed to determine if the data submitted in an application are authentic and accurate and if the procedures listed in the application were actually used to produce the data contained in the application. Additionally, they are designed to confirm that plants (including the quality control laboratory) are in compliance with CGMP regulations.
The analytical sections of drug applications usually contain only test results and the methods used to obtain them. Sponsors are not required to file all the test data because such action would require voluminous submissions and would often result in filing redundant information. Sponsors may deliberately or unintentionally select and report data showing that a drug is safe and effective and deserves to be approved. The inspection team must decide if there is valid and scientific justification for the failure to report data which demonstrates the product failed to meet its predetermined specifications.
Coordination between headquarters and the field is essential for a complete review of the application and the plant. Experienced investigators and analysts may contact the review chemist (with appropriate supervisory concurrence) when questions concerning specifications and standards arise.
Inspections should compare the results of analyses submitted with results of analysis of other batches that may have been produced. Evaluate the methods and note any exceptions to the procedures or equipment actually used from those listed in the application and confirm that it is the same method listed in the application. The analyst is expected to evaluate raw laboratory data for tests performed on the test batches (biobatches and clinical batches) and to compare this raw data to the data filed in the application.
5. FAILURE (OUT-OF-SPECIFICATION) LABORATORY RESULTS
Evaluate the company's system to investigate laboratory test failures. These investigations represent a key issue in deciding whether a product may be released or rejected and form the basis for retesting, and resampling.
In a recent court decision the judge used the term "out-of-specification" (OOS) laboratory result rather than the term "product failure" which is more common to FDA investigators and analysts. He ruled that an OOS result identified as a laboratory error by a failure investigation or an outlier test. The court provided explicit limitations on the use of outlier tests and these are discussed in a later segment of this document., or overcome by retesting. The court ruled on the use of retesting which is covered in a later segment of this document. is not a product failure. OOS results fall into three categories:
- laboratory error
- non-process related or operator error
- process related or manufacturing process error
A. LABORATORY ERRORS
Laboratory errors occur when analysts make mistakes in following the method of analysis, use incorrect standards, and/or simply miscalculate the data. Laboratory errors must be determined through a failure investigation to identify the cause of the OOS. Once the nature of the OOS result has been identified it can be classified into one of the three categories above. The inquiry may vary with the object under investigation.
B. LABORATORY INVESTIGATIONS
The exact cause of analyst error or mistake can be difficult to determine specifically and it is unrealistic to expect that analyst error will always be determined and documented. Nevertheless, a laboratory investigation consists of more than a retest. The inability to identify an error's cause with confidence affects retesting procedures, not the investigation inquiry required for the initial OOS result.
The firm's analyst should follow a written procedure, checking off each step as it is completed during the analytical procedure. We expect laboratory test data to be recorded directly in notebooks; use of scrap paper and loose paper must be avoided. These common sense measures enhance the accuracy and integrity of data.
Review and evaluate the laboratory SOP for product failure investigations. Specific procedures must be followed when single and multiple OOS results are investigated. For the single OOS result the investigation should include the following steps and these inquiries must be conducted before there is a retest of the sample:
- the analyst conducting the test should report the OOS result to the supervisor
- the analyst and the supervisor should conduct an informal laboratory investigation which addresses the following areas:
1. discuss the testing procedure
2. discuss the calculation
3. examine the instruments
4. review the notebooks containing the OOS result
An alternative means to invalidate an initial OOS result, provided the failure investigation proves inconclusive, is the "outlier" test. However, specific restrictions must be placed on the use of this test.
1. Firms cannot frequently reject results on this basis.
2. The USP standards govern its use in specific cases only.
3. The test cannot be used for chemical testing results. An initial content uniformity test was OOS followed by a passing retest. The initial OOS result was claimed the result of analyst error based on a statistical evaluation of the data. The court ruled that the use of an outlier test is inappropriate in this case..
4. It is never appropriate to utilize outlier tests for a statistically based test, i.e., content uniformity and dissolution.
Determine if the firm uses an outlier test and evaluate the SOP.
Determine that a full scale inquiry has been made for multiple OOS results. This inquiry involves quality control and quality assurance personnel in addition to laboratory workers to identify exact process or non process related errors.
When the laboratory investigation is inconclusive (reason for the error is not identified) the firm:
1. Cannot conduct 2 retests and base release on average of three tests
2. Cannot use outlier test in chemical tests
3. Cannot use a re-sample to assume a sampling or preparation error
4. Can conduct a retest of different tablets from the same sample when a retest is considered appropriate (see criteria elsewhere)
C. FORMAL INVESTIGATIONS
Formal investigations extending beyond the laboratory must follow an outline with particular attention to corrective action. The company must:
1. State the reason for the investigation
2. Provide summation of the process sequences that may have caused the problem
3. Outline corrective actions necessary to save the batch and prevent similar recurrence
4. List other batches and products possibly affected, the results of investigation of these batches and products, and any corrective action. Specifically:
- examine other batches of product made by the errant employee or machine
- examine other products produced by the errant process or operation
5. Preserve the comments and signatures of all production and quality control personnel who conducted the investigation and approved any reprocessed material after additional testing
D. INVESTIGATION DOCUMENTATION
Analyst's mistakes, such as undetected calculation errors, should be specified with particularity and supported by evidence. Investigations along with conclusions reached must be preserved with written documentation that enumerates each step of the investigation. The evaluation, conclusion and corrective action, if any, should be preserved in an investigation or failure report and placed into a central file.
E. INVESTIGATION TIME FRAMES
All failure investigations should be performed within 20 business days of the problem's occurrence and recorded and written into a failure or investigation report.
6. PRODUCT FAILURES
An OOS laboratory result can be overcome (invalidated) when laboratory error has been documented. However, non-process and process related errors resulting from operators making mistakes, equipment (other than laboratory equipment) malfunctions, or a manufacturing process that is fundamentally deficient, such as an improper mixing time, represent product failures.
Examine the results of investigations using the guidance in section 5 above and evaluate the decision to release, retest, or rework products.
7. RETESTING
Evaluate the company's retesting SOP for compliance with scientifically sound and appropriate procedures. A very important ruling in one recent court decision sets forth a procedure to govern the retesting program. This district court ruling provides an excellent guide to use in evaluating some aspects of a pharmaceutical laboratory, but should not be considered as law, regulation or binding legal precedent. The court ruled that a firm should have a predetermined testing procedure and it should consider a point at which testing ends and the product is evaluated. If results are not satisfactory, the product is rejected.
Additionally, the company should consider all retest results in the context of the overall record of the product. This includes the history of the product. The court ordered a recall of one batch of product on the basis of an initial content uniformity failure and no basis to invalidate the test result and on a history of content uniformity problems with the product., type of test performed, and in-process test results. Failing assay results cannot be disregarded simply on the basis of acceptable content uniformity results.
The number of retests performed before a firm concludes that an unexplained OOS result is invalid or that a product is unacceptable is a matter of scientific judgment. The goal of retesting is to isolate OOS results but retesting cannot continue ad infinitum.
In the case of nonprocess and process-related errors, retesting is suspect. Because the initial tests are genuine, in these circumstances, additional testing alone cannot contribute to product quality. The court acknowledged that some retesting may precede a finding of nonprocess or process-based errors. Once this determination is made, however, additional retesting for purposes of testing a product into compliance is not acceptable.
For example, in the case of content uniformity testing designed to detect variability in the blend or tablets, failing and non-failing results are not inherently inconsistent and passing results on limited retesting do not rule out the possibility that the batch is not uniform. As part of the investigation firms should consider the record of previous batches, since similar or related failures on different batches would be a cause of concern.
Retesting following an OOS result is ruled appropriate only after the failure investigation is underway and the failure investigation determines in part whether retesting is appropriate. It is appropriate when analyst error is documented or the review of analyst's work is "inconclusive" , but it is not appropriate for known and undisputed non-process or process related errors.
The court ruled that retesting:
- must be done on the same, not a different sample
- may be done on a second aliquot from the same portion of the sample that was the source of the first aliquot
- may be done on a portion of the same larger sample previously collected for laboratory purposes
8. RESAMPLING
Firms cannot rely on resampling. The court ordered the recall of one batch of product after having concluded that a successful resample result alone cannot invalidate an initial OOS result. to release a product that has failed testing and retesting unless the failure investigation discloses evidence that the original sample is not representative or was improperly prepared.
Evaluate each resampling activity for compliance with this guidance.
9. AVERAGING RESULTS OF ANALYSIS
Averaging can be a rational and valid approach when the object under consideration is total product assay, but as a general rule this practice should be avoided. The court ruled that the firm must recall a batch that was released for content uniformity on the basis of averaged test results. because averages hide the variability among individual test results. This phenomenon is particularly troubling if testing generates both OOS and passing individual results which when averaged are within specification. Here, relying on the average figure without examining and explaining the individual OOS results is highly misleading and unacceptable.
Content uniformity and dissolution results never should be averaged to obtain a passing value.
In the case of microbiological turbidimetric and plate assays an average is preferred by the USP. In this case, it is good practice to include OOS results in the average unless an outlier test (microbiological assays) suggests the OOS is an anomaly.
10. BLEND SAMPLING AND TESTING
The laboratory serves a vital function in blend testing which is necessary to increase the likelihood of detecting inferior batches. Blend uniformity testing cannot be waived in favor of total reliance on finished product testing because finished product testing is limited.
One court has ruled that sample size influences ultimate blend test results and that the sample size should resemble the dosage size. Any other practice would blur differences in portions of the blend and defeat the object of the test. If a sample larger than the unit must be taken initially, aliquots which resemble the dosage size should be carefully removed for the test, retests, and reserve samples. Obviously, the initial larger sample should not be subjected to any additional mixing or manipulation prior to removing test aliquots as this may obscure non-homogeneity.
Multiple individual blend uniformity samples taken from different areas cannot be composited. However when variation testing is not the object of assay testing, compositing is permitted.
If firms sample product from sites other than the blender, they must demonstrate through validation that their sampling technique is representative of all portions and concentrations of the blend. This means that the samples must be representative of those sites that might be problems; e.g. weak or hot spots in the blend.
11. MICROBIOLOGICAL
The review of microbiological data on applicable dosage forms is best performed by the microbiologist (analyst). Data that should be reviewed include preservative effectiveness testing, bioburden data, and product specific microbiological testing and methods.
Review bioburden (before filtration and/or sterilization) from both an endotoxin and sterility perspective. For drug substance labs evaluate methods validation and raw data for sterility, endotoxin testing, environmental monitoring, and filter and filtration validation. Also, evaluate the methods used to test and establish bioburdens.
Refer to the Microbiological Inspection Guide for additional information concerning the inspection of microbiological laboratories.
12. SAMPLING
Samples will be collected on pre-approval inspections. Follow the sampling guidelines in CP 7346.832, Part III, pages 5 and 6.
13. LABORATORY RECORDS AND DOCUMENTATION
Review personal analytical notebooks kept by the analysts in the laboratory and compare them with the worksheets and general lab notebooks and records. Be prepared to examine all records and worksheets for accuracy and authenticity and to verify that raw data are retained to support the conclusions found in laboratory results.
Review laboratory logs for the sequence of analysis versus the sequence of manufacturing dates. Test dates should correspond to the dates when the sample should have been in the laboratory. If there is a computer data base, determine the protocols for making changes to the data. There should be an audit trail for changes to data.
We expect raw laboratory data to be maintained in bound, (not loose or scrap sheets of paper), books or on analytical sheets for which there is accountability, such as prenumbered sheets. For most of those manufacturers which had duplicate sets of records or "raw data", non-numbered loose sheets of paper were employed. Some companies use discs or tapes as raw data and for the storage of data. Such systems have also been accepted provided they have been defined (with raw data identified) and validated.
Carefully examine and evaluate laboratory logs, worksheets and other records containing the raw data such as weighings, dilutions, the condition of instruments, and calculations. Note whether raw data are missing, if records have been rewritten, or if correction fluid has been used to conceal errors. Results should not be changed without explanation. Cross reference the data that has been corrected to authenticate it. Products cannot be "tested into compliance" by arbitrarily labeling out-of-specification lab results as "laboratory errors" without an investigation resulting in scientifically valid criteria.
Test results should not have been transcribed without retention of the original records, nor should test results be recorded selectively. For example, investigations have uncovered the use of loose sheets of paper with subsequent selective transcriptions of good data to analyst worksheets and/or workbooks. Absorbance values and calculations have even been found on desk calendars.
Cut charts with injections missing, deletion of files in direct data entry systems, indirect data entry without verification, and changes to computerized programs to override program features should be carefully examined. These practices raise questions about the overall quality of data.
The firm should have a written explanation when injections, particularly from a series are missing from the official work-sheets or from files and are included among the raw data. Multiple injections recorded should be in consecutive files with consecutive injection times recorded. Expect to see written justification for the deletion of all files.
Determine the adequacy of the firm's procedures to ensure that all valid laboratory data are considered by the firm in their determination of acceptability of components, in-process, finished product, and retained stability samples. Laboratory logs and documents when cross referenced may show that data has been discarded by company officials who decided to release the product without a satisfactory explanation of the results showing the product fails to meet the specifications. Evaluate the justification for disregarding test results that show the product failed to meet specifications.
14. LABORATORY STANDARD SOLUTIONS
Ascertain that suitable standards are being used (i.e. in-date, stored properly). Check for the reuse of stock solutions without assuring their stability. Stock solutions are frequently stored in the laboratory refrigerator. Examine the laboratory refrigerators for these solutions and when found check for appropriate identification. Review records of standard solution preparation to assure complete and accurate documentation. It is highly unlikely that a firm can "accurately and consistently weigh" to the same microgram. Therefore data showing this level of standardization or pattern is suspect and should be carefully investigated.
15. METHODS VALIDATION
Information regarding the validation of methods should be carefully evaluated for completeness, accuracy and reliability. In particular, if a compendial method exists, but the firm chooses to use an alternate method instead, they must compare the two and demonstrate that the in-house method is equivalent or superior to the official procedure. For compendial methods firms must demonstrate that the method works under the actual conditions of use.
Methods can be validated in a number of ways. Methods appearing in the USP are considered validated and they are considered validated if part of an approved ANDA. Also a company can conduct a validation study on their method. System suitability data alone is insufficient for and does not constitute method validation.
In the review of method validation data, it is expected that data for repetitive testing be consistent and that the varying concentrations of test solutions provide linear results. Many assay and impurity tests are now HPLC, and it is expected that the precision of these assays be equal or less than the RSD's for system suitability testing. The analytical performance parameters listed in the USP XXII, , under the heading of Validation of Compendial Methods, can be used as a guide for determining the analytical parameters (e.g., accuracy, precision, linearity, ruggedness, etc.) needed to validate the method.
16. EQUIPMENT
Laboratory equipment usage, maintenance, calibration logs, repair records, and maintenance SOPs also should be examined. The existence of the equipment specified in the analytical methods should be confirmed and its condition noted. Verify that the equipment was present and in good working order at the time the batches were analyzed. Determine whether equipment is being used properly.
In addition, verify that the equipment in any application was in good working order when it was listed as used to produce clinical or biobatches. One would have to suspect the data that are generated from a piece of equipment that is known to be defective. Therefore, continuing to use and release product on the basis of such equipment represents a serious violation of CGMP's.
17. RAW MATERIAL TESTING
Some inspections include the coverage of the manufacturer of the drug substance. The safety and efficacy of the finished dosage form is largely dependent on the purity and quality of the bulk active drug substance. Examine the raw data reflecting the analysis of the drug substance including purity tests, charts, etc.
Check the impurity profiles of the BPC used in the biobatch and clinical production batches to determine if it is the same as that being used to manufacture full scale production batches. Determine if the manufacturer has a program to audit the certificate of analysis of the BPC, and, if so, check the results of these tests. Report findings where there is substantial difference in impurity profiles and other test results.
Some older compendial methods may not be capable of detecting impurities as necessary to enable the control of the manufacturing process, and newer methods have been developed to test these products. Such methods must be validated to ensure that they are adequate for analytical purposes in the control and validation of the BPC manufacturing process. The drug substance manufacturer must have complete knowledge of the manufacturing process and the potential impurities that may appear in the drug substance. These impurities cannot be evaluated without a suitable method and one that has been validated.
Physical tests such as particle size for raw materials, adhesion tests for patches, and extrusion tests for syringes are essential tests to assure consistent operation of the production and control system and to assure quality and efficacy. Some of these tests are filed in applications and others may be established by the protocols used to manufacture the product. The validation of methods for such tests are as important as the test for chemical attributes.
Physical properties tests often require the use of unique equipment and protocols. These tests may not be reproducible in other laboratories, therefore, on site evaluation is essential.
18. IN PROCESS CONTROLS AND SPECIFICATIONS
Evaluate the test results from in-process tests performed in the production areas or laboratory for conformance with established sampling and testing protocols, analytical methods, and specifications. For example, evaluate the tests for weight variation, hardness, and friability. These tests may be performed every fifteen or thirty minutes during tableting or encapsulating procedures. All testing must comply with CGMP's.
The drug application may contain some of the in-process testing plan, including methods and specifications. The inspection must confirm that the in-process tests were done, as described in the plan, and ascertain that the results were within specifications. The laboratory work for the lengthier tests should also be reviewed.
The methods used for in-process testing may differ from those used for release testings. Usually, whether the methods are the same or different, the specifications may be tighter for the in-process tests. A product with a 90.0%-110.0% assay release specification may have a limit of 95.%-105.0% for the in-process blend. Some of the tests done may differ from those done at release. For example, a firm may perform disintegration testing as an in-process test but dissolution testing as a release test.
Expect to see consistent in-process test results within batches and between batches of the same formulation/process (including development or exhibit batches). If this is not the case, expect to see scientific data to justify the variation.
19. STABILITY
A stability-indicating method must be used to test the samples of the batch. If there is no stability-indicating assay additional assay procedures such as TLC should be used to supplement the general assay method. Evidence that the method is stability indicating must be presented, even for compendial methods.
Manufacturers may be required to accelerate or force degradation of a product to demonstrate that the test is stability indicating. In some cases the sponsor of ANDA's may be able to search the literature and find background data for the specificity of a particular method. This information may also be obtained from the supplier of the drug substance. Validation would then be relatively straightforward, with the typical parameters listed in the USP in chapter on validation of compendial methods addressed as applicable.
Evaluate the manufacturer's validation report for their stability testing. Again, review the raw laboratory data and the results of testing at the various stations to determine if the data actually reported matches the data found in on site records.
Evaluate the raw data used to generate the data filed documenting that the method is stability indicating and the level of impurities.
20. COMPUTERIZED LABORATORY DATA ACQUISITION SYSTEMS
The use of computerized laboratory data acquisition systems is not new and is addressed in the following CGMP guidance documents:
- Compliance Policy Guide 7132a.07 Computerized Drug Processing: Input/Output Checking.
- Compliance Policy Guide 7132a.08 Computerized Drug Processing: Identification of "Persons" on Batch Production and Control Records.
- Compliance Policy Guide 7132a.11 Computerized Drug Processing: CGMP Applicability to Hardware and Software
- Compliance Policy Guide 7132a.12 Computerized Drug Processing: Vendor Responsibility
- Compliance Policy Guide 7132a.15 Computerized Drug Processing: Source Code for Process Control Application Programs
- Guide to Inspection of Computerized Systems in Drug Processing.
It is important, for computerized and non computerized systems, to define the universe of data that will be collected, the procedures to collect it, and the means to verify its accuracy. Equally important are the procedure to audit data and programs and the process for correcting errors. Several issues must be addressed when evaluating computerized laboratory systems. These include data collection, processing, data integrity, and security.
Procedures should only be judged adequate when data are secure, raw data are not accidentally lost, and data cannot be tampered with. The system must assure that raw data are stored and actually processed.
The agency has provided some basic guidance on security and authenticity issues for computerized systems:
- Provision must be made so that only authorized individuals can make data entries.
- Data entries may not be deleted. Changes must be made in the form of amendments.
- The data base must be made as tamperproof as possible.
- The Standard Operating Procedures must describe the procedures for ensuring the validity of the data.
One basic aspect of validation of laboratory computerized data acquisition requires a comparison of data from the specific instrument with that same data electronically transmitted through the system and emanating on a printer. Periodic data comparisons would be sufficient only when such comparisons have been made over a sufficient period of time to assure that the computerized system produces consistent and valid results.
21. LABORATORY MANAGEMENT
Overall management of the laboratory work, its staff, and the evaluation of the results of analysis are important elements in the evaluation of a control laboratory. Span of supervisory control, personnel qualifications, turnover of analysts, and scope of the laboratory's responsibility are important issues to examine when determining the quality of overall management and supervision of work. Individually or collectively, these factors are the basis for an objection only when they are shown to result in inadequate performance of responsibilities required by the CGMPs.
Review laboratory logs for the sequence of analysis and the sequence of manufacturing dates. Examine laboratory records and logs for vital information about the technical competence of the staff and the quality control procedures used in the laboratory.
Observe analysts performing the operations described in the application. There is no substitute for actually seeing the work performed and noting whether good technique is used. You should not stand over the analysts, but watch from a distance and evaluate their actions.
Sometimes the company's employees have insufficient training or time to recognize situations that require further investigation and explanation. Instead they accept unexplained peaks in chromatograms with no effort to identify them. They may accept stability test results showing an apparent increase in the assay of the drug with the passage of time with no apparent question about the result. Also, diminishing reproducibility in HPLC chromatograms appearing several hours after system suitability is established is accepted without question.
Good manufacturing practice regulations require an active training program and the documented evaluation of the training of analysts.
The authority to delete files and override computer systems should be thoroughly examined. Evaluate the history of changes to programs used for calculations. Certain changes may require management to re-examine the data for products already released.
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text:
When Rahul Dravid is called up to the Indian squad, he becomes "emotional" and adds, "When I got injured again, he noted…"
When the T20I lineup for India's series against Sri Lanka was announced last month, most predictions were met. While Rohit Sharma was recovering from a thumb injury, Hardik Pandya served as the captain. While Virat Kohli was napping, Jasprit Bumrah and Ravindra Jadeja had also taken a break. Suryakumar Yadav was elevated to vice-captain, while Harshal Patel made a comeback. Overall fewer misses and more hits. However, the squad was unprepared for the fast bowlers Mukesh Kumar and Shivam Mavi. Both players had a memorable IPL 2022 auction that brought in substantial money after years of competition in the local circuit, but the subsequent event was far more pleasurable.
Mukesh was chosen by the Delhi Capitals for the 5.5 core, but Shivam Mavi's chances of playing cricket for India improved dramatically. Along with Shubman Gill and Prithvi Shaw, Mavi was a part of the Indian team that won the Under-19 World Cup in New Zealand in 2018. Mavi was left behind as a consequence of several illnesses that only served to impede him and demote him in the hierarchy, while the other two openers went on to have success.
His comeback in 2022, when he concluded with 14 wickets in seven games to finish as the 10th-highest wicket-taker in the Vijay Hazare Trophy and another 10 in the Syed Mushtaq Ali Trophy, assisted in him receiving his due. Mavi became the most expensive uncapped Indian acquisition in history when Gujarat Titans, the reigning IPL champions, paid 6 crores for him at the auction. Mavi immediately realized his career had gained momentum.
"To obtain a decent night's sleep after playing home games, we often go to bed early. But because I had heard that day that the team was going to be unveiled, Samarth [Singh] and I sat in Saurabh bhaiyya's room. A left-arm spinner, Saurabh. When I learned of my decision, everything paused for a little period. It was an amazing feeling. Despite my feelings, I was aware that my time had come." Speaking with ESPNCricinfo Mavi.
Mavi already has a significant number of wounds. He has suffered an ACL injury before, along with two stress fractures that kept him out of action for approximately a year. Mavi had to take it easier as he recovered since he routinely bowled in the 140s. Mavi recalls that despite these challenges, the 24-year-old decided to remain optimistic rather than allow them to bring him down. While Mavi was having therapy at the National Cricket Academy, he also shared tales of how Rahul Dravid, the head coach of India and his coach when that country won the World Cup five years ago, had assisted him in getting back on his feet.
"I've always been mentally strong. Over the years, I've learned that accidents do occur in sports. It is easy to be upbeat while things are going your way, but staying upbeat when you are wounded is more important. All I ever did was keep saying to myself, "And Mavi," and when I was wounded the second time, Rahul [Dravid] sir was also there and we were both at the NCA. I was under pressure because I kept getting hurt. I went to him at that time and requested his advice. I was told by him to focus only on the playing field. Despite the cyclical nature of ailments, it is essential to always remain open to new alternatives."


text:
"Михајло Петровић Алас" је југословенски кратки документарни филм из 1968. године. Режирао га је Миодраг Мија Јакшић који је са Драганом Трифуновићем написао и сценарио.

Спољашње везе

Југословенски филмови
Српски филмови
Филмови 1968.
Документарни филмови
Српски телевизијски краткометражни филмови
Српски краткометражни играни филмови
Краткометражни филмови


Data has been called "the new oil", and to run well, oil must be refined. Today's modern data management practices can create well-refined data to power your organization's growth. As the world of data management rapidly evolves along with the latest technologies, so should your practices.
From building a successful data governance program to managing data quality requirements that support self-service analytics and reporting, an effective data management practice is paramount for your modern data-driven practices. Learn techniques and best practices from industry experts to fuel your company's growth without derailing your existing architectures and practices.
One year into GDPR and coming up on the California Consumer Privacy Act, organizations must think strategically how to manage their data assets and provide consumer security without hindering the internal use of valuable data.
M6A Data Catalogs – Finally a Mechanism to Tame Analytics Chaos!NEW!
T3A The Data Interpreter: The Hottest New Role in Analytics!


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text:
Franz Joseph Clement (November 17 or 18?, 1780 – November 3, 1842), was an Austrian violinist, pianist, composer, conductor of Vienna's Theater an der Wien, and a friend of Ludwig van Beethoven.

Life and career
A talented violinist from a young age, he was known for his extraordinary ability to play complex pieces from memory after only briefly viewing them. He would alternate his virtuoso performances with lighthearted showmanship, with such intermission antics as playing a sonata on one string with the violin upside-down. A critic in 1805 described his unique style as follows:

"His is not the marked, bold, strong playing, the moving, forceful Adagio, the powerful bow and tone which characterise the Rode-Viotti School; rather, his playing is indescribably delicate, neat and elegant; it has an extremely delightful tenderness and cleanness that undoubtedly secures him a place among the most perfect violinists. At the same time, he has a wholly individual lightness, which makes it seem as if he merely toys with the most incredible difficulties, and a sureness that never deserts him for a moment, even in the most daring passages."

Beethoven became acquainted with Clement in 1794 when he attended a performance in Vienna by the prodigy, then just 14.

It was at the Theater an der Wien's benefit concert of April 7, 1805 that Beethoven first publicly conducted his Eroica symphony. At the same performance, Clement premiered his own violin concerto in D Major, one of Clement's six known violin concertos.

Clement went on to commission Beethoven's Violin Concerto in D major from his friend for the next benefit concert, given on  December 23, 1806. It is said that Beethoven worked on it up until shortly before the performance, and that Clement played the piece without rehearsing.

His works include, besides a number of compositions for violin and piano or orchestra, an offertorium "Ave, o rosa mistica" published in 1848.

Recordings
 Violin Concerto in D major by Franz Clement. Paired with the Violin Concerto in D major, Op. 61, by Ludwig van Beethoven.  Rachel Barton Pine (violin), José Serebrier (conductor), Royal Philharmonic Orchestra. Cedille Records: CDR 90000 106 (info)
Violin Concertos Nos. 1 – 2. Mirijam Contzen (Violin), WDR Symfonieorchester, Reinhard Goebel (conductor). Sony Masterworks, 2019.

References

Sources
Short bio by Betsy Schwarm
 (See final page.)

External links

1780 births
1842 deaths
Austrian conductors (music)
Male conductors (music)
Austrian classical pianists
Male classical pianists
Austrian classical violinists
Austrian Romantic composers
19th-century classical composers
19th-century conductors (music)
19th-century classical pianists
19th-century classical violinists
Male classical violinists
19th-century German musicians


Understanding and recognising how graduate teaching assistants (GTAs) carry out their teaching practice is of vital important as they play a key role in University teaching. However, their voices are often drowned in a complex environment, where competing demands, such as research and publications, jostle for time and attention. This study examined GTAs' use of collaborative learning scripts through lesson planning and micro-teaching sessions. Findings are discussed in relation to academic developers' understanding of how GTAs develop their knowledge and skills to engage students in meaningful collaborative learning and how best to design instructional support in learning how to teach.
Kollar, I., Fischer, F., & Hesse, F.W. (2006). Collaboration scripts – A conceptual analysis. Educational Psychology Review, 18, 159-185.
O'Donnell, A. M. (2006). The role of peers and group learning. In P. Alexander & P. Winne (Eds)., Handbook of educational psychology, 2nd Edition. Mahwah, NJ: Lawrence Erlbaum.


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