پیشگیری از معلولیت جسمی

پیشگیری از معلولیت جسمی

معاون امور پیشگیری بهزیستی شهرستان های استان تهران گفت:با انجام غربالگری و آزمایشات به هنگام ژنتیک و ایجاد سبک زندگی صحیح می توان حداقل تا ۵۰ درصد از متولد شدن نوزادان معلول و دچار مشکل پیشگیری کرد.مشاوره ژنتیک راهکار موثر در پیشگیری از معلولیت نوزادانفاطمه عباسی روز دوشنبه در گفت و گو با خبرنگار اجتماعی ایرنا، سبک زندگی صحیح و مشاوره ژنتیک را راهکار موثر در پیشگیری از تولد نوزادان دچار مشکل دانست.

وی افزود: غربالگری قبل از ازدواج، قبل از بارداری و پس از به دنیا آمدن نوزاد برای تمام خانواده هایی که دارای کودکان سالم هستند و یا حتی دارای سابقه فامیلی فرزند عقب مانده ذهنی و جسمی نیستند لازم است تا از برروز علایم جدی و جبران ناپذیر آن جلوگیری کنند.

عباسی تصریح کرد: مشاوره ژنتیک قبل از ازدواج و قبل از بارداری در پیشگیری از ۵۰ درصد معلولیت ها بسیار موثر است و باید با آگاه سازی تمام افراد جامعه به خصوص والدین از علل بوجودآورنده معلولیت های جسمی ، ذهنی و رعایت اصول بهداشتی از ایجاد مشکلات تا حد امکان جلوگیری کرد.

وی با تاکید بر اهمیت مشاوره ژنتیک به عنوان پایه و اساس پیشگیری از معلولیت ها ادامه داد: بیماریهای ژنتیکی از عوامل بسیارمهم نابینایی ها و ناشنوایی های دوران کودکی و عقب ماندگی های ذهنی شدید است که با افزایش آگاهی عمومی در پیشگیری از معلولیت ها تشخیص و مداخله به هنگام ، آشنایی با معلولیت ها و راههای جلوگیری از آن می توان نرخ معلولیت را کاهش داد.

معاون امور پیشگیری بهزیستی شهرستانهای استان تهران عوامل خطرزا در بروز شیوع بالای اختلالات ژنتیکی را میزان بالای ازدواج های فامیلی ، تمایل به بچه دارشدن در سنین بالا، خطر بیماریهای ارثی به ویژه اختلالات کروموزومی ذکر کرد.

** مددجویان بهزیستی رایگان مشاوره می گیرند

ژیلا باقری کارشناس مسوول پیشگیری از معلولیتهای بهزیستی شهرستانهای استان تهران نیزگفت: تاکنون دربین شهرستانهای استان تهران یک مرکز مشاوره ژنتیک دولتی و دو مرکز خصوصی فعالیت داشته و در سال ۹۴ دو مرکز دیگر نیز افتتاح و شروع به کار کرده اند.

وی باتوجه به ضرورت مشاوره ژنتیک در پیشگیری از معلولیت ها افزود: در راستای خدمت رسانی صحیح به تمامی خانواده های تحت پوشش، تفاهم نامه ای بین بهزیستی شهرستانهای استان تهران و بنیاد ژنتیک استان تهران درقالب مشاوره ژنتیک رایگان به مددجویان شهرستانهای تابعه تحت پوشش بهزیستی منعقد شده است.

وی گفت: همچنین برای سهولت و راحتی مددجویان و معلولان تحت پوشش، تیم مشاوره ژنتیک برای خدمت رسانی رایگان در تمام ادارات بهزیستی شهرستانهای استان تهران با برنامه ی زمانبندی مستقر می شوند.

آدرس : مشهد مقـدس ، میدان شهید فهمیده، به طرف میدان قائم(عج)، جاده اختصاصــی آسایشـگاه

تلفــــن مشارکــت‌های مردمــی : 05136666336

روابط عمومی : 05136666000 و 05136666166

تلفکس روابط عمومی : 05136666290

سامانه پیامک : 100005136666336

پست الکترونیک : Info At Fbrc .Ir

طراحی شده توسط واحد فناوری اطلاعات آسایشگاه شهیدفیاض بخشکلیه حقوق این سایت متعلق به موسسه فیاض بخش می باشد.حقوق قانونی وب سایت

اين دفتر به منظور پيشگيري از معلوليت هاي جسمي و ذهني برنامه هاي زير را اجرا مي نمايد :

1- برنامه پيشگيري از تنبلي چشم :

از آنجايي كه بهترين سن تشخيص و درمان آمبليوپي زير 5 سالگي است ، لذا براي پيشگيري از تنبلي چشم مي بايست چشم همه كودكان در سنين طلايي ( زير 5 سالگي ) مورد سنجش بينايي قرار گيرند ، لذا همه ساله معاونت پيشگيري سازمان بهزيستي از طريق آموزش مربيان مهدكودك ها و قرار داد با بينايي سنج و چشم پزشك همكار طرح و خريد خدمت از مراكز غير دولتي و پايگاههاي سنجش بينايي دائم و غیر دائمی با استفاده از E چارت و دستگاه اپتيك پلاس كليه كودكان 3 تا 6 ساله تحت پوشش مهدها و آمادگي ها و كودكان 3 تا 6 ساله مراجعه كننده به پايگاه هاي سنجش بينايي را تحت معاينات غربالگري سنجش بينايي قرار مي دهد. در حال حاضر شهرستانهای شیراز(2 دستگاه ) ، لارستان ، داراب ، خرم بید ، جهرم(2 دستگاه) و زرین دشت،نی ریز ،اقلید،مرودشت،سپیدان،آباده، خنج مجهز به دستگاه غربالگری بینایی می باشند و کلیه شهرستاهای استان دارای پایگاههای سنجش بینایی دایمی می باشند. آدرس پایگاههای دائمی به پیوست(شماره 1) ذکر شده است.

2-طرح آگاهسازي پيشگيري از معلوليت ها و آسيب هاي اجتماعي

در اين طرح كليه افراد شركت كننده در كلاسهاي مجتمع هاي بهزيستي روستايي و شهري و فراگيران و كم سوادان گروه هاي پيگير و سوادآموزان نهضت سوادآموزي و مربيان روستا مهدهاي خصوصي توسط كتابچه هاي 8گانه چاپ شده با عنوان هاي زير به زبان ساده از طريق آموزشياران نهضت و مربيان آموزش ديده توسط سازمان بهزيستي تحت آموزشهای لازم قرار مي گيرند .همچنين طرح مذكور در اجتماعات محلي CBO ها اجرا مي گردد.و در این رابطه تشکلهای غیر دولتی وجمعیت همیاران سلامت روان همکاری نزدیکی دارند.ضمنا از افراد تحت آموزش پیش آزمون و پس آزمون بعمل می آید.
عناوین کتابچه های 8 گانه آموزشی:
1- چگونه مي توان فرزند سالم داشت ( توصيه هاي دوران بارداري )
2- چگونه مي توان فرزند سالم داشت ( مراقبت از كودك )
3- چگونه مي توان فرزند سالم داشت ( پرهيزهاي دوران بارداري )
4- چگونه مي توان فرزند سالم داشت ( توصيه هاي پيش از ازدواج )
5- بيماري هاي استخوان
6- پيشگيري از نابينايي
7- پيشگيري از ناشنوايي
8- تغذيه دوران بارداري و شيردهي

3-طرح غربالگري شنوايي نوزادان :

پیشگیری در جهت ارتقاء سطح سلامت عمومی جامعه و کاهش هزینه های درمانی و توانبخشی نقش عمده ای در جامعه بشری ایفاء می نماید ، که در طی سالهای اخیر روز به روز توجه بیشتری به آن معطوف گردیده و غربالگری شنوایی یکی از این موارد مهم می باشد .
هر روزه در کشور ما حدود 20 تا 30 کودک کم شنوا به دنیا می آیند و از هر 1000 تولد نوزاد 2 تا 3 نوزاد دچار کم شنوایی خفیف تا عمیق می باشند لذا به منظور پیشگیری از اختلالات شنوایی لازم است کیله نوزادان تا روز هفتم زندگی و حداکثر تا 3 ماهگی مورد غربالگری شنوایی قرار گیرند
لازم به ذکر است کمیته استانی غربالگری شنوایی نوزادان در سال 1388 تشکیل و شبکه غربال شنوایی با همکاری معاونت توانبخشی و هماهنگی با مراکز غیر دولتی مجهز به ABR تشخیصي و پزشک متخصص ENT و اطفال راه اندازی گردید و موارد نیازمند از طریق شبکه مذکور ارجاع می گردند و در حال حاضر با استفاده از دستگاه OAE و OAE مجهز به AABR غربالگري طرح مذکور توسط سازمان بهزیستی در حال انجام می باشد.
آدرس و مشخصات مراکز غیر دولتی غربالگری شنوایی در شهرستانهای استان به شرح پیوست(شماره 2) است.

5- مشاوره پزشكي ژنتيك :

علم ژنتیک علم روز جهان است و امروزه اهمیت پیشگیری از معلولیت ها به کسی پوشیده نیست . والدین کودکان مبتلا به اختلالات ژنتیک می خواهند بدانندکه چرا این معلولیت اتفاق افتاده است و شانس بروز این معلولیت در کودکان بعدی چقدر است .و پاسخ به سوالات را با مشاوره ژنتیک می توان یافت .

مشاوره ژنتیک یک فرآیند ارتباطی و تحقیقاتی است که هدف آن تعیین نوع اختلال ژنتیکی و توضیح ریسک تکرار آن درخانواده هاست .

مراحل مشاوره ژنتیک به صورت زیر است :
1- مشاوره اطلاعاتی
2- تعیین ضریب هم خونی
3- تشخیص
4-تعيين ريسك بروز بيماري
5- مشاوره حمایتی
6- پیگیری

از آنجايي كه مشاوره ژنتيك بهترين و آسان ترين راه پيشگيري از بيماري هاي ارثي و ژنتيكي است ، لذا مراكز مشاوره ژنتیک در موارد زير مشاوره ارائه مي دهند :

1- ازدواج های فاميلي
2- بارداري در سنين بالاي 35 سالگي
3- وجود افراد معلول در فاميل
4- نازايي ، سقط جنين
5-اختلالات شنوایی و بینایی

در حال حاضر مراكز مشاوره ژنتيك بصورت دولتي و غيردولتي جهت راهنمايي افراد مراجعه كننده فعاليت مي نمايند و تعداد 1 مركز دولتي و 11 مركز غيردولتي در استان فارس فعاليت مي نمايند . لیست مراکز دولتی و غیر دولتی مشاوره ژنتیک در استان به پیوست(شماره 3) می باشد.

پیوست شماره 1: مشخصات پایگاه های دائمی تنبلی چشم – استان فارس (کلیک کنید)

پیوست شماره 2 : واحد غربالگری و آدرس و شماره تلفن (کلیک کنید)

پیوست شماره 3 : جدول ثبت آمار و مشخصات مربوط به مرکز مشاوره ژنتیک دولتی (کلیک کنید)

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پیشگیری از معلولیت جسمی

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1University of Florida, Gainesville FL

2University of Maryland School of Medicine, Baltimore, MD

4University of South Carolina, Columbia, SC

پیشگیری از معلولیت جسمی

5National Heart, Lung and Blood Institute, Bethesda, MD

6Pennington Biomedical Research Center, LA

7Tufts University, Boston, MA

8Yale School of Medicine, New Haven, CT

9VA San Diego Healthcare System and University of California San Diego, San Diego, CA

10Stanford University, School of Medicine, Stanford, CA

1University of Florida, Gainesville FL

11Northwestern University Feinberg School of Medicine, Chicago, IL

12University of Pittsburgh, Pittsburgh, PA

In older adults reduced mobility is common and is an independent risk factor for morbidity, hospitalization, disability, and mortality. Limited evidence suggests that physical activity may help prevent mobility disability; however, there are no definitive clinical trials examining if physical activity prevents or delays mobility disability.

To test the hypothesis that a long-term structured physical activity program is more effective than a health education program (also referred to as a successful aging program) in reducing the risk of major mobility disability.

The Lifestyle Interventions and Independence for Elders (LIFE) study was a multicenter, randomized trial that enrolled participants between February 2010 and December 2011, who participated for an average of 2.6 years. Follow-up ended in December 2013. Outcome assessors were blinded to the intervention assignment. Participants were recruited from urban, suburban and rural communities at 8 field centers throughout the US. We randomized a volunteer sample of 1,635 sedentary men and women aged 70–89 years who had physical limitations, defined as a score on the Short Physical Performance Battery of 9 or below, but were able to walk 400 m.

Participants were randomized to a structured moderate intensity physical activity program (n=818) done in a center and at home that included including aerobic, resistance and flexibility training activities or to a health education program (n=817) consisting of workshops on topics relevant to older adults and upper extremity stretching exercises.

The primary outcome was major mobility disability objectively defined by loss of ability to walk 400 m.

Incident major mobility disability occurred in 30.1% (n=246/818) of physical activity and 35.5% (n=290/817) of health education participants (HR=0.82, 95%CI=0.69–0.98, p=0.03). Persistent mobility disability was experienced by 120/818 (14.7%) physical activity and 162/817 (19.8%) health education participants (HR=0.72; 95%CI=0.57–0.91; p=0.006). Serious adverse events were reported by 404/818 (49.4%) of the physical activity and 373/817 (45.7%) of the health education participants (Risk Ratio=1.08; 95%CI=0.98–1.20).

A structured moderate intensity physical activity program, compared with a health education program, reduced major mobility disability over 2.6 years among older adults at risk of disability. These findings suggest mobility benefit from such a program in vulnerable older adults.

ClinicalsTrials.gov identifier {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01072500″,”term_id”:”NCT01072500″}}NCT01072500.

The life expectancy of older Americans continues to increase, with persons aged 65 years or older representing the fastest growing segment of the U.S. population.1 While prolongation of life remains an important public health goal, of even greater significance is preservation of the capacity to live independently and to function well during late life.2 Identification of proven interventions to prevent disability is an important public health challenge.3

Mobility – the ability to walk without assistance – is a critical characteristic for functioning independently.4;5 Those who lose mobility have higher rates of morbidity, disability, and mortality,6–13 and yet are often excluded from clinical trials. Preserving the ability to walk 400 m, an excellent proxy for community ambulation, is central to maintaining a high quality of life and independence in the community.

To our knowledge, no trial has conclusively tested that physical activity can prevent or delay the onset of mobility disability over an extended follow-up. Therefore, we conducted the Lifestyle Interventions and Independence for Elders (LIFE) Pilot study from 2004 to 2006 to plan for the Phase 3 randomized trial.14 As hypothesized, the LIFE Pilot study (N=424) showed significant improvements in walking speed and physical performance measures. The pilot was not powered for a disability endpoint, but showed a non-significant reduction in risk of major mobility disability in the physical activity group, compared with the health education group, also referred to as the successful aging group. In the LIFE study we hypothesized that compared with a health education program, a long-term structured physical activity program would reduce the risk of major mobility disability.

The LIFE study was a multicenter, single-blinded, parallel randomized trial conducted at 8 field centers across the U.S. (University of Florida, Gainesville and Jacksonville, Florida; Northwestern University, Chicago, Illinois; Pennington Biomedical Research Center, Baton h21-Rouge, Louisiana; University of Pittsburgh, Pittsburgh, Pennsylvania; Stanford University, Stanford, California; Tufts University, Boston, Massachusetts; Wake Forest School of Medicine, Winston-Salem, North Carolina; and Yale University, New Haven, Connecticut) between February 2010 and December 2013. The Administrative Coordinating Center was located at the University of Florida and the Data Management, Analysis, and Quality Control Center at Wake Forest School of Medicine. The field centers included rural, suburban and urban communities.

Details of the methods were published previously.15 Briefly, the eligibility criteria consisted of men and women aged 70–89 years who (a) were sedentary (reporting <20 min/week in the past month performing regular physical activity and <125 min/week of moderate physical activity); (b) were at high risk for mobility disability based on lower extremity functional limitations measured by the Short Physical Performance Battery (SPPB)16 score ≤9 out of a of 12 (45% of participants were targeted to have a score <8); (c) could walk 400 m in ≤15 minutes without sitting, leaning, or the help of another person or walker; (d) had no major cognitive impairment (Modified Mini-Mental State Examination17 [3MSE] 1.5 standard deviations below education- and race-specific norms); and (e) could safely participate in the intervention as determined by medical history, physical exam and resting ECG.

Targeted mass mailings to the community was the primary recruitment strategy.18

The study protocol was approved by the institutional review boards at all participating sites. Written informed consent was obtained from all study participants. The trial was monitored by a data and safety monitoring board appointed by the National Institute on Aging. The trial is registered at ClinicalsTrials.gov with the identifier {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01072500″,”term_id”:”NCT01072500″}}NCT01072500.

Participants were randomized to a physical activity or to a health education program, via a secure web-based data management system using a permuted block algorithm (with random block lengths) stratified by field center and gender. Both groups received an initial individual 45-minute face-to-face introductory session by a health educator who described the intervention, communicated expectations, and answered questions.

The physical activity intervention involved walking, with a goal of 150 min/week, strength, flexibility, and balance training.15 The intervention included attendance at two center-based visits per week and home-based activity 3–4 times per week for the duration of the study. A protocol was in place to restart the intervention for the participants who suspended the physical activity for medical reasons. The physical activity sessions were individualized and progressed towards a goal of 30 min of walking daily at moderate intensity, 10 min of primarily lower extremity strength training by means of ankle weights (2 sets of 10 repetitions), 10 min of balance training, and large muscle group flexibility exercises. The participants began with lighter intensity and gradually increased intensity over the first 2–3 weeks of the intervention. The Borg’s scale of self-perceived exertion19 that ranges from 6 to 20, was used to measure intensity of activity. Participants were asked to walk at an intensity of 13 (activity perception “somewhat hard”), and lower extremity strengthening exercises were performed at an intensity of 15 to 16.

The health education program focused on successful aging, and which has been termed the successful aging arm of the study in previous publications. The health education group attended weekly workshops of health education during the first 26 weeks, and then monthly sessions thereafter (bi-monthly attendance was optional). Workshops included topics, other than physical activity, relevant to older adults, such as how to effectively negotiate the health care system, how to travel safely, preventive services and screenings recommended at different ages, where to go for reliable health information, nutrition, etc. The program also included a 5- to 10-minute instructor-led program of gentle upper extremity stretching or flexibility exercises.

Participants were assessed every six months at clinic visits. Home, telephone, and proxy assessments were attempted if the participants could not come to the clinic. The assessment staff was blinded to the intervention and remained separate from the intervention team. Participants were asked not to disclose their assigned group and not to talk about their interventions during the assessment. Self-reported physical activity was ascertained by a separate set of un-blinded assessors.

The main baseline assessments included self-reported demographic and contact information, medical and hospitalization history, medication inventory, ECG, physical exam, Quality of Well-Being questionnaire,20 health care utilization, physical activity assessed with the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire,21 and with accelerometry over 7-day periods (Actigraph Inc., Pensacola FL), cognitive testing, 400 m walk test,22 the SPPB; body weight, blood pressure, and pulse rate. These measures were repeated during follow-up at varied intervals. Details of these measures and their frequency are described elsewhere.15 The SPPB consisted of 4 m walk at usual pace, a timed repeated chair stand, and three increasingly difficult standing balance tests.16,23 Each measure was assigned a categorical score ranging from 0 (inability to complete the test) to 4 (best performance). A summary score ranging from 0 (worst performers) to 12 (best performers) was calculated by summing the three component scores. Race and ethnicity were reported by the participants and were collected according to NIH requirements. To minimize reporting bias, adverse events originating from the blinded assessments are presented.پیشگیری از معلولیت جسمی

The primary outcome of major mobility disability was defined as the inability to complete a 400 m walk test within 15 min without sitting and without the help of another person or walker.15 Use of a cane was acceptable. Participants were asked to walk 400 m at their usual pace, without over exerting, on a 20 m course for 10 laps (40 m per lap). Participants were allowed to stop for up to 1 minute for fatigue or related symptoms. When major mobility disability could not be objectively measured because of the inability of the participant to come to the clinic and absence of a suitable walking course at the participant’s home, institution or hospital, an alternative adjudication of the outcome was based on objective inability to walk 4 m in ≤10 sec, or self-, proxy-, or medical record-reported inability to walk across a room. If participants met these alternative criteria, they would not be able to complete the 400 m walk within 15 minutes. Reports of death were tracked through regular surveillance. Two consecutive major mobility disability assessments, or major mobility disability followed by death defined persistent mobility disability. Censoring was defined at the time of the last definitive assessment for major mobility disability.

At each contact, participants (or proxies if the participant was not available) were questioned about outcomes and hospitalizations since the last visit. All records for hospitalizations were obtained and outcomes were reviewed and adjudicated independently by two experts who were blinded to the group randomization. If the two reviewers disagreed, the information was forwarded to the adjudication committee and a determination was made by consensus.

Power calculations for the primary outcome, time until the first post-randomization occurrence of major mobility disability, were based on a log-rank test with a 2-sided, 0.05 significance level. Based on the LIFE Pilot study,14 the annual incidence rate of major mobility disability in the health education group was assumed to increase from 18% in the first year to 21% after two years. We further assumed that recruitment would be uniform over 21 months, follow-up would average 31 months, and loss to follow-up would be 8%/year. Under these assumptions, randomization of 1600 participants provides 80% power to detect a 21% reduction, and 90% power to detect 24% reduction in the hazard for major mobility disability in the physical activity participants. These effect size targets were determined based on consistency with effects derived from observational research, the LIFE Pilot experience, clinical relevance (around 20% reduction) and available funding resources.

Baseline characteristics were summarized by intervention group using mean (SD) or percentages. Intervention adherence was calculated as the percentage of scheduled intervention sessions attended by participants. Self-reported minutes of activity and minutes spent in activity associated with >760 counts/minute (by accelerometry)24 were analyzed using mixed effects ANCOVA models for repeatedly measured outcomes with an unstructured parameterization for longitudinal covariance. Models contained the following terms: field center and gender (both used to stratify randomization), baseline value of the relevant physical activity measure, intervention, clinic visit and intervention-by-visit interaction. Least squares means were obtained from these models and contrasts were used to estimate the average effects (95% CI) over follow-up. Risk ratios (95% CI) were calculated to determine the relative effect of the intervention on the proportion of participants reporting adverse effects. A test of equality of the risk ratios for hospitalization between baseline subgroups defined by SPPB levels (< 8 vs ≥ 8) was performed using Poisson regression.

The effect of the intervention on the primary outcome (i.e. time until the initial ascertainment of major mobility disability) was tested based on a two-tailed significance of 0.05 using the intention to treat approach in which participants are grouped according to randomization assignment. To compare intervention, we used a likelihood ratio test from a Cox regression model, stratified by field center and gender. Failure time was measured from the time of randomization; follow-up was censored at the last successfully completed 400m walk test. For participants who did not have any outcome assessments, we assigned one hour of follow-up time, since we knew that they completed the 400m walk at baseline. An assessment for non-proportionality of hazards was made with the addition of the interaction between log(time) and intervention.25 Interaction terms were entered into these Cox models and likelihood ratio tests were used to assess the consistency of the intervention effect across levels of baseline subgroups (ethnicity/race, gender, cardiovascular disease, diabetes, walking speed, and physical performance). The secondary endpoints were analyzed using the same approach as used for the primary outcome.

Sensitivity analyses were performed to investigate the effect of loss to follow-up on major mobility disability. These analyses used stabilized inverse probability weights that were a function of baseline covariates hypothesized to be predictive of loss-to-follow-up (i.e. gender, race-ethnicity, age (80+), history of diabetes, gait speed <0.8 m/sec, low SPPB score (<8), 3MS<90, clinical site, and living alone (yes/no)) and follow-up gait speed and SPPB scores to explore how the estimated hazard ratios and confidence intervals may have been altered under these missing data assumptions. Statistical analyses were performed in SAS 9.3 and R.26

From February 2010 to December 2011, we screened 14,831 participants; of these, 1,635 were eligible and randomized (818 to physical activity and 817 to health education; Figure 1). Details regarding screening, recruitment yields and baseline characteristics have been published.18 Baseline characteristics were similar in the two groups (Table 1). The mean age was 78.9 years, 67.2% were women, 17.6% were African American, the average body mass index was 30.2 kg/m2, and the average SPPB score was 7.4. The mean follow-up for any contact (including telephone) was 2.6 years (median=2.7 years; Inter-Quartile Range [IQR]=2.3–3.1 years). The trial ended in December 2013 as planned in the study protocol.

Study flow

1Participants who did not receive the allocated intervention, i.e. attended no intervention sessions.

2For participants who did not have any MMD assessments, we assigned one hour of follow-up time, since we knew that they were able to do the 400m walk at baseline.

3Partial follow-up indicates participants who had censoring times prior to the last planned follow-up visit.

4Discontinuation of the intervention was operationalized as participants who did not attend at least one intervention session during their last 6-months of follow-up prior to the last planned follow-up visit date. Deaths and intervention withdrawals are included in these numbers. As an example, a participant may have discontinued the intervention in the initial six month of follow-up due to illness and then died prior to the 6-months assessment for the primary outcome. This participant would be reflected as missing the primary outcome due to death and also discontinuing the intervention.

Baseline characteristics of the participants

Data are means and standard deviations or n (%); SPPB = short physical performance battery. We defined “moderate physical activity” for accelerometry based on the 760 counts/minute cut-point.24

Some values may slightly differ from those previously published18 due to data updates.

The physical activity group attended 63%, SD=27% (median=71%; IQR=50–83) of the scheduled sessions after excluding medical leave. A total of 479 (58.6%) participants went on medical leave at least once and 210 (25.7%) more than once. The mean duration of medical leave was 135±203 days (median=49 days; IQR=21–140). Health education participants attended 73±25% (median=82%; IQR=63–90). Based on CHAMPS questionnaires, through the 24 month follow-up visit (the minimum planned intervention duration for all participants), the physical activity group maintained an average of 218 min/week (95%CI 210–227; average change from baseline=138 min, 95%CI=129–146) in walking/weight training activities; whereas, the health education group maintained an average of 115 min/week (95%CI=106–123; average change from baseline=34 min, 95%CI=24–42) (Figure 2). Thus, the physical activity intervention maintained a 104 min (95%CI=92–116; p<0.001) difference in walking/weight training activities compared with the health education group during the initial two years where all participants were followed.

Self-reported and accelerometry derived physical activity by treatment group in the LIFE study participants. Plotted values represent least squares means (95% CI) from a mixed effects model adjusting for clinical site and gender (both used to stratify randomization) and the baseline self-reported walking/weight training activities or accelerometry counts. In addition to the above mentioned terms, the model contained a term for intervention group, follow-up clinic visit (i.e. 6, 12, 18, … months) and the intervention by visit interaction. All participants had expected follow-up through 24 months and approximately 47% of randomized participants had expected visits at 36 months. Accelerometry data were not collected at the 36 month visit. Baseline values represent the overall mean of both groups combined: this is the assumed value for both groups when obtaining least squares means at follow-up using mixed effects ANCOVA. The baseline, pre-randomization value, is reflected by follow-up time 0. P-values represent tests of the average intervention effect across all visits.

Based on accelerometry using a definition of >760 counts/minute for moderate activity,24 through follow-up, on average, the physical activity group participated in 213 min/week (95%CI=205–221; average change from baseline=15 min, 95%CI 7–23) of moderate activity; whereas, the health education group maintained 173 min/week (95%CI=165–181; average change from baseline= −25 min, 95%CI=−33, −17 min) (Figure 2). Thus, the physical activity intervention maintained a 40 min/week (95%CI=29–52; p<0.001) difference in moderate physical activity assessed with accelerometry, compared with the health education group during two years of follow-up.

Data for major mobility disability were obtained for 794/818 (97.1%) physical activity and 803/817 (98.3%) health education participants. Loss to follow-up was 4.0% annually. Major mobility disability was experienced by 246/818 (30.1%) physical activity participants and 290/817 (35.5%) health education participants (HR=0.82; 95%CI=0.69–0.98; p=0.03, Figure 3). Of the 246 and 290 physical activity and health education participants classified with major mobility disability, 42 (17%) and 32 (11%) resulted from alternative adjudications in each group, respectively. The sensitivity analyses exploring the effect of loss to follow-up on conclusions altered the estimates of the hazard ratio and confidence limits by less than 0.016 for all analyses (see online appendix table). Persistent mobility disability was experienced by 120/818 (14.7%) physical activity and 162/817 (19.8%) health education participants (HR=0.72; 95%CI=0.57–0.91; p=0.006). Major mobility disability or death was experienced by 264/818 (32.3%) physical activity and 309/817 (37.8%) health education participants (HR=0.82; 95%CI=0.70–0.97; p=0.02).

The effect of a moderate physical activity intervention on the onset of major mobility disability and persistent mobility disability: The Life Study. Kaplan Meier plot of major mobility disability occurrence and persistent mobility disability occurrence are presented in the top and bottom panels, respectively. The graph for major mobility disability was truncated at 3.5 years and the health education group had 4 additional failures between 3.5 and 3.6 years of follow-up. Number of events represents cumulative events and adjusted hazard ratios and p-values are from proportional hazards regression models defined in the methods.

In pre-specified subgroup analyses, results for major mobility disability did not significantly differ when participants were categorized by ethnicity/race, gender, history of cardiovascular disease, history of diabetes, baseline walking speed, and baseline physical performance (Figure 4). The subgroup with lower physical function at baseline (SPPB<8), representing 44.7% of the study population yet 71% (283 of 536 total events) of major mobility disability events, received considerable benefit (HR=0.81). In post-hoc analyses, the benefit of physical activity on major mobility disability was similar in participants with 3MSE score <90 and ≥90 (Figure 4).

Forest plot of the hazard ratio of major mobility disability for physical activity vs. health education according to sub-groups (PA= Physical Activity; HA = Health education; FG = Fasting Glucose). P-values were obtained from likelihood ratios tests of the interaction terms added to the Cox regression model.

Safety Serious adverse events were reported by 404/818 (49.4%) of the physical activity and 373/817 (45.7%) of the health education participants (Risk Ratio=1.08; 95%CI=0.98–1.20, Table 2). For inpatient hospitalizations, 396/818 (48.4%) physical activity and 360/817 (44.1%) health education participants reported an event (Risk Ratio=1.10; 95%CI=0.99–1.22). The reasons for hospitalization were highly heterogeneous, and most of them deemed unrelated to the intervention. Among those with SPPB < 8 the Risk Ratio was 1.04 (95%CI=0.90–1.20); and among those with SPPB ≥ 8 the Risk Ratio was 1.17 (95%CI=1.00–1.36). The test of equality of risk ratios for hospitalization for physical activity vs. health education between the two baseline SPPB subgroups was not significant (p=0.44).

All Deaths and number of participants reporting adverse events at blinded assessments

The LIFE study showed that, over 2.6 years of follow-up, the physical activity intervention, compared with the health education intervention, significantly reduced major mobility disability (HR=0.82, p=0.03), persistent mobility disability (HR=0.72, p=0.006) and the combined outcome of major mobility disability or death (HR=0.82, p=0.02). The subgroup with lower physical function at baseline (SPPB<8), representing 44.7% of the study population yet 71% (283 of 536 total events) of major mobility disability events, received considerable benefit (HR=0.81). These results suggest the potential for structured physical activity as a feasible and effective intervention to reduce the burden of disability among vulnerable older persons, in spite of functional decline in late life. To our knowledge, the LIFE study is the largest and longest duration randomized trial of physical activity in older persons.

The LIFE study has important strengths, including the objectively measured primary outcome of major mobility disability that is a reliable,22 well-validated and important clinical and public health outcome in older people.11 Participants at high risk of disability were recruited from 8 field centers spanning the US, including urban, suburban and rural settings, and included a high proportion of older adults from African American/Hispanic backgrounds. Although highly prevalent and increasing in size, the older, more vulnerable population has been understudied and typically is not included in large randomized trials. Retention throughout the follow-up was excellent. The adherence rates to the physical activity intervention were similar or higher than those achieved in other much shorter studies involving older adults.27–29 The physical activity program was likely successful in part because of the adherence and lifestyle motivation procedures put in place.30 The participants were reimbursed for their transportation costs, which added to the cost of the intervention, but likely contributed to the high levels of attendance. According to initial cost data collected in the LIFE study, the physical activity intervention cost, including transportation, was approximately $4,900 per participant over the 2.6 years of average participation ($1,815 per year). The physical activity intervention was designed to be simple for widespread implementation in a variety of communities and settings, as it does not require any special equipment.

The LIFE study has limitations. We could not ascertain whether participants who were excluded because of their high level of physical function or severe cognitive deficits, would also benefit from physical activity. The participants were recruited from the community, but may have been self-referred, so they may not be fully representative of all people in the community. The average follow-up duration of 2.6 years was relatively short vs. the estimated average 9 year life-expectancy of the LIFE cohort.31 Ideally, it would be useful to assess the effect of the intervention on the quality of the remaining years of life. The study, which was powered based on assumptions of 21%–24% risk reduction, achieved a hazard ratio of 0.82 and an absolute risk difference of 5.4%. While the effect size was slightly lower than planned, we believe that it is clinically relevant given the major health impact of mobility disability and the lack of proven interventions to avert mobility disability in vulnerable older populations. In addition, persistent mobility disability was significantly reduced by a larger degree in the physical activity group (HR=0.72), indicating that physical activity not only prevents the onset of major mobility disability, but also favors improved recovery in those who lose mobility.

Based on observational cohorts,32 we expected a lower hospitalization rate in the physical activity group. In the LIFE study, Physical activity did not decrease the hospitalizations rate. We found a higher rate of hospitalizations in the physical activity group that did not reach statistical significance. The hospitalizations comprised a range of heterogeneous diagnoses mostly deemed unrelated to the intervention. Our finding may have several explanations. First, physical activity may unmask symptoms resulting in earlier detection of underlying medical conditions. For example, sedentary older persons with subclinical left ventricular dysfunction may observe heart failure symptoms when they start moderate physical activity. Second, the physical activity group’s more frequent contact, and testing of vital signs at each intervention session may have led to a higher rate of recognition of health events. Third, the stress of exercise in the context of lowered homeostatic reserve in vulnerable participants,33 may have led to a higher risk of adverse events. However, our data do not support this explanation. The hospitalization results were not significantly different among those with SPPB score <8, and those with score 8 or 9. Finally, there may be no causal association between physical activity and hospitalizations.

Physical activity did not decrease the death rate. We found a higher rate of mortality in the physical activity group that did not reach statistical significance, and which was compatible with benefit or harm of physical activity (Table 2). Given the small number of events the data regarding mortality are inconclusive. Further studies are needed to assess the effects of physical activity on mortality and hospitalizations in vulnerable older adults.

The Lifestyle Interventions and Independence for Elders Study is funded by a National Institutes on Health/National Institute on Aging Cooperative Agreement UO1AG22376 and a supplement from the National Heart, Lung and Blood Institute 3U01AG022376-05A2S, and was sponsored in part by the Intramural Research Program, National Institute on Aging, NIH. The NIH sponsor was a voting member (1 vote out of 12 votes) of the LIFE Steering Committee, which approved the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, and approval of the manuscript; and decision to submit the manuscript for publication.

We are indebted to Evan C. Hadley, MD, and Sergei Romashkan, MD, PhD from the National Institute on Aging, Bethesda, MD, for their substantial intellectual contribution to the development and implementation of the LIFE study. Dr. Hadley and Dr. Romashkan are federal employees fully paid by the NIH. They did not receive any additional compensation from the study.

The research is partially supported by the Claude D. Pepper Older Americans Independence Centers at the University of Florida (1 P30 AG028740), Wake Forest University (1 P30 AG21332), Tufts University (1P30AG031679), University of Pittsburgh (P30 AG024827), and Yale University (P30AG021342) and the NIH/NCRR CTSA at Stanford University (UL1 RR025744), at University of Florida (U54RR025208) and at Yale University (UL1 TR000142) Tufts University is also supported by the Boston Rehabilitation Outcomes Center (1R24HD065688-01A1).

LIFE investigators are also partially supported by the following:

Dr. Thomas Gill (Yale University) is the recipient of an Academic Leadership Award (K07AG3587) from the National Institute on Aging.

Dr. Carlos Fragoso (Spirometry Reading Center, Yale University) is the recipient of a Career Development Award from the Department of Veterans Affairs.

Dr. Roger Fielding (Tufts University) is partially supported by the U.S. Department of Agriculture, under agreement No. 58-1950-0-014. Any opinions, findings, conclusion, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Dept of Agriculture.

The Lifestyle Interventions and Independence for Elders Study is funded by a National Institutes of Health/National Institute on Aging Cooperative Agreement #UO1 AG22376 and a supplement from the National Heart, Lung and Blood Institute 3U01AG022376-05A2S, and sponsored in part by the Intramural Research Program, National Institute on Aging, NIH.

Tufts University is also supported by the Boston Rehabilitation Outcomes Center (1R24HD065688-01A1).

LIFE investigators are also partially supported by the following:

Dr. Thomas Gill (Yale University) is the recipient of an Academic Leadership Award (K07AG3587) from the National Institute on Aging.

Dr. Carlos Fragoso (Spirometry Reading Center, Yale University) is the recipient of a Career Development Award from the Department of Veterans Affairs.

Marco Pahor, MD – Principal Investigator of the LIFE Study

Jack M. Guralnik, MD, PhD – Co-Investigator of the LIFE Study (University of Maryland School of Medicine, Baltimore, MD)

Christiaan Leeuwenburgh, PhD

Connie Caudle

Lauren Crump, MPH

Latonia Holmes

Jocelyn Lee, PhD

Ching-ju Lu, MPH

Michael E. Miller, PhD – DMAQC Principal Investigator

Mark A. Espeland, PhD – DMAQC Co-Investigator

Walter T. Ambrosius, PhD

William Applegate, MD

Daniel P. Beavers, PhD, MS

Robert P. Byington, PhD, MPH, FAHA

Delilah Cook, CCRP

Curt D. Furberg, MD, PhD

Lea N. Harvin, BS

Leora Henkin, MPH, Med

John Hepler, MA

Fang-Chi Hsu, PhD

Laura Lovato, MS

Wesley Roberson, BSBA

Julia Rushing, BSPH, MStat

Scott Rushing, BS

Cynthia L. Stowe, MPM

Michael P. Walkup, MS

Don Hire, BS

W. Jack Rejeski, PhD

Jeffrey A. Katula, PhD, MA

Peter H. Brubaker, PhD

Shannon L. Mihalko, PhD

Janine M. Jennings, PhD

Evan C. Hadley, MD (National Institute on Aging)

Sergei Romashkan, MD, PhD (National Institute on Aging)

Kushang V. Patel, PhD (National Institute on Aging)

Denise Bonds, MD, MPH

Mary M. McDermott, MD – Field Center Principal Investigator

Bonnie Spring, PhD – Field Center Co-Investigator

Joshua Hauser, MD – Field Center Co-Investigator

Diana Kerwin, MD – Field Center Co-Investigator

Kathryn Domanchuk, BS

Rex Graff, MS

Alvito Rego, MA

Timothy S. Church, MD, PhD, MPH – Field Center Principal Investigator

Steven N. Blair, PED (University of South Carolina)

Valerie H. Myers, PhD

Ron Monce, PA-C

Nathan E. Britt, NP

Melissa Nauta Harris, BS

Ami Parks McGucken, MPA, BS

Ruben Rodarte, MBA, MS, BS

Heidi K. Millet, MPA, BS

Catrine Tudor-Locke, PhD, FACSM

Ben P. Butitta, BS

Sheletta G. Donatto, MS, RD, LDN, CDE

Shannon H. Cocreham, BS

Abby C. King, PhD – Field Center Principal Investigator

Cynthia M. Castro, PhD

William L. Haskell, PhD

Randall S. Stafford, MD, PhD

Leslie A. Pruitt, PhD

Kathy Berra, MSN, NP-C, FAAN

Veronica Yank, MD

Roger A. Fielding, PhD – Field Center Principal Investigator

Miriam E. Nelson, PhD – Field Center Co-Investigator

Sara C. Folta, PhD – Field Center Co-Investigator

Edward M. Phillips, MD

Christine K. Liu, MD

Erica C. McDavitt, MS

Kieran F. Reid, PhD, MPH

Won S. Kim, BS

Vince E. Beard, BS

Todd M. Manini, PhD – Field Center Principal Investigator

Marco Pahor, MD – Field Center Co-Investigator

Stephen D. Anton, PhD

Susan Nayfield, MD

Thomas W. Buford, PhD

Michael Marsiske, PhD

Bhanuprasad D. Sandesara, MD

Jeffrey D. Knaggs, BS

Megan S. Lorow, BS

William C. Marena, MT, CCRC

Irina Korytov, MD

Holly L. Morris, MSN, RN, CCRC (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)

Margo Fitch, PT (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)

Floris F. Singletary, MS, CCC-SLP (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)

Jackie Causer, BSH, RN (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)

Katie A. Radcliff, MA (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)

Anne B. Newman, MD, MPH – Field Center Principal Investigator

Stephanie A. Studenski, MD, MPH – Field Center Co-Investigator

Bret H. Goodpaster, PhD

Nancy W. Glynn, PhD

Oscar Lopez, MD

Neelesh K. Nadkarni, MD, PhD

Kathy Williams, RN, BSEd, MHSA

Mark A. Newman, PhD

George Grove, MS

Janet T. Bonk, MPH, RN

Jennifer Rush, MPH

Piera Kost, BA (deceased)

Diane G. Ives, MPH

Stephen B. Kritchevsky, Ph.D. – Field Center Principal Investigator

Anthony P. Marsh, PhD – Field Center Co-Investigator

Tina E. Brinkley, PhD

Jamehl S. Demons, MD

Kaycee M. Sink, MD, MAS

Kimberly Kennedy, BA, CCRC

Rachel Shertzer-Skinner, MA, CCRC

Abbie Wrights, MS

Rose Fries, RN, CCRC

Deborah Barr, MA, RHEd, CHES

Thomas M. Gill, MD – Field Center Principal Investigator

Robert S. Axtell, PhD, FACSM – Field Center Co-Investigator (Southern Connecticut State University, Exercise Science Department)

Susan S. Kashaf, MD, MPH (VA Connecticut Healthcare System)

Nathalie de Rekeneire, MD, MS

Joanne M. McGloin, MDiv, MS, MBA

Karen C. Wu, RN

Denise M. Shepard, RN, MBA

Barbara Fennelly, MA, RN

Lynne P. Iannone, MS, CCRP

Raeleen Mautner, PhD

Theresa Sweeney Barnett, MS, APRN

Sean N. Halpin, MA

Matthew J. Brennan, MA

Julie A. Bugaj, MS

Maria A. Zenoni, MS

Bridget M. Mignosa, AS

Jeff Williamson, MD, MHS – Center Principal Investigator

Kaycee M Sink, MD, MAS – Center Co-Investigator

Hugh C. Hendrie, MB, ChB, DSc (Indiana University)

Stephen R. Rapp, PhD

Joe Verghese, MB, BS (Albert Einstein College of Medicine of Yeshiva University)

Nancy Woolard

Mark Espeland, PhD

Janine Jennings, PhD

Carl J. Pepine MD, MACC

Mario Ariet, PhD

Eileen Handberg, PhD, ARNP

Daniel Deluca, BS

James Hill, MD, MS, FACC

Anita Szady, MD

Geoffrey L. Chupp, MD

Gail M. Flynn, RCP, CRFT

Thomas M. Gill, MD

John L. Hankinson, PhD (Hankinson Consulting, Inc.)

Carlos A. Vaz Fragoso, MD

Erik J. Groessl, PhD (University of California, San Diego and VA San Diego Healthcare System)

Robert M. Kaplan, PhD (Office of Behavioral and Social Sciences Research, National Institutes of Health)

Dr. Mike Miller had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Data analyses were conducted by Dr. Mike Miller, Dr. Walter Ambrosius and Dr. Mark Espeland.

National Center for
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U.S. National Library of Medicine

8600 Rockville Pike, Bethesda
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1Centre for Global Health and School of Psychology, Trinity College, University of Dublin, Dublin, Ireland.

3School of Nursing and Midwifery, National University of Ireland Galway, Galway, Ireland.

4Department of Psychology, National University of Ireland, Maynooth, Ireland.

5School of Nursing, Dublin City University, Dublin, Ireland.

پیشگیری از معلولیت جسمی

6Department of Psychiatry, University Hospital, Zurich, Switzerland.

Traumatic physical injury can result in many disabling sequelae including physical and mental health problems and impaired social functioning.

To assess the effectiveness of psychosocial interventions in the prevention of physical, mental and social disability following traumatic physical injury.

Randomised controlled trials that consider one or more defined psychosocial interventions for the prevention of physical disability, mental health problems or reduced social functioning as a result of traumatic physical injury. We excluded studies that included patients with traumatic brain injury (TBI).

Two authors independently screened the titles and abstracts of search results, reviewed the full text of potentially relevant studies, independently assessed the risk of bias and extracted data.

We included five studies, involving 756 participants. Three studies assessed the effect of brief psychological therapies, one assessed the impact of a self-help booklet, and one the effect of collaborative care. The disparate nature of the trials covering different patient populations, interventions and outcomes meant that it was not possible to pool data meaningfully across studies. There was no evidence of a protective effect of brief psychological therapy or educational booklets on preventing disability. There was evidence from one trial of a reduction in both post-traumatic stress disorder (PTSD) and depressive symptoms one month after injury in those who received a collaborative care intervention combined with a brief psycho-educational intervention, however this was not retained at follow up. Overall mental health status was the only disability outcome affected by any intervention. In three trials the psychosocial intervention had a detrimental effect on the mental health status of patients.

This review provides no convincing evidence of the effectiveness of psychosocial interventions for the prevention of disability following traumatic physical injury. Taken together, our findings cannot be considered as supporting the provision of psychosocial interventions to prevent aspects of disability arising from physical injury. However, these conclusions are based on a small number of disparate trials with small to moderate sample sizes and are therefore necessarily cautious. More research, using larger sample sizes, and similar interventions and patient populations to enable pooling of results, is needed before these findings can be confirmed.

Injuries account for 9% of the world’s deaths and 12% of the world’s disease burden (WHO 2002), and may arise from road traffic crashes, poisoning, falls, fires, drowning, interpersonal violence and war, self-inflicted injuries, as well as other sources. The World Health Organization (WHO) states that “while mortality is an important indicator of the magnitude of a health problem, it is important to realise that for each injury death, there are several thousand injury survivors who are left with permanent disabling sequelae” (WHO 2002, p 3). Even in patients with physical problems that do not arise from traumatic injury, the ability to function effectively is strongly influenced by factors such as mood, coping skills and social support. Interventions that influence these factors are therefore likely to contribute to better health and more cost-effective outcomes (Sobel 1995).

Schnyder et al found that 25.5% of severely injured accident victims showed some form of psychiatric morbidity after one year and that this “can be predicted to some degree by mainly psychosocial variables” (Schnyder 2001, p 653), in particular patients’ early cognitive appraisal of their accident. However, while NICE (Gersons 2005) has endorsed the effectiveness of longer-term psychosocial interventions in the aftermath of psychological trauma, the effectiveness of short-term ‘debriefing’ has not been demonstrated (Rose 2002). While psychosocial interventions following physical injury may alleviate psychiatric co-morbidity, we wish to focus on the benefits of preventive interventions rather than therapeutic interventions per se. To date, there has been no attempt to systematically review the effects of psychosocial interventions that seek to alleviate the distress of those who have acquired physical injuries, including subsequent disability. This review will provide this evidence. For the purposes of this review, by disability we mean any diminution in an individual’s psychological, social or physical functioning that has arisen following, and as a consequence of, a traumatic physical injury.

This review will focus on primary preventive rather than therapeutic interventions, as intervening early after the traumatic event to a general population of trauma patients presents a novel approach to the reduction of disability following traumatic injury. Psychosocial interventions are interventions that have their primary mode of action through psychological or social processes. Such interventions include, for instance, direct therapeutic work, health education and social support.

Physical injury may result in impairment of physical functioning. The way in which people respond to such impairment, along with the social and environmental context they live in, determines the degree of disability associated with the injury. A physical injury may disable people in terms of their physical, mental or social functioning. An individual’s own ability to cope with physical impairment, as well as their broader social situation, offers opportunities to reduce the extent to which physical injury results in disability. By providing people with psychological and social resources that assist their coping responses to physical impairment, psychosocial interventions may be able to prevent physical impairment resulting in physical, mental and social disability.

This is the first systematic review to consider the effectiveness of psychosocial interventions designed to prevent disability following an injury that produces physical impairment.

To assess the effectiveness of psychosocial interventions in the prevention of physical, mental and social disability following traumatic physical injury (excluding traumatic brain injury (TBI)), when compared to usual care or other experimental intervention.

To assess the effectiveness of different types of psychosocial interventions.

To assess the effectiveness of psychosocial interventions on different post-injury outcomes (physical disability, mental health and social functioning).

Randomised controlled trials that considered one or more defined psychosocial interventions for the prevention of physical disability, mental health problems or reduced social functioning as a result of traumatic physical injury. We included cross-over trials, cluster-randomised trials and factorial trials.

We excluded non-randomised intervention studies.

Patients who have suffered a traumatic physical injury.

We excluded trials which included people with traumatic brain injury (TBI) unless they could be disaggregated from other physically injured people who received the intervention, or comprised less than 20% of trial participants. We excluded trials which included people without traumatic physical injury (for example, psychological de-briefing following a traumatic incident not resulting in physical injury) if the results could not be disaggregated to include only those who had suffered a traumatic physical injury or those without physical injury comprise less than 20% of trial participants. We retrieved the full text of trials including patients with TBI or without traumatic physical injury and only excluded trials if the above conditions were not met. We excluded musculoskeletal conditions incurred other than through a physical injury. We only included sexual assault if it resulted in a physical injury.

We define ‘psychosocial interventions’ as being any intervention that focuses on psychological and/or social factors rather than biological factors (definition taken from Ruddy 2005). This may include, but is not limited to:

psychological therapies such as cognitive behavioural therapy (CBT), interpersonal psychotherapy, non-directive counselling, psychological debriefing and problem-solving therapy;

social interventions such as befriending, mentoring and social support.

We included psychosocial interventions as long as they were sufficiently described by trialists to facilitate replication. Interventions may be administered by any health professional (for example, psychologist, medical practitioner, nurse or occupational therapist) or lay person and in any form, for example, individual or group therapy, over the telephone, or in the form of written material. Psychosocial interventions may be offered to enhance a person’s coping resources without any suggestion that they are currently suffering through any type of psychopathology or psychological disorder. Such interventions may prevent circumstances arising where their ability to cope is exceeded, resulting in a state of psychological disorder or variously defined psychopathologies. It may well be the case that people who are currently experiencing psychological disorder benefit from interventions designed to be preventive, and in this sense they may be understood as being therapeutic. However, our focus here is on prevention and not treatment.

Psychosocial interventions were compared with:

usual care;

pharmacological interventions, for example, treatments for mental health problems and pain relief;پیشگیری از معلولیت جسمی

physical interventions, for example physiotherapy, provision of prosthetic devices or surgery;

any mix of the above.

Trials were excluded if:

the primary basis of action of the intervention is physical, such as pharmacological or physical interventions (for example, drug treatments, assistive technology, physiotherapy, or acupuncture);

the primary basis of action of the intervention is economic (for example, direct cash transfers to pay for assistive technology or work-related training courses);

the intervention is complex and includes pharmacological, physical and/or financial components as well as a psychosocial component and the results of the psychosocial component can not be disaggregated;

the intervention is aimed solely at the treatment rather than the prevention of physical disability, mental health problems or social problems resulting from traumatic physical injury, for example the treatment of depression or post-traumatic stress disorder following physical injury amongst people post-injury who also have developed a mental illness;

participants have been selected on the basis of poor mental health status;

the intervention takes place more than 12 months after the traumatic injury as these trials will be dealing with the treatment rather than prevention of physical, mental and social sequelae;

the intervention is designed to be therapeutic rather than preventative;

the intervention is received by people with TBI unless they can be disaggregated from other physically injured people or constitute less than 20% of trial participants.

Physical disability such as extent of disability, measured using validated instruments.

Mental health status measured using validated instruments or through structured mental state assessment.

Global assessment of functioning, including quality of life and physical and social functioning, measured using validated instruments.

Social functioning, including social participation and employment status.

Health care utilisation.

The search was not restricted by date, language or publication status.

We searched the following electronic databases;

Cochrane Injuries Group Specialised Register (searched 5 Feb 2008),

CENTRAL (The Cochrane Library 2009, Issue 1),

MEDLINE (Ovid SP) 1950 to Jan (week 5) 2008,

EMBASE (Ovid SP) 1980 to (week 5) Jan 2008,

PsycINFO (Ovid SP) 1806 to Jan (week 5) 2008,

Controlled Trials metaRegister (www.controlled-trials.com) (Searched 5 Feb 2008),

ISI Web of Science: Social Sciences Citation Index (SSCI) 1970 to Feb 2008,

PubMed [www.ncbi.nlm.nih.gov/sites/entrez/] (searched from 2006 to Feb 2008)

Full details of the search strategies can be found in Appendix 1.

We scanned the reference lists of all selected papers and contacted authors of relevant studies to seek out additional studies.

The Cochrane Injuries Group’s Trials Search Co-ordinator ran the relevant search strategies across the appropriate databases. Two authors (MDS and MM) separately screened the titles and abstracts of the citations identified by the search to determine which papers met the pre-determined criteria. In case of doubt or disagreement, we obtained the full article for inspection. Full text copies of all potentially relevant studies were obtained and independently assessed by MDS and MM to determine whether they met the inclusion criteria. In the event of a disagreement, the third author (DD) was asked to give his opinion to resolve the issue. We stored all identified study records using electronic bibliographic software (Endnote XI).

Two authors (MDS and MM) extracted data from the trial reports using a purposefully designed data extraction form. In the event of a disagreement, the third author (DD) was asked to give his opinion. We contacted trial authors for missing data where appropriate.

Two authors (MDS and MM) independently assessed the methodological quality of selected trials. In the event of a disagreement, the third author (DD) was consulted.

We used the ‘Risk of bias’ tool to assess the risk that a study over- or under-estimates the true intervention effect. This tool involves a description and a judgement for the following criteria: sequence generation; allocation sequence concealment; blinding of outcome assessment; incomplete outcome data; selective outcome reporting; intention-to-treat analyses and other potential sources of bias. Each criterion was judged ‘Yes’ indicating low risk of bias, ‘No’ indicating high risk of bias, or ‘Unclear’ indicating either lack of information or uncertainty over the potential for bias. Plots of ‘Risk of bias’ assessments were created in Review Manager. We assessed missing data and attrition rates for each of the included studies, and reported the number of participants who were included in the final analysis as a proportion of all participants in the study. Reasons given for missing data are provided in the narrative summary. We ascertained the extent to which the results were altered by missing data. This qualitative quality assessment was not used as a threshold for inclusion of studies, but as a possible explanation for differences between studies when interpreting the results of the review (Schulz 1995).

We contacted authors of all studies included in the review in order to obtain information absent from the published reports.

As the studies were too disparate to allow pooling of results in a meta-analysis, we described the results of the trials using a qualitative summary. We performed no subgroup or sensitivity analyses.

See: Characteristics of included studies; Characteristics of excluded studies; Characteristics of studies awaiting classification.

The search strategy generated 1420 citations; 1417 from database searching, two from searching reference lists and one from contacting authors. MDS and MM independently checked the titles and abstracts of these citations and excluded 1350 as clearly irrelevant. We identified 70 citations as potentially relevant and located these for full text screening. We were unable to locate the full text of two studies (see ‘Characteristics of studies awaiting classification’), and one study only had unpublished data. MDS and MM independently screened the full text of 67 studies. Sixty-two were excluded as they did not meet the inclusion criteria (see’Characteristics of excluded studies’). Seventeen were not RCTs, 17 evaluated interventions for the treatment rather than prevention of disability, 11 evaluated a complex intervention for which the psychosocial component could not be disaggregated, seven did not measure an aspect of disability as the outcome of the trial, eight included more than 20% of patients who had not suffered a traumatic physical injury and two did not evaluate a psychosocial intervention. In total five studies met the inclusion criteria and were included in the review.

There were no disagreements which could not be resolved between MM and MDS when screening abstracts and titles, and two disagreements when screening the full text of reports. These were referred to DD for a third opinion and in both cases the studies were excluded. The kappa score for inter-rater reliability on a sample of 413 citations was 0.94.

We made a flowchart of the process of trial selection in accordance with the QUORUM statement (Moher 1999) see Figure 1.

Selection process of eligible randomised controlled trials from all identified citations.

See: ‘Characteristics of included studies’; ‘Characteristics of excluded studies’.

Five trials, involving 756 participants, are included in this review. The included trials were very different in terms of population studied, intervention assessed and outcomes. As such, pooling the results in a meta-analysis was not possible. Instead, studies are discussed according to intervention type.

Four trials included patients admitted to a trauma centre following a traumatic physical injury (Holmes 2007; Pirente 2007; Turpin 2005; Zatzick 2001) and one included patients who had undergone surgery for hip fracture (Burns 2007).

The eight included studies examined the following group comparisons:

CBT versus treatment as usual (Burns 2007; Pirente 2007);

interpersonal counselling versus treatment as usual (Holmes 2007);

collaborative care with a personally assigned trauma support specialist versus treatment as usual (Zatzick 2001);

self-help information booklet versus a letter without the booklet (Turpin 2005).

All but one study measured physical disability outcomes (Turpin 2005), and all included at least one mental health status outcome. Only one study assessed social functioning or health care utilisation (Burns 2007).

In total the five trials assessed 12 different outcomes. Four measured physical disability (mobility, pain and changes in pain, physical illness and physical functioning); six measured mental health status (depression and change in depressive symptoms, anxiety, PTSD and change in PTSD symptoms, alcohol abuse, substance abuse and any psychological disorder); one assessed global assessment of functioning (health related quality of life); and one assessed social functioning and health care use (length of stay in hospital). With the exception of depression, where two studies used the same tool, each study used a different tool to measure the outcomes.

Where it was possible to assess this, included trials had generally poor ratings of trial quality and many suffered from biases in addition to those assessed by the Cochrane criteria (see Figure 2 and Figure 3).

Methodological quality graph: review authors’ judgements about each methodological quality item presented as percentages across all included studies.

Methodological quality summary: review authors’ judgements about each methodological quality item for each included study.

All trials had adequate sequence generation, using computer generated randomisation or random number tables. All trials also had adequate allocation concealment, using either an independent telephone randomisation service or sealed opaque envelopes.

Blinding of outcome assessment was only adequately addressed in two trials, with four trial reports containing insufficient detail and one using patient self-assessment (Menzel 2006).

Only one trial adequately addressed incomplete outcome data with the reasons for losses to follow up clearly stated (Zatzick 2001). Two trials had less than 60% follow up (Pirente 2007; Turpin 2005).

Selective reporting of results occurred in all but two of the trial reports (Holmes 2007; Turpin 2005), with many not reporting all pre-specified outcomes or insignificant effect estimates.

Only three trials performed intention-to-treat analyses. Significant other potential sources of bias included the small sample size (especially after high losses to follow up) and therefore lack of power for some studies.

We did not pool data due to heterogeneity between trials in terms of the intervention, outcomes, time point at which the outcome was assessed and the population studied. Instead, trials’ results are discussed by intervention type (brief psychological therapies, self-help information and collaborative care). In addition, we performed no subgroup or sensitivity analyses due to the heterogeneity of the included studies. See Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8 for full results of the included studies.

Brief psychological therapy.

Self-help information.

Collaborative care/complex interventions.

Two studies examined the preventive effect of individual CBT (Burns 2007; Pirente 2007) on disability outcomes. No significant between group differences were found for any disability outcome.

This study examined 170 patients over 60 years old who had undergone surgery for hip fracture and who had been classified as not at risk of suffering from depression (score of six or less on the Geriatric Depression Scale). The intervention consisted of up to seven sessions of CBT delivered by an assistant psychologist. The control group received treatment as usual. Outcomes were assessed at six weeks (79.4% follow up), three months (66.5% follow up) and six months (64.7% follow up). There were no significant differences in any of the outcomes (depression, mobility, pain, physical illness, functioning, or length of hospital stay) at any of the follow-up points. It is possible that the selection of participants who screened negative for depression may have reduced the effectiveness of the intervention on the subsequent development of mental health problems. Indeed, 18% of the intervention group (and 11% of the control group) were already taking antidepressants at baseline, suggesting that the screening tool used was not sensitive, creating commonality between groups and possibly further reducing the effect of the intervention.

In a similarly sized trial, the authors randomised 171 severely injured trauma patients to receive up to eight sessions of individual CBT or treatment as usual. Only the 92 patients with complete outcome data at both six and 12 months were analysed (53.8%). There were significant between group differences at baseline with a higher proportion of anxiety (57.8% versus 40.4%, P = 0.006) and depression (73.3% versus 44.7%, P = 0.014) in the intervention compared to the control group. There were no significant differences at any follow-up time between the two groups in any of the outcomes (health-related quality of life (HRQoL), depression or anxiety), possibly because of the initial differences between groups. There was significant within group reduction in depression among the intervention group from surgical ward to discharge (P = < 0.001), from surgical ward to six months follow up (P = 0.004) and from six to 12 months follow up (P = 0.013). The same reduction in anxiety was apparent in the intervention group from surgical ward to discharge (P = 0.001) and from surgical ward to six months follow up (P = 0.002).

One study examined the effect of interpersonal therapy (Holmes 2007). No significant differences between groups were found for any outcome.

Ninety major physical trauma patients admitted to two trauma centres were randomised to an average of 5.9 Interpersonal Counselling (IPC) sessions delivered by a clinical psychologist. Follow up at six months was 63.3%. There was a high rate of drop-out from the intervention group (24/51, 47.1%), though they did not differ in characteristics from completers. No significant between group differences were found for any of the outcomes (depression, anxiety, PTSD, alcohol and substance abuse, any psychiatric disorder and physical functioning – effect estimates and P values not reported). The lack of differences between groups may be partly explained by the high degree of ‘non-specific psychological support’ (mean 22.6 hours) and psychiatric/psychological treatment (mean 0.8 hours) the control group received as well as the small sample size for analysis. Participants with a past history of major depression who received IPC had significantly higher levels of depression at six months (P = 0.018), indicating that the intervention may be harmful to a vulnerable group of individuals.

One study examined the effect of self-help information delivered as a booklet (Turpin 2005). The intervention had no protective effect on any disability outcome.

Two hundred and ninety-one Accident and Emergency patients who had sustained a physical injury were randomised to receive either a self-help information booklet six to eight weeks after hospital attendance, or a letter without the booklet. The booklet described and normalised common physiological, psychological and behavioural reactions to traumatic injury and provided advice on non-avoidance, emotional help and seeking further help. Only 10% (291/2818) of those eligible agreed to participate. There were significant differences between consenters and non-consenters in terms of age, gender and trauma type. Follow up was poor with only 34% of those randomised followed up at six months. This was partly due to an administrative error which resulted in 66 participants who had completed baseline measures being removed from the analysis. There were no significant differences between groups in anxiety or PTSD symptoms. However, there was evidence that the booklet may have a detrimental impact on mental health status. At three months follow up there was a greater reduction in PTSD cases in the control than the intervention group (P = 0.06), and in an intention-to-treat analysis at six months there was a higher proportion of depressed patients in the intervention rather than the control group (18% versus 7%, P = 0.054).

One study assessed the effect of collaborative care. The intervention had no protective effect on any disability outcome.

In a pilot study, 34 injured patients admitted to a trauma centre were randomised to receive either collaborative care comprising a personally assigned trauma support specialist and a brief psychoeducational intervention targeting PTSD, or treatment as usual. The trauma support specialists spent on average 1.5 hours with each patient. Follow up at four months was 74.5%. At one-month follow up in intention-to-treat analyses the intervention group had significantly decreased PTSD (effect estimate 0.99, F[1,33] = 6.8 P < 0.05) and borderline significant decreased depression (effect estimate 0.58, F[1,33] = 3.7 P = 0.07) symptoms when compared to the control group. Due to the complex intervention it is not possible to determine which aspect of the intervention had a positive impact on mental health status. At four months the intervention groups symptoms had significantly increased relative to the control groups for both PTSD (effect estimate 1.75, F[1,27] = 6.1 P < 0.05) and depression (effect estimate 1.15, F[1,33] = 6.8 P < 0.05). There were no significant between group differences at either one or four months for the other outcomes: drinking to the point of intoxication and functional limitations.

The aim of this review was to evaluate the effectiveness of psychosocial interventions for the prevention of disability following traumatic injury. Five trials were identified. The disparate nature of the trials covering different patient populations, interventions and outcomes meant that it was not possible to pool data meaningfully across studies. Three studies assessed the effect of brief psychological therapies, one assessed the impact of a self-help booklet, and one the effect of collaborative care.

Overall there was no evidence of a protective effect of brief psychological therapies or self-help booklets on preventing disability, and evidence from one trial of a reduction in both PTSD and depressive symptoms one month after injury in those who received a collaborative care intervention combined with a brief psychoeducational intervention (Zatzick 2001). Mental health status was the only disability outcome affected by any intervention. In three trials the psychosocial intervention had a detrimental effect on the mental health status of patients.

The findings from this review must be viewed in light of the small sample size and the heterogeneous characteristics of trials published in this area.

The absence of effect in the brief psychological therapy trials is surprising given the strong evidence for the effectiveness of these interventions, in particular CBT, in treating a range of mental health problems (Bisson 2007; Hunot 2007; Soo 2007) and other conditions including sleep problems (Montgomery 2003). This may be the result of low power in all three brief psychological therapy trials (the sample size for the analysis ranged from 57 to 135) and relatively large losses to follow up (range 53.8% to 64.7%). The lack of effect may also be due to the universal application of the intervention to all traumatically injured patients including those who may not be at risk of a secondary disability. In particular, one trial specifically excluded those who were considered at risk of developing mental health problems (Burns 2007), and another trial excluded those who had previously suffered a major psychiatric illness or alcohol abuse (Pirente 2007). In addition, the lack of effect of any of the brief psychological therapies on nonmental health outcomes may be due to the targeted approach of these therapies focusing relatively more strongly on mental health status and coping skills per se rather than on physical health and social functioning.

The ‘light touch’ nature of some of the interventions may explain their lack of effect, in particular the self-help booklet intervention which reported no significant between group differences despite adequate power. It is likely that a short booklet received some weeks after injury is not sufficient to significantly modify feelings and behaviour in order to have a measurable impact on disability outcomes. The only significant effect on a primary outcome in this review was for a complex intervention comprising collaborative care with a dedicated trauma specialist combined with a brief psycho-educational intervention (Zatzick 2001). However the protective effect was not maintained over the medium term once the frequency of contact decreased, possibly suggesting that only complex, time-consuming and therefore costly interventions may have a measurable effect on disability prevention.

There was evidence from three trials that psychosocial interventions have a detrimental effect on the mental health status of some patients (Holmes 2007; Turpin 2005; Zatzick 2001). In one study, subjects with a past history of depression who received interpersonal therapy had significantly higher levels of depressive symptoms at six months (Holmes 2007), while a greater reduction in PTSD ‘caseness’ between baseline and follow up was observed in the control group compared to those who received an educational booklet (Turpin 2005). In addition, while there was a reduction in depressive and PTSD symptoms in those who had received collaborative care compared to the control group one month after injury, these effects were short-lived. Once patient contact had dropped off by four months post-injury, symptoms of depression and PTSD significantly increased in the intervention group relative to the controls (Zatzick 2001). These findings may be partly explained by high rates of drop-out from the intervention group in one of the brief psychological therapy trials (Holmes 2007), perhaps indicating high participant burden resulting in increased participant stress. These results may reflect similar processes to those operating when single session debriefing following a traumatic event leads to increased symptoms of PTSD (Rose 2002). These include ‘secondary traumatisation’ of the injury and ‘medicalising’ normal distress whereby increasing awareness of potential psychological distress may paradoxically induce distress in those who would otherwise not have developed it (Rose 2002).

Two studies showed a trend towards a reduction in mental health symptoms over time in both the control and intervention groups, indicating natural recovery from the psychological consequences of physical trauma (Burns 2007; Pirente 2007), and re-enforcing the conclusion that a universally targeted intervention may impose an unnecessary burden on those who may recover naturally from any psychological trauma.

Taken together, our findings cannot be taken as supporting the provision of psychosocial intervention to prevent aspects of disability arising from physical injury. Our findings may indicate that the monitoring of high-risk patients followed by early intervention, whereby resources are allocated at gradually increasing levels to patients whose difficulties do not abate, may be a better strategy for reducing secondary disability arising from traumatic physical injury.

The quality of trials was generally poor. In particular the quality of reporting of the trials was generally very poor with non-significant effect estimates and the results of many outcomes not reported. With the exception of two trials the sample sizes available for analysis were small, with a large proportion of participants lost to follow up.

The wide range of papers selected from our search criteria and the diverse range of studies eligible for inclusion meant that we had to refine our inclusion criteria from the protocol, for example by removing the restriction that the physical injury must have happened within 12 months of the intervention, as many trials did not report this and we sought to be inclusive in our selection of trials. Instead, the emphasis for inclusion was whether the intervention was aimed at prevention rather than treatment.

The poor quality of reporting of outcomes in the trials may have biased the review as effect estimates for many of the non-significant outcomes were not available despite repeated attempts to contact the authors.

This review contributes to the understanding of psychosocial treatments for the prevention of disability following traumatic injury. This review excluded 62 studies which did not meet our inclusion criteria, indicating a significant body of work in this area. Eleven trials were excluded because they evaluated complex interventions which included but were not restricted to psychosocial interventions. It is possible that the combination of different preventive strategies incorporating medication, psychological interventions and physiotherapy as appropriate may be more effective in preventing the disabling sequelae of traumatic injury than psychosocial interventions alone, though this remains untested in a systematic review.

Seventeen of the excluded studies were trials of the treatment rather than the prevention of disability (primarily mental health problems) following traumatic injury, reflecting the focus of this review on the prevention rather than treatment of secondary conditions. However, given the possible harmful effects that a preventive intervention may have on the mental health status of participants found in this review, in addition to the time and economic cost of such universal interventions, it is important to assess the effect that more targeted interventions may have on ameliorating the negative consequences of traumatic injury. One way of achieving this is to target interventions at groups of patients who have been identified as being at risk of developing a mental or physical disability, or using a stepped care approach to increase the level of intervention based on individual need. A recent systematic review and meta-analysis of early trauma-focused cognitive behavioural therapy to prevent chronic post-traumatic stress disorder and related symptoms concluded that there is evidence for the effectiveness of trauma-focused CBT compared to supportive counselling in preventing chronic PTSD in patients with an initial diagnosis of acute stress disorder. The overall relative risk (RR) for a PTSD diagnosis was 0.56 (95% CI 0.42 to 0.76), 1.09 (95% CI 0.46 to 2.61) and 0.73 (95% CI 0.51 to 1.04) at three to six months, nine months and three to four years post-treatment, respectively, though this evidence came from one research team and therefore needs replication (Kornør 2008). A wider review into psychosocial interventions after crises and accidents found insufficient research evidence on other types of interventions to conclude about effects (Kornør 2007).

This review does not provide convincing evidence for the effectiveness of psychosocial interventions for the prevention of disability following traumatic physical injury. No protective effect of brief psychological therapies or self-help booklets was found. There was moderate evidence from one trial that collaborative care reduced symptoms of depression and PTSD in the short but not medium term. However, there was also evidence that psychosocial interventions may have a detrimental effect on mental health. Nonetheless, these conclusions are necessarily tentative as they are based on a small number of disparate trials with small to moderate sample sizes. More research, using larger sample sizes and comparable interventions and patient populations to enable pooling of results, is needed before these findings can be confirmed. Any such research should undertake intensive monitoring of participants’ short-term response to psychosocial interventions and be vigilant to their potential negative effects.

The heterogeneity of studies included in this review precluded the pooling of data across studies. In order to combine data across trials we recommend further trials of adequate power which focus on comparable psychosocial interventions, patient populations and outcome measures of disability. Interventions which target mental health as a result of traumatic injury are needed, as this remains the most common disabling sequelae of traumatic injury (Mossey 1990; Schnyder 2001; Shalev 1998; Zatzick 2002) and the outcome which holds the most promise for modification by psychosocial interventions.

The research studies reported on in this review were primarily conducted within North America and Europe. Further research on the prevention of disability following physical injury in different cultures and contexts is needed to develop a fuller understanding of efficacious interventions, particularly in low-income countries where the majority of persons with disabilities live (MacLachlan 2009).

More research is needed into stepped care approaches involving the monitoring of patients at risk of developing a mental health problem followed by early intervention whereby resources are allocated at gradually increasing levels to patients whose symptoms do not abate.

Traumatic physical injury such as that resulting from road traffic accidents, falls and fires can cause high levels of subsequent disability in the person affected. This may include physical disability as a result of the initial injury and subsequent complications, mental health problems such as depression, anxiety and post-traumatic stress disorder (PTSD) as a result of the trauma of the event which caused the injury and the resulting physical and social problems, and social problems such as loss of social life and unemployment. It is therefore important to evaluate interventions which seek to prevent these adverse secondary outcomes. Psychosocial interventions, which include psychological therapies such as interpersonal counselling and cognitive behavioural therapy (CBT), and social interventions such as befriending, social support and self-help advice, delivered soon after the injury, may help to prevent these problems.

This review identified five randomised controlled trials, involving 756 participants, which evaluated psychosocial interventions for the prevention of disability following traumatic injury. No convincing evidence was found supporting the efficacy of these interventions. In particular, self-help booklets and interpersonal therapies had no effect on preventing disability. There was some evidence that a more complex intervention involving collaborative care reduced symptoms of depression and PTSD in the short but not the medium term. There was evidence from three trials that psychosocial interventions had a detrimental effect on mental health. Taken together, our findings cannot be taken as supporting the provision of psychosocial interventions to prevent aspects of disability arising from physical injury. These results suggest that future interventions should focus on screening patients at risk of poor outcomes and only treating those who develop subsequent problems. However, the strength of these conclusions is limited by the small size and varied nature of many of the trials, which means that their results cannot be pooled.

This review was supported by a Cochrane Fellowship grant from the Health Research Board (Ireland) to Malcolm MacLachlan.

Mary De Silva is supported by an ESRC/MRC Interdisciplinary Post Doctoral Fellowship.

Vikram Patel is supported by a Wellcome Trust Senior Clinical Research Fellowship in Tropical Medicine.

We thank the Cochrane Injuries Group for assistance throughout the review process, in particular Ian Roberts for comments on the initial review design, Karen Blackhall for conducting the search and Emma Sydenham and Pablo Perel for support throughout the process.

CONTRIBUTIONS OF AUTHORS MM and MDS were jointly responsible for reviewing papers and writing the review.

MDS was responsible for co-ordinating the overall review process, the collation of review papers and for communication with co-authors regarding their feedback.

DD was responsible for offering a third opinion on any disputes between MM and MDS regarding their reviewing of papers.

DD, US, MB, VP and PG were responsible for commenting on the protocol and the final review, and confirming the inclusion of key papers in the area.

DECLARATIONS OF INTEREST None known.

SOURCES OF SUPPORT

Internal sources • No sources of support supplied

External sources

Malcolm MacLachlan, Health Research Board (All-Ireland) Cochrane Fellowship, Ireland.

Mary J De Silva, ESRC/MRC Interdisciplinary Post Doctoral Fellowship, UK.

Vikram Patel, UK.

Wellcome Trust Senior Clinical Research Fellowship in Tropical Medicine.

DIFFERENCES BETWEEN PROTOCOL AND REVIEW The following text was added:

Secondary outcomes: health care utilisation.

Searching other resources: the reference sections of all selected papers were screened for additional studies.

Because of the types of trials identified, we conducted no quantitative analysis and completed the review using a qualitative summary. Should there be trials in the future that enable a quantitative analysis, these will be performed as per the original protocol.

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1University of Florida, Gainesville FL

1University of Florida, Gainesville FL

2University of Maryland School of Medicine, Baltimore, MD

4University of South Carolina, Columbia, SC

5National Heart, Lung and Blood Institute, Bethesda, MD

6Pennington Biomedical Research Center, LA

7Tufts University, Boston, MA

8Yale School of Medicine, New Haven, CT

10Stanford University, School of Medicine, Stanford, CA

1University of Florida, Gainesville FL

11Northwestern University Feinberg School of Medicine, Chicago, IL

12University of Pittsburgh, Pittsburgh, PA

Targeted mass mailings to the community was the primary recruitment strategy.18

Study flow

Baseline characteristics of the participants

LIFE investigators are also partially supported by the following:

LIFE investigators are also partially supported by the following:

Marco Pahor, MD – Principal Investigator of the LIFE Study

Christiaan Leeuwenburgh, PhD

Connie Caudle

Lauren Crump, MPH

Latonia Holmes

Jocelyn Lee, PhD

Ching-ju Lu, MPH

Michael E. Miller, PhD – DMAQC Principal Investigator

Mark A. Espeland, PhD – DMAQC Co-Investigator

Walter T. Ambrosius, PhD

William Applegate, MD

Daniel P. Beavers, PhD, MS

Robert P. Byington, PhD, MPH, FAHA

Delilah Cook, CCRP

Curt D. Furberg, MD, PhD

Lea N. Harvin, BS

Leora Henkin, MPH, Med

John Hepler, MA

Fang-Chi Hsu, PhD

Laura Lovato, MS

Wesley Roberson, BSBA

Julia Rushing, BSPH, MStat

Scott Rushing, BS

Cynthia L. Stowe, MPM

Michael P. Walkup, MS

Don Hire, BS

W. Jack Rejeski, PhD

Jeffrey A. Katula, PhD, MA

Peter H. Brubaker, PhD

Shannon L. Mihalko, PhD

Janine M. Jennings, PhD

Evan C. Hadley, MD (National Institute on Aging)

Sergei Romashkan, MD, PhD (National Institute on Aging)

Kushang V. Patel, PhD (National Institute on Aging)

Denise Bonds, MD, MPH

Mary M. McDermott, MD – Field Center Principal Investigator

Bonnie Spring, PhD – Field Center Co-Investigator

Joshua Hauser, MD – Field Center Co-Investigator

Diana Kerwin, MD – Field Center Co-Investigator

Kathryn Domanchuk, BS

Rex Graff, MS

Alvito Rego, MA

Timothy S. Church, MD, PhD, MPH – Field Center Principal Investigator

Steven N. Blair, PED (University of South Carolina)

Valerie H. Myers, PhD

Ron Monce, PA-C

Nathan E. Britt, NP

Melissa Nauta Harris, BS

Ami Parks McGucken, MPA, BS

Ruben Rodarte, MBA, MS, BS

Heidi K. Millet, MPA, BS

Catrine Tudor-Locke, PhD, FACSM

Ben P. Butitta, BS

Sheletta G. Donatto, MS, RD, LDN, CDE

Shannon H. Cocreham, BS